Two Level Fuzzy Approach for Dynamic Load Balancing in the Cloud Computing

The concept of the Cloud computing has significantly changed the field of parallel and distributed computing systems today. Cloud computing enables a wide range of users to access distributed, scalable, virtualized hardware and/or software infrastructure over the Internet. Load balancing is the process of distributing the load among various nodes of a distributed system to improve resource utilization, minimum response time and maximize throughput while also avoiding a situation where some of the nodes are heavily loaded while other nodes are idle or doing very little work. Load balancing ensures that all the processor in the system or every node in the network does approximately the equal amount of work at any instant of time. In this paper, we propose a new two level fuzzy approach for dynamic load balancing in cloud computing. This approach characterizes the uncertainty in a distributed system by using the fuzzy logic. The processor speed and queue length of nodes are used to balance the load of the nodes in cluster level and processing power and average queue length of clusters are used to balance the load of the clusters in cloud level through fuzzy logic. In comparative study, proposed algorithm shows better average of response time and throughput than Round Robin and Randomize algorithms.