Resource Allocation in Cloud Computing Using Agents

In cloud computing scenario, efficiency of application execution not only depends on quality and quantity of the resources in the data center, but also on underlying resource allocation approaches. An efficient resource allocation technique is necessary for building an efficient system. The objective of this work is to propose an agent based Best-Fit resource allocation scheme which increases utilization of the resources, lowers the service cost and reduces the execution time. The work employs two types of agents: user's cloudlet agent and provider's resource agent. Cloudlet agent is located at the client system, which collects job requirement and offers various QoS options for its execution. Resource agent at the server, uses Best-Fit approach to allocate resources for jobs received from Cloudlet agent. The proposed work is simulated and the results are compared with other agent based resource allocation approaches using First-Come-First-Serve and Round-Robin. It is observed that Best-Fit approach performs better in terms of VMs allocation, job execution time, cost and resource utilization.