Task scheduling is an integrated component of computing. With the emergence of grid and ubiquitous computing, newer challenges have arisen in task scheduling. Unlike traditional parallel computing, grid is a shared enterprising environment where is no central control. The goal of grid task scheduling is to achieve high system throughput and to match the application needs with the available computing resources. This matching of resources in a non-deterministically shared heterogeneous environment leads to concerns on Quality of Service (QoS).
In this paper we introduce a novel QoS guided task scheduling algorithm for grid computing. This new algorithm is based on the general adaptive scheduling heuristics and an added in QoS guide component. It has been tested in a simulated grid environment. The experimental results show that the new QoS guided min-min heuristic can lead to significant performance gain in various applications, and it is as tolerable as existing heuristics for inaccurate inputs of computing resources.
Source: Illinois Institute of Technology
Authors: Xiaoshan He | Xian-He Sun | Gregor Von Laszewski
Scheduling Algorithms for Grid Computing: State of the Art and Open Problems
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