Efficient Service Routing and Load Allocation Strategies for CloudSim-Enabled Visual Modeling Environment
Priyanka Chawla, Sanjaya Kumar Panda, Akash Patel · 2023
Cloud computing has significantly transformed the deployment and management of applications. It has simplified the complexities of handling service demand, installation and maintenance. However, selecting the most suitable cloud service provider (CSP) can be challenging due to the diversity in pricing models, geographical coverage regions and service offerings. A tool named Cloud Analyst has been developed to tackle these diversities. This tool employs service broker and load balancing strategies to allocate user bases (UBs) to datacenters (DCs) and virtual machines (VMs), respectively. However, these strategies’ performance can be further improved by developing more efficient ones. This paper introduces efficient service routing (between UBs to DCs), VM provisioning and load allocation (UBs to VMs) strategies for a CloudSim-enabled visual modeling environment. Their performance is assessed in comparison to existing using three factors: overall response time (ORT), DC request servicing time (DCRST) and total cost (TC) through the Cloud Analyst tool. Our strategies reduce ORT by 68.82%, resulting in faster application delivery, DCRST by 41.19%, and yield a TC savings of 51.78% compared to the existing strategies. These findings demonstrate the effectiveness of our strategies in enhancing performance over existing strategies.