A B S T R A C T
Cloud computing, a framework for enabling convenient, and on-demand network access to a shared pool of computing resources is emerging as a new paradigm of large-scale distributed computing. It has widely been adopted by the industry, though there are many existing issues like Load Balancing, Virtual Machine Migration, Server Consolidation, Energy Management, etc. that are not fully addressed. The objective and motivation load balancing techniques in cloud computing and encourage the amateur researcher in this field, so that they can contribute in developing more efficient load balancing algorithm. This will benefit interested researchers to carry out further work in this research area. Load balancing is a methodology to distribute work load across multiple computers, or other resources over the network links to achieve the optimal resource utilization, minimum data processing, minimum average response time and avoid overhead. We are proposing the OLB + LBMM to balance the load on the cloud and compared it with the existing load balancing methods such as Honeybee Foraging Behavior, Active Clustering. The main objective of the research is balance the load on cloud and consumes less energy as compared to previous, on the cloud by using proposed method. Also we have to prove that our proposed technique is more efficient for load balancing and energy consumption on cloud as compared to previous.
Load balancing, OLB+LBMM, Active Clustering, Honeybee, Paas, Iaas, Saas.