Discrete Event Command and Control of Multiple Military Missions in Network Centric Warfare Chee Khiang Pang, Cao Vinh Le, and Oon Peen Gan
Greg Hudas
Matthew B. Middleton
U.S. Army RDECOM-TARDEC and Frank L. Lewis Joint Center for Robotics Department of Electrical & Computer Engineering Automation & Robotics Research Institute Warren, MI 48397-5000, USA National University of Singapore University of Texas at Arlington Singapore 117576 Fort Worth, TX 76118, USA Email:
[email protected]
Abstract—To meet both symmetrical and asymmetrical warfare requirements, new large-scale systems engineering solutions are required to transform the fighting capabilities of armed forces to Network Centric Warfare (NCW). In this paper, a formal Discrete Event Command and Control (DEC2) structure is presented which enables effective task planning, resource assignment, shared resource dispatching, and adaptability to dynamic missions. Two phases are included in the functionality of the DEC2 structure; namely, the planning phase and the operational phase. In the planning phase, the mission tasks and available resources are prescribed by the mission commander and field commanders, respectively, using the notion of Boolean matrices. In the operational phase, mission tasks and required resources based on active agents’ statuses are sequenced automatically. Our proposed DEC2 structure is simulated on a Singapore Armed Forces (SAF) team on two realistic ambush attack missions, and its effectiveness in sequencing the mission tasks and required resources online without conflicts and deadlocks is verified.
communication, sensor, control, actuator, and weapon systems, etc. Independent new resources and services should also be configured to be included in an ad-hoc fashion, while depleted resources should be removed from the system automatically without the commanders’ instructions. To meet these requirements, a Discrete Event Command and Control (DEC2) structure is proposed in this paper. Using the proposed DEC2 structure, the distributed networked team can be automatically reconfigured to ensure the overall system’s control and integrity, effectively mitigating the corrupting issues of uncertainties in the design, analysis, and optimization of these large-scale interconnected and networked military systems. Our proposed DEC2 are formulated using Boolean matrices and vectors, which is portable and easy-to-install on any platform with minimum coding required [3]. The DEC2 is operated through two phases; namely, the planing phase and the operational phase. In the planing phase, task planing and resource assignment are prescribed by mission commander and field commanders using the Task Sequencing Matrix (TSM) and the Resource Assignment Matrix (RAM), respectively. In the operational phase, mission tasks and available resources are sequenced correctly and fairly based on the current missions’ statuses. The tasks of multiple missions are ensured to be correctly sequenced in real-time, and shared resources are suitably assigned to competing tasks using dispatching policies.
I. I NTRODUCTION
L
ARGE-scale systems complexity arises from the challenging and often-conflicting user requirements, scale, scope, inter-connectivity with different interconnected networked teams and the environment, inter-disciplinary nature of the problems encountered, and the presence of many poorlyperceived system structures, etc. This complexity requires a scalable, deployable, and mobile networking capability that supports mission tailoring, force responsiveness and agility, ability to change missions without exchanging forces, and general adaptability to changing networked systems conditions. These emergent behaviours also prompt for the need of a scientific, robust, and holistic framework to conceptualize, design, manage, and implement increasingly complex rules and missions demanded in the networked systems successfully [1]. With the advancement of secured communication technologies, military forces around the world are evolving their fighting capabilities to Network Centric Warfare (NCW) to meet both symmetrical and asymmetrical warfare requirements [2]. The employment of secured communications using NCW requires new mathematical machineries to coordinate, command, and control of the interconnected yet distributed network of
II. BACKGROUND In this section, the rule-based formulation of military missions and the mathematical rigor of the Discrete Event Control (DEC) are reviewed. The proposed DEC2 structure is also described. A. Rule-Based Formulation of Missions A military mission is characterized by a set of tasks V to be performed. Each task has a set of preceding tasks and a set of required resources, i.e., a task cannot be performed until all of its preceding tasks are completed and all of its required resources are available. Let R represent the set of available resources utilized by the mission. Each mission is also uniquely associated with a set of external input events U and a set of mission outputs Y .
1 This work was supported in part by Singapore MOE AcRF Tier 1 Grants R-263-000-564-133 and R-266-000-058-112.
Proc. of the 8th International Conference on Intelligent Unmanned Systems (ICIUS 2012) Copyright © 2012 ICIUS 2012 Organisers ISBN: 978-981-07-4225-6 74
Proc. of the 8th International Conference on Intelligent Unmanned Systems (ICIUS 2012)
Given a military mission with a set of tasks V properly predefined by the mission commander and a set of available resources R specified by the field commanders, it is convenient to describe the mission using a finite set of linguistic IFTHEN rules denoted by X. Each rule xi ∈ X consists of the condition and the consequence parts. In the condition part, the sets of preceding tasks, required resources, and input events needed to activate each rule are predefined. Once a rule is activated, its consequence part is executed. The consequence part of each rule specifies the consequent tasks to be performed, the completed resources to be released, and the mission outputs in the next iteration. Generally, rule xi ∈ X takes the following form:
iteration are defined by the following output equations: vs (k + 1)
=
Sv ⊗ x(k + 1),
(2)
rs (k + 1) y(k + 1)
= =
Sr ⊗ x(k + 1), Sy ⊗ x(k + 1).
(3) (4)
IF (all tasks required as precursors to rule xi are completed) AND (all resources required by rule xi are available) THEN (activate rule xi )
Su is a task start matrix, Sr is a resource release matrix, and Sy is an output matrix. Similarly, task start vector vs , resource release vector rs , and output vector y can be defined. In general, a real-time event (an external input event or a task completion) occurs and triggers the DEC to compute the logical state equation in (1). The DEC obtains the system’s information (vc , rc , and u) via sensors, and then sequences subsequent commands to the system (vs , rs , and y). ud is the conflict resolution control vector, which is used to resolve conflicts and avoid blocking phenomena including deadlocks and bottlenecks. ud can be dynamically computed at each event using current job/resource statuses. The use of Fud and ud will be introduced later in Section II-D.
Consequences:
C. Programming Large-Scale Missions
Conditions:
One key advantage of the DEC’s matrix formulation is its scalability, which makes it straightforward to model large-scale systems. Multiple missions can be programmed into the same networked system of resources. Suppose several missions are prescribed, with mission m having its jobs ordering given by m Fm v and its required resources is given by Fr . The overall matrices Fv , Fr are then given by ⎡ 1 ⎡ 1 ⎤ ⎤ Fv 0 Fr 0 ⎢ ⎢ 2 ⎥ ⎥ 2 0 Fv 0 ⎥ , Fr = ⎢ Fr ⎥ , Fv = ⎢ (5) ⎣ ⎣ ⎦ ⎦ .. .. . 0 0 .
IF (rule xi is activated) THEN (start all consequent tasks of rule xi ) AND (release all completed resources). B. Discrete Event Control To represent the linguistic IF-THEN rules in a compact form, Boolean matrices and vectors are used. To map the set of preceding tasks to the set of rules, the Task Sequencing v Matrix TSM Fv is defined such that element fij = 1 if task v vj is a preceding task needed to activate rule xi and fij =0 otherwise. To map the set of required resources to the set of rules, the Resource Assignment Matrix RAM Fr is defined r such as element fij = 1 if resource rj is a required resource r needed to activate rule xi and fij = 0 otherwise. Fu is an input matrix that maps the set of input events to the set of u rules, having element fij = 1 if input uj is required activate r rule xi and fij = 0 otherwise. Therefore, the DEC has the following logical state equation [4]:
and similarly for matrices Fu , Sv , Sr , and Sy . It is noted that the mission job sequences are independent, each using its own jobs, and so Fv is block diagonal. However, all the missions use the same resources available in the networked team, and hence Fr has as many columns as the number of available resources. The DEC facilitates mission transferability between teams by capturing mission information in Fv , which can easily be moved and programmed into another system. In the DEC, various missions in a system can be added or removed by users and all missions use the same common pool of system resources. At any time, additional missions can be programmed by other users, without having to know which missions are already programmed to the resource network. This drastically reduces the complexity and provides the essential flexibility to integrate multiple combat teams in such a largescale systems framework. Moreover, it was also proven that the DEC provides the required consistency, completeness, and conciseness in rule-based analysis, which guarantees a proper sequencing of tasks and resources in multiple military missions [5].
x(k + 1) = Fv ⊗ vc (k) ⊕ Fr ⊗ rc (k) ⊕ Fu ⊗ u(k) ⊕ Fud ⊗ ud (k),
(1)
where k is the loop iteration. The overbar in (1) denotes a Boolean negation. ⊗ and ⊕ denote the logical and/or multiplication and addition, respectively. Each element xi of the rule vector x represents the rule xi ∈ X. If all conditions (IF part) required for rule xi are met, then xi = 1 (true). vc is the task completed vector having element vjc = 1 if task vj is completed and vjc = 0 otherwise. rc is the resource available vector having element rjc = 1 if resource rj is available and vjc = 0 otherwise. u is the input vector having element uj = 1 if input event uj occurs and uj = 0 otherwise. The DEC’s commands to the distributed team in the next
D. Adaptability to Dynamic Missions As mission tasks change or are added, the TSMs can be easily reconfigured. Similar when the resources fail or new
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resources are added, the RAMs can be easily reconfigured in real-time. Modifications of mission tasks and resources can be performed readily by rearranging the “1”s in the corresponding matrices accordingly. Another dynamic problem in military missions is that of shared-resource conflict. Modern military missions have numerous distributed resources, and often, many of them can perform the same or similar tasks. Given the presence of such shared resources, simultaneous activation of conflicting rules may arise, i.e., several tasks (possibly from different missions) may request the same set of resources simultaneously. The function of the conflict-resolution input vector ud in (1) is to appropriately assign shared resources. An inappropriate assignment of shared resources can lead to blocking phenomena including deadlocks, which can be avoided using the proposed methodologies in [6]. To correctly resolve shared-resource conflicts, matrix Fud in (1) must be suitably defined. The matrix Fud has as many columns as the number of tasks performed by shared resources. ud The element fij = 1 if shared task vj is a preceding task ud needed to activate rule xi and fij = 0 otherwise. As such, d element uj = 1 determines the inhibition of logic state xi , i.e., whether rule xi can be activated and different dispatching strategies can be selected depending on the way one selects the conflict resolution strategy to generate vector ud . A possible dispatching strategy is to depend on the nature of the missions involved, i.e., being symmetrical or asymmetrical. Symmetrical warfare focuses on the destruction of enemy forces and sources of military power. Symmetrical conflict places a priority on detecting, tracking, engaging, and assessing battle damage against enemy forces and infrastructure. Therefore, destructive resources such as missile launchers, cannons, and mortars, etc., are given higher priority to symmetrical missions. In contrast, asymmetrical warfare occurs when the adversary’s military capabilities are insufficient to engage in direct and open warfare [7]. In such cases, tracing, investigation, and interrogation are preferred over destruction and direct engagement. Resources that are preferred in asymmetrical missions include commandos, guards, intelligent agents, and undercover police, etc.
Fig. 1. Centralized and distributed deployment of combat team.
and without conflict, thus contributing to the concept of safe operations [9]. To describe our proposed DEC2 structure, let us consider the distributed deployment of a combat team as depicted in Fig. 1. There is typically one mission commander who overlooks the entire distributed networked team. The whole combat team is divided into several smaller groups, each group targeted to complete a certain mission. Each group has one field commander and is assigned a specific sequence of tasks. However, all groups share the same pool of available resources. Depending on the deployment scale of the combat team, the mission commander can be a brigadier general or above such as lieutenant general, while the field commanders are usually lower-ranked sub-unit commanders. For example, consider the brigade combat team which is a deployable unit of maneuver in many armies. In this case, the mission commander is a brigadier general, while the field commanders are battalion commanders (majors or lieutenant colonels). The functionality of DEC2 structure consists of the following two phases: 1) Planning/Programming Phase: Mission task requirements, external input events, and desired goal states are prescribed by the mission commander in terms of Fv , Sv , Fu , and Sy . Shared-resource conflict resolution and priority dispatching are prescribed in terms of Fud and ud . This allows the mission commander to convey purpose without providing detailed instructions on how the tasks or missions are executed. Next, the resource assignment to the mission tasks is prescribed by the field commanders in terms of Fr and Sr . All this information could be entered via graphical user interfaces on laptops, handheld Personal Digital Assistants (PDA), or even smart handphones, etc. 2) Operational Phase. The DEC2 will automatically poll active resources for their status at each event update and
III. D ISCRETE E VENT C OMMAND AND C ONTROL S TRUCTURE In this section, a DEC2 structure for programming multiple missions into heterogeneous teams of distributed agents, and controlling the performance of these missions in real-time is described. This is a decision-making DEC2 which contains rules to sequence the tasks in each mission and assigns resources to those tasks. The DEC2 has a NCW message-passing architecture that is in conformance with joint architecture for unmanned ground systems, and is an efficient means to realize the high-level observe, orient, decide, and act loops of 4D real-time control system reference model architecture [8]. The DEC2 is able to coordinate the sequencing of operations between multiple agents, soldiers, and robots, etc., efficiently
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on priority measures or war-fighter decision inputs, the DEC2 decides which tasks the team should perform next, and then sends message-based commands to each agent to perform certain tasks or release certain resources. All of these are accomplished efficiently using the proposed DEC2 framework. The commands sent by the DEC2 to the team agents could be command inputs into semi-autonomous machine nodes, or in the form of messages for decision assistance over a PDA for human agents, etc. IV. I LLUSTRATIVE E XAMPLE To illustrate the effectiveness of our proposed DEC2 structure, two sample missions are presented. In this example, a Singapore Armed Forces (SAF) team is used as distributed networked combat team. The army is a branch of the SAF responsible for land operations. It is the largest of the three armed services and is heavily reliant on a conscript army, comprising mainly of Singapore’s operationally ready national servicemen. Typical resources in a SAF team include [11][12]: 1) Singapore Self-Propelled Howitzer 1 Primus: A selfpropelled howitzer armed with a 155 mm howitzer. With the aim of providing better fire support to the armour brigades, this weapon system would require the ability to keep pace with the high tempo of armoured operations, while providing the range, firepower, and accuracy, etc; 2) TPQ 37 Radar: An essential long range weapon locating radar designed for automatic first-round location of weapons firing projectile-type rounds. The primary mission of TPQ 37 radar is to detect and locate enemy mortars and artillery rounds quickly and accurately for immediate engagement; 3) The VHF 900A Series Radio: A light and small radio, making it easier to for ground troops to carry. The added features of this new radio included improved physical characteristics, selective call transmission, higher data rates, digital display, and improved encrypted security features, etc; 4) Tactical Access Switch: The tactical access switch has packet switching capabilities supporting both voice and data traffic. It also supports the split node concept, which enables a quantum leap in capability through enhancing the survivability, flexibility, and range of the network; 5) SAF Commando Formation: An offensive unit, it specializes in preemptive operations such as reconnaissance or recce, involving small groups of specially trained soldiers to be deployed in enemy territory. 6) Armoured Battalions: An armoured battalion typically includes armoured personnel carriers, troop soldiers, and tanks. Some tank models currently in service with SAF include the AMX 13-SM1, M113 Ultra Ows, and M113 Ultra 40/50, etc. A SAF team consisting of two armoured battalions (B1 and B2) including armed soldiers and tanks, two commando companies (CDO1 and CDO2), one self-propelled howitzer coupled with a TPQ 37 radar (Primus), and one tactical access switch (TAS) is considered in our simulation study. In addition,
Fig. 2. DEC2 structure for distributed networked teams.
properly sequence the tasks of all programmed missions, and assign the required resources. Conflicting requests for resources are automatically handled to avoid blocking phenomena. During real-time operations, the resource assignment matrix can be easily reconfigured to allow uninterrupted mission performance in spite of resource additions and failures. At any time, additional missions can also be programmed into the team or removed. As missions change or are added, these matrices can be easily reprogrammed in real-time. Multiple missions can also be programmed by multiple mission commanders into the same networked team that shares the same resources. The overall architecture of our proposed DEC2 structure is displayed in Fig. 2. It can be seen that the DEC2 runs on a computer and functions as a feedback controller in real-time. The DEC2 obtains information from each networked agent on which tasks have just been completed and which resources are currently available. This information about team status can be transmitted via a NCW message-passing protocol over a wireless sensor network, wi-fi, radio, and handphones [10]. Given such information from all active nodes, the DEC2 computes which mission tasks could be performed next. Based
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all soldiers are equipped with the VHF 900A series radio (VHF 900A SR). The simulated SAF team is to perform two realistic offensive missions against two enemy troops using an ambush tactic, which is a long-established military tactic where the aggressors use concealment to attack a passing enemy. The simulated battlefield happens in the middle of tropical forest as illustrated in Fig. 3. Two enemy troops (Tr1 and Tr2) are moving toward meeting point D from two different roads (A→D and G→D). It is known that Tr1 is equipped with heavier defensive systems than Tr2. The simulated SAF team is equipped with anti-radar tools so that Tr1 and Tr2 are not capable of detecting them. For simplicity but without loss of generality, it is assumed that both uplink and downlink channels of TAS operate at very high bandwidth and are always available. The Primus is placed far away from the battlefield and communicates with the team through the TAS, and is equipped with very high precision lethal attack rockets which is able to destroy enemy targets from distance.
TABLE I S UPPRESSING E NEMY T ROOP 1 Mission 1 Input 1 Task 1
Task label u1 CDO1rB1P
Resource
Task 2
B1block
B1
Task 3
P f ire1
Primus
Task 4
CDO1rP
CDO1
Task 5
P f ire2
Primus
Task 6
B1attack
B1
Output
y1
–
– CDO1
Task description Tr1 arrives at B. CDO1 reports to ABN1 and Primus about Tr1 arrival at B. 20% of B1 goes to A (rear blocking) and another 20% of B1 goes to C (front blocking). Primus fires a number of rockets to destroy Tr1. CDO1 takes measurement and reports to Primus about percentage of damage. Primus fires a number of rockets to destroy Tr1. B1 at A (20%), C (20%), and station (60%) face-to-face attack Tr1. Mission 1 completed.
TABLE II S UPPRESSING E NEMY T ROOP 2
are reported in corresponding to 0 0 0
0 1 0
0 0 0
0 0 1
Task label u2 CDO2rB2P
Resource
Task 2
B2block
B2
Task 3
P f ire3
Primus
Task 4
B2attack
B2
Output
y2
–
the TSM F2v and ⎡ 0 0 ⎢ ⎢ 1 0 ⎢ F2v = ⎢ ⎢ 0 1 ⎢ ⎣ 0 0 0 0
Fig. 3. Simulated battlefield with distributed SAF team using ambush attack tactic. Component figures are taken from [12].
The details of two simulated missions Tables I and II, respectively. The TSM matrix F1v and RAM matrix F1r the tasks and resources in Table I are ⎤ ⎡ ⎡ 0 0 0 0 0 0 1 ⎥ ⎢ ⎢ ⎢ 1 0 0 0 0 0 ⎥ ⎢ 0 ⎥ ⎢ ⎢ ⎢ 0 1 0 0 0 0 ⎥ ⎢ 0 ⎥ ⎢ ⎢ ⎥ 1 ⎢ ⎢ 1 Fv = ⎢ 0 0 1 0 0 0 ⎥ , F r = ⎢ 1 ⎥ ⎢ ⎢ ⎢ 0 0 0 1 0 0 ⎥ ⎢ 0 ⎥ ⎢ ⎢ ⎥ ⎢ ⎢ ⎣ 0 0 0 0 1 0 ⎦ ⎣ 0 0 0 0 0 0 1 0
Mission 2 Input 1 Task 1
– CDO2
Task description Tr1 arrives at F. CDO1 reports to ABN1 and Primus about Tr2 arrival at F. 20% of B1 goes to G (rear blocking) and another 20% of B1 goes to E (front blocking). Primus fires a number of rockets to destroy Tr2. B2 at G (20%), E (20%), and station (60%) face-to-face attacks Tr1. Mission 2 completed.
input RAM F2r for Mission 2 ⎤ ⎡ 0 0 0 1 0 ⎥ ⎢ 0 0 ⎥ ⎢ 0 0 0 ⎥ 2 ⎢ ⎢ 0 0 ⎥ ⎥ , Fr = ⎢ 0 0 0 ⎥ ⎢ 1 0 ⎦ ⎣ 0 0 0 0 1 0 0 0
in Table II are ⎤ 0 0 ⎥ 1 0 ⎥ ⎥ 0 1 ⎥ ⎥ . (7) ⎥ 1 0 ⎦ 0 0
The overall TSM and RAM for both missions now in the network are F1v 0 F1r Fv = , Fr = . (8) 0 F2v F2r
⎤
⎥ ⎥ ⎥ ⎥ ⎥ ⎥ 0 0 0 0 ⎥, ⎥ 0 0 0 1 ⎥ ⎥ ⎥ 0 1 0 0 ⎦ 0 0 0 0 (6) where the matrix columns are corresponding to the tasks and resources, while the matrix rows corresponds to the rules. Next,
Similarly, the output matrices for both missions can be easily derived. In general, Missions 1 and 2 are performed using the same tactic. The key difference is that the Primus has to fire twice in order to reduce or destroy Tr1 because it is known to be armed with heavy defensive weapons a priori. As such, a higher priority is assigned to Mission 1. When there is a request for the same resource by two tasks (one from
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each mission), the DEC2 will automatically assign resources to complete the tasks in the Mission 1 first. The simulated resulting event traces are shown in Fig. 4.
[4] V. Giordano, P. Ballal, F. Lewis, B.Turchiano, and J. B. Zhang, “Supervisory control of mobile sensor networks: math formulation, simulation and implementation,” IEEE Transactions on Systems, Man, and Cybernetics–Part B: Cybernetics, vol. 36, no. 4, pp. 806–819, Aug. 2006. [5] C. K. Pang, G. Hudas, M. B. Middleton, C. V. Le, O. P. Gan, and F. L. Lewis, “Discrete event command and control for networked teams with multiple military missions,” submitted to The Journal of Defense Modeling and Simulation: Applications, Methodology, Technology, 2012. [6] F. L. Lewis, A. Gurel, S. Bogdan, A. Doganalp, and O. Pastravanu, “Analysis of deadlock and circular waits using a matrix model for flexible manufacturing systems,” Automatica, vol. 34, no. 9, pp. 1083–1100, Sep. 1998. [7] M. Mayo, M. J. Singer, and L. Kusumoto, “Massively multi-player (MMP) environments for asymmetric warfare,” The Journal of Defense Modeling and Simulation: Applications, Methodology, Technology, vol. 3, no. 3, pp. 155–166, 2006. [8] J. S. Albus, “4D/RCS a reference model architecture for intelligent unmanned ground vehicles,” in Proceedings of the SPIE 16th Annual International Symposium on Aerospace/Defense Sensing, Simulation and Controls, Orlando, FL, USA, Apr. 1–5, 2002. [9] D. E. Pearson, The World Wide Military Command and Control System. Montogomery, Alabama: Air University Press, 2000. [10] S. -C. Lim, “Network centric warfare: a command and control perspective,” Naval Postgraduate School Monterey, CA, USA, Technical Report ADA422430, Mar. 2004. [11] T. Huxley, Defending the Lion City: The Armed Forces of Singapore. Sydney, NSW, Australia: Allen & Unwin Academic, 2000. [12] Ministry of Defence Singapore. [Online]. http://www.mindef.gov.sg/ imindef/mindef websites/atozlistings/army/ourforces.html [Accessed: 22 Jun. 2012].
Fig. 4. DEC2 sequencing mission tasks in the distributed SAF team example.
The processing time of mission tasks are realistically assumed. Tr1 and Tr2 are assumed to arrive at B and F at the 5th and the 20th minute, respectively. In the task traces, an “up” means a task is being performed or completed but waiting for next task; while in the resource traces, a “down” means the resource is being used. It can be seen from Fig. 4 that both missions request for the same resource Primus at the 48th minute. As priority is given to complete Mission 1, the Primus is assigned to Mission 1 first. After the completion of the task, the Primus is then assigned to Mission 2 at the 58th minute as Mission 1 releases it. As can be seen from Fig. 4, the proposed DEC2 sequences the tasks and resources of the two missions effectively, and the missions are achieved without deadlocks. V. C ONCLUSION In this paper, a Discrete Event Command and Control (DEC2) structure is proposed for event-triggered systems of distributed teams with multiple missions. The DEC2 operates on a rule base which requires pre-programming of the Boolean matrices, and the tasks to be fired next can be easily computed using the DEC2 state/output equations which operates on logical and/or matrix operations. It is shown that the DEC2 is a complete proper and fair framework, which is portable, scalable, and adaptable to dynamic missions with no blocking, bottleneck, and deadlock issues. The effectiveness of the proposed DEC2 structure for military systems on multiple missions is verified with simulation results. R EFERENCES [1] M. Jamshidi, Large-Scale Systems: Modeling, Control, and Fuzzy logic. Upper Saddle River, NJ, USA: Prentice-Hall, Inc., Dec. 1996. [2] X. Wang, X. Wei, and H. Wang, “Network centric warfare analysis of U.S. army,” in Advances in Information Technology and Industry Applications, D. Zeng, Ed. Berlin, Germany: SpringerLink, vol. 136, pp. 573–578, 2012. [3] C. K. Pang, F. L. Lewis, T. H. Lee, and Z. Y. Dong, Intelligent Diagnosis and Prognosis of Industrial Networked Systems. Boca Raton, FL, USA: CRC Press, Taylor and Francis Group, 2011.
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