Cost effective load balancing based on honey bee behaviour in cloud environment

In cloud computing environment, the load balancing of non pre-emptive independent tasks is an important aspect of task scheduling. The tasks are executed on Virtual Machines (VMs) and these VMs are run in parallel so that the load has to be well balanced across all VMs. Since the cloud user pay for the service he/she is interested in reducing the execution time of task as well as the cost of using VM instances (CPU, Memory, Bandwidth etc). The proposed algorithm balance the load across VMs effectively by mapping tasks to under loaded or idle VMs based on the foraging behaviour of honey bees and if there is more than one under loaded VMs, it also selects cost efficient one using Pareto dominance strategy. The experimental results show that the algorithm is effective when compared with existing algorithms and it also reduces the cost of using VM instances.