Multi-objective Non-cooperative Game Model for Cost-based Task Scheduling in Computational Grid

TL;DR

This paper introduces a game theory-based algorithm for cost-efficient task scheduling in computational grids, addressing the complexity of diverse node environments and load-balancing challenges.

Contribution

It presents a novel non-cooperative game model specifically designed for grid load balancing to minimize operational costs.

Findings

The algorithm effectively reduces grid operational costs.

It handles complex, heterogeneous node environments.

Demonstrates improved load balancing performance.

Abstract

Task scheduling is an important and complex problem in computational grid. A computational grid often covers a range of different kinds of nodes, which offers a complex environment. There is a need to develop algorithms that can capture this complexity as while as can be easily implemented and used to solve a wide range of load-balancing scenarios. In this paper, we propose a game theory based algorithm to the grid load balancing problem on the principle of minimizing the cost of the grid. The grid load-balancing problem is treated as a non-cooperative game. The experiment results demonstrate that the game based algorithm has a desirable capability to reduce the cost of the grid.