GridSim: A Toolkit for the Modeling and Simulation of Distributed Resource Management and Scheduling for Grid Computing

TL;DR

GridSim is a Java-based simulation toolkit designed to evaluate resource management and scheduling algorithms in grid computing environments, enabling repeatable and controllable performance testing across diverse scenarios.

Contribution

The paper introduces GridSim, a novel toolkit that facilitates modeling and simulation of heterogeneous grid resources and scheduling algorithms in a controlled environment.

Findings

Simulated a Nimrod-G like resource broker.

Evaluated deadline and budget constrained scheduling algorithms.

Demonstrated effectiveness of GridSim for performance analysis.

Abstract

Clusters, grids, and peer-to-peer (P2P) networks have emerged as popular paradigms for next generation parallel and distributed computing. The management of resources and scheduling of applications in such large-scale distributed systems is a complex undertaking. In order to prove the effectiveness of resource brokers and associated scheduling algorithms, their performance needs to be evaluated under different scenarios such as varying number of resources and users with different requirements. In a grid environment, it is hard and even impossible to perform scheduler performance evaluation in a repeatable and controllable manner as resources and users are distributed across multiple organizations with their own policies. To overcome this limitation, we have developed a Java-based discrete-event grid simulation toolkit called GridSim. The toolkit supports modeling and simulation of heterogeneous grid resources (both time- and space-shared), users and application models. It provides primitives for creation of application tasks, mapping of tasks to resources, and their management. To demonstrate suitability of the GridSim toolkit, we have simulated a Nimrod-G like grid resource broker and evaluated the performance of deadline and budget constrained cost- and time-minimization scheduling algorithms.