Handling emergent resource use oscillations

Distributed computing systems are increasingly being created as self-organizing collections of many autonomous (human or software) agents cooperating as peers. Peer-to-peer coordination introduces, however, unique and potentially serious challenges. When there is no one "in charge", dysfunctions can emerge as the collective effect of locally reasonable decisions. In this paper, we consider the dysfunction wherein inefficient resource use oscillations occur due to delayed status information, and describe novel approaches, based on the selective use of misinformation, for dealing with this problem. A model of several servers offering equivalent service to independent clients is presented and studied numerically and analytically; the spreading of misinformation about the queue status is found to dampen oscillations and improve system performance for a wide range of parameters.

[1]  Hao Che,et al.  Adaptive control algorithms for decentralized optimal traffic engineering in the Internet , 2004, IEEE/ACM Transactions on Networking.

[2]  Shahar Hod,et al.  Temporal oscillations and phase transitions in the evolutionary minority game. , 2003, Physical review. E, Statistical, nonlinear, and soft matter physics.

[3]  Yi-Cheng Zhang,et al.  Emergence of cooperation and organization in an evolutionary game , 1997 .

[4]  Gary J. Nutt,et al.  Open Systems , 2019 .

[5]  Yicheng Zhang.  Modeling Market Mechanism with Evolutionary Games , 1998, cond-mat/9803308.

[6]  Ashok Erramilli,et al.  Oscillations and Chaos in a Flow Model of a Switching System , 1991, IEEE J. Sel. Areas Commun..

[7]  Angela L. Chiu,et al.  Overview and Principles of Internet Traffic Engineering , 2002, RFC.

[8]  John D. Sterman,et al.  Learning in and about complex systems , 1994 .

[9]  T. V. Lakshman,et al.  SRED: stabilized RED , 1999, IEEE INFOCOM '99. Conference on Computer Communications. Proceedings. Eighteenth Annual Joint Conference of the IEEE Computer and Communications Societies. The Future is Now (Cat. No.99CH36320).

[10]  Deborah Estrin,et al.  Recommendations on Queue Management and Congestion Avoidance in the Internet , 1998, RFC.

[11]  G. Reents,et al.  A stochastic strategy for the minority game , 2001 .

[12]  Bernardo A. Huberman,et al.  Clustered volatility in multiagent dynamics , 1995, adap-org/9502006.

[13]  Rick L. Riolo,et al.  Adaptive Competition, Market Efficiency, and Phase Transitions , 1999 .

[14]  W. Hamilton,et al.  The evolution of cooperation. , 1984, Science.

[15]  Anthony P. Reeves,et al.  Strategies for Dynamic Load Balancing on Highly Parallel Computers , 1993, IEEE Trans. Parallel Distributed Syst..

[16]  Ramesh Johari,et al.  End-to-end congestion control for the internet: delays and stability , 2001, TNET.

[17]  Michael Mitzenmacher,et al.  How Useful Is Old Information? , 2000, IEEE Trans. Parallel Distributed Syst..

[18]  Shahar Hod,et al.  Self-segregation versus clustering in the evolutionary minority game. , 2002, Physical review letters.

[19]  Mark Klein,et al.  The Dynamics of Collaborative Design: Insights from Complex Systems and Negotiation Research , 2003, Concurr. Eng. Res. Appl..

[20]  S. Kauffman.  At Home in the Universe: The Search for the Laws of Self-Organization and Complexity , 1995 .

[21]  Fernando Paganini,et al.  Linear stability of TCP/RED and a scalable control , 2003, Comput. Networks.

[22]  Tad Hogg,et al.  Controlling chaos in distributed computational systems , 1998, SMC'98 Conference Proceedings. 1998 IEEE International Conference on Systems, Man, and Cybernetics (Cat. No.98CH36218).

[23]  Mark Klein,et al.  Handling Resource Use Oscillation in Multi-agent Markets , 2003, AMEC.

[24]  A. Khanna,et al.  The revised ARPANET routing metric , 1989, SIGCOMM '89.

[25]  Matteo Marsili,et al.  Trading Behavior and excess volatility in Toy Markets , 2001, Adv. Complex Syst..

[26]  Ariel Rubinstein,et al.  A Course in Game Theory , 1995 .

[27]  Victor Lesser,et al.  Social Pathologies of Adaptive Agents , 2002 .

[28]  C. D. Gelatt,et al.  Optimization by Simulated Annealing , 1983, Science.

[29]  J. J. Garcia-Luna-Aceves,et al.  A simple approximation to minimum-delay routing , 1999, SIGCOMM '99.

[30]  Mark Allman,et al.  A web server's view of the transport layer , 2000, CCRV.

[31]  G. Hardin,et al.  The Tragedy of the Commons , 1968, Green Planet Blues.

[32]  Jeffrey O. Kephart,et al.  Dynamic pricing by software agents , 2000, Comput. Networks.

[33]  N. Johnson,et al.  Self-Organized Segregation within an Evolving Population , 1998, cond-mat/9810142.

[34]  Richard J. La,et al.  Global stability conditions for rate control of discretized model with communication delays , 2004, IEEE Global Telecommunications Conference, 2004. GLOBECOM '04..

[35]  Soundar Kumara,et al.  Decision Making In Logistics: A Chaos Theory Based Analysis , 2003 .

[36]  Victor R. Lesser,et al.  Poaching and distraction in asynchronous agent activities , 1998, Proceedings International Conference on Multi Agent Systems (Cat. No.98EX160).

[37]  Victor Lesser.  ICMAS-95 : proceedings First International Conference on Multi-Agent Systems, June 12-14, 1995, San Francisco, California , 1995 .

[38]  Mark Klein,et al.  Efficiency through disinformation , 2003 .

[39]  Tad Hogg,et al.  Controlling chaos in distributed systems , 1991, IEEE Trans. Syst. Man Cybern..

[40]  Jon Crowcroft,et al.  Shortest Path First with Emergency Exits , 1990, SIGCOMM.

[41]  Yaneer Bar-Yam,et al.  Dynamics Of Complex Systems , 2019 .

[42]  Mark Klein,et al.  Exception handling in agent systems , 1999, AGENTS '99.

[43]  Yong Jiang,et al.  Inter-domain routing stability measurement , 2002, Workshop on High Performance Switching and Routing, Merging Optical and IP Technologie.

[44]  Jiming Liu,et al.  Modeling agent-based load balancing with time delays , 2003, IEEE/WIC International Conference on Intelligent Agent Technology, 2003. IAT 2003..

[45]  Bernardo A. Huberman,et al.  Resource Contention in Multiagent Systems , 1995, ICMAS.

[46]  Hong Va Leong,et al.  An adaptive clustering approach to dynamic load balancing , 2004, 7th International Symposium on Parallel Architectures, Algorithms and Networks, 2004. Proceedings..