Optimization of Decentralized Scheduling for Physic Applications in Grid Environments

TL;DR

This paper introduces a decentralized scheduling framework tailored for physics applications in grid environments, optimizing resource utilization for satellite image processing tasks.

Contribution

It proposes a novel scheduling approach that efficiently maps data and compute-intensive applications onto grid resources at the group level.

Findings

Achieves near-optimal resource utilization.

Demonstrates effective scheduling of concurrent application groups.

Provides a framework adaptable to physics and satellite image processing applications.

Abstract

This paper presents a scheduling framework that is configured for, and used in physic systems. Our work addresses the problem of scheduling various computationally intensive and data intensive applications that are required for extracting information from satellite images. The proposed solution allows mapping of image processing applications onto available resources. The scheduling is done at the level of groups of concurrent applications. It demonstrates a very good behavior for scheduling and executing groups of applications, while also achieving a near-optimal utilization of the resources.