Queue Theory based Response Time Analyses for Geo-Information Processing Chain

TL;DR

This paper introduces a queue theory-based mathematical model using game theory to analyze and optimize response times in geo-information processing chains, especially under concurrent task conditions, improving performance over existing methods.

Contribution

It proposes a non-cooperative game model with an iterative algorithm to find Nash equilibrium, enhancing task utility and conflict management in geo-information service chains.

Findings

Better convergence to Nash equilibrium.

Improved task utility compared to existing methods.

Enhanced performance in concurrent task scenarios.

Abstract

Typical characteristics of remote sensing applications are concurrent tasks, such as those found in disaster rapid response. The existing composition approach to geographical information processing service chain, searches for an optimisation solution and is what can be deemed a "selfish" way. This way leads to problems of conflict amongst concurrent tasks and decreases the performance of all service chains. In this study, a non-cooperative game-based mathematical model to analyse the competitive relationships between tasks, is proposed. A best response function is used, to assure each task maintains utility optimisation by considering composition strategies of other tasks and quantifying conflicts between tasks. Based on this, an iterative algorithm that converges to Nash equilibrium is presented, the aim being to provide good convergence and maximise the utilisation of all tasks under concurrent task conditions. Theoretical analyses and experiments showed that the newly proposed method, when compared to existing service composition methods, has better practical utility in all tasks.