Cloud computing is an emerging computing environment which facilitates on demand services. As it contributes a large pool of computing resources, scheduling of tasks in an efficient manner is one of the main problems. Poor allocation of tasks affects the performance of the whole system. Hence it is very important to schedule the tasks for better utilization of resources by allocating them properly to particular resources in particular time. Efficient scheduling algorithms fulfill the user requirements and also satisfy the needs of the cloud service providers without affecting the performance of the environment. Execution Time based Sufferage Algorithm (ETSA), Cost and Completion Time based Sufferage Algorithm (CCTSA) and Modified Artificial Fish Swarm(MAFSA) Algorithm are efficient task scheduling approaches developed in cloud environment. These algorithms considered the parameters such as makespan, cost and resource utilization while scheduling the tasks and produced better performance. This paper presents a scheduling framework which converts the above said algorithms in to services and deployed in the cloud. Depends on the user’s requirements, the services will be delivered.
A Study Of BNP Parallel Task Scheduling Algorithms Metric's For Distributed Database System
