Simgrid: A Toolkit for the Simulation of Application Scheduling
CCGRID '01 Proceedings of the 1st International Symposium on Cluster Computing and the Grid
The Grid 2: Blueprint for a New Computing Infrastructure
The Grid 2: Blueprint for a New Computing Infrastructure
Characterizing mobility and network usage in a corporate wireless local-area network
Proceedings of the 1st international conference on Mobile systems, applications and services
A Generic Mobility Model for Resource Prediction in Mobile Grids
CTS '06 Proceedings of the International Symposium on Collaborative Technologies and Systems
Efficient task replication and management for adaptive fault tolerance in mobile Grid environments
Future Generation Computer Systems - Special section: Information engineering and enterprise architecture in distributed computing environments
Mobility-Aware Efficient Job Scheduling in Mobile Grids
CCGRID '07 Proceedings of the Seventh IEEE International Symposium on Cluster Computing and the Grid
A Classification of Emerging and Traditional Grid Systems
IEEE Distributed Systems Online
WiGriMMA: A Wireless Grid Monitoring Model Using Agents
Journal of Grid Computing
An effective job replication technique based on reliability and performance in mobile grids
GPC'10 Proceedings of the 5th international conference on Advances in Grid and Pervasive Computing
Monitoring service using markov chain model in mobile grid environment
GPC'10 Proceedings of the 5th international conference on Advances in Grid and Pervasive Computing
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The emerging Grid is extending the scope of resources to mobile devices and sensors that are connected through unreliable networks. Nowadays the number of mobile device users is increasing dramatically and the mobile devices provide various capabilities such as location awareness that are not normally incorporated in fixed Grid resources. Nevertheless, mobile devices exhibit inferior characteristics such as poor performance, limited battery life, and unreliable communication, compared to fixed Grid resources. Therefore, the job scheduling and the load balancing are more challenging and sophisticated in mobile Grid environment. This paper presents a novel balanced scheduling algorithm in mobile Grid, taking into account the mobility and availability in scheduling. We analyzed users' mobility patterns to quantitatively measure the resource availability that is classified into three types: full availability, partial availability, and unavailability. We also propose a load balancing technique by classifying mobile devices into nine groups depending on availability. The experimental results show that our scheduling algorithm provides a superior performance in terms of execution times to one without considering availability and load-balancing.