A Dynamic ACO-Based Elastic Load Balancer for Cloud Computing (D-ACOELB)

Abstract

Cloud computing is for the delivery of computational service like servers, software, databases, storage, networks, intelligence, analytics, and more via the Internet (“the cloud”) for tendering faster innovation, economies of scale, and flexible resources. The workload in cloud computing is defined as the amount of computational work at a given time that the computer has been given to do. This computational workload comprises of some number of users connected to and interacting with the computer’s applications additionally to the computer’s application programs running in the system. This workload may alter dynamically based on the available resources and the end-users. Hence, the key challenging duty in the cloud computing is balancing the workload among the Virtual Machines (VM’s) of the systems. So, there is a need for introducing an elastic dynamic load balancer for distributing the workloads efficiently in the cloud. A load balancer can distribute the loads among the VM’s of multiple servers or compute resources. The utilization of such elastic and dynamic load balancer can enhance the fault tolerance capability of applications and the availability of cloud resources. As your needs change, adding or removing of computing resources without disrupting the overall flow of requests is made possible utilizing this elastic and dynamic load balancer. Generally, an elastic load balancing task chains three types of balancers, they are Application Load Balancers, Classic Load Balancers, and Network Load Balancers. The Application Load Balancer can be chosen based on the need of applications. In this chapter, it proposed a dynamic and elasticity approach (D-ACOELB) for workload balancing in cloud data centers based on Ant Colony Optimization (ACO).