Heterogeneous workload consolidation technique for green cloud

Abstract

Cloud Computing offers service to end-users rather than a product, by sharing resources, software and other information under a usage based payment model. It enables hosting of various kinds of applications such as business, scientific, social network, etc. as it has key characteristics like multi-tenancy, scalability, performance, security, etc. Economic benefits are the main driver for the Cloud, since it promises the reduction of capital expenditure (CapEx) and operational expenditure (OpEx). Cloud Computing is facing many challenges like Data Security, Energy Consumption, Server Consolidation, Virtual Machine Migration, etc. Existing approaches of workload management have investigated the consolidation of VMs using the similar type of workload. This research work focuses on the study of management of heterogeneous workloads in a cloud environment. Management of heterogeneous workloads helps in reducing the energy consumption of data centers, achieving the efficient resource usage and reduction in operational costs which benefits the end-users from decreased prices for resource usage. In this thesis, available workload consolidation techniques have been compared. A Workload Consolidation Cloud portal has been designed, developed and presented for the implementation of heterogeneous workload consolidation technique for green cloud. This technique allows the dynamic adaption of VM allocation at run-time according to the current utilization of resources applying live migration, switching idle nodes to the sleep mode, and thus minimizing energy consumption. A simulated environment, CloudSim Toolkit has been used to validate the experimental results. The experimental results demonstrate that the proposed approach can effectively handle strict SLAs, heterogeneous infrastructure and heterogeneous VMs.