A New Era to Balance the Load on Cloud using ACCLB Hybrid Load Balancing Technique
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Cloud computing is rapidly improving the latest technology. It is a term which is generally used in internet. This technological trend has enabled the realization of a new computing model called cloud computing, in which shared resources , information ,software & other devices are provided according to client requirement at specific time, are provided as general utilities that can be leased and released by users through the Internet in an on-demand fashion. In cloud computing, load balancing is required to distribute the dynamic local workload evenly across all the nodes. It helps to achieve a high user satisfaction and resource utilization ratio by ensuring an efficient and fair allocation of every computing resource. Load balancing in large distributed server systems is a complex optimization problem of critical importance in cloud systems and data centers. Load balancing algorithms are classified as static and dynamic algorithms. Static algorithms are mostly suitable for homogeneous and stable environments and can produce very good results in these environments. However, they are usually not flexible and cannot match the dynamic changes to the attributes during the execution time. In this paper, we have studied and implemented three algorithm using Java Programming and simulate the algorithms on CloudSim. CloudSim provides novel support for modeling and simulation of virtualized Cloud based data center environments such as dedicated management interfaces for VMs, memory, storage, and bandwidth. CloudSim layer manages the instantiation and execution of core entities (VMs, hosts, data centers, application) during the simulation period. And, we have proved that our proposed algorithm ACCLB gives the better results as compared to Vector Dot and Join Idle queue. We analyzed the results on the basis of different performance parameters such as Response time, Total Execution time and Energy consumption.
ACCLB, Join idle queue, Vector Dot, VMs, Data Center, Load balancing, Cloudsim