Title: TAAG: An Efficient Task Allocation Algorithm for Grid Environment
Abstract: Grid computing is a form of distributed computing where the resources of various computers are shared to solve a particular problem. Due to heterogeneity of resources, scheduling a task is significantly complex in nature. Scheduling strategy plays a vital role in the grid environment to schedule the user tasks and dispatch them to the appropriate grid resources. A good task scheduling method is the one which reduces the total time taken for execution of a given task in the grid. In this paper, we propose a new scheduling algorithm called TAAG (An Efficient Task Allocation for Grid) for efficient allocation of tasks on resources in the Grid environment. The proposed algorithm tries to use the advantages of the recent popular task scheduling algorithm known as Improved Min-Min Task Scheduling Algorithm (2) and covers its disadvantages by using a new resource allocation model. In this paper, the loads of the task are divided and are allocated into resources with respect to the computing capacity of the resource. Experimental results show that the proposed algorithm obtain better solution in terms of completion time, cost, makespan and load balancing compared to the existing algorithms. Keyword- Grid scheduling, Resource management, Workload distribution, Task selection, Resource allocation. I. INTRODUCTION Computational Grids are becoming more prevalent, due to the sharp decrease in the hardware and integration costs. Scientific applications in general, require higher computation capabilities. But affordability of a single system becomes very high. Due to the low cost nature of the grids, and their obvious advantages over super computers, grids are mostly preferred for usage in scientific applications. Further, grids can provide better performance than larger parallel super computers. But for providing higher processor efficiencies, efficient scheduling policies are required. The performance of a grid largely depends on optimal scheduling policies used in it. A proper scheduling algorithm should consider most or all of the QoS properties, viz. waiting time, makespan, load balance, flow time, turn-around time, response time, total completion time, bounded slowdown time, stretch time, fairness etc. The more alluring advantages of grids and the highly available nature of the grids have persuaded potential researchers to work in the area. Scheduling refers to the process of providing the processor time to threads, process or data flows. This is usually done to load balance and to share system resources effectively or to achieve a target quality of service. The need for a scheduling algorithm arises from the requirement for most modern systems to perform multiplexing. Scheduling in a grid is not considered as a single problem, instead a family of problems, with many constraints, and each with different properties which are to be considered while designing a scheduling algorithm for a grid. It is observed that Grid Scheduling is a Non-deterministic Polynomial time (NP-Complete) problem (1). The Improved Min-Min Task Scheduling Algorithm in Grid Computing (2) estimates the execution time of each task on different resources. With estimated result the suitable algorithm is used to schedule the task on the selected resource. Thus the execution of the task is delayed during the estimation process done on each resource. This paper proposes a new algorithm, named TAAG (An Efficient Task Allocation in Grid) to resolve the resource allocation problem by executing a single task on a number of resources by dividing the load of the task with respect to the computing capacity of the resource, by avoiding communication delay to submit a portion of the load to the resources.
Publication Year: 2014
Publication Date: 2014-01-01
Language: en
Type: article
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Cited By Count: 1
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