Public Cloud Server partition based on location and Load

Authors: Megha Birthare, Prof. Rasna Sharma

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Abstract

With growth of cloud computing load balancing is important impact on performance. Cloud computing efficiency depends on good load balancer. Many type of situation occur that time cloud partitioning is done by load balancer. Different type of situation needed different type of strategies for public cloud portioning using load balancer.in this paper we work on, partition of public cloud using two type of situation first is load status evaluation and second is cloud division rules. Load status evaluation is measure in number of cloudlets arrives at datacenter and cloud divisions rules are based on cloudlet come from which geographical location. On the basis of geographical location we partition public cloud and improve performance of load balancing in cloud computing. We implement pro

Introduction

Cloud Computing has become the most viable solution for the problems that are computation intensive. Cloud provides the method of sharing resources and services to user on demand. Virtualized resource and services can be used without the knowledge of geographical differences. Cloud computing provides mechanisms that concentrate on run time demand of computing resources, like storage, availability, software etc. The available Cloud platforms distinguish among the service type, the cost, the Quality of Service (QoS) as well as performance. This fact brings Cloud customers the flexibility of freely selecting target architecture from broad range of Cloud platforms. However at the same time, this raises the issue of the interoperability among the different Clouds [13]. Development of efficient service provisioning policies is the major issues in Cloud research. Modern Clouds exists in an open world characterized by constant changes occurring autonomously and unpredictably. In this context, game theoretic methods allow in-depth analytical understanding of the service-provisioning problem [2]. The cloud computing mainly offers three types of services viz: Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS).

Conclusion

The several strategies lack efficient scheduling and load balancing resource allocation techniques leading to increased operational cost and give less customer satisfaction. Load balancing in the cloud-computing environment has an important impact on the performance. Good load balancing makes cloud computing more efficient and improves user satisfaction. In this paper we have proposed a better load balance model for the Job Seeker’s Web Portal based on the cloud-partitioning concept with a switch mechanism to choose different strategies for different situations. Thus, this model divides the public cloud into several cloud partitions. When the environment is very large and complex, these divisions simplify the load balancing. The cloud has a main controller that chooses the suitable partitions for arriving jobs based on arrival date. Thus with cloud partitioning concept it is possible to provide good load balancing and hence improving the overall performance of cloud environment and user satisfaction.