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Cloud computing is the emerging interne based technology which emphasizes commercial computing. Cloud is a platform providing dynamic pool resources and virtualization. Based on a pay-as-you-go model, it enables hosting of pervasive applications from consumer, scientific, and business domains. To properly manage the resources of the service provider we require balancing the load of the jobs that are submitted to the service provider. Load balancing is required as we don't want one centralized server's performance to be degraded. A lot of algorithms have been proposed to do this task. In this paper we have analyzed of various policies utilized with different algorithm for load balancing using a tool called cloud analyst. Basically we have compared different variants of RR for load balancing.

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Cloud computing is gaining more popularity due to its advantages over conventional computing. It offers utility based services to subscribers on demand basis. Cloud hosts a variety of web applications and provides services on the pay-per-use basis. As the users are increasing in the cloud system, the load balancing has become a critical issue in cloud computing. Scheduling workloads in the cloud environment among various nodes are essential to achieving a better quality of service. Hence it is a prominent area of research as well as challenging to allocate the resources with changeable capacities and functionality. In this paper, a metaheuristic load balancing algorithm using Particle Swarm Optimization (MPSO) has been proposed by utilizing the benefits of particle swarm optimization (PSO) algorithm. Proposed approach aims to minimize the task overhead and maximize the resource utilization. Performance comparisons are made with Genetic Algorithm (GA) and other popular algorithms on different measures like makespan calculation and resource utilization. Different cloud configurations are considered with varying Virtual Machines (VMs) and Cloudlets to analyze the efficiency of proposed algorithm. The proposed approach performs better than existing schemes.

Cloud computing is an internet based computing. This computing paradigm has enhanced the use of network where the capability of one node can be utilized by other node. Cloud provides services on demand to distributive resources such as database, servers, software, infrastructure etc. in pay as you go basis. Load balancing is one of the vexing issues in distributed environment. Resources of service provider need to balance the load of client request. Different load balancing algorithms have been proposed in order to manage the resources of service provider efficiently and effectively. This paper presents a comparison of various policies utilized for load balancing.

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