Abstract
With robots entering the world of Cyber Physical Systems (CPS), ordering the execution of allocated tasks during runtime becomes crucial. This is so because, in the real world, there can be several physical tasks that use shared resources that need to be executed concurrently. In this article, we propose a mechanism to solve this issue of ordering task executions within a CPS that inherently handles mutual exclusion. The mechanism caters to a decentralized and distributed CPS comprising nodes such as computers, robots, and sensor nodes and uses mobile software agents that knit through them to aid the execution of the various tasks while also ensuring mutual exclusion of shared resources. The computations, communications, and control are achieved through these mobile agents. Physical execution of the tasks is performed by the robots in an asynchronous and pipelined manner without the use of a clock. The mechanism also features addition and deletion of tasks and insertion and removal of robots facilitating On-The-Fly Programming. As an application, a Warehouse Management System as a CPS has been implemented. The article concludes with the results and discussions on using the mechanism in both emulated and real-world environments.
- Anchal, P. Saini, and C. R. Krishna. 2014. An efficient permission-cum-cluster based distributed mutual exclusion algorithm for mobile adhoc networks. In Proceedings of the 2014 International Conference on Parallel, Distributed and Grid Computing (PDGC’14). 141--146.Google Scholar
- H. Attiya, A. Kogan, and J. L. Welch. 2010. Efficient and robust local mutual exclusion in mobile ad hoc networks. IEEE Trans. Mobile Comput. 9, 3 (March 2010), 361--375. Google Scholar
Digital Library
- R. Baheti and H. Gill. 2011. Cyber-physical systems. The Impact of Control Technology 12 (2011), 161--166.Google Scholar
- S. Basagni, M. Conti, S. Giordano, and I. Stojmenovic. 2004. Mobile Ad Hoc Networking. John Wiley 8 Sons.Google Scholar
- F. Bellifemine, A. Poggi, and G. Rimassa. 2001. JADE: A FIPA2000 compliant agent development environment. In Proceedings of the International Conference on Autonomous Agents and Multiagent Systems. 216--217. Google Scholar
Digital Library
- S. C. Botelho and R. Alami. 1999. M+: A scheme for multi-robot cooperation through negotiated task allocation and achievement. In Proceedings of the IEEE International Conference on Robotics and Automation. Vol. 2. 1234--1239. Google Scholar
Cross Ref
- A. Boukerche, R. B. Machado, K. R. L. Jucá, J. B. M. Sobral, and M. S. M. A. Notare. 2007. An agent based and biological inspired real-time intrusion detection and security model for computer network operations. Comput. Commun. 30, 13 (2007), 2649--2660. Google Scholar
Digital Library
- S. Bulgannawar and N. F. Vaidya. 1995. A distributed K-mutual exclusion algorithm. In Proceedings of the 15th International Conference on Distributed Computing Systems. 153--160. Google Scholar
Cross Ref
- K. M. Chandy and J. Misra. 1984. The drinking philosophers problem. ACM Trans. Program. Lang. Syst. 6, 4 (Oct. 1984), 632--646. Google Scholar
Digital Library
- M. Chen, S. Gonzalez, and V. C. M. Leung. 2007. Applications and design issues for mobile agents in wireless sensor networks. Wireless Commun. IEEE 14 (Dec. 2007), 20--26. Google Scholar
Digital Library
- R. Chertov, S. Fahmy, and N. B. Shroff. 2006. Emulation versus simulation: A case study of TCP-targeted denial of service attacks. In Proceedings of the 2nd International Conference on Testbeds and Research Infrastructures for the Development of Networks and Communities (TRIDENTCOM). Google Scholar
Cross Ref
- H. N. Chu, A. Glad, O. Simonin, F. Sempe, A. Drogoul, and F. Charpillet. 2007. Swarm approaches for the patrolling problem, information propagation vs. pheromone evaporation. In Proceedings of the 19th IEEE International Conference on Tools with Artificial Intelligence (ICTAI’07), Vol. 1. 442--449.Google Scholar
- E. G. Coffman, M. Elphick, and A. Shoshani. 1971. System deadlocks. ACM Comput. Surv. 3, 2 (June 1971), 67--78. Google Scholar
Digital Library
- M. M. Cruz-Cunha. 2011. Handbook of Research on Mobility and Computing: Evolving Technologies and Ubiquitous Impacts. Vol. 1. IGI Global. Google Scholar
Cross Ref
- S. S. Dhenakaran and A. Parvathavarthini. 2013. An overview of routing protocols in mobile ad-hoc network. Int. J. Adv. Res. Comput. Sci. Softw. Eng. 3, 2 (2013), 251--259.Google Scholar
- M. B. Dias and A. Stentz. 2000. A free market architecture for distributed control of a multirobot system. In Proceedings of the 6th International Conference on Intelligent Autonomous Systems (IAS’06). 115--122.Google Scholar
- L. D. Fife and L. Gruenwald. 2003. Research issues for data communication in mobile ad-hoc network database systems. ACM SIGMOD Rec. 32, 2 (June 2003), 42--47. Google Scholar
Digital Library
- S. Franklin and A. Graesser. 1997. Is it an agent, or just a program? A taxonomy of autonomous agents. Intell. Agents III 1193 (1997), 21--36. Google Scholar
Cross Ref
- J. Gaber and M. Bakhouya. 2008. Mobile agent-based approach for resource discovery in peer-to-peer networks. In Agents and Peer-to-Peer Computing. 63--73. Google Scholar
Digital Library
- B. P. Gerkey and M. J. Mataric. 2001. Principled communication for dynamic multi-robot task allocation. In Proceedings of the International Symposium on Experimental Robotics 271 (2001), 353--362.Google Scholar
- B. P. Gerkey and M. J. Mataric. 2003. Multi-robot task allocation: Analyzing the complexity and optimality of key architectures. In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA’03), Vol. 3. 3862--3868.Google Scholar
- W. W. Godfrey, S. S. Jha, and S. B. Nair. 2013. On a mobile agent framework for an internet of things. In Proceedings of the 2013 International Conference on Communication Systems and Network Technologies. 345--350. Google Scholar
Digital Library
- W. W. Godfrey and S. B. Nair. 2008. An immune system based multi-robot mobile agent network. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 5132 (2008), 424--433.Google Scholar
- W. W. Godfrey and S. B. Nair. 2010. A pheromone based mobile agent migration strategy for servicing networked robots. In Proceedings of the International Conference on Bio-Inspired Models of Network, Information, and Computing Systems. Springer, 533--541.Google Scholar
- V. Hadzilacos. 2001. A note on group mutual exclusion. In Proceedings of the 20th Annual ACM Symposium on Principles of Distributed Computing (PODC’01). 100--106. Google Scholar
Digital Library
- S. S. Jha, W. W. Godfrey, and S. B. Nair. 2014. Stigmergy-based synchronization of a sequence of tasks in a network of asynchronous nodes. Cybernet. Syst. 45, 5 (June 2014), 373--406. Google Scholar
Digital Library
- S. S. Jha and S. B. Nair. 2012. A logic programming interface for multiple robots. In Proceedings of the 3rd National Conference on Emerging Trends and Applications in Computer Science (NCETACS’12). IEEE, 152--156. Google Scholar
Cross Ref
- A. B. Kahn. 1962. Topological sorting of large networks. Commun. ACM 5, 11 (1962), 558--562. Google Scholar
Digital Library
- Y. Kambayashi, M. Takimoto, and Y. Kodama. 2005. Controlling biped walking robots using genetic algorithms in mobile agent environment. In Proceedings of the IEEE 3rd International Conference on Computational Cybernetics (ICCC’05). IEEE, 29--34. Google Scholar
Cross Ref
- Y. Khaluf and F. Rammig. 2013. Task allocation strategy for time-constrained tasks in robots swarms. In Proceedings of the European Conference on Artificial Life. 737--744.Google Scholar
- D. B. Lange. 1998. Mobile Objects and Mobile Agents: The Future of Distributed Computing? In Proceedings of the European Conference on Object-Oriented Programming (ECOOP’98). Lecture Notes in Computer Science, vol 1445. 1–12.Google Scholar
Cross Ref
- P. Maes, R. H. Guttman, and A. G. Moukas. 1999. Agents that buy and sell. ACM Communication 42, 3 (March 1999), 81--91. Google Scholar
Digital Library
- J. Matani and S. B. Nair. 2011. Typhon: A mobile agents framework for real world emulation in prolog. In Proceedings of the 5th International Conference on Multi-Disciplinary Trends in Artificial Intelligence (MIWAI’11). 261--273. Google Scholar
Digital Library
- N. Minar, M. Gray, O. Roup, R. Krikorian, and P. Maes. 2000. Hive: Distributed agents for networking things. IEEE Concurr. 8 (2000), 24--33. Google Scholar
Digital Library
- N. Minar, K. H. Kramer, and P. Maes. 1999. Cooperating Mobile Agents for Dynamic Network Routing. 287--304.Google Scholar
- S. Mostinckx, T. V. Cutsem, S. Timbermont, E. G. Boix, É. Tanter, and W. D. Meuter. 2009. Mobile-C: A mobile agent platform for mobile C/C++ agents. Softw. Prac. Exp. 39 (2009), 661--699.Google Scholar
Digital Library
- L. Null and J. Lobur. 2014. The Essentials of Computer Organization and Architecture. Jones 8 Bartlett.Google Scholar
- A. Outtagarts. 2009. Mobile agent-based applications: A survey. Int. J. Comput. Sci. Netw. Secur. 9, 11 (2009), 331--339.Google Scholar
- L. E. Parker. 1998. ALLIANCE: An architecture for fault tolerant multirobot cooperation. IEEE Trans. Robot. Automat. 14, 2 (1998), 220--240. Google Scholar
Cross Ref
- J. L. Posadas, J. L. Poza, J. E. Simó, G. Benet, and F. Blanes. 2008. Agent-based distributed architecture for mobile robot control. Eng. Appl. Arti. Intell. 21, 6 (Sept. 2008), 805--823. Google Scholar
Digital Library
- F. L. W. Ratnieks and C. Anderson. 1999. Task partitioning in insect societies. Insect. Soc. 46, 2 (1999), 95--108. Google Scholar
Cross Ref
- M. Raynal. 1986. Algorithms for Mutual Exclusion. The MIT Press, Cambridge, MA (1986).Google Scholar
- M. Schumacher. 2001. Multi-agent systems. Objective Coordination in Multi-Agent System Engineering: Design and Implementation (2001), 9--32.Google Scholar
- F. Sempe and A. Drogoul. 2003. Adaptive patrol for a group of robots. In Proceedings of the 2003 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS’03), Vol. 3. 2865--2869. Google Scholar
Cross Ref
- T. Semwal, M. Bode, V. Singh, S. S. Jha, and S. B. Nair. 2015. Tartarus: A multi-agent platform for integrating cyber-physical systems and robots. In Proceedings of the 2015 Conference on Advances in Robotics (AIR’15). Article 20, 6 pages. Google Scholar
Digital Library
- T. Semwal, Nikhil S, S. S. Jha, and S. B. Nair. 2016. TARTARUS: A multi-agent platform for bridging the gap between cyber and physical systems. In Proceedings of the 2016 International Conference on Autonomous Agents 8 Multiagent Systems. International Foundation for Autonomous Agents and Multiagent Systems, 1493--1495.Google Scholar
- J. Shi, J. Wan, H. Yan, and H. Suo. 2011. A survey of cyber-physical systems. In Proceedings of the 2011 International Conference on Wireless Communications and Signal Processing (WCSP’11). 1--6. Google Scholar
Cross Ref
- P. Tarau. 1999. Jinni: Intelligent mobile agent programming at the intersection of java and prolog. In Proceedings of the 4th International Conference on the Practical Application of Intelligent Agents and Multi-Agents (PAAM’99), Vol. 99. 109--123.Google Scholar
- W. Wu, J. Zhang, A. Luo, and J. Cao. 2015. Distributed mutual exclusion algorithms for intersection traffic control. IEEE Trans. Parallel Distrib. Syst. 26, 1 (Jan. 2015), 65--74. Google Scholar
Cross Ref
- O. R. Zaiane. 2002. Building a recommender agent for e-learning systems. In Proceedings of the International Conference on Computers in Education. 55--59. Google Scholar
Cross Ref
Index Terms
On Ordering Multi-Robot Task Executions within a Cyber Physical System
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