A Modified Performance Oriented Approach for Load Balancing in Cloud Computing

Abstract

Cloud computing is advancing with a great pace. It has been already adopted over a large user base. Easy to use and anywhere access like capabilities of cloud computing has made it attractive among other technologies. It has not only reduced the deployment cost on user side but also allowed the big companies to sell their infrastructure to reduce the installation cost for the small organization. Roots of cloud computing extends to Grid computing. Along with the features of its ancestor technologies it also carries the loopholes present in those technologies. Some of these are identified and corrected in the recent times but still there remains the need for the improvement in cloud computing. These improvements can be divided widely into two categories viz. performance and security. The work done in this paper is devoted to performance enhancement for the user of existing cloud system. There are many simulation environments available to simulate this type of work. Among these available tools cloud Analyst is having attractive GUI along with transparent control of parameters. The Cloud Analyst is used to simulate the enhancements done in the existing system. Among various components load balancing task is used for the modification and enhancement aiming to reduce the response time, computational time and cost included. The results are analyzed and compared with the existing algorithms and as observed, proposed work is one step ahead of existing techniques.

Performance Evaluation of Novel Random Biased-Genetic Algorithm (NRB-GA): A Hybrid Load Balancing Algorithm in a Cloud Computing Environment

“…Ouhame and Hadi proposed a modifcation in the local search section and ftness function value in the grey wolf optimization algorithm to improve throughput, energy consumption, and average network execution time in VM for cloud computing [14]. Load-balancing algorithms that distributed the load among a number of heterogeneous servers were developed by Kaur and Jain [15]. VMs from diferent data centers were created with a host specifcation that detailed the core processor, processing speed, memory, storage, etc.…”