Apply agent to build grid service management

Abstract

This paper presents an Agent-based Grid Service Management, which applies the concept of agents to computational grid. All entities in the Grid environment including computing resources and services can be represented as agents. Each entity is registered with a Grid Service Manager. A Grid service can be a service agent that provides the actual grid service to the other grid member. Grid members communicate with each other by communication space that is an implementation of tuple space. The design of three grid protocols for grid resource management is given. They are Grid Service Discovery Protocol, Grid Service Subscription Protocol and Grid Service Access Protocol. Grid service Subscription Protocol allows user/requestor agents to dynamically subscribe some grid services for a finite time period. A grid service can be subscribed before it can be configured or used by the user/requestor agent. A basic performance evaluation is given. Finally, some conclusions are given.

Introduction

The computational grid is a combination of distributed and heterogeneous computing resources for executing large-scale applications. Providing an efficient and scalable infrastructure to support the management of worldwide computational and data resources is a very complex task. The Grid should provide the necessary computational and data power to computational and data intensive applications. Inside the Grid many autonomous components, including computational resource schedulers, replication managers, indexing systems, monitoring systems, etc., must be combined in order to provide high level services to applications. A feasible structure for the Grid is the one in which each component is specialized in a specific set of services, and complex services that involve the use of many services, are achieved by making the simpler components collaborate with one another (Foster and Kesselman, 1999, Chunlin and Layuan, 2001, Chunlin et al., 2001, Chunlin et al., 2002, Litzkow et al., 1988, Buyya et al., 2000a, Buyya et al., 2000b). Agents and Multi-Agent Systems can provide the necessary technology to fast prototype, experiment, and implement forms of Grid collaboration.

A series of workshops on Agent-Based Cluster and Grid Computing were initiated in 2001 as part of the IEEE/ACM International Conference on Cluster Computing and the Grid (Frank Manola and Craig Thompson, Rana and Walker, 2000, Krauter et al., 2002). The most interesting work in the literature might be is ARMS (Cao et al., 2001). In ARMS, a hierarchy of identical agents is used to provide an abstraction of the system architecture. According to Cao et al. (2001), Scalability is one key challenge that must be addressed for Grid computing. Our approach described below is to address scalable resource management architecture. In this paper, we propose an Agent-based Computational Grid (ACG), which combines concept computational grid with agent. It provides a completely distributed environment within which agent systems and individual agents can participate in a broader community of agents, utilizing services and capabilities provided by other participants or the grid itself. ACG allows user/requestor agents to dynamically subscribe some grid services for a finite time period. A grid service can be subscribed before it can be configured or used by the user/requestor agent. Grid members communicate with each other by communication space that is an implementation of tuple space. ACG supports grid service subscription that allows user/requestor agents to dynamically subscribe some grid services for a finite time period. The design goals of our model focus on providing a flexible and efficient grid resource discovery system to collaborate Grid Service Agents (GSA) in the grid.

The rest of the paper is organized as follows. Section 2 gives an overview of ACG grid. Section 3 presents grid members communication. Section 4 describes grid resource specification. Section 5 describes the design of grid protocols to implement grid service management. Section 6 gives experiment. Section 7 describes some related work. Section 8 concludes the paper.