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Using organization knowledge to improve routing performance in wireless multi-agent networks

Published: 12 May 2008 Publication History

Abstract

Multi-agent systems benefit greatly from an organization design that guides agents in determining when to communicate, how often, with whom, with what priority, and so on. However, this same organization knowledge is not utilized by general-purpose wireless network routing algorithms normally used to support agent communication. We show that incorporating organization knowledge (otherwise available only to the application layer) in the network-layer routing algorithm increases bandwidth available at the application layer by as much as 35 percent. This increased bandwidth is especially important in communication-intensive application settings, such as agent-based sensor networks, where node failures and link dynamics make providing sufficient inter-agent communication especially challenging.

References

[1]
J. Boyan and M. Littman. Packet Routing in dynamically changing networks: A reinforcement learning approach. Cowan, J. D.; Tesauro, G.; and Alspector, J., eds., Advances in Neural Information Processing Systems, 1994.
[2]
T. Clausen and P. Jacquet. Optimized Link State Routing Protocol. RFC 3626, Internet Engineering Task Force (IETF), October 2003.
[3]
D. Corkill, D. Holzhauer, and W. Koziarz. Turn Off Your Radios! Environmental Monitoring Using Power-Constrained Sensor Agents. First International Workshop on Agent Technology for Sensor Networks (ATSN-07), 2007.
[4]
D. Corkill and V. Lesser. The use of meta-level control for coordination in a distributed problem solving network. Proceedings of the Eighth International Joint Conference on Artificial Intelligence, pages 748--756, August 1983.
[5]
B. Horling and V. Lesser. A Survey of Multi-Agent Organizational Paradigms. The Knowledge Engineering Review, 19(4):281--316, 2005.
[6]
S. Keshav. REAL: A Network Simulator. tech. report 88/472, University of California, Berkeley, 1998.
[7]
M. Krainin, B. An, and V. Lesser. An Application of Automated Negotiation to Distributed Task Allocation. In 2007 IEEE/WIC/ACM International Conference on Intelligent Agent Technology (IAT 2007), Fremont, California, November 2007.
[8]
S. Kumar. Confidence based Dual Reinforcement Q-Routing: An On-line Adaptive Network Routing Algorithm. Master's thesis, Department of Computer Sciences, The University of Texas at Austin, TX-78712, USA Tech. Report, A:198--267, 1998.
[9]
J. McQuillan and D. Walden. The ARPANET Design Decisions. Computer Networks, 1, August 1992.
[10]
R. Onishi, S. Yamaguchi, H. Morino, H. Aida, and T. Saito. A multi-agent system for dynamic network routing. IEICE Transactions of Communications, 84-B(10):2721--2728, 2001.
[11]
C. Perkins and P. Bhagwat. Highly dynamic Destination-Sequenced Distance-Vector routing (DSDV) for mobile computers. ACM SIGCOMM Computer Communication Review, 24(4):234--244, October 1994.
[12]
C. Perkins and E. Royer. Ad-hoc On-Demand Distance Vector Routing. Proc. 2nd IEEE Workshop. Mobile Comp. Sys. and Apps, pages 90--100, 1999.
[13]
C. Watkins and P. Dayan. Q-learning. Machine Learning, 8:279--292, 1989.

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Published In

cover image ACM Conferences
AAMAS '08: Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 2
May 2008
673 pages
ISBN:9780981738116

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In-Cooperation

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International Foundation for Autonomous Agents and Multiagent Systems

Richland, SC

Publication History

Published: 12 May 2008

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Author Tags

  1. agents
  2. bandwidth
  3. communication
  4. multi-agent sensor networks
  5. organization design
  6. wireless routing

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