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Article type: Research Article
Authors: Manvi, S.S.a | Birje, M.N.b | Prasad, Bhanuc; *; **
Affiliations: [a] Department of Electronics and Communication Engineering, Basaveshwar Engineering College, Bagalkot 587 102, India | [b] Department of Information Science and Engineering, Basaveshwar Engineering College, Bagalkot 587 102, India | [c] Department of Computer and Information Sciences, Florida A&M University, Tallahassee, FL 32307, USA
Correspondence: [*] Corresponding author. Tel.: +1 850 412 7350; Fax: +1 850 599 3221; E-mail: [email protected]
Note: [**] This research was partly supported by the National Science Foundation under the Grant Award CNS-0424556. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing official policies, either expressed or implied, of the US government or any of the sponsoring organizations.
Abstract: The paper presents an Agent-based Resource Allocation Model (ARAM) for grid computing. Three types of agents, namely Job Agents (JAs), Resource Brokering Agents (RBAs), and Resource Monitoring Agents (RMAs), are used. The JAs are mobile and they represent the users and perform tasks such as completing the job requests of the users and executing the jobs at suitable grid nodes. The RBAs are static and they act as resource schedulers as well as brokers for the users to submit their jobs through JAs. The RBAs incorporate an economic model and a queuing model. The RMAs are static and they reside in the nodes of the local clusters and inform the status of the resources to the local cluster servers. The model differs from other existing models, as it has the following characteristics: 1) topology-based migration of the agents, 2) analysis of different types of migrations according to the topology and the agents' overheads, and 3) resource allocation based on dynamic pricing and negotiation. The model is evaluated in a simulated environment to investigate the behavior of several parameters.
DOI: 10.3233/MGS-2005-1103
Journal: Multiagent and Grid Systems, vol. 1, no. 1, pp. 17-27, 2005
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