A new fuzzy negotiation protocol for grid resource allocation

  • Authors:

  • Sepideh Adabi;Ali Movaghar;Amir Masoud Rahmani;Hamid Beigy;Hengameh Dastmalchy-Tabrizi

  • Affiliations:

  • Department of Computer Engineering, North Tehran Branch, Islamic Azad University, Tehran, Iran;Department of Computer Engineering, Sharif University of Technology, Tehran, Iran;Department of Computer Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran;Department of Computer Engineering, Sharif University of Technology, Tehran, Iran;School of Electrical and Computer Engineering, University of Tehran, Tehran, Iran

  • Venue:
  • Journal of Network and Computer Applications
  • Year:
  • 2014

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Abstract

In real-life trading, relaxing decisions in the face of trading pressure is common. Similarly, in market-based grid resource allocation problem designing negotiator agents with the flexibility to relax their decision to (quickly) complete a deal in the face of intense Grid Market Pressure (GMP) is essential. To make this idea possible, we design Enhanced Market- and Behavior-driven Negotiation Agents (EMBDNAs) that adopt new fuzzy negotiation protocol. The protocol focuses on both (1) enhancing Rubinstein's sequential alternating offer protocol to handle multiple trading opportunities and market competition and (2) designing two new Fuzzy Grid Market Pressure Determination Systems (FGMPDSs) for both grid resource consumers and grid resource owners to guide negotiator agents in relaxing their bargaining terms under intense GMP to enhance their chance of successfully acquiring/leasing out resources. Implementing the idea in an agent-based testbed, an experiment for evaluating and comparing EMBDNA against EMDA (Enhanced Market-Driven Agent) and our previous work in name MBDNA (Market- and Behavior-driven Negotiation Agent) were carried out through stochastic simulations. While EMDA relaxes its bargaining term in the face of intense GMP by considering just two relaxation factors the MBDNA uses the same negotiation strategy as EMBDNA but does not relax its bargaining term in the face of intense GMP. The results show that adopting the new fuzzy negotiation protocol, EMBDNAs outperform MBDNAs and EMDAs.