The cloud has several nodes or VM that receive the requests for processing. The increased number of cloud users from different areas has made the requests (the load) that go to the servers too much. Even they cannot tell exactly from which server or virtual machine (VM) they are processing their data.Ĭloud computing operates in a distributed computing manner by using the cloud, people who are found in different geographical locations can access a single cloud system. These cloud users are masked from their background operations. Due to its simplicity to use and other factors, cloud systems have multiple customers, increasing each year. However, it has several critical issues that need serious consideration, like security, fault tolerance, and load balancing. These days cloud computing is an excellent platform that is used to store users’ data at low cost, being available entirely all the time. The one which is adapted from the National Institute of Standards and Technology (NIST) which is commonly known as the NIST definition defines cloud computing as a model that lets and provisions its users to get ubiquitous, convenient, on-demand network access to a shared pool of configurable computing resources (e.g., networks, servers, storage, applications, and services). There are several definitions of cloud computing. They can use it simply from their device, which can access the Internet through the browser or preinstalled cloud application. That means people suffering from different constraints, either hardware or software or power, can proceed to their work from the cloud itself without requiring extra facilities in which they can have a high amount of storage, and they can use their application software and others without any random access memory (RAM), central processing unit (CPU), and other constraints. IntroductionĬloud computing is the use of computer system resources on-demand as a public utility for the users of the cloud. The newly proposed “component-based throttled load balancing algorithm” is found to be better than the existing throttled algorithm and the other five selected algorithms in terms of response time, processing time, and resource utilization. ![]() The proposed algorithm resulted in 325.30-microsecond response time and 27.12-microsecond processing time by the closest data center service broker policy. Based on the comparative analysis with the other five popularly used load balancing algorithms, the component-based algorithm’s performance is significantly enhanced. For the performance test, the cloud analyst simulation tool was used. The free VM component holds free VMs temporarily until they are moved to the free VM manager component. The VM reader component reads all available VMs. This research paper proposes a component-based throttled load balancing algorithm with VM reader, free VM holder, and free VM manager components. Such issues create a curiosity to enhance this algorithm’s performance for efficiently managing the dynamic loads of the cloud VMs. These strategic issues most often degrade the performance of the applied load balancing algorithm. The throttled algorithm utilizes only the first VMs available, the next, and so on. Throttled load balancing algorithm manages loads of the virtual machines by dividing the virtual machines into two segments, that is, “available” and “free.” To do this, the throttled algorithm uses a single component to assign the virtual machines and other tasks. Load balancing algorithms have varied issues of efficiency due to certain parameters like the capability of the lowest resource utilization, response time, higher overhead while checking the idle or normal nodes, and many others. Load balancing issues are managed by load balancing algorithms. There are possibilities of the highest loads to be tolerated by the VMs over the cloud servers without crashing. VMs need to be balanced with the varied loads or dynamics of traffic. One of the most critical challenges the cloud data centers face is managing the loads over geographically dispersed data centers and their virtual machines (VMs). ![]() Cloud services are accessed from different geographical locations where client migration or switching from one server to another based on the loads is a common phenomenon.
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