Distributed tasks-platforms scheduling method to holonic-C2 organization

doi:10.21629/JSEE.2019.01.11

Journal of Systems Engineering and Electronics ›› 2019, Vol. 30 ›› Issue (1): 110-120.doi: 10.21629/JSEE.2019.01.11

• Systems Engineering • Previous Articles Next Articles

Distributed tasks-platforms scheduling method to holonic-C2 organization

Xun WANG^1,*(), Peiyang YAO¹(), Jieyong ZHANG¹(), Lujun WAN²(), Fangchao JIA³()

¹ Information and Navigation College, Air Force Engineering University, Xi'an 710077, China
² Air Traffic Control and Navigation College, Air Force Engineering University, Xi'an 710051, China
³ Sergeant School, Air Force Communication, Dalian 116600, China

Received:2017-11-01 Online:2019-02-27 Published:2019-02-27
Contact: Xun WANG E-mail:wxkgdxy@163.com;ypy_664@163.com;dumu3110728@126.com;pandawlj@126.com;hijiafc@163.com
About author:WANG Xun was born in 1990. He is currently a Ph.D. candidate of Air Force Engineering University. He received his B.S. degree in communication engineering from Shandong University in 2013, and his M.S. degree in command information system from Air Force Engineering University in 2013. His research interests include command information system and mission planning. E-mail:wxkgdxy@163.com|YAO Peiyang was born in 1960. Currently he is a professor in Information and Navigation College, Air Force Engineering University. He received his B.S. degree in 1982 and his M.S. degree in 1991 from Xidian University. His research interests include command and control theory and command automation system. E-mail: ypy_664@163.com|ZHANG Jieyong was born in 1983. Currently he is a lecturer in Information and Navigation College, Air Force Engineering University. He received his B.S. degree in 2006, his M.S. degree in 2008 and his Ph.D. degree in 2012 from Air Force Engineering University. His research interests include mission planning technique and military organizational analysis. E-mail:dumu3110728@126.com|WAN Lujun was born in 1986. Currently he is a lecturer in Air Traffic Control and Navigation College, Air Force Engineering University. He received his B.S. degree in 2007, his M.S. degree in 2010 and his Ph.D. degree in 2014 from Air Force Engineering University. His research interest includes combat agent modeling and simulation. E-mail:pandawlj@126.com|JIA Fangchao was born in 1989. Currently he is a lecturer in Dalian Sergeant School of Air Force Communication. He received his B.S. degree in 2011 from Taiyuan University of Technology. He received his M.S. degree in 2013 from Air Force Engineering University. His research interest includes command information system. E-mail:hijiafc@163.com
Supported by:
the National Natural Science Foundation of China(61573017);the National Natural Science Foundation of China(61703425);the Aeronautical Science Fund(20175796014);Shaanxi Province Natural Science Foundation(2016JQ6062);Shaanxi Province Natural Science Foundation(2017JM6062);This work was supported by the National Natural Science Foundation of China (61573017; 61703425), the Aeronautical Science Fund (20175796014), and Shaanxi Province Natural Science Foundation (2016JQ6062; 2017JM6062)

Abstract

Abstract:

To solve the problem of distributed tasks-platforms scheduling in holonic command and control (C2) organization, the basic elements of the organization are analyzed firstly and the formal description of organizational elements and structure is provided. Based on the improvement of task execution quality, a single task resource scheduling model is established and the solving method based on the m-best algorithm is proposed. For the problem of tactical decision-holon cannot handle tasks with low priority effectively, a distributed resource scheduling collaboration mechanism based on platform pricing and a platform exchange mechanism based on resource capacities are designed. Finally, a series of experiments are designed to prove the effectiveness of these methods. The results show that the proposed distributed scheduling methods can realize the effective balance of platform resources.

Key words: command and control (C2), decision-holon, distributed task allocation, task execution quality, platform price, order optimization

Xun WANG, Peiyang YAO, Jieyong ZHANG, Lujun WAN, Fangchao JIA. Distributed tasks-platforms scheduling method to holonic-C2 organization[J]. Journal of Systems Engineering and Electronics, 2019, 30(1): 110-120.

Figures/Tables 13

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References 22

1	SUN Y, YAO P Y, SHUI D D, et al. Uncertain optimal model and solving method to platform scheduling problem in battlefield. Journal of Systems Engineering and Electronics, 2016, 27 (1): 157- 165.
2	LEVCHUK G M, LEVCHUK Y N, LUO J, et al. Normative design of organizations-Part I:mission planning. IEEE Trans. on Systems, Man, and Cybernetics-Part A:Systems and Humans, 2002, 32 (3): 346- 359. doi: 10.1109/TSMCA.2002.802819
3	LEVCHUK G M, LEVCHUK Y N, MEIRINA C, et al. Normative design of project-based organizations-Part III:modeling congruent, robust, and adaptive organizations. IEEE Trans. on Systems, Man, and Cybernetics-Part A:Systems and Humans, 2004, 34 (3): 337- 350. doi: 10.1109/TSMCA.2003.822268
4	KOESTLER A. The ghost in the machine. London: Arkana Books, 1967.
5	PARK C, PATTIPATI K R, KLEINMAN D L. Multi-level operational C2 holonic reference architecture modeling for MHQ with MOC. Mansfield: Faculty Publications, 2009.
6	YU F, TU F, PATTIPATI K R. Integration of a holonic organizational control architecture and multiobjective evolutionary algorithm for flexible distributed scheduling. IEEE Trans. on Systems, Man, and Cybernetics-Part A:Systems and Humans, 2008, 38 (5): 1001- 1017. doi: 10.1109/TSMCA.2008.923082
7	HAN X. Optimization-based decision support algorithms for network identification and dynamic resource management. Connecticut: University of Connecticut, 2016.
8	TANG S Y, ZHU Y F, QUN L I, et al. Survey of task allocation in multi agent systems. Systems Engineering and Electronics, 2010, 32 (10): 2155- 2161.
9	DE MENDONÇ A R M, NEDJAH N, DE MACEDO MOURELLE L. Efficient distributed algorithm of dynamic task assignment for swarm robotics. Neurocomputing, 2016, 172, 345- 355. doi: 10.1016/j.neucom.2015.05.117
10	NEDJAH N, DE MENDONÇ A R M, DE MACEDO MOURELLE L. PSO-based distributed algorithm for dynamic task allocation in a robotic swarm. Procedia Computer Science, 2015, 51, 326- 335. doi: 10.1016/j.procs.2015.05.250
11	KIA S S. An augmented Lagrangian distributed algorithm for an in-network optimal resource allocation problem. Proc. of the IEEE American Control Conference, 2017: 3312-3317.
12	SUN Y. Research on multi-agent intelligent decision support system based on blackboard. Electronic Design Engineering, 2012, 562-264 (21): 1638- 1641.
13	CHEN X, WEI X M, XU G Y. Multiple unmanned aerial vehicle decentralized cooperative air combat decision making with fuzzy situation. Journal of Shanghai Jiaotong University, 2014, 48 (7): 907- 913, 921.
14	ZHANG Y Z, ZHANG L, DU Z. Distributed blackboard decision-making framework for collaborative planning based on nested genetic algorithm. Journal of Systems Engineering and Electronics, 2015, 26 (6): 1236- 1243. doi: 10.1109/JSEE.2015.00136
15	GUO F J. Research on C2S of manned vehicle/UAV formation air-to-ground attack based on Holon. Xi'an: Northwestern Polytechnical University, 2012. (in Chinese)
16	ZHANG Y X. Research on C2S of manned vehicle/UAV formation air-to-sea attack based on Holon-Agent. Xi'an: Northwestern Polytechnical University, 2016. (in Chinese)
17	SUN Y, YAO P Y, WAN L J, et al. A quantitative method to design command and control structure of distributed military organization. Proc. of the IEEE International Conference on Information System and Artificial Intelligence (ISAI), 2016: 451-458.
18	HAN X, MANDAL S, PATTIPATI K R, et al. An optimizationbased distributed planning algorithm:a blackboard-based collaborative framework. IEEE Trans. on Systems, Man, and Cybernetics:Systems, 2014, 44 (6): 673- 686. doi: 10.1109/TSMC.2013.2276392
19	HAN X, BUI H, MANDAL S, et al. Optimization-based decision support software for a team-in-the-loop experiment:asset package selection and planning. IEEE Trans. on Systems, Man, and Cybernetics:Systems, 2013, 43 (2): 237- 251. doi: 10.1109/TSMCA.2012.2201467
20	GUHA S, MUNAGALA K, SHI P. Approximation algorithms for restless bandit problems. Journal of the Association for Computing Machinery (ACM), 2007, 58 (1): 1- 50.
21	GUPTA O K, RAVINDRAN A. Branch and bound experiments in convex nonlinear integer programming. Management Science, 1985, 31 (12): 1533- 1546. doi: 10.1287/mnsc.31.12.1533
22	WU R J, SUN P, SUN Y. Distributed dynamic task plan adjustment model and algorithm. Systems Engineering and Electronics, 2017, 39 (2): 322- 328.

Task	$r_{1}$	$r_{2}$	$r_{3}$	$r_{4}$	$r_{5}$	$r_{6}$	$r_{7}$	$r_{8}$	$r_{9}$	$r_{10}$	$r_{11}$	$r_{12}$	$t_{s, i}$	$t_{p, i}$	$\rho $
$T_{1}$	5	–	5	–	–	–	–	–	5	–	–	–	0	30	1
$T_{2}$	5	–	12	14	10	–	–	–	12	–	4	–	0	30	4
$T_{3}$	3	–	8	8	7	–	–	–	6	–	4	–	0	30	6
$T_{4}$	2	–	–	–	–	–	–	–	–	5	–	–	0	30	3
$T_{5}$	2	–	–	–	–	–	–	5	–	4	–	–	6	10	10
$T_{6}$	5	–	10	–	8	10	6	–	5	5	–	–	26	4	11
$T_{7}$	2	–	–	–	8	–	–	–	–	5	–	–	0	24	7
$T_{8}$	2	5	5	–	–	–	–	–	–	–	2	3	0	24	8
$T_{9}$	2	6	–	–	–	–	–	–	–	–	–	5	0	30	2
$T_{10}$	2	8	5	–	–	–	–	–	–	–	–	5	0	18	9
$T_{11}$	2	7	–	–	–	–	–	–	–	–	5	7	0	30	5

Platform	$r_{1}$	$r_{2}$	$r_{3}$	$r_{4}$	$r_{5}$	$r_{6}$	$r_{7}$	$r_{8}$	$r_{9}$	$r_{10}$	$r_{11}$	$r_{12}$
$PH_{1}$	5	6	5	–	2	5	2	1	5	5	2	5
$PH_{2}$	3	5	8	7	6	4	3	3	7	5	–	–
$PH_{3}$	2	5	8	7	6	4	3	3	6	4	–	–
$PH_{4}$	–	3	–	–	–	5	4	2	1	3	1	–
$PH_{5}$	1	–	–	–	–	6	2	–	–	6	–	3
$PH_{6}$	–	–	–	–	–	–	–	4	–	–	–	–
$PH_{7}$	5	–	5	–	–	–	–	–	8	3	1	–
$PH_{8}$	3	–	–	–	–	–	–	–	–	1	6	3
$PH_{9}$	–	–	–	–	–	–	–	–	3	2	4	3
$PH_{10}$	2	–	–	–	–	–	–	–	4	3	3	2
$PH_{11}$	–	–	–	–	–	–	–	–	–	1	5	5
$PH_{12}$	5	7	5	–	–	1	–	–	4	1	3	3

ID	Task	No coordination			Quality/%
$TDH_1$	$T_1$	1 $PH_7$			100
	$T_2$	1 $PH_3$	1 $PH_7$		64.94
	$T_3$	1 $PH_3$	1 $PH_2$		0
$TDH_2$	$T_9$	1 $PH_1$			100
	$T_7$	1 $PH_2$			90.86
	$T_8$	1 $PH_3$	2 $PH_4$	1 $PH_5$	100
	$T_5$	2 $PH_5$	1 $PH_6$		92.83
	$T_6$	1 $PH_2$	1 $PH_3$	1 $PH_5$	100
$TDH_3$	$T_4$	1 $PH_{10}$	2 $PH_{11}$		100
	$T_{11}$	1 $PH_{11}$	1 $PH_{12}$		100
	$T_{10}$	1 $PH_9$	1 $PH_8$		0
Average					77.15

ID	Task	After coordination			Quality/%
$TDH_1$	T1	1 $PH_7$			100
	$T_2$	1 $PH_3$	1 $PH_7$		64.94
	$T_3$	1 $PH_3$	1 $PH_4(TDH_2)$		70.71
$TDH_2$	$T_9$	1 $PH_1$			100
	$T_7$	1 $PH_2$			90.86
	$T_8$	1 $PH_3$	1 $PH_4$	1 $PH_5$	87.06
	$T_5$	2 $PH_5$	1 $PH_6$		92.83
	$T_6$	1 $PH_2$	1 $PH_3$	1 $PH_5$	100
$TDH_3$	$T_4$	1 $PH_{10}$	2 $PH_{11}$		100
	$T_{11}$	1 $PH_{11}$	1 $PH_{12}$		100
	$T_{10}$	1 $PH_2(TDH_1)$	1 $PH_9$		95.32
Average					91.07

ID	Task	After coordination			Quality/%
$TDH_1$	T1	1 $PH_7$			100
	$T_2$	1 $PH_3$	1 $PH_7$	1 $PH_{11}(TDH_3)$	81.82
	$T_3$	1 $PH_3$	1 $PH_4(TDH_2)$		70.71
$TDH_2$	$T_9$	1 $PH_1$			100
	$T_7$	1 $PH_2$			90.86
	$T_8$	1 $PH_3$	1 $PH_4$	1 $PH_5$	87.06
	$T_5$	2 $PH_5$	1 $PH_6$		92.83
	$T_6$	1 $PH_2$	1 $PH_3$	1 $PH_5$	100
$TDH_3$	$T_4$	1 $PH_{10}$	2 $PH_{11}$		100
	$T_{11}$	1 $PH_{12}$			71.21
	$T_{10}$	1 $PH_2(TDH_1)$	1 $PH_9$		95.32
Average					89.98

Distributed tasks-platforms scheduling method to holonic-C2 organization

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