Recently, there has been a growing interest in a class of complex systems whose constituents are
themselves complex. Performance optimization, robustness and reliability among an emerging group
of heterogeneous systems in order to realize a common goal has become the focus of various
applications including military, security, aerospace, space, manufacturing, service industry,
environmental systems, disaster management, to name a few [Crossley 2006; Lopez 2006; Wojcik and
Hoffman 2006]. There is an increasing interest in achieving synergy between these independent
systems to achieve the desired overall system performance [Azarnoosh, et al. 2006]. In the literature,
researchers have addressed the issue of coordination and interoperability in a SoS [Abel and Sukkarieh
2006; DiMario 2006]. SoS technology is believed to more effectively implement and analyze large,
complex, independent, and heterogeneous systems working (or made to work) cooperatively [Abel
and Sukkarieh 2006]. The main thrust behind the desire to view the systems as an SoS is to obtain
higher capabilities and performance than would be possible with a traditional system view. The SoS
concept presents a high-level viewpoint and explains the interactions between each of the independent
systems. However, the SoS concept is still at its developing stages [Meilich 23006; Abbott 2006].
Next section will present some definitions out of many possible definitions of SoS. However, a
practical definition may be that a System of Systems is a “super system” comprised of other elements
which themselves are independent complex operational systems and interact among themselves to
achieve a common goal. Each element of a SoS achieves well-substantiated goals even if they are
detached from the rest of the SoS. For example a Boeing 747 airplane, as an element of a SoS, is not
SoS, but an airport is a SoS, or a rover on Mars is not a SoS, but a robotic colony (or a robotic swarm)
exploring the red planet, or any other place, is a SoS. As will be illustrated shortly, associated with
SoS, there are numerous problems and open-ended issues which need a great deal of fundamental
advances in theory and verifications. It is hoped that this volume will be a first effort towards bridging
the gaps between an idea and a practice.
Based on the literature survey on system of systems, there are numerous definitions whose detailed
discussion is beyond the space allotted to this chapter [Jamshidi 2005; Sage and Cuppen 2001; Kotov
1997; Carlock and Fenton 2001; Pei 2000; Luskasik 1998]. Here we enumerate only 6 of many
potential definitions:
Definition 1: Enterprise Systems of Systems Engineering is focused on coupling traditional systems
engineering activities with enterprise activities of strategic planning and investment analysis [Carlock
and Fenton 2001].
Definition 2: System of Systems Integration is a method to pursue development, integration,
interoperability, and optimization of systems to enhance performance in future battlefield scenarios
[Pei 2000].
Definition 3: Systems of systems exist when there is a presence of a majority of the following five
characteristics: operational and managerial independence, geographic distribution, emergent behavior,
and evolutionary development [Jamshidi 2005].
Definition 4: Systems of systems are large-scale concurrent and distributed systems that are
comprised of complex systems [Jamshidi 2005; Carlock and Fenton 2001].
Definition 5: In relation to joint war-fighting, system of systems is concerned with interoperability and
synergism of Command, Control, Computers, Communications, and Information (C4I) and
Intelligence, Surveillance, and Reconnaissance (ISR) Systems [Manthorpe 1996].
Definition 6: SoSE involves the integration of systems into systems of systems that ultimately
contribute to evolution of the social infrastructure [Luskasik 1998].
Detailed literature survey and discussions on these definitions are given in [Jamshidi 2005, 2008].
Various definitions of SoS have their own merits, depending on their application.
Favorite definition of this author and the volume’s editor is Systems of systems are large-scale
integrated systems which are heterogeneous and independently operable on their own, but are
networked together for a common goal. The goal, as mentioned before, may be cost, performance,
robustness, etc.
In the realm of open problems in SoS, just about anywhere one touches, there is an unsolved problem
and immense attention is needed by many engineers and scientists. No engineering field is more
urgently needed in tackling SoS problems than SE – system engineering. On top of the list of
engineering issues in SoS is the “engineering of SoS,” leading to a new filed of SoSE (Wells and Sage,
2008). How does one extend SE concepts like analysis, control, estimation, design, modeling,
controllability, observability, stability, filtering, simulation, etc. can be applied to SoS? Among
numerous open questions are how can one model and simulate such systems (see Chapter 4 by Sahin,
et al.). In almost all cases a chapter in this volume will accommodate the topic raised. Additional
references are given to enhance a search by the interested reader.
1.3.1 Theoretical Problems
In this section a number of urgent problems facing SoS and SoSE are discussed. The major issue
here is that a merger between SoS and engineering needs to be made. In other words, systems
engineering (SE) needs to undergo a number of innovative changes to accommodate and encompass
Architecting System-of-Systems Solutions – Cole in Chapter 2 presents solution ideas for SoS
architectures. Author indicates that along with defining the problem, one of the most important jobs of
the systems engineer is to partition the problem into smaller, more manageable problems and make
critical decisions about the solution. One of the most critical decisions is the architecture – the
fundamental organization of a system embodied in its components, their relationships to each other,
and to the environment, and the principles guiding its design and evolution [ANSI/IEEE-1472, 2000].
While it is impossible to understand all the characteristics and consequences of the architecture at the
time the system is designed, it is possible to produce a system architecture that maximizes the ability of
the system to meet user needs, while minimizing the unintentional consequences.
In one sense, architecting a complex system that is comprised of a number of collaborating
independent systems is no different than designing a simple system. Both start with definition of a problem
and conception of solution. Both warrant consideration of environmental context. Both involve analysis of
factors related to effectiveness. And both require design compromises and balancing of competing
priorities. The basic process is the same. In fact, it has been well documented for nearly 50 years [Asimow,
1962]. But compared to the design of simple systems, the complexity of designing a system-of-systems
(SoS) solution is daunting and the design process must be approached with that complexity in mind.
Details are found here in Chapter 2.
Dagli and Ergin [2008] also provide a framework for SoS Architectures. As the world is moving towards a
networked society, the authors assert, the business and government applications require integrated systems
that exhibit intelligent behavior. The dynamically changing environmental and operational conditions
necessitate a need for system architectures that will be effective for the duration of the mission but evolve
to new system architectures as the mission changes. This new challenging demand has led to a new
operational style: Instead of designing or subcontracting systems from scratch, business or government
gets the best systems the industry develops and focuses on becoming the lead system integrator to provide
a System of Systems (SoS). SoS is a set of interdependent systems that are related or connected to provide
a common mission. In the SoS environment, architectural constraints imposed by existing systems have a
major effect on the system capabilities, requirements and behavior. This fact is important, as it complicates
the systems architecting activities. Hence, architecture becomes a dominating but confusing concept in
capability development. There is a need to push system architecting research to meet the challenges
imposed by new demands of the SoS environment. This chapter focuses on System of Systems architecting
in terms of creating meta-architectures from collections of different systems. Several examples are
provided to clarify System of Systems architecting concept. Since the technology base, organizational
needs, and human needs are changing, the System of System architecting becomes an evolutionary
process. Components and functions are added, removed, and modified as owners of the SoS experience
and use the system. Thus in evolutionary system architecting is described and the challenges are identified
for this process. Finally, the authors discuss the possible use of artificial life tools for the design and
architecting of SoS. Artificial life tools such as swarm intelligence, evolutionary computation and
multi-agent systems have been successfully used for the analysis of complex adaptive systems. The
potential use of these tools for SoS analysis and architecting are discussed, by the authors, using several
domain application specific examples.
Emergence of SoS, Socio-Cognitive Aspects – McCarter and White in Chapter 3, address emergence in
SoS. The authored have offered a human-centric treatment of the concepts of multi-scale analysis and
emergence in system of systems (SoS) engineering, or more generally, complex systems engineering
(CSE) . This includes a characterization of what an individual might do in conceptualizing a given systems
engineering situation s/he is facing. The authors suggest fresh interpretations of the terms scale and
emergence that will contribute to a more collaborative approach to improving the CSE practice. Because
other authors use “scale” in several different ways, potentially causing confusion, the present authors
propose “view” instead. Here a given view is defined as a combination of “scope”, “granularity”,
“mindset”, and “timeframe”. Although “emergence” has a rich spectrum of definitions in the literature, the
authors prefer to emphasize the unexpected, especially “surprising”, flavor of emergence. In this endeavor
socio-cognitive aspects are paramount, and in an age of increasing organizational complexity, small group
dynamics are becoming more significant. Human psychological and social behaviors that impact
information sharing, productivity, and system interoperability need closer examination as organizations
increasingly rely on decentralization to achieve their goals. Therefore, this chapter also highlights
important dynamic social issues, although the authors do not focus on trying to solve them. Rather, areas
of further research are suggested which can lead to better CSE, when people are considered part of any
(complex) system in the SoS.
Emergence of SoS, Socio-Cognitive Aspects – McCarter and White, in Chapter 3, have offered a
human-centric treatment of the concepts of multi-scale analysis and emergence in system of systems (SoS)
engineering, or more generally, complex systems engineering (CSE) [Gladwell, 2005]. This includes a
characterization of what an individual might do in conceptualizing a given systems engineering situation
s/he is facing. The authors suggest fresh interpretations of the terms scale and emergence that will
contribute to a more collaborative approach to improving the CSE practice. Because other authors use
“scale” in several different ways, potentially causing confusion, the present authors propose “view”
instead. Here a given view is defined as a combination of “scope”, “granularity”, “mindset”, and
“timeframe”. Although “emergence” has a rich spectrum of definitions in the literature, the authors prefer
to emphasize the unexpected, especially “surprising”, flavor of emergence. In this endeavor
socio-cognitive aspects are paramount, and in an age of increasing organizational complexity, small group
dynamics are becoming more significant. Human psychological and social behaviors that impact
information sharing, productivity, and system interoperability need closer examination as organizations
increasingly rely on decentralization to achieve their goals. Therefore, this chapter also highlights
important dynamic social issues, although the authors do not focus on trying to solve them. Rather, areas
of further research are suggested which can lead to better CSE, when people are considered part of any
(complex) system in the SoS.
SoS Simulation – Sahin, et al. in Chapter 4 provide a framework for simulation of SoS. They have
presented a SoS architecture based on Extensible Markup Language (XML) in order to wrap data coming
from different systems in a common way. The XML can be used to describe each component of the SoS
and their data in a unifying way. If XML based data architecture is used in a SoS, only requirement for the
SoS components to understand/parse XML file received from the components of the SoS. In XML, data
can be represented in addition to the properties of the data such as source name, data type, importance of
the data, and so on. Thus, it does not only represent data but also gives useful information which can be
used in the SoS to take better actions and to understand the situation better. The XML language has a
hierarchical structure where an environment can be described with a standard and without a huge
overhead. Each entity can be defined by the user in the XML in terms of its visualization and
functionality. As a case study in this effort (see also [Mittal, et al. 2008]) a master-scout rover
combination representing a SoS where first a sensor detects a fire in a field. The fire is detected by the
master rover and commands the scout rover to verify the existence of the fire. It is important to note that
such an architecture and simulation does not need any mathematical model for members of the systems.
Biltgen in Chapter 5 provides a fundamental view of technology and its evaluation for SoS. The author
notes that technology evaluation is the assessment of the relative benefit of a proposed technology for a
particular purpose with respect to one or more metrics. While a number of quantitative assessment
techniques have been developed to support engineering and design of systems, a flexible, traceable, rapid
method for technology evaluation for systems-of-systems is needed. The primary difficulty in the
assessment process is the complexity associated with large-scale systems-of-systems and the integrated
nature of models required to study complex phenomena. The author goes on to note that many qualitative
techniques exist for resource allocation, an approach based on modeling and simulation is usually required
to quantify technology potential with respect to systems-of-systems level Measures of Effectiveness
(MoEs). The modeling and simulation environment relies on a linked suite of variable fidelity models that
calculate the impact of technologies across a system-of-systems hierarchy. Unfortunately, the run time of
this suite of tools is often prohibitive for exploratory analysis and domain spanning optimization
applications. In this chapter, the concept of surrogate models is introduced to speed up the analysis
process, provide a measure of transparency to the underlying physical phenomena, and to enable the
execution of design-of-experiments across a range of technology parameters at all levels of the
system-of-systems hierarchy. While polynomial surrogate models have exhibited much promise in
systems design applications, neural network surrogates are introduced in this chapter due to their ability to
capture the nonlinearities and discontinuities often present in systems-of-systems problems. Techniques
for data farming and visualization of results are also introduced as a means to understand the intricacies of
complex design spaces and an approach to “inverse design” where any variable can be treated as an
independent variable is demonstrated. The inverse design technique allows the user to set thresholds for
capability-based MoEs and decompose the problem to identify the critical technology factors that are most
significant to the responses in question. Finally, insight is provided into the value of the surrogate-based
approach for understanding sensitivities and quantifying the relative benefit of proposed technologies
with respect to the appropriate MoEs at the system-of-systems level.
Enterprise Systems of Systems – Rebovitch in Chapter 6 takes on the enterprise systems engineering. The
author notes that the 21st century is an exciting time for the field of systems engineering. Advances in our
understanding of the traditional discipline are being made. At the same time new modes of systems
engineering are emerging to address the engineering challenges of systems-of-systems and enterprise
systems. Even at this early point in their evolution, these new modes of systems engineering are evincing
their own principles, processes and practices. Some are different in degree than engineering at the system
level while others are different in kind.
While it is impossible to predict how the traditional and new forms of systems engineering will evolve in
the future, it is clear even now that there is a long and robust future for all three. Increases in technology
complexity have led to new challenges in architecture, networks, hardware and software engineering, and
human systems integration. At the same time, the scale at which systems are engineered is exceeding
levels that could have been imagined only a short time ago. As a consequence, all three forms of systems
engineering will be needed to solve the engineering problems of the future, sometimes separately but
increasingly in combination with each other.
This chapter defines three modes of systems engineering, discusses the challenge space each addresses,
describes how they differ from and complement each other, and suggests what their interrelationships
should be in solving engineering problems of the future.
Definition, Classification and Methodological Issues Of System of Systems – Bjelkemyr, et. al. in
Chapter 7 present a number of basic issues in Sos, similar to those discussed in this chapter. They present
a generic definition of the term System-of-Systems is established. This definition, the authors go on, is
based both on common definitions of SoS and on the characteristics that systems that are usually labeled
SoS exhibit. Due to the inclusive nature of this generic definition, a wide range of socio-technical systems
of very different size and complexity are included in the concept of SoS. In an attempt to delimit the
concept, a classification is suggested based on the redundancy of higher-level subsystems. Most systems
that traditionally are considered SoS are labeled SoS type I, e.g. International Space Station, an integrated
defense systems, national power supply networks, transportation systems, larger infrastructure
constructions; and systems with non-redundant subsystems are simply labeled SoS type II., in this chapter
exemplified by a production system. The purpose of this classification is partly to advance knowledge of
both SoS characteristics and how to address them, and partly to improve transferring of this knowledge
from the area of traditional SoS to other areas where SoS characteristics are present.
1.3.2 Implementation Problems
Asides from many theoretical and essential difficulties with SoS, there are many implementation
challenges facing SoS. Here some of these implementation problems are briefly discussed and references
are made to some with their full coverage.
Policymaking to Reduce Carbon Emissions – Agusdinata, et al. in Chapter 8, presents a
system-of-systems perspective combined with exploratory modeling and analysis method as an approach
to deal with complexity and uncertainty in policymaking. The test case is reduction of CO2 (carbon)
emissions, which stems from the interactions of many independent players involved and the multiple
aspects. The uncertainty about the physical and socio-economic systems is compounded by the long time
horizon the policymaking covers. Using a case of the long-term carbon emissions in Dutch residential
sector, the SoS perspective is used as a way to decompose the policy issue into interdependent relevant
policy systems. This representation of the policy system provides a framework to test a large number of
hypotheses about the evolution of the system’s performance by way of computational experiments, which
forms the core of the EMA method. In particular, in a situation where the realized emission level misses
the intermediate target in the year 2025, policies can be adapted, amongst others, by increasing the subsidy
on energy efficiency measures and tightening the standard for dwelling energy performance. As some of
the system uncertainties are resolved, we test whether adapting policies can lead to meeting the policy
target in the year 2050. Our approach shows the extent to which the constraints imposed on the
System-of-Systems should be relaxed in order to bring the emission level back to the intended target. The
relaxation of the constraints, which include among others energy prices, investment behavior,
demographic, and technological developments also point out to the different policy designs that
decisionmakers can envisioned to influence the performance of a System-of-Systems.
Medical and Health Management System of Systems – In Chapter 9, Hata, et al. have bridged a gap
between medical systems and SoS. Such system is widely used in diagnosis, treatment, and management
for patients. Human health management for healthy persons has much considerable attentions as a new
application domain in system engineering. In this chapter, we focused on ultrasonic surgery support,
medical imaging, and health management system of systems engineering. These application domains
discussed here are indeed broad and essential in daily clinical practice and health management. First one is
“Systems of Systems in Medical Ultrasonics”. Current modern ultrasonic systems require an integrated
system of systems engineering, i.e., integrated hardware system and modern software system. This section
introduces a novel ultrasonic surgery support system in orthopedic surgery. Second one is “System of
Systems in Medical Imaging.” This section introduces an approach to embed medical expert knowledge
into image processing based on fuzzy logic. To demonstrate the effectiveness of the new approach,
applications to human brain MR images and orthopedic kinematic analysis are introduced. Third one is
“System of Systems in Human Health Management”. An idea of health management is introduced and
discussed from the views of system of systems. As its application to human health, sensing and control
technology during sleep is focused on because quality and quantity of sleep has serious influence to our
body health.
The Microgrid as a System of Systems – Phillips, in Chapter 10 , has introduced electric microgrids as a
SoS. The author point souf that microgrids offer exciting possibilities for efficient, uninterruptible power.
A microgrid is a collection of small, non-collocated electric power sources, storage devices, and power
conditioners interconnected to meet the power consumption needs of a designated community. The
general vision is that a microgrid might produce power for a small to mid-size neighborhood, industrial
park, or commercial enclave. A microgrid is different from a power plant primarily because the generators
aren’t collocated, so it can’t easily be operated, managed, or controlled in a unified way by a single
committee. At the same time, a microgrid, because of the interconnectivity, can be operated more
efficiently than independent sources of similar capacity; more of the sources at any given point can be
operated at peak efficiency, transmission losses are minimized, and—perhaps the most enticing
thought—significant co-produced heat can be used for space and water heating and a myriad of industrial
uses because the sources are near the loads. All well and good, but if this is such a great idea, where are all
the microgrids? Unfortunately, fielding a microgrid requires a relatively complex system of systems, only
part of which is the already complicated electric power substrate. In addition, to have significant impact,
microgrids need to operate in conjunction with the primary power grid; this adds to operational difficulty
and forces economic considerations to be taken into account operationally. In this chapter we delineate and
discuss the communication, management, decisionmaking, and other systems needed for microgrid
Intelligent Decision Support System based on Sensor and Computer Networks – Wu, et al. in Chapter
11, have presented an intelligent decision support system based on sensor and computer networks that
incorporates various subsystems for sensor deployment, data routing, distributed computing, and
information fusion. The integrated system is deployed in a distributed environment composed of both
wireless sensor networks for data collection and wired computer networks for data processing. For these
subsystems, we formulate the analytical problems and develop approximate or exact solutions: (i) sensor
deployment strategy based on a two-dimensional genetic algorithm to achieve maximum coverage with
cost constraints; (ii) data routing scheme to achieve maximum signal strength with minimum path loss,
energy efficiency, and fault tolerance; (iii) network mapping method based on dynamic programming to
assign computing modules to network nodes for distributed sensor data processing; and (iv) binary
decision fusion rule that derive threshold bounds to improve system hit rate and false alarm rate. These
subsystems are implemented and evaluated through either experiments or simulations in various
application scenarios. The extensive results demonstrate that these component solutions imbue the
integrated system with the desirable and useful quality of intelligence.
Defense applications of SoS – Dickerson, in Chapter 12, takes on the defense applications of SoS. The
author notes that the defense community continues to move towards increasingly complex weapon
systems that must support joint and coalition operations, the need for system of systems (SoS) engineering
becomes more critical to the achievement of military capabilities. The U.S. Department of Defense (DoD)
and the U.K. Ministry of Defence (MOD) continue to face a critical challenge: the integration of multiple
capabilities across developing and often disparate legacy systems that must support multiple warfare areas.
Over the past decade, the need for SoS enabled mission capabilities have led to changes in policy for the
acquisition of systems and the assemblage of battle forces. Defense acquisition structures have been
reorganizing in order to integrate acquisition activities in a way that leads to the achievement of
capabilities through a system of systems approach rather than from just the performance of individual
systems or platforms. Earlier efforts to meet the challenge faced by the defense community have included
solutions using Network Centric Operations (NCO) and Network Enabled Capabilities (NEC). Although
progress has been made, future progress can be expected to depend upon the advancement of the practice
of systems engineering at the SoS level. System of Systems Engineering (SoSE) processes and practices
must enable the acquisition of systems of systems that support the integration of multiple capabilities
across multiple warfare areas. Recently there has been extensive debate across a broad community of
government, industry, and academic stakeholders about systems engineering processes and practices at the
SoS level. But whatever form SoSE takes for defense systems, the technical processes of SoSE must
support the realization of mission capabilities attainable from a system of systems that cannot be attained
from a single system. Chapter 12 will focus on SoS initiatives and SoSE technical processes being used for
the development and acquisition of defense systems of systems. It will begin with the Revolution in
Military Affairs that led to Network Centric Warfare then show how the concepts of SoSE and network
enablement are intertwined. Together they not only enable mission capabilities but also are key to the
integration of capabilities. Key SoS initiatives in the DoD are discussed. Chapter 12 will conclude with
some of the current activities and emerging research opportunities in SoSE.
Systems of Air Vehicles – Colgren in Chapter 13, has considered a system of air vehicles as a natural test
bed for a SoS. The author reminds us that a longstanding example of such a system, developed long
before the term system-of-systems was coined, is the international airspace system intended for the safe
and efficient flight control of air vehicles. The International Civil Aviation Organization (ICAO), which
manages the international Air Traffic Control (ATC) system, has been in operation since April 1947. It
was build around pre-existing international agreements and regulations as an agency of the United Nations
(Ref. 1). It codifies the principles and techniques of international air navigation and fosters the planning
and development of international air transport to ensure safe and orderly growth (Ref. 2). It insures
standards, such as the international use of English for communications and the specific frequency ranges
to be used for these and all other required command and control operations. The ICAO Council adopts
standards and recommended practices for its 190 member states concerning air navigation, the prevention
of unlawful interference, and for facilitating border crossings for international civil aviation. In addition,
the ICAO defines the protocols for air accident investigations used by transport safety authorities in the
signatory countries, also commonly known as the Chicago Convention. The United States air traffic
control system is managed by the Federal Aviation Administration (FAA) to provide safe separation of
aircraft within U.S. airspace and in and out of U.S. airports (Ref. 3). While the basic design of the air
traffic control system dates back to the 1950s, this design has been adapted as the demands on the system’s
capacity has continued to rise. The three critical components of the ATC — communications, navigation,
and surveillance — must continuously be modernized to maintain the safety and efficiency of the air
transportation system. Such updates must be accomplished under international agreements, maintaining
global compatibility throughout the ATC system.
System of Autonomous Rovers and Their Applications – Sahin, et al in Chapter 14, present a typical
test bed for system of systems in the realm of mobile robotics. Here a system of autonomous rovers will be
presented in the context of system of systems. In addition, a system of homogenous modular micro robots
will be presented in the context of system of systems. The chapter starts with the introduction of the
components and their roles in the system of autonomous rovers. Then, each system will be presented
focusing on electrical, mechanical and control characteristics and their capabilities in the system of
autonomous rovers. Robust data aggregation and mine detection are then examined as applications of the
system of autonomous rovers.
Space Applications of System of Systems – Caffall and Michael in Chapter 15, have started by referring
to future applications of SoS via the popular fictional space program on television – “Space…the Final
Frontier”. These are the voyages of the starship Enterprise. Its five-year mission: to explore strange new
worlds, to seek out new life and new civilizations, to boldly go where no man has gone before. The authors
asks the question: How many of us heard these words and dreamed of standing alongside Star Trek’s
Captain James T. Kirk and First Officer Mr. Spock to explore new worlds? Interesting enough, Chief
Engineer Commander Scott performs countless technological miracles as he saves his beloved USS
Enterprise and crew from certain destruction; however, Scotty never mentions the miracle of the
Enterprise as a wonderful system-of-systems. Could it be that future engineers solved all the problems of
system-of-systems? Could it be that Scotty never encountered problems with the system-of-systems
comprising the Enterprise, freeing him up to devote his time on advancing the interplanetary
communications, warp engine, phaser, transporter, deflector shield and other systems of the Enterprise?
Apparently not, at least as evidenced by, for instance, the emergent behavior of the Enterprise as it
interacts with a (fictitious) legacy unmanned scientific probe named Voyager 6 whose onboard systems
have been reconfigured and augmented by an alien race. The author further note that it is up to us to
advance the system-of-systems technology for the development of a space foundation that, indeed, may
lead to the Federation and star ships. While many folks almost exclusively think of space exploration as
the Shuttle Orbiter that has captured worldwide interest for over twenty-five years, space exploration is
multi-faceted. The National Aeronautics and Space Administration (NASA) has a extraordinary history
of space exploration to include the Rovers that continue to explore Mars, space telescopes that can see into
deep space, a human-inhabitable space station that orbits the Earth, unmanned spacecraft that explore the
Sun and the planets in our solar system, and the unforgettable lunar exploration that began on July 20,
1969 as Commander Neil Armstrong stepped onto the Moon’s surface. So, what is the relationship of
space exploration with a system-of-systems concept? Well, let us first consider space exploration
missions that are planned for the next couple of decades.
Airport Operations: A System of Systems Approach – Nahavandi, et al., in Chapter 16, have presented
a SoS approach t airport security. Analysis of airport operations is commonly performed in isolation,
sharing only simple information such as flight schedules. With the increased concern over security in our
airports a new approach is required whereby all aspects of the airport operations are considered. A System
of Systems methodology is proposed and demonstrated through example. This method provides the
decision maker with an improved understanding of the implication of policy decisions, resource
allocations and infrastructure investment strategies, through the capture of emergent behaviours and
interdependencies. New tools and methodologies are required for model development and analysis. These
tools and methods are presented in this paper.
KASERS in SoS Design – Rubin in Chapter 17 has used KASER – Knowledge Amplification by
Structured Expert Randomization as a tool for the SoS design. The author indicates that the U.S. Army
needs robotic combat vehicles that can autonomously navigate the battlefield and carry out planned
missions that necessarily embody unplanned details. On one end of the spectrum lie the simple insect-like
robots that have been popularized by Steel and Brooks [1995]. Their simple behaviors can be evolved
much in the same manner as a simple program can be created through the use of chance alone. Of course,
more complex behaviors cannot be tractably evolved because the search space here grows exponentially.
What is needed are heuristics to guide the evolutionary process. We can of course program search
strategies and have indeed programmed robots to perform a myriad of complex functions – from the robot
Manny’s (U.S. Army) ability to walk the battlefield to UAVs. What is needed is a means to program more
complex and reliable functionality for constant cost. That is, a System of Systems (SoS) is needed. For
example, one can program a robotic vehicle to sense and avoid an obstacle on the right say. But then, what
is the cost of programming the same robot to sense and avoid an obstacle on the left? It should be less and
is to some extent if object-oriented component-based programs are written. The problem here though is
that the cost is front loaded. The programmer needs to know a priori most of the domain symmetries if he
or she is to capture them in the form of objects. A better solution is to do for symbolic programming what
fuzzy logic did for Boolean logic [Zadeh, 1996; Rubin 1999]. That is, we need the programmer to be able
to constrain the robot’s behavior in the form generalized actions. Then, instances of these generalizations
constitute the desired program. Even search-control heuristics can be acquired through the exercise of this
paradigm. Instead of programming the robot to do a specific action, we program the robot to (heuristically)
search a space of actions for one or more that is consistent with environmental constraints. The writing of
such programs is easier for the human and the constraints that instantiate them serve to render the search
space tractable for the machine.
18 Johnson
In this section, for the benefit of the readers, a wider perspective on system of systems and system of
systems engineering from a recent work by the author [Jamshidi, 2008] will be given.
Standards of SoS – System of systems literature, definitions, and perspectives are marked with great
variability in the engineering community. Viewed as an extension of systems engineering to a means of
describing and managing social networks and organizations, the variations of perspectives leads to
difficulty in advancing and understanding the discipline. Standards have been used to facilitate a common
understanding and approach to align disparities of perspectives to drive a uniform agreement to definitions
and approaches. By having the ICSOS – International Consortium on System of Systems [De Larentis, et
al. 2007] represent to the IEEE and INCOSE for support of technical committees to derive standards for
system of systems will help unify and advance the discipline for engineering, healthcare, banking, space
exploration and all other disciplines that require interoperability among disparate systems [De Larentis
Open Systems Approach to System of Systems Engineering – Azani [2008] in Jamshidi [2008] has
discussed an open systems approach to SoSE. The author notes that SoS exists within a continuum that
contains ad-hoc, short-lived, and relatively speaking simple SoS on one end, and long lasting, continually
evolving, and complex SoS on the other end of the continuum. Military operations and less sophisticated
biotic systems (e.g., bacteria and ant colonies) are examples of ad-hoc, simple, and short lived SoS, while
galactic and more sophisticated biotic systems (e.g., ecosystem, human colonies) are examples of SoS at
the opposite end of the SoS continuum. The engineering approaches utilized by galactic SoS are at best
unknown and perhaps forever inconceivable. However, biotic SoS seem to follow, relatively speaking,
less complicated engineering and development strategies allowing them to continually learn and adapt,
grow and evolve, resolve emerging conflicts, and have more predictable behavior. Based on what the
author already knows about biotic SoS, it is apparent that these systems employ robust reconfigurable
architectures enabling them to effectively capitalize on open systems development principles and
strategies such as modular design, standardized interfaces, emergence, natural selection, conservation,
synergism, symbiosis, homeostasis, and self-organization. Azani [2008] provides further elaboration on
open systems development strategies and principles utilized by biotic SoS, discusses their implications for
engineering of man-made SoS, and introduces an integrated SoS development methodology for
engineering and development of adaptable, sustainable, and interoperable SoS based on open systems
principles and strategies.
SoS Integration – Integration is probably the key viability of any SoS. Integration of SoS implies that
each system can communicate and interact (control) with the SoS regardless of their hardware, software
characteristics or nature. This means that they need to have the ability to communicate with the SoS or a
part of the SoS without compatibility issues such as operating systems, communication hardware, and so
on. For this purpose, a SoS needs a common language the SoS’s systems can speak. Without having a
common language, the systems of any SoS cannot be fully functional and the SoS cannot be adaptive in the
sense that new components cannot be integrated to it without major effort. Integration also implies the
control aspects of the SoS because systems need to understand each other in order to take commands or
signals from other SoS systems. For further insight, see the work by Cloutier, et al [2008] on network
centric architecture of SoS.
Engineering of SoS – Emerging needs for a comprehensive look at the applications of classical systems
engineering issue in SoSE will be discussed in this volume. The thrust of the discussion will concern the
reality that the technological, human, and organizational issues are each far different when considering a
system of systems or federation of systems and that these needs are very significant when considering
system of systems engineering and management. As we have noted, today there is much interest in the
engineering of systems that are comprised of other component systems, and where each of the component
systems serves organizational and human purposes. These systems have several principal characteristics
that make the system family designation appropriate: operational independence of the individual systems,
managerial independence of the systems; often large geographic and temporal distribution of the
individual systems; emergent behavior, in which the system family performs functions and carries out
purposes that do not reside uniquely in any of the constituent systems but which evolve over time in an
adaptive manner and where these behaviors arise as a consequence of the formation of the entire system
family and are not the behavior of any constituent system. The principal purposes supporting engineering
of these individual systems and the composite system family are fulfilled by these emergent behaviors.
Thus, a system of systems is never fully formed or complete. Development of these systems is
evolutionary and adaptive over time, and structures, functions, and purposes are added, removed, and
modified as experience of the community with the individual systems and the composite system grows and
evolves. The systems engineering and management of these systems families poses special challenges.
This is especially the case with respect to the federated systems management principles that must be
utilized to deal successfully with the multiple contractors and interests involved in these efforts. Please
refer to the paper by Sage and Biemer [2007] and De Larentis, et al. [2007] for the creation of a SoS
Consortium (ICSOS) of concerned individuals and organizations by the author of this chapter. See Wells
and Sage [2008] for more information and challenges ahead in SoSE.
SoS Management: The Governance of Paradox – Sauser and Boardman [2008] in Jamshidi [2008] have
presented an SoS approach to the management problem. They note that the study of SoS has moved many
to support their understanding of these systems through the groundbreaking science of networks. The
understanding of networks and how to manage them may give one the fingerprint which is independent of
the specific systems that exemplify this complexity. The authors point out that it does not matter whether
they are studying the synchronized flashing of fireflies, space stations, structure of the human brain, the
internet, the flocking of birds, a future combat system or the behavior of red harvester ants. The same
emergent principles apply: large is really small; weak is really strong; significance is really obscure; little
means a lot; simple is really complex; and, complexity hides simplicity. The conceptual foundation of
complexity is paradox, which leads us to a paradigm shift in the SE (systems engineering) body of
Paradox exists for a reason and there are reasons for systems engineers to appreciate paradox even
though they may be unable to resolve them as they would a problem specification into a system solution.
Hitherto paradoxes have confronted current logic only to yield at a later date to more refined thinking. The
existence of paradox is always the inspirational source for seeking new wisdom, attempting new thought
patterns and ultimately building systems for the “flat world.” It is our ability to govern, not control, these
paradoxes that will bring new knowledge to our understanding on how to manage the emerging complex
systems called System of Systems.
Sauser and Boardman [2008] have established a foundation in what has been learnt about how one
practices project management, establish some key concepts and challenges that make the management of
SoS different from our fundamental practices, present an intellectual model for how they classify and
manage a SoS, appraise this model with recognized SoS, and conclude with grand challenges for how they
may move their understanding of SoS management beyond the foundation.
Deepwater Coastguard Program – One of the earliest realization of a SoS in the United States is the
so-called Deepwater Coastguard Program shown in Figure 1). As seen here, the program takes advantage
of all the necessary assets at their disposal, e.g. helicopters, aircrafts, cutters, satellite (GPS), ground
station, human, computers, etc. – all systems of the SoS integrated together to react to unforeseen
circumstances to secure the coastal borders of the Southeastern United States, e.g. Florida Coast. The
Deepwater program is making progress in the development and delivery of mission effective command,
control, communications, computers, intelligence, surveillance, and reconnaissance (C4ISR) equipment
[Keeter 2007]. The SoS approach, the report goes on, has “improved the operational capabilities of legacy
cutters and aircraft, and will provide even more functionality when the next generation of surface and air
platforms arrives in service. “ The key feature of the system is its ability to interoperate among all Coast
Guard mission assets and capabilities with those of appropriate authorities both at local and federal levels.
Figure 1. A security example of a SoS – Deepwater coastguard configuration in US
Future Combat Missions – Another national security or defense application of SoS is the future combat
mission (FCM). Figure 2) shows one of numerous possible configuration of an FCM. The FCM system is
“envisioned to be an ensemble of manned and potentially unmanned combat systems, designed to ensure
that the Future Force is strategically responsive and dominant at every point on the spectrum of operations
from non-lethal to full scale conflict. FCM will provide a rapidly deployable capability for mounted tactical
operations by conducting direct combat, delivering both line-of-sight and beyond-line-of-sight precision
munitions, providing variable lethal effect (non-lethal to lethal), performing reconnaissance, and
transporting troops. Significant capability enhancements will be achieved by developing multi-functional,
multi-mission and modular features for system and component commonality that will allow for multiple
state-of-the-art technology options for mission tailoring and performance enhancements. The FCM force
will incorporate and exploit information dominance to develop a common, relevant operating picture and
achieve battle space situational understanding” [Global Security Organization, 2007].
Figure 2. A defense example of a SoS (Courtesy, Don Walker, Aerospace Corporation)
Systems Engineering for the Department of Defense System of Systems – Dahmann and Baldwin
[2008] in Jamshidi [2008], have addressed the national defense aspects of SoS. Military operations are the
synchronized efforts of people and systems toward a common objective. In this way from an operational
perspective, defense is essentially a ‘systems of systems’ (SoS) enterprise. However, despite the fact that
today almost every military system is operated as part of a system of systems, most of these systems were
designed and developed without the benefit of systems engineering at the SoS level factoring the role the
system will play in the broader system of systems context. With changes in operations and technology, the
need for systems that work effectively together is increasingly visible.
Sensor Networks – The main purpose of sensor networks is to utilize the distributed sensing capability
provided by tiny, low powered and low cost devices. Multiple sensing devices can be used cooperatively
and collaboratively to capture events or monitor space more effectively than a single sensing device
[Sridhar, et. al., 2007]. The realm of applications for sensor networks is quite diverse, which include
military, aerospace, industrial, commercial, environmental, health monitoring, to name a few. Applications
include: traffic monitoring of vehicles, cross-border infiltration detection and assessment, military
reconnaissance and surveillance, target tracking, habitat monitoring and structure monitoring, etc.
Communication capability of these small devices and often with heterogeneous attributes makes
them good candidates for system of systems. Numerous issues exist with sensor networks such as data
integrity, data fusion and compression, power consumption, multi-decision making, and fault tolerance all
make these SoS very challenging just like other SoS. It is thus necessary to devise a fault-tolerant
mechanism with a low computation overhead to validate the integrity of the data obtained from the sensors
(“systems”). Moreover, a robust diagnostics and decision making process should aid in monitoring and
control of critical parameters to efficiently manage the operational behavior of a deployed sensor network.
Specifically, Sridhar, et al [2008]. will focus on innovative approaches to deal with multi-variable
multi-space problem domain as well as other issues, in wireless sensor networks within the framework of a
SoS. In this book, see Chapter 11 by Wu, et. Al. for a SoS approach in treating sensor networks.
Healthcare Systems – Under a 2004 Presidential Order, the US Secretary of Health has initiated the
development of a National Healthcare Information Network (NHIN), with the goal of creating a nationwide
information system that can build and maintain Electronic Health Records (EHRs) for all citizens by 2014.
The NHIN system architecture currently under development will provide a near-real-time heterogeneous
integration of disaggregated hospital, departmental, and physician patient care data, and will assemble and
present a complete current EHR to any physician or hospital a patient consults [Sloane 2006]. The NHIN
will rely on a network of independent Regional Healthcare Information Organizations (RHIOs) that are
being developed and deployed to transform and communicate data from the hundreds of thousands of
legacy medical information systems presently used in hospital departments, physician offices, and
telemedicine sites into NHIN-specified meta-formats that can be securely relayed and reliably interpreted
anywhere in the country. The NHIN “network of networks” will clearly be a very complex SoS, and the
performance of the NHIN and RHIOs will directly affect the safety, efficacy, and efficiency of healthcare in
the US. Simulation, modeling, and other appropriate SoSE tools are under development to help ensure
reliable, cost-effective planning, configuration, deployment, and management of the heterogeneous,
life-critical NHIN and RHIO systems and subsystems [Sloane, et al. 2007]. ICSOS represents an invaluable
opportunity to access and leverage SoSE expertise already under development in other industry and
academic sectors. ICSOS also represents an opportunity to discuss the positive and negative emergent
behaviors that can significantly affect personal and public health status and the costs of healthcare in the US
[DeLarentis, et al. 2007].
Global Earth Observation System of Systems – GEOSS is a global project consisting of over 60 nations
whose purpose is to address the need for timely, quality, long-term, global information as a basis for sound
decision making [Butterfield, et al, 2006]. Its objectives are: (i) Improved coordination of strategies and
systems for Earth observations to achieve a comprehensive, coordinated, and sustained Earth observation
system or systems;, (ii) A coordinated effort to involve and assist developing countries in improving and
sustaining their contributions to observing systems, their effective utilization of observations and the
related technologies, and (iii) The exchange of observations recorded from in situ, air full and open
manner with minimum time delay and cost. In GEOSS, the “SoSE Process provides a complete, detailed,
and systematic development approach for engineering systems of systems. Boeing’s new
architecture-centric, model-based systems engineering process emphasizes concurrent development of the
system architecture model and system specifications. The process is applicable to all phases of a system’s
lifecycle. The SoSE Process is a unified approach for system architecture development that integrates the
views of each of a program’s participating engineering disciplines into a single system architecture model
supporting civil and military domain applications” [Pearlman 2006]. ICSoS will be another platform for
all concerned around the globe to bring the progress and principles of GEOSS to formal discussions and
examination on an annual basis.
ar Profil
Weather Systems
Integrated Storm
Impact & Response
Measurements &
California Pictures
Figure 3. SoS of the GEOSS Project (Courtesy, Jay Pearlaman, Boeing Company)
E-enabling and SoS Aircraft Design via SoSE – A case of aeronautical application of SoS worth noting
is that of E-enabling in aircraft design as a system of a SoS at Boeing Commercial Aircraft Division
[Wilber 2008]. The project focused on developing a strategy and technical architecture to facilitate making
the airplane (Boeing 787, see Figure 4 ) network-aware and capable of leveraging computing and network
advances in industry. The project grew to include many ground based architectural components at the
airlines and at the Boeing factory, as well as other key locations such as the airports, suppliers and
terrestrial Internet Service Suppliers (ISPs).
Wilber [2008] points out that the e-Enabled project took on the task of defining a system of systems
engineering solution to problem of interoperation and communication with the existing, numerous and
diverse elements that make up the airlines’ operational systems (flight operations and maintenance
operations). The objective has been to find ways of leveraging network-centric operations to reduce
production, operations and maintenance costs for both Boeing and the airline customers.
One of the key products of this effort is the “e-Enabled Architecture”. The e-Enabling Architecture is
defined at multiple levels of abstraction. There is a single top-level or “Reference Architecture” that is
necessarily abstract and multiple “Implementation Architectures”. The implementation architectures
map directly to airplane and airline implementations and provide a family of physical solutions that all
exhibit common attributes and are designed to work together and allow re-use of systems components.
The implementation architectures allow for effective forward and retrofit installations addressing a wide
range of market needs for narrow and widebody aircraft.
The 787 “Open Data Network” is a key element of one implementation of this architecture. It
enabled on-board and off-board elements to be networked in a fashion that is efficient, flexible and
secure. The fullest implementations are best depicted in Boeing’s GoldCare Architecture and
Wilber [2008] presented an architecture at the reference level and how it has been mapped into the 787
airplane implementation. GoldCare environment is described and is used as an example of the full
potential of the current e-enabling.
Figure 4a. Boeing’s 787 Dreamliner
Figure 4b. E-Enabling Sos fro Boeing 787
Figure 4. Application of a SoS for the Boeing 787
A Systems of Systems perspective on Infrastructures – Thissen and Herder [2008] in Jamshidi [2008]
have touched upon a very important application in the service industry. Infrastructure Systems (or
infrasystems) providing services such as energy, transport, communications, and clean and safe water are
vital to the functioning of modern society. Key societal challenges with respect to our present and future
infrastructure systems relate to, among other things, safety and reliability, affordability, and transitions to
sustainability. Infrasystem complexity precludes simple answers to these challenges. While each of the
infrasystems can be seen as a complex system of systems in itself, increasing interdependency among these
systems (both technologically and institutionally) adds a layer of complexity.
One approach to increased understanding of complex infrasystems that has received little attention in the
engineering community thus far is to focus on the commonalities of the different sectors, and to develop
generic theories and approaches such that lessons from one sector could easily be applied to other sectors.
The system of systems paradigm offers interesting perspectives in this respect. The authors present, as an
initial step in this direction, a fairly simple three-level model distinguishing the physical/technological
systems, the organisation and management systems, and the systems and organisations providing
infrastructure related products and services. The authors use the model as a conceptual structure to identify
a number of key commonalities and differences between the transport, energy, drinking water, and ICT
sectors. Using two energy related examples, the authors further illustrate some of the system-of-systems
“the real-time connectivity of the
airplane to the ground, the delivery
of information across the
related complexities of analysis and design at a more operational level. The authors finally discuss a
number of key research and engineering challenges related to infrastructure systems, with a focus on the
potential contributions of systems of systems perspectives.
A System of Systems View of Services – Tien [2008] in Jamshidi [2008] has covered a very important
applications of SoS in our today’s global village – service industry. The services sector employs a large
and growing proportion of workers in the industrialized nations, and it is increasingly dependent on
information technology. While the interdependences, similarities and complementarities of manufacturing
and services are significant, there are considerable differences between goods and services, including the
shift in focus from mass production to mass customization (whereby a service is produced and delivered in
response to a customer’s stated or imputed needs). In general, a service system can be considered to be a
combination or recombination of three essential components – people (characterized by behaviors,
attitudes, values, etc.), processes (characterized by collaboration, customization, etc.) and products
(characterized by software, hardware, infrastructures, etc.). Furthermore, inasmuch as a service system is
an integrated system, it is, in essence, a system of systems which objectives are to enhance its efficiency
(leading to greater interdependency), effectiveness (leading to greater usefulness), and adaptiveness
(leading to greater responsiveness). The integrative methods include a component’s design, interface and
interdependency; a decision’s strategic, tactical and operational orientation; and an organization’s data,
modeling and cybernetic consideration. A number of insights are also provided, including an alternative
system of systems view of services; the increasing complexity of systems (especially service systems),
with all the attendant life-cycle design, human interface, and system integration issues; the increasing need
for real-time, adaptive decision making within such systems of systems; and the fact that modern systems
are also becoming increasingly more human-centered, if not human-focused – thus, products and services
are becoming more complex and more personalized or customized.
System of Systems Engineering in Space Exploration – Jolly and Muirhead [2008], in Jamshidi [2008]
have covered SOSE topics that are largely unique for Space Exploration with the intent to provide the
reader a discussion of the key issues, the major challenges of the twenty-first century in moving from
systems engineering to SOSE, potential applications in the future, and the current state-of-the-art. Specific
emphasis is placed on how software and electronics are revolutionizing the way space missions are being
designed, including both the capabilities and vulnerabilities introduced. The role of margins, risk
management, and interface control are all critically important in current space mission design and
execution – but in SOSE applications they become paramount. Similarly, SOSE space missions will have
extremely large, complex, and intertwined command and control and data distribution ground networks,
most of which will involve extensive parallel processing to produce tera-to-petabytes of products per day
and distribute them worldwide.
Robotic swarms as a SoS – As another application of SoS, a robotic swarm is considered by Sahin [2008]
in Jamshidi [2008]. A robotic swarm based on ant colony optimization and artificial immune systems is
considered. In the ant colony optimization, the author has developed a multi agent system model based on
the food gathering behaviors of the ants. Similarly, a multi agent system model is developed based on the
human immune system. These multi agent system models, then, tested on the mine detection problem. A
modular micro robot is designed to perform to emulate the mine detection problem in a basketball court.
The software and hardware components of the modular robot are designed to be modular so that robots can
be assembled using hot swappable components. An adaptive TDMA communication protocol is
developed in order to control connectivity among the swarm robots without the user intervention.
Communication & Navigation in Space SoS – Bahsin and Hayden [2008] in Jamshidi [2008] have taken
upon the challenges in communication and navigation for space SoS. They indicate that communication
and navigation networks provide critical services in the operation, system management, information
transfer, and situation awareness to the space system of systems. In addition, space systems of systems are
requiring system interoperability, enhanced reliability, common interfaces, dynamic operations, and
autonomy in system management. New approaches to communications and navigation networks are
required to enable the interoperability needed to satisfy the complex goals and dynamic operations and
activities of the space system of systems. Historically space systems had direct links to Earth ground
communication systems, or they required a space communication satellite infrastructure to achieve higher
coverage around the Earth. It is becoming increasingly apparent that many systems of systems may include
communication networks that are also systems of systems. These communication and navigation networks
must be as nearly ubiquitous as possible and accessible on the demand of the user, much like the cell phone
link is available at any time to an Earth user in range of a cell tower. The new demands on communication
and navigation networks will be met by space Internet technologies. It is important to bring Internet
technologies, Internet Protocols (IP), routers, servers, software, and interfaces to space networks to enable
as much autonomous operation of those networks as possible. These technologies provide extensive
savings in reduced cost of operations. The more these networks can be made to run themselves, the less
humans will have to schedule and control them. The Internet technologies also bring with them a very
large repertoire of hardware and software solutions to communication and networking problems that
would be very expensive to replicate under a different paradigm. Higher bandwidths are needed to support
the expected voice, video, and data transfer traffic for the coordination of activities at each stage of an
exploration mission.
Existing communications, navigation, and networking have grown in an independent fashion with
experts in each field solving the problem just for that field. Radio engineers designed the payloads for
today’s “bent pipe” communication satellites. The Global Positioning satellite (GPS) system design for
providing precise Earth location determination is an extrapolation of the LOng RAnge Navigation
(LORAN) technique of the 1950’s where precise time is correlated to precise position on the Earth. Other
space navigation techniques use artifacts in the RF communication path (Doppler shift of the RF and
transponder-reflected ranging signals in the RF) and time transfer techniques to determine the location and
velocity of a spacecraft within the solar system. Networking in space today is point-to-point among ground
terminals and spacecraft, requiring most communication paths to/from space to be scheduled such that
communications is available only on an operational plan and is not easily adapted to handle
multidirectional communications under dynamic conditions.
Bahsin and Hayden [2008] begins with a brief history of the communications, navigation, and
networks of the 1960s and 1970s in use by the first system of systems, the NASA Apollo missions; it is
followed by short discussions of the communication and navigation networks and architectures that the
DoD and NASA employed from the 1980s onwards. Next is a synopsis of the emerging space system of
systems that will require complex communication and navigation networks to meet their needs.
Architecture approaches and processes being developed for communication and navigation networks in
emerging space system and systems are also described. Several examples are given of the products
generated in using the architecture development process for space exploration systems. The architecture
addresses the capabilities to enable voice, video, and data interoperability needed among the explorers
during exploration, while in habitat, and with Earth operations. Advanced technologies are then described
that will allow space system of systems to operate autonomously or semi-autonomously.
National Security – Perhaps one of the most talked-about application areas of SoSE is national security.
After many years of discussion the goals, merits and attributes of SoS, very few tangible results or solutions
have appeared in this or other areas of this technology. It is commonly believed that, “Systems Engineering
tools, methods, and processes are becoming inadequate to perform the tasks needed to realize the systems of
systems envisioned for future human endeavors. This is especially becoming evident in evolving national
security capabilities realizations for large-scale, complex space and terrestrial military endeavors.
Therefore the development of Systems of Systems Engineering tools, methods and processes is imperative
to enable the realization of future national security capabilities,” [Walker 2007]. In most SoSE applications,
heterogeneous systems (or communities) are brought together to cooperate for a common good and
enhanced robustness and performance. “These communities range in focus from architectures, to lasers, to
complex systems, and will eventually cover each area involved in aerospace related national security
endeavors. These communities are not developed in isolation in that cross-community interactions on
terminology, methods, and processes are done,” [Walker 2007]. The key is to have these communities
work together to guarantee the common goal of making our world a safer place for all.
Electric Power Systems Grids as SoS – Hiskens and Korba [2008] in Jamshidi [2008] provide an
overview of the systems of systems that are fundamental to the operation and control of electrical power
systems. Perspectives are drawn from industry and academia, and reflect theoretical and practical
challenges that are facing power systems in an era of energy markets and increasing utilization of
renewable energy resources (see also Duffy, et al. [2008]). Power systems cover extensive geographical
regions, and are composed of many diverse components. Accordingly, power systems are large-scale,
complex, dynamical systems that must operate reliably to supply electrical energy to customers. Stable
operation is achieved through extensive monitoring systems, and a hierarchy of controls, that together seek
to ensure total generation matches consumption, and that voltages remain at acceptable levels. Safety
margins play an important role in ensuring reliability, but tend to incur economic penalties. Significant
effort is therefore being devoted to the development of demanding control and supervision strategies that
enable reduction of these safety margins, with consequent improvements in transfer limits and
SoS Approach for Renewable Energy – Duffy, et. al. [2008] in Jamshidi [2008] have detailed the SoS
approach to sustainable supply of energy. They note that over one-half of the petroleum consumed in the
United States is imported, and that percentage is expected to rise to 60% by 2025. America’s
transportation system of systems relies almost exclusively on refined petroleum products, accounting for
over two-thirds of the oil used. Each day, over eight million barrels of oil
are required to fuel over 225
million vehicles
that constitute the U.S. light-duty transportation fleet. The gap between U.S. oil
production and transportation oil needs is projected to grow, and the increase in the number of light-duty
vehicles will account for most of that growth. On a global scale, petroleum supplies will be in increasingly
higher demand as highly-populated developing countries expand their economies and become more
energy intensive. Clean forms of energy are needed to support sustainable global economic growth while
mitigating impacts on air quality and the potential effects of greenhouse gas emissions. USA’s growing
dependence on foreign sources of energy threatens her national security. As a nation, the authors assert
that, we must work to reduce our dependence on foreign sources of energy in a manner that is affordable
and preserves environmental quality.
Sustainable Environmental Management from a System of Systems Engineering Perspective –
Hipel, et al. [2008] in Jamshidi [2008] have provided a rich range of decision tools from the field of SE are
described for addressing complex environmental SoS problems in order to obtain sustainable, fair and
responsible solutions to satisfy as much as possible the value systems of stakeholders, including the
natural environment and future generations who are not even present at the bargaining table. To better
understand the environmental problem being investigated and thereby eventually reach more informed
decisions, the insightful paradigm of a system of systems can be readily utilized. For example, when
developing solutions to global warming problems, one can envision how societal systems, such as
agricultural and industrial systems, interact with the atmospheric system of systems, especially at the
tropospheric level. The great import of developing a comprehensive toolbox of decision methodologies
and techniques is emphasized by pointing out many current pressing environmental issues, such as global
warming and its potential adverse affects, and the widespread pollution of our land, water and air systems
of systems. To tackle these large-scale complex systems of systems problems, systems engineering
decision techniques that can take into account multiple stakeholders having multiple objectives are
explained according to their design and capabilities. To illustrate how systems decision tools can be
employed in practice to assist in reaching better decisions for benefiting society, different decision tools
are applied to three real-world systems of systems environmental problems. Specifically, the Graph Model
for Conflict Resolution is applied to the international dispute over the utilization of water in the Aral Sea
Basin; a large-scale optimization model founded upon concepts from cooperative game theory, economics
and hydrology is utilized for systematically investigating the fair allocation of scarce water resources
among multiple users in the South Saskatchewan River Basin in Western Canada; and multiple criteria
decision analysis methods are used to evaluate and compare solutions to handling fluctuating water levels
in the five Great Lakes located along the border of Canada and the USA [Wang, et. al. 2007].
Transportation Systems – The National Transportation System (NTS) can be viewed as a collection of
layered networks composed by heterogeneous systems for which the Air Transportation System (ATS) and
its National Airspace System (NAS) is one part. At present, research on each sector of the NTS is generally
conducted independently, with infrequent and/or incomplete consideration of scope dimensions (e.g.
multi-modal impacts and policy, societal, and business enterprise influences) and network interactions (e.g.
layered dynamics within a scope category). This isolated treatment does not capture the higher level
interactions seen at the NTS or ATS architecture level; thus, modifying the transportation system based on
limited observations and analyses may not necessarily have the intended effect or impact. A systematic
method for modeling these interactions with a system-of-systems (SoS) approach is essential to the
formation of a more complete model and understanding of the ATS, which would ultimately lead to better
outcomes from high-consequence decisions in technological, socio-economic, operational and political
policy-making context [De Laurentis 2005]. This is especially vital as decision-makers in both the public
and private sector, for example at the inter-agency Joint Planning and Development Office (JPDO) which is
charged with transformation of air transportation, are facing problems of increasing complexity and
uncertainty in attempting to encourage the evolution of superior transportation architectures [De Laurentis
and Callaway 2006].
Keating [2008] in Jamshidi [2008] has also provided insight into this important aspect of SoS. Emergent
behavior of a SoS resembles the slow down of the traffic going through a tunnel, even in the absence of any
lights, obstacles or accident. A tunnel, automobiles and the highway, as systems of a SoS, have an
emergent behavior or property in slowing down [Morley, 2006]. Fisher [2006] has noted that a SoS can not
achieve its goals depends on its emergent behaviors. The author explores “interdependencies among
systems, emergence, and interoperation” and develops maxim-like findings such as these: 1. Because they
cannot control one another, autonomous entities can achieve goals that are not local to themselves only by
increasing their influence through cooperative interactions with others. 2. Emergent composition is often
poorly understood and sometimes misunderstood because it has few analogies in traditional systems
engineering. 3. Even in the absence of accidents, tight coupling can ensure that a system of systems is
unable to satisfy its objectives. 4. If it is to remain scalable and affordable no matter how large it may
become, a system’s cost per constituent must grow less linearly with its size. 5. Delay is a critical aspect of
systems of systems.
This chapter is written to serve as an introduction to the book. We also gave an up-to-date state of the art in
systems of systems and systems of systems engineering based on other works of the author. The subject
matter of this book is an unsettled topic in engineering in general and in systems engineering in particular.
Attempt has been made to cover as many open questions in both theory and applications of SoS and SoSE.
It is our intention that this book would be the beginning of much debate and challenges among and by the
readers of this book. The book is equally intended to benefit industry, academia or government. A sister
volume, by the author, on the subject is under press at the present time and can give readers further insight
into SoS [Jamshidi 2008].
Abbott, R. 2006, “Open at the Top; Open at the Bottom; and Continually (but Slowly) Evolving,”
Proc. of IEEE International Conference on System of Systems Engineering, Los Angeles, April 2006.
Abel, A. and Sukkarieh, S. 2006, “The Coordination of Multiple Autonomous Systems using
Information Theoretic Political Science Voting Models, Proc. of IEEE International Conference on
System of Systems Engineering, Los Angeles, April 2006.
ANSI/IEEE 1471-2000 – Recommended Practice for Architecture Description of
Software-Intensive Systems, Institute Of Electrical And Electronics Engineers, 2000.
Asimow, M., 1962, Introduction to Design, Prentice-Hall, 1962.
Azani, C. 2008, “An Open Systems Approach to System of Systems Engineering” System of Systems
Engineering – Innovations for the 21st Century, (M. Jamshidi, Ed.), John Wiley Series on Systems
Engineering, New York, 2008.
Azarnoosh H., Horan B., Sridhar P., Madni A. M., Jamshidi M., 2006, “Towards optimization of a
real-world robotic-sensor system of systems”, in the Proceedings of World Automation Congress
(WAC) 2006, July 24-26, Budapest, Hungary.
Butterfield, M. L., J. Pearlman, and S. C. Vickroy, 2006,” System-of-Systems Engineering in a Global
Environment,” Proceedings of International Conference on Trends in Product Life Cycle,Modeling,
Simulation and Synthesis PLMSS, 2006
Carlock, P. G., and R. E. Fenton, 2001, “System of Systems (SoS) Enterprise Systems for
Information-Intensive Organizations,” Systems Engineering, Vol. 4, No. 4, pp. 242-261, 2001.
Cloutier, R. M. J. DiMario, H. W. Polzer, 2008,“Net-Centricity and System of Systems,” System of
Systems Engineering – Innovations for the 21st Century, (M. Jamshidi, Ed.), John Wiley Series on
Systems Engineering, New York, 2008.
Crossley, W. A., 2004, “System of Systems: An Introduction of Purdue University Schools of
Engineering’s Signature Area,” Engineering Systems Symposium, March 29-31 2004, Tang Center –
Wong Auditorium, MIT.
Dahmann, J. and K. Baldwin, 2008, “Systems Engineering for Department of Defense Systems of Systems ,
“System of Systems Engineering – Innovations for the 21st Century, Chapter 9, (M. Jamshidi, Ed.), John Wiley
Series on Systems Engineering, New York, 2008.
Dagli, C. H. and N. K. Ergin 2008, “System of Systems Architecting,” System of Systems Engineering
– Innovations for the 21st Century, (M. Jamshidi, Ed.), John Wiley Series on Systems Engineering,
New York, 2008.
De Laurentis, D.A., 2005, “Understanding Transportation as a System-of-Systems Design,
Problem,” AIAA Aerospace Sciences Meeting and Exhibit, 10-13 Jan. 2005. AIAA-2005-123.
De Laurentis, D.A., Callaway, R.K., 2006, “A System-of-Systems Perspective for Future Public
Policy,” Review of Policy Research, Vol. 21, Issue 6, Nov. 2006.
De Laurentis , D., C. Dickerson, M. Di Mario, P. Gartz, M. Jamshidi, S. Nahavandi, A. Sage, E.
Sloane, D. Walker, 2007,’ A Case for an International Consortium on System of Systems
Engineering” IEEE Systems Journal, Volume 1, No. 1, pp. 68-73, 2007.
De Larentis, D., 2008, “Understanding Transportation as a System-of-Systems Problem,” System of
Systems Engineering – Innovations for the 21st Century, Chapter 20, (M. Jamshidi, Ed.), John Wiley
Series on Systems Engineering, New York, 2008.
DiMario, M., J., 2006, “System of Systems Interoperability Types and Characteristics in Joint
Command and Control,” Proc. of IEEE International Conference on System of Systems Engineering,
Los Angeles, April 2006.
Duffy, M. B. Garrett, C. Riley and D. Sandor, “Future Transportation Fuel System of Systems ,” System of
Systems Engineering – Innovations for the 21st Century, Chapter 17, (M. Jamshidi, Ed.), John Wiley Series on
Systems Engineering, New York, 2008.
Fisher, D., 2006, An Emergent Perspective on Interoperation in Systems of Systems,
(CMU/SEI-2006-TR- 003). Pittsburgh, PA: Software Engineering Institute, Carnegie Mellon
University, 2006.
Gladwell, M. 2005 Blink: The Power of Thinking Without Thinking, Little, Brown and Company,
Time Warner Book Group, New York, 2005.
Global Security Organization, 2007,
Hipel, K., A. Obeidi, L. Fang and D. M. Kilgour, 2008, “Sustainable Environmental Management
From A System Of Systems Engineering Perspective ,”System of Systems Engineering – Innovations
for the 21st Century, Chapter 11, (M. Jamshidi, Ed.), John Wiley Series on Systems Engineering, New
York, 2008.
Jamshidi, M., 2005, “Theme of the IEEE SMC 2005, Waikoloa, Hawaii, USA”, http://ieeesmc2005., October 2005.
Jamshidi, M. 2008, System of Systems Engineering – Innovations for the 21st Century, Wiley & Sons,
Inc., New York, 2008.
Jamshidi, M. 2008, “Introduction to System of Systems Engineering,” System of Systems
Engineering – Innovations for the 21st Century, Chapter 1, (M. Jamshidi, Ed.),Wiley & Sons, Inc.,
New York, 2008.
Jolly, S. D. and B. Muirhead, 2008, “Communication and Navigation Networks In Space System of
Systems System of Systems Engineering – Innovations for the 21st Century, Chapter 15, (M. Jamshidi,
Ed.), John Wiley Series on Systems Engineering, New York, 2008.
Keating, C. B. 2008,“Emergence in System of Systems” System of Systems Engineering – Innovations
for the 21st Century, (M. Jamshidi, Ed.), John Wiley Series on Systems Engineering, New York, 2008.
Keeter, H. C. 2007, “ Deepwater Command, Communication, Sensor Electronics Build Enhanced
Operational Capabilities,” US Coastguard Deepwater Prorgam site,
media/ feature/july07/c4isr072007.htm
Korba, P. and I. A. Hiskins, 2008, “Operation and Control of Electrical Power Systems,” System of
Systems Engineering – Innovations for the 21st Century, Chapter 16, (M. Jamshidi, Ed.), John Wiley
Series on Systems Engineering, New York, 2008.
Kotov, V., “Systems of Systems as Communicating Structures,” Hewlett Packard Computer Systems
Laboratory Paper HPL-97-124, pp. 1-15, 1997.
Lopez, D., 2006, “Lessons Learned From the Front Lines of the Aerospace,” Proc. of IEEE
International Conference on System of Systems Engineering, Los Angeles, April 2006.
Luskasik, S.J., 1998, “Systems, Systems of Systems, and the Education of Engineers,”Artificial
Intelligence for Engineering Design, Analysis, and Manufacturing, Vol. 12, No. 1, pp. 11-60, 1998.
Meilich, A., 2006, “System of Systems (SoS) Engineering & Architecture Challenges in a Net Centric
Environment,” Proc. of IEEE International Conference on System of Systems Engineering, Los
Angeles, April 2006.
Manthorpe, W.H., 1996, “The Emerging Joint System of Systems: A Systems Engineering Challenge
and Opportunity for APL,” John Hopkins APL Technical Digest, Vol. 17, No. 3, pp. 305-310, 1996.
Mittal, S. B. P. Zeigler, J. L. R. Martin and F. Sahin. 2008,“? Modeling and Simulation for Systems of
Systems Engineering,” Systems Engineering – Innovations for the 21st Century, (M. Jamshidi, Ed.),
John Wiley Series on Systems Engineering, New York, 2008.
Morley, J., 2006, Five Maxims about Emergent Behavior in Systems of Systems, http://www.sei., 2006
Pearlamn, J., 2006, GEOSS- Global Earth Observation System of Systems, Keynote presentation,
2006 IEEE SoSE Conference, Los Angeles, CA, USA, April 24, 2006.
Pei, R.S., 2000, “Systems of Systems Integration (SoSI) – A Smart Way of Acquiring Army C4I2WS
Systems,” Proceedings of the Summer Computer Simulation Conference, pp. 134-139, 2000.
Sage, A. P. and C. D. Cuppan, 2001, “On the Systems Engineering and Management of Systems of
Systems and Federations of Systems,” Information, Knowledge, Systems Management, Vol. 2, No. 4,
pp. 325-34, 2001.
Sage, A. P. and S. M. Biemer, 2007, “Processes for System Family Architecting, Design, and
Integration,”IEEE Systems Journal, ISJ1-1, September, pp. 5-16, 2007.
Sahin, F., 2008, “Robotic Swarm as a System of Systems,” System of Systems Engineering – Innovations for
the 21st Century, Chapter 19, (M. Jamshidi, Ed.), John Wiley Series on Systems Engineering, New York,
Sahin, F., M. Jamshidi, and P. Sridhar, 2007, “A Discrete Event XML based Simulation Framework
for System of Systems Architectures,” Proceedings the IEEE International Conference on System of
Systems, April 2007.
Saurabh M., S., B. P. Zeigler, J. L. Risco Martín,F. Sahin,and M. Jamshidi, ” Modeling and
Simulation for Systems of Systems Engineering, “ System of Systems Engineering – Innovations for
the 21st Century, (M. Jamshidi, Ed.), John Wiley Series on Systems Engineering, New York, 2008.
Sauser, B., J. Boardman, “System of Systesm management,”System of Systems Engineering –
Innovations for the 21st Century, Chapter 8, (M. Jamshidi, Ed.), John Wiley Series on Systems
Engineering, New York, 2008.
Sloane, E. 2006, “Understanding the Emerging National Healthcare IT Infrastructure,“24×7
Magazine. December, 2006.
Sloane, E., T. Way, V. Gehlot and R. Beck, 2007, “Conceptual SoS Model and Simulation Systems
for A Next Generation National Healthcare Information Network (NHIN-2)”, Proceedings of the
1st Annual IEEE Systems Conference, Honolulu, HI, April 9-12, 2007.
Sridhar, P., A. M. Madni, M. Jamshidi, 2007, “Hierarchical Aggregation and Intelligent Monitoring
and Control in Fault-Tolerant Wireless Sensor Networks,”IEEE Systems Journal, Volume1, No. 1,
September, 2007, pp.38-54.
Thussen, W. and P. M. Herder, 2008, “System of Systems Perspectives on Infrastructures,” System of
Systems Engineering – Innovations for the 21st Century, Chapter 11, (M. Jamshidi, Ed.), John Wiley
Series on Systems Engineering, New York, 2008.
Tien, J. M., 2008, “A System of Systems View of Services – Innovations for the 21st Century, Chapter 13, (M.
Jamshidi, Ed.), John Wiley Series on Systems Engineering, New York, 2008.
Walker, D., 2007 “Realizing a Corporate SOSE Environment”, Keynote presentation, 2007 IEEE
SoSE Conference, San Antonio, USA, 18 April 2007.
Wang, L., L. Fang, and K. W. Hipel, 2007,” On Achieving Fairness in the Allocation of Scarce
Resources: Measurable Principles and Multiple Objective Optimization Approaches,” IEEE Systems
Journal, Volume 1, No. 1, pp.17-28, 2007.
Wells, G. D. and A. P. Sage 2008, “Engineering of a System of Systems,” System of Systems
Engineering – Innovations for the 21st Century, (M. Jamshidi, Ed.), John Wiley Series on Systems
Engineering, New York, 2008.
Wickramasingh, N., S. Chalaani, R, V. Boppana, and A. M. Madni, 2008, “Healthcare System of
Systems,” System of Systems Engineering – Innovations for the 21st Century, Chapter 11, (M.
Jamshidi, Ed.), John Wiley Series on Systems Engineering, New York, 2008.
Wilber, F. R., 2007,“A System of Systems Approach to e-Enabling the Commercial Airline
Applications from an Airframer’s Perspective”, Keynote presentation, 2007IEEE SoSE Conference,
San Antonio, USA, 18 April 2007.
Wilber, F. R., 2008, “Boeing’s SOSE Approach to E-Enabling Commercial Airlines,” System of Systems
Engineering – Innovations for the 21st Century, (M. Jamshidi, Ed.), John Wiley Series on Systems
Engineering, New York, 2008.
Wojcik, L., A., Hoffman, K. C., 2006, “Systems of Systems Engineering in the Enterprise Context: A
Unifying Framework for Dynamics,” Proc. of IEEE International Conference on System of
Systems Engineering, Los Angeles, April 2006.

Leave a Reply

Fill in your details below or click an icon to log in: Logo

You are commenting using your account. Log Out /  Change )

Google photo

You are commenting using your Google account. Log Out /  Change )

Twitter picture

You are commenting using your Twitter account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )

Connecting to %s

This site uses Akismet to reduce spam. Learn how your comment data is processed.

%d bloggers like this: