An Antisocial Strategy for Scheduling Mechanisms

  • Authors:
  • Nandan Garg;Daniel Grosu;Vipin Chaudhary

  • Affiliations:
  • Wayne State University, Detroit, MI;Wayne State University, Detroit, MI;Wayne State University, Detroit, MI

  • Venue:
  • IPDPS '05 Proceedings of the 19th IEEE International Parallel and Distributed Processing Symposium (IPDPS'05) - Workshop 8 - Volume 09
  • Year:
  • 2005

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Abstract

Previous work on task scheduling mechanisms assumed that the agent's goal is to maximize its own profit without considering the effect of its strategy on the other agents' profit. This is not always the case, an agent may want to cause loses to the other agents besides maximizing its profit. Such an agent is said to be an antisocial agent. An antisocial agent will try to gain as much profit as possible relative to the other agents. In this paper we consider a mechanism for task scheduling on related machines in which each machine is associated with an agent. We develop an antisocial strategy which can be used by an antisocial agent to inflict losses to the other participating agents. We analyze the effect of different degrees of agent's antisociality on the losses inflicted to the other agents.