Cloud computing mainly does not focus on local resource instead; it uses shared computing resources applications or resources. It has emerged as a new type of computing for accessing present network, managing computer resources and managing distributed computing across the network in order to achieve high degree of precision and reliability various challenges needs to be addressed. One of the challenges in cloud computing is load balancing. Load balancing is important due to the fact that it allows achieving balance in the load by distributing it across the system to all its nodes. Cloud environment allows various ways to achieve load balancing. This includes managing the load on CPU, network load and the load capacity of storage. The greatest impact of balancing the load in cloud computing environment is that it has higher satisfaction of the users as well as it utilizes the resources efficiently. Proper load balancing support substantial improvement of the system, building a fault tolerant system by creating backup and increase flexibility of the system so that it adapts the modification. In cloud computing, there are various algorithms to achieve load balancing and these algorithms behave differently with its some advantages and disadvantages. In this paper we present a study on the different load balancing algorithms in cloud computing environment and analyze the results based on make span metrics. The results of the experiments depict the efficiency of Round Robin, Shortest Job First, Ant Colony Optimization and Honey Bee load balancing algorithm in terms of make span and we find that Honey Bee load balancing algorithm give the best results among the other load balancing algorithms.

Cloud computing; Load balancing; Static Load balancing; Dynamic Load balancing; Algorithms; Load balancer; Load balancing metrics

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