A genetic algorithm based scheduler for cloud environment

Cloud Computing is a computing model that is widely accepted both in the academia and industry mainly because it offers resources on-demand and they are rapidly provisioned. Such a provisioning sytem calls for efficient scheduling mechanisms for allocation and de-allocation of resources. A good scheduling mechanism should satisfy the QoS requirements of the user and at the same time make an efficent utilization of resources. Scheduling algorithms which are application-centric tend to optimize the performance of each individual application whereas those that are resource-centric tend to optimize the performance of each resource. Hence there exists a need for a good scheduling algorithm that optimizes both these factors. This paper proposes a bi-ojective Genetic Algorithm based scheduler for cloud that optimizes the makespan (application-centric) and average processor utilization (resource-centric).