A cluster-based load balancing algorithm in cloud computing

Workload and resource management are two essential functions provided at the service level of the distributed systems infrastructure. To improve the global throughput of these software environments, workloads have to be evenly scheduled among the available resources. To realize this goal, several load balancing strategies and algorithms have been proposed. Most o f t h e s e strategies were developed assuming homogeneous set of sites linked with homogeneous and fast networks. However, for computational grids, we must address some new issues, namely: heterogeneity, scalability and adaptability. In this paper, we propose a decentralized cluster-based algorithm which achieves dynamic load balancing in the cloud architecture. The proposed algorithm presents the following main features: (i) it supports heterogeneity, (ii) scalability, (iii) low network congestion and (iv) absence of any bottleneck node due to its decentralized nature. Simulation results using CloudSim show the performance analysis of the algorithm for patronizing our claims about the load balancing achieved in the system.