A PSO-Based algorithm for load balancing in virtual machines of cloud computing environment
ICSI'12 Proceedings of the Third international conference on Advances in Swarm Intelligence - Volume Part I
CuteCloud: putting "Credit Union" cloud computing into practice
Proceedings of the 2012 ACM Research in Applied Computation Symposium
Replica-aided load balancing in overlay networks
Journal of Network and Computer Applications
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The current virtual machine(VM) resources scheduling in cloud computing environment mainly considers the current state of the system but seldom considers system variation and historical data, which always leads to load imbalance of the system. In view of the load balancing problem in VM resources scheduling, this paper presents a scheduling strategy on load balancing of VM resources based on genetic algorithm. According to historical data and current state of the system and through genetic algorithm, this strategy computes ahead the influence it will have on the system after the deployment of the needed VM resources and then chooses the least-affective solution, through which it achieves the best load balancing and reduces or avoids dynamic migration. This strategy solves the problem of load imbalance and high migration cost by traditional algorithms after scheduling. Experimental results prove that this method is able to realize load balancing and reasonable resources utilization both when system load is stable and variant.