Resource availability prediction using semi-Markov model in mobile grid environment

Abstract

Integration of mobile resources in grid environment increases the complexity of resource prediction owing to heterogeneity, dynamic nature of resources, mobility pattern and uncertainty in the availability. The mobile grid has geographically distributed autonomous resources and is composed of hardware and software resources that need to be located. The existing resource prediction approaches in mobile grid treat resources equally. These approaches face problems in terms of resource prediction times. This can be reduced by predicting the availability of resources based on its characteristics. The dynamic characteristics of mobile resources increase complexities in resource prediction and filtering process, which in turn increases resource prediction time. In this paper, a semi-Markov model based availability prediction mechanism is proposed for the mobile grid environment. This mechanism uses a semi-Markov model to predict the resources availability and a mapper to filter the resources based on task requirement, which reduces resource prediction time.