Design of Optimal Service Scheduling based Task Allocation for Improving CRM in Cloud Computing

Abstract

Cloud computing is a service level computing that provide various service to the customers in order to establish an effective customer Relationship management (CRM). This offers various services like virtual machine, self-service provisioning, elasticity computing and storage (pay-as-you-go). Cloud computing provides shared services by enhancing resource management scalability, interoperability and prediction resources as a key to realize the resource utilization with high-performance management metrics. However, when the number of users increase, the process of task scheduling and service allocation using a traditional computing environment will degrade the CRM. In order to address this challenge, this research study proposes an Optimal Service Level Scheduling (OSLS) based task allocation design for improving CRM in cloud computing environment. The Adaptive Service Level Scheduling Algorithm (ASLSA) and the Support Level Load Balancer (SLLB) will reduce the workload in cloud computing environment in order to improve the Quality of Service (QoS) of CRM. This process will optimize the resource utilization in cloud platform based on the service requirement. It provides optimal scheduling features to CRM in order to improve the service optimality based on task and enhance the computational processes such as service load management, heterogeneous service delivery, pricing, resource pools and elasticity. The proposed system leverages high performance when compared to the existing models.