In the field of network technology, the cloud computing technology is showing phenomenal growth due to the advancement of communication technology, explosive use of Internet and solve large-scale problems. It allows both hard5 ware, and software applications as resources over the Internet for the cloud user. The cloud computing is an Internet-based computing model that share resources (e.g., networks, servers, storage, applications, and services), software, and information to various devices of the user on demand [1]. The Cloud computing is a path to utility computing embraced by some major IT companies 10 such as Amazon, Apple, Google, HP, IBM, Microsoft, Oracle, and others. The Cloud Computing model has three service models, namely, Software as a Service (SaaS), Platform as a Service (PaaS), Infrastructure as a Service (IaaS) and four deployment models, namely, private, public, hybrid and community. 15 The efficient and scalable features of cloud computing can achieve by maintaining proper management of cloud resources. These cloud resources are in the virtual form which is the most important characteristics of the cloud system. The Cloud Service Provider (CSP) provides services to the users in rented basis. The role of CSP to provide the services to the user is a very complex one with 20 the available virtual cloud resources. Therefore, researchers have been given more attention towards the balancing of the load. This load balancing has a sound impact on the system performance. The CSP design a trade-off between the financial benefits and user satisfactory through load balancing. The load balancing procedure also taking care of the Service Level Agreements (SLAs), 25 the agreement between the CSP and the cloud users. The load balancing in clouds may be among physical hosts or VMs. This balancing mechanism distributes the dynamic workload evenly among all the nodes (hosts or VMs). The load balancing in the cloud is also referred as load balanc30 ing as a service (LBaaS). There are two versions of load balancing algorithms: 2 static and dynamic. The static-based balancing algorithms are mostly fit for stable environments with homogeneous system. Dynamic-based balancing algorithms are more adaptable and effective in both homogeneous and heterogeneous environment. However, the application of static load balancing procedures has 35 less system overhead as compared to the dynamic load balancing procedures. A large number of heuristics has been proposed in the literature to this problem. Also, some metaheuristics techniques are applied to this, and here, we explained those technologies [2].