ABSTRACT
Self-stabilization is an excellent approach for adding fault tolerance to a distributed multi-agent system. However, two properties of self-stabilization theory, closure and convergence, may not be satisfied if agents are selfish. To guarantee closure in the presence of selfish agents, we propose fault-containment as a method to constrain legitimate configurations of the self-stabilizing system to be Nash equilibria. To guarantee convergence, we introduce probabilistic self-stabilization to set the probabilities of rules such that agents’ self-interests are satisfied. We also assume selfish agents as capable of performing unauthorized actions at any time, which threatens both properties, and present a stepwise solution to handle it. As a case study, we consider the problem of distributed clustering and propose self-stabilizing algorithms for forming clusters. Simulation results show that our algorithms react correctly to rule deviations and outperform comparable schemes in terms of fairness and stabilization time.
- Krzysztof R Apt and Ehsan Shoja. 2018. Self-stabilization through the lens of game theory. In It’s All About Coordination. Springer, 21–37.Google Scholar
- Yasir Arfat and Fathy Elbouraey Eassa. 2016. A survey on fault tolerant multi agent system. IJ Inf. Technol. Comput. Sci 9 (2016), 39–48.Google Scholar
- Albert-László Barabási and Réka Albert. 1999. Emergence of scaling in random networks. science 286, 5439 (1999), 509–512.Google Scholar
- R Bellman. 1957. Dynamic programming princeton university press princeton. New Jersey Google Scholar(1957).Google Scholar
- Russell Cooper. 1999. Coordination games. Cambridge University Press.Google Scholar
- Anurag Dasgupta, Sukumar Ghosh, and Sébastien Tixeuil. 2006. Selfish stabilization. In Symposium on Self-Stabilizing Systems. Springer, 231–243.Google ScholarCross Ref
- Stéphane Devismes and Colette Johnen. 2019. Self-stabilizing distributed cooperative reset. In 2019 IEEE 39th International Conference on Distributed Computing Systems (ICDCS). IEEE, 379–389.Google ScholarCross Ref
- Stéphane Devismes, Sébastien Tixeuil, and Masafumi Yamashita. 2008. Weak vs. self vs. probabilistic stabilization. In 2008 The 28th International Conference on Distributed Computing Systems. IEEE, 681–688.Google ScholarDigital Library
- Edsger W Dijkstra. 1974. Self-stabilizing systems in spite of distributed control. Commun. ACM 17, 11 (1974), 643–644.Google ScholarDigital Library
- Shlomi Dolev. 2000. Self-stabilization. MIT press.Google Scholar
- Paul Erdős and Alfréd Rényi. 1960. On the evolution of random graphs. Publ. Math. Inst. Hung. Acad. Sci 5, 1 (1960), 17–60.Google Scholar
- Petra Funk and Ingo Zinnikus. 2002. Self-stabilization as multiagent systems property. In Proceedings of the first international joint conference on Autonomous agents and multiagent systems: part 3. 1413–1414.Google ScholarDigital Library
- Sukumar Ghosh, Arobinda Gupta, Ted Herman, and Sriram V Pemmaraju. 1996. Fault-containing self-stabilizing algorithms. In Proceedings of the fifteenth annual ACM symposium on Principles of distributed computing. 45–54.Google ScholarDigital Library
- Sukumar Ghosh, Arobinda Gupta, Ted Herman, and Sriram V Pemmaraju. 2007. Fault-containing self-stabilizing distributed protocols. Distributed Computing 20, 1 (2007), 53–73.Google ScholarDigital Library
- Mohamed G Gouda. 2001. The theory of weak stabilization. In International Workshop on Self-Stabilizing Systems. Springer, 114–123.Google ScholarCross Ref
- Mohamed G Gouda and Hrishikesh B Acharya. 2009. Nash equilibria in stabilizing systems. In Symposium on Self-Stabilizing Systems. Springer, 311–324.Google ScholarDigital Library
- Alon Grubshtein, Roie Zivan, and Amnon Meisels. 2012. Partial Cooperation in Multi-agent Local Search.. In ECAI. 378–383.Google Scholar
- Nabil Guellati and Hamamache Kheddouci. 2010. A survey on self-stabilizing algorithms for independence, domination, coloring, and matching in graphs. J. Parallel and Distrib. Comput. 70, 4 (April 2010), 406–415.Google ScholarDigital Library
- Ted Herman. 1990. Probabilistic self-stabilization. Inform. Process. Lett. 35, 2 (1990), 63–67.Google ScholarDigital Library
- Matthew O. Jackson. 2008. Social and Economic Networks. Princeton University Press, Princeton, NJ, USA.Google Scholar
- Aaron D Jaggard, Neil Lutz, Michael Schapira, and Rebecca N Wright. 2014. Self-stabilizing uncoupled dynamics. In International Symposium on Algorithmic Game Theory. Springer, 74–85.Google ScholarCross Ref
- Rajendra K Jain, Dah-Ming W Chiu, William R Hawe, 1984. A quantitative measure of fairness and discrimination. Eastern Research Laboratory, Digital Equipment Corporation, Hudson, MA (1984).Google Scholar
- Oday Jubran and Oliver Theel. 2015. Recurrence in Self-Stabilization. In 2015 IEEE 34th Symposium on Reliable Distributed Systems (SRDS). IEEE, 58–67.Google Scholar
- Sara Kassan, Jaafar Gaber, and Pascal Lorenz. 2018. Game theory based distributed clustering approach to maximize wireless sensors network lifetime. Journal of Network and Computer Applications 123 (Dec. 2018), 80–88.Google ScholarCross Ref
- Georgios Koltsidas and Fotini-Niovi Pavlidou. 2011. A game theoretical approach to clustering of ad-hoc and sensor networks. Telecommunication Systems 47, 1-2 (2011), 81–93.Google ScholarDigital Library
- R Duncan Luce and Howard Raiffa. 1989. Games and decisions: Introduction and critical survey. Courier Corporation.Google Scholar
- Thomas Moscibroda and Roger Wattenhofer. 2004. Efficient computation of maximal independent sets in unstructured multi-hop radio networks. In 2004 IEEE International Conference on Mobile Ad-hoc and Sensor Systems. IEEE, 51–59.Google ScholarCross Ref
- John F Nash 1950. Equilibrium points in n-person games. Proceedings of the national academy of sciences 36, 1 (1950), 48–49.Google ScholarCross Ref
- A. Ramtin, V. Hakami, and M. Dehghan. 2014. Self-stabilizing algorithms of constructing virtual backbone in selfish wireless ad-hoc networks. In 2014 22nd Iranian Conference on Electrical Engineering (ICEE). 914–919.Google Scholar
- Federico Rossi, Saptarshi Bandyopadhyay, Michael Wolf, and Marco Pavone. 2018. Review of multi-agent algorithms for collective behavior: a structural taxonomy. IFAC-PapersOnLine 51, 12 (2018), 112–117.Google ScholarCross Ref
- L. S. Shapley. 1953. Stochastic Games. Proceedings of the National Academy of Sciences 39, 10 (1953), 1095–1100.Google ScholarCross Ref
- Sandeep K Shukla, Daniel J Rosenkrantz, S Sekharipuram Ravi, 1995. Observations on self-stabilizing graph algorithms for anonymous networks. In Proceedings of the second workshop on self-stabilizing systems, Vol. 7. 15.Google Scholar
- Volker Turau. 2007. Linear self-stabilizing algorithms for the independent and dominating set problems using an unfair distributed scheduler. Inform. Process. Lett. 103, 3 (2007), 88–93.Google ScholarDigital Library
- Li-Hsing Yen, Jean-Yao Huang, and Volker Turau. 2016. Designing self-stabilizing systems using game theory. ACM Transactions on Autonomous and Adaptive Systems (TAAS) 11, 3(2016), 1–27.Google ScholarDigital Library
Index Terms
- Self-Stabilization with Selfish Agents
Recommendations
A self-stabilizing link-coloring protocol resilient to unbounded byzantine faults in arbitrary networks
OPODIS'05: Proceedings of the 9th international conference on Principles of Distributed SystemsSelf-stabilizing protocols can tolerate any type and any number of transient faults. However, in general, self-stabilizing protocols provide no guarantee about their behavior against permanent faults. This paper proposes a self-stabilizing link-coloring ...
Design and Communication Complexity of Self-Stabilizing Protocols Resilient to Byzantine Faults
ICNC '11: Proceedings of the 2011 Second International Conference on Networking and ComputingFault-tolerance is one of the most important properties in designing distributed systems. Self-stabilization guarantees that the system eventually behaves according to its specification regardless of the initial configuration. Byzantine fault resilience ...
Comments