Novel load balancing approach based on ant colony optimization technique in cloud computing

Abstract

The cloud is the framework in which communication is connected with virtual machines, data centers, hosts, and brokers. The broker searches for a highly reliable cloudlet virtual machine for execution. Vulnerability can occur in the network because of which framework gets overburden. A research strategy is introduced in this article to expand the fault tolerance of the framework. The proposed approach improvement depends on the algorithm of ant colony optimization (ACO) that can choose the better virtual machine on which is to migrate the cloudlet to reduce the execution time and energy consumption. The efficiency of the proposed approach simulated in terms of execution time, energy consumption and examined with CloudSim. The introduction is provided in this article with a detailed description of cloud computing and, in addition, green cloud computing with its models. This article also discussed the virtual machine (VM) in more depth in the introduction section, which allows cloud service providers to supervise cloud resources competently while dispensing with the need for human oversight. Then the article submitted and explained the related works with their discussion and then it explained the novel proposed load balancing based on ACO technique and concluded that the execution time and energy consumption of the proposed technique is better than the three-threshold energy saving algorithm (TESA) technique that is commonly used in cloud load balancing.

An efficient cloudlet scheduling via bin packing in cloud computing

“…In [18] developed an efficient task scheduling method to enhance resource efficiency and fault tolerance utilising a dynamic load-based distributed queue for dependent jobs. In [19] developed an ACO method to select the best virtual machine for executing a cloudlet to reduce energy consumption and execution time. We also proposed two tasks scheduling works [20] and [21]; the first accelerated the PSO task scheduling algorithm, and the second improved the makespan and other performance metrics using deep q-learning.…”

Load‐Balancing Strategy: Employing a Capsule Algorithm for Cutting Down Energy Consumption in Cloud Data Centers for Next Generation Wireless Systems

“…Virtualization is an important method in data centers because it allows customers to share resources by using virtual machines (VMs). Each virtual machine is separated and utilized to run customer applications, with storage capacity, primary memory, CPU, I/O capabilities, and network bandwidth requirements [ 9 ]. Some of the important characteristics that promote cloud computing performance are physical machine consolidation, fault tolerance, and load balancing.…”

Hybrid algorithm for cloud-fog system based load balancing in smart grids

“…Many studies have been done regarding fog and cloud load balancing based on meta-heuristic algorithms [34]. PSO performance was enhanced in multiple studies by combining it with other algorithms to overcome its drawbacks in global solution.…”