Optimized service level agreement based workload balancing strategy for cloud environment

The emerging technological demands of users call for expanding service model which avoids problem of purchasing and maintaining IT infrastructure and supports for computation-intensive services. This has directed to the development of a new computing model termed Cloud Computing. In cloud computing, the computing resources are distributed in various data centers worldwide and these resources are offered to the customers on demand on a pay as usage basis. Currently, due to the increased usage of cloud, there is a tremendous increase in workload. The uneven distribution of load among the servers results in server overloading and may lead to the server crash. This affects the performance. Cloud computing service providers can attract the customers and maximize their profit by providing Quality of Service (QoS). Providing both QoS and load balancing among the servers are the most challenging research issues. Hence, in this paper, a framework is designed to offer both QoS and balancing the load among the servers in cloud. This paper proposes a two stage scheduling algorithm. The servers with different processing power are grouped into different clusters. In the first stage, Service Level Agreement (SLA) based scheduling algorithm determines the priority of the tasks and assigns the tasks to the respective cluster. In the second stage, the Idle-Server Monitoring algorithm balances the load among the servers within each cluster. The proposed algorithm has used the response time as a QoS parameter and is implemented using CloudSim simulator. Experimental results shows that our algorithm provides better response time, waiting time, effective resource utilization and balancing load among the servers as compared to other existing algorithms.