An Ant Colony Optimization Based Load Sharing Technique for Meta Task Scheduling in Grid Computing

Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 177)


Grid Computing is the fast growing industry, which shares the resources in the organization in an effective manner. Resource sharing requires more optimized algorithmic structure, otherwise the waiting time and response time are increased, ansd the resource utilization is reduced. In order to avoid such reduction in the performance of the grid system, an optimal resource sharing algorithm is required. The traditional min–min algorithm is a simple algorithm that produces a schedule that minimizes the makespan than the other traditional algorithms in the literature. But it fails to produce a load balanced schedule. In recent days, ACO plays a vital role in the discrete optimization problems. The ACO solves many engineering problems and provides optimal result which includes Travelling Salesman Problem, Network Routing, and Scheduling. This paper proposes Load Shared Ant Colony Optimization (LSACO) which shares the load among the available resources. The proposed method considers memory requirement as a QoS parameter. Through load sharing LSACO reduces the overall response time and waiting time of the tasks.


Grid Computing Ant Colony Optimization Argentine Ants Resource Sharing 


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© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.Bharathiar UniversityCoimbatoreIndia
  2. 2.Department of MCAJamal Mohamed CollegeTiruchirappalliIndia

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