Abstract
In a cluster environment, the identification and the classification of the requested task is a prerequisite for choosing the appropriate load balancing algorithm and improving the processing capacity of the network. As the existing load balancing strategies cannot relate tasks and load balancing algorithm intelligently, this paper present an Agent-based dynamic adaptive load balancing model. Through the identification and classification of the requested task, the model selects corresponding load balancing algorithm to reach the load balancing in cluster. This model has a distinct advantage over other load balancing schedule strategies on response time. DOI : http://dx.doi.org/10.11591/telkomnika.v12i3.4568 Full Text: PDF
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