Scheduling on Grid with communication Delay

TL;DR

This paper discusses scheduling challenges in Grid computing environments, emphasizing the impact of communication delays on task execution and resource management in distributed high-performance systems.

Contribution

It introduces a novel scheduling approach that accounts for communication delays in Grid environments, enhancing efficiency and resource utilization.

Findings

Improved scheduling algorithms reduce task completion time.

Communication delay modeling enhances resource allocation accuracy.

Experimental results show significant performance gains.

Abstract

Parallel processing, the core of High Performance Computing (HPC), was and still the most effective way in improving the speed of computer systems. For the past few years, the substantial developments in the computing power of processors and the network speed have strikingly changed the landscape of HPC. Geography distributed heterogeneous systems can now cooperate and share resources to execute one application. This computing infrastructure is known as computational Grid or Grid Computing. Grid can be viewed as a distributed large-scale cluster computing. From other perspective, it constitutes the major part of Cloud Computing Systems in addition to thin clients and utility computing [1,2, 3]. Hence, Grid computing has attracted many researchers [4]. The interest in Grid computing has gone beyond the paradigm of traditional Grid computing to a Wireless Grid computing [5,6].