Comparison of Server Load Balancing Techniques in Cloud Simulated Environment

The performance of cloud services depends on the scheduling algorithms that distribute the incoming network traffic among their servers to achieve effectiveness in execution of tasks. These algorithms assign the tasks to various computing resources which are virtual in nature. In a cloud environment, assigning tasks to corresponding resources is NP-hard in nature. The traditional scheduling algorithms like FCFS, SJF, and Round Robin etc. will not be suitable to solve NP-hard scheduling problems. Cloud scheduling considers various criteria like resource utilization, cost, makespan and throughput. In this paper, cloud scheduling algorithms such as Max-Min Algorithm, Min-Min Algorithm, Enhanced Max-Min Algorithm and Greedy algorithms for server load balancing in cloud environments are implemented. The paper concludes with the comparative analysis of these algorithms.