When multiagent systems are used, design of an energy-efficient and autonomous data routing mechanism for wireless sensor networks is challenging. We see this challenge in the problem of coalition formation of agents (transmitters) for allocating dynamic-motion tasks (sensors) where the tasks have different service deadlines, and are in motion. The problem becomes harder when there are more tasks than agents, and when the data transmission is noisy. To address this, we design a novel and anytime decentralized heuristic algorithm to form coalitions. This algorithm can achieve at least 72±0.8% and at most 102±2.2% performance relative to the best known centralized coalition formation algorithm in such a sensor network.


Coalition formation sensor networks data routing simulation 


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  1. 1.
    Ramchurn, S.D., Polukarov, M., Farinelli, A., Truong, C., Jennings, N.R.: Coalition formation with spatial and temporal constraints. In: AAMAS 2010, pp. 1181–1188 (2010)Google Scholar
  2. 2.
    Saad, W., Han, Z., Basar, T., Merouane, D., Hjorungnes, A.: Hedonic Coalition Formation for Distributed Tak Allocation Among Wireless Agents. IEEE Transactions on Mobile Computing, 1327–1334 (2011)Google Scholar
  3. 3.
    Proakis, J., Salehi, M.: Digital Communications, 5th edn. McGraw-Hill (2007)Google Scholar
  4. 4.
    Vinyals, M., Rodriguez-Aguilar, J.A., Cerquides, J.: A survey on sensor networks from a multiagent perspective. The Computer Journal, 455–470 (2011)Google Scholar
  5. 5.
    Rogers, A., David, E., Jennings, N.R.: Self-organized routing for wireless micro-sensor networks. IEEE Transactions on Systems, Man, and Cybernetics - Part A, 349–359 (2005)Google Scholar
  6. 6.
    Michalewicz, Z., Fogel, D.B.: How to Solve It: Modern Heuristics, 2nd edn. Springer (2010)Google Scholar
  7. 7.
    Aggarwal, N., Aggarwal, K.: An Improved K-means Clustering Algorithm for Data Mining, 2nd edn. LAP LAMBERT Academic Publishing (2012)Google Scholar
  8. 8.
    Helsgaun, K.: General k-opt submoves for the lin-kernighan tsp heuristic. Mathematical Programming Computation 1(2-3), 119–163 (2009)MathSciNetzbMATHCrossRefGoogle Scholar
  9. 9.
    Turgut, D., Bölöni, L.: Three heuristics for transmission scheduling in sensor networks with multiple mobile sinks. In: AAMAS Workshop on Agent Technology for Sensor Networks, pp. 1–8 (2008)Google Scholar
  10. 10.
    Akkaya, K., Younis, M.: A survey of routing protocols in wireless sensor networks. Ad Hoc Network 3(3), 325–349 (2005)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Udara Weerakoon
    • 1
  • Vicki Allan
    • 1
  1. 1.Computer Science DepartmentUtah State UniversityLoganUSA

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