Abstract
Grid computing is emerged as a new distributed computing technology that implements flexible and coordinated resource sharing among dynamic, heterogeneous, unpredictable and geographically distributed collections of resources owned by different individuals and organizations. Due to heterogeneous and dynamic nature of the grid, resource management and application scheduling is a complex undertaking. This paper proposed a multi-agent architecture that addressed resource management and application execution with support for Quality of Services (QoS) in grid environment. Five types of collaborative intelligent and mobile agents proposed to manage grid resources and applications in a decentralized, autonomous and intelligent manner. In the proposed architecture, negotiation, advanced reservation and QoS measurements handled by collaborative intelligent agents. Resources and applications are managed independently with respect to their defined policies. The simulation results showed that the multi-agent architecture is practical, flexible and effective.
Highlights
Grid technology enables the sharing and dynamic allocation of distributed, high-performance computational resources while minimizing the associated ownership and operating costs, it facilitates access to such resources and promotes flexibility and collaboration among diverse organizations[4]
Due to large-scale heterogeneity present in resources and applications requirements in grid environments, resource management and application scheduling are complex undertaking[2,6]. In respond to this heterogeneity, we proposed a new Multi-Agent Architecture for Grid Environment (MAAG), which fits in heterogeneous nature of grid’s resources and applications
Simulation software is developed to evaluate the against Average system utility, Drop Ratio and performance of the Service Agent (SA) as an important Importance Level in Fig. 5, 6 and 7
Summary
Grid technology enables the sharing and dynamic allocation of distributed, high-performance computational resources while minimizing the associated ownership and operating costs, it facilitates access to such resources and promotes flexibility and collaboration among diverse organizations[4]. The resources are heterogeneous in terms of their architecture, power, configuration and availability They are managed by different access policies and cost models that vary with time, users and priorities. Due to large-scale heterogeneity present in resources and applications requirements in grid environments, resource management and application scheduling are complex undertaking[2,6]. In respond to this heterogeneity, we proposed a new Multi-Agent Architecture for Grid Environment (MAAG), which fits in heterogeneous nature of grid’s resources and applications. These characteristic features of MAS make them ideal for spontaneous and opportunistic collaborations using autonomous agents[8,10] which continuously adapt to their environment
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