Abstract
This paper presents a new negotiation model for designing Market- and Behavior-driven Negotiation Agents (MBDNAs) that address computational grid resource allocation problem. To determine the amount of concession for each trading cycle, the MBDNAs are guided by six factors: (1) number of negotiator's trading partners, (2) number of negotiator's competitors, (3) negotiator's time preference, (4) flexibility in negotiator's trading partner's proposal, (5) negotiator's proposal deviation from the average of its trading partners’ proposals, and (6) previous concession behavior of negotiator's trading partner. In our experiments, we compare grid resource consumer (GRC) of type MBDNAs (respectively grid resource owner (GRO) of type MBDNAs) with MDAs (Market Driven Agents) in terms of the following metrics: total tasks complementation and average utility (respectively resource utilization level and average utility). The results show that by taking the proposed factors into account, MBDNAs of both types make a more efficient concession amount than MDAs and are, therefore, considered an appropriate mechanism for grid resource allocation in different grid workloads and market types.
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