An Efficient Framework for Resource Optimization and Task Scheduling in Cloud Computing

Abstract

Cloud computing is the provision of computer services through the cloud (Internet), such as servers, storage, databases, networks, software, analytics, intelligence, etc.Cloud computing provides an alternative to local data centers. We can rent out any necessary services.Cloud optimization is the action of correctly selecting the right resources and assigning them to workloads or applications. Efficiency can be achieved when workload performance, compliance, and cost are balanced with the most suitable infrastructure in real time, correctly and continuously. Load balancing in the cloud is the distribution of workload across multiple computer sources. DNS load balancing uses software or hardware to perform functions, while cloud load balancing uses services provided by various computer network companies. Resource allocation (RA) is an important aspect of cloud computing. It can provide cloud resources to cloud consumers and provide services based on traffic. The cloud resource manager is in charge for allocating available resources to tasks for execution in an effective manner, thereby improving system performance, reducing response time, shortening the validity period, and effectively using resources. Therefore, resource mapping is predominant matter when considering task allocation and load balancing. This article aims to focus on solving problems related to task allocation by using the recommended optimization algorithm and applying the recommended load balancing algorithm, and then implement resource mapping.