Effect of Alternative Distributed Task Allocation Strategy Based on Local Observations in Contract Net Protocol

  • Toshiharu Sugawara
  • Kensuke Fukuda
  • Toshio Hirotsu
  • Satoshi Kurihara
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7057)


This paper presents a distributed task allocation method whose strategies are alternatively selected based on the estimated workloads of the local agents. Recent Internet, sensor-network, and cloud computing applications are large-scale and fully-distributed, and thus, require sophisticated multi-agent system technologies to enable a large number of programs and computing resources to be effectively used. To elicit the capabilities of all the agents in a large-scale multi-agent system (LSMAS) in which thousands of agents work concurrently requires a new negotiation strategy for appropriately allocating tasks in a distributed manner. We start by focusing on the contract net protocol (CNP) in LSMAS and then examine the effects of the awardee selection strategies, that is, the task allocation strategies. We will show that probabilistic awardee selections improve the overall performance in specific situations. Next, the mixed strategy in which a number of awardee selections are alternatively used based on the analysis of the bid from the local agents is proposed. Finally, we show that the proposed strategy does not only avoid task concentrations but also reduces the wasted efforts, thus it can considerably improve the performance.


Distributed task allocation Adaptive Behavior Negotiation Load-balancing 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Toshiharu Sugawara
    • 1
  • Kensuke Fukuda
    • 2
  • Toshio Hirotsu
    • 3
  • Satoshi Kurihara
    • 4
  1. 1.Department of Computer Science and EngineeringWaseda UniversityJapan
  2. 2.National Institute of InformaticsChiyodaJapan
  3. 3.Faculty of Computer and Information SciencesHosei UniversityJapan
  4. 4.Institute of Scientific and Industrial ResearchOsaka UniversityJapan

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