Cloud Service ranking using Checkpoint based Load balancing in real time scheduling of Cloud Computing

TL;DR

This paper proposes a checkpoint-based load balancing algorithm for real-time cloud service scheduling that predicts service ranks using historical data to reduce invocation overhead.

Contribution

It introduces a novel algorithm that predicts cloud service rankings based on past service data, enhancing efficiency in real-time scheduling.

Findings

Reduces service invocation time

Improves accuracy of service ranking

Enhances load balancing efficiency

Abstract

Cloud computing has been gaining popularity in the recent years. Several studies are being proceeded to build cloud applications with exquisite quality based on users demands. In achieving the same, one of the applied criteria is checkpoint based load balancing in real time scheduling through which suitable cloud service is chosen from a group of cloud services candidates. Valuable information can be collected to rank the services within this checkpoint based load balancing. In order to attain ranking, different services are needed to be invoked in the cloud, which is time consuming and wastage of services invocation. To avoid the same, this chapter proposes an algorithm for predicting the ranks of different cloud services by using the values from previously offered services.