Grid is the collection of geographically distributed computing resources. For effective management of these resources, the manager must maximize its utilization, which can be achieved by efficient load balancing algorithm, The objective of load balancing algorithms is to assign the load on resources to optimize resource use while reducing total jobs execution time. The proposed agent based load balancing model aims to take advantage of the agent characteristics to generate an autonomous system. It also addresses similar systems drawbacks such as instability, scalability or adaptability. The performance of the proposed algorithms were tested in Alea 2 simulator by using different parameters such as response time, resources utilization and overall queue time. The performance evaluation suggests that the proposed algorithm can enhance the overall performance of grid computing.Povzetek: Predstavljena in s simulatorjem analizirana je agentna metoda razporejanja obremenitev v omrežju.

Grid is the collection of geographically distributed computing resources. For efficient management of these resources, the manager must maximize its utilization, which can be achieved by efficient load balancing with Job Migration techniques. Job Migration from overloaded resources to underloaded is an attempt to load balancing across all processors, thus reduce average response time. The decision of migration is based on the information exchange between resources.In this paper, the authors propose a novel Job Migration Algorithm for Dynamic Load Balancing (JMADLB), in which parameters such as CPU load and queue length have been considered and have been used for the selection of overloaded resources (or underloaded ones) in Grid. Here, the overloaded resources do not accept any new job; but, the new jobs are migrated to underloaded resources, even though this mechanism migrate extra jobs to obtain load balancing. The performances of the proposed algorithms were tested in Alea 2 simulator by using different parameters like response time, resources utilization and waiting time in the global queue. In addition, they were compared with other scheduling algorithms such as First Come First Served (FCFS) and Earliest Deadline First (EDF).

Load-Balancing is an important problem in distributed heterogeneous systems. In this paper, an Agent-based load-balancing model is developed for implementation in a grid environment. Load balancing is realized via migration of worker agents from overloaded resources to underloaded ones. The proposed model purposes to take benefit of the multi-agent system characteristics to create an autonomous system. The Agent-based load balancing model is implemented using JADE (Java Agent Development Framework) and Alea 2 as a grid simulator. The use of MAS is discussed, concerning the solutions adopted for gathering information policy, location policy, selection policy, worker agents migration, and load balancing.

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