Dynamic Scheduling for Cloud Reliability using Transportation Problem

Abstract

Problem statement: Cloud is purely a dynamic environment and the existing task scheduling algorithms are mostly static and considered various parameters like time, cost, make span, speed, scalability, throughput, resource utilization, scheduling success rate and so on. Available scheduling algorithms are mostly heuristic in nature and more complex, time consuming and does not consider reliability and availability of the cloud computing environment. Therefore there is a need to implement a scheduling algorithm that can improve the availability and reliability in cloud environment. Approach: We propose a new algorithm using modified linear programming problem transportation based task scheduling and resource allocation for decentralized dynamic cloud computing. The Main objective is to improve the reliability of cloud computing environment by considering the resources available and it’s working status of each Cluster periodically and maximizes the profit for the cloud providers by minimizing the total cost for scheduling, allocation and execution cost and minimizing total turn-around, total waiting time and total execution time. Our proposed algorithm also utilizes task historical values such as past success rate, failure rate of task in each Cluster and previous execution time and total cost for various Clusters for each task from Task Info Container (TFC) for tasks scheduling resource allocation for near future. Results: Our approach TP Scheduling (Transpotation Problem based) responded for various tasks assigned by clients in poisson arrival pattern and achieved the improved reliability in dynamic decentralized cloud environment. Conclusion: With our proposed TP Scheduling algorithn we improve the Reliability of the decentralized dynamic cloud computing.