Cloud computing — The effect of generalized spring tensor algorithm on load balancing

In business world, competitors use innovative approaches to improve their performance and profits. Cloud computing is one of these creative concepts that allowed companies to further taking advantage of their potential. Cloud computing is assisting companies to execute their business plans more efficiently. As cloud computing has multi-tenancy structure, availability and efficiency of the resources is essential foundation of the cloud architecture. Recent studies showed that, optimized cloud computing could be seen as an elastic network of resources that are interacting with each other, to minimize the waiting time and utilize the throughput. Therefore load balancing and resource management can be highlighted as the main concerns in cloud computing as they are impacting the network performance directly. This research aims to discuss the current challenges existing in load balancing algorithms. Different metrics and policies of the relevant load balancer algorithms have been investigated and as a result, collective behavior has been proposed as a new policy for classification of elasticity mechanism in load balancing.