An Energy-Efficient Middleware for Supporting Multimedia Services in Mobile Grid Environments
ITCC '05 Proceedings of the International Conference on Information Technology: Coding and Computing (ITCC'05) - Volume II - Volume 02
Energy-Constrained Scheduling for Weakly-Hard Real-Time Systems
RTSS '05 Proceedings of the 26th IEEE International Real-Time Systems Symposium
ICPP '06 Proceedings of the 2006 International Conference on Parallel Processing
Utility-based QoS optimisation strategy for multi-criteria scheduling on the grid
Journal of Parallel and Distributed Computing
Joint QoS optimization for layered computational grid
Information Sciences: an International Journal
A Robust Decentralized Job Scheduling Approach for Mobile Peers in Ad-hoc Grids
CCGRID '07 Proceedings of the Seventh IEEE International Symposium on Cluster Computing and the Grid
CCGRID '07 Proceedings of the Seventh IEEE International Symposium on Cluster Computing and the Grid
Energy-Efficient Scheduling for Parallel Applications Running on Heterogeneous Clusters
ICPP '07 Proceedings of the 2007 International Conference on Parallel Processing
WETICE '07 Proceedings of the 16th IEEE International Workshops on Enabling Technologies: Infrastructure for Collaborative Enterprises
Performance evaluation of mobile grid services
KES-AMSTA'08 Proceedings of the 2nd KES International conference on Agent and multi-agent systems: technologies and applications
Agent framework to support the computational grid
Journal of Systems and Software
Selective grid access for energy-aware mobile computing
UIC'07 Proceedings of the 4th international conference on Ubiquitous Intelligence and Computing
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Mobile grid, which combines grid and mobile computing, supports mobile users and resources in a seamless and transparent way. However, mobility, QoS support, energy management, and service provisioning pose challenges to mobile grid. The paper presents a tradeoff policy between energy consumption and QoS in the mobile grid environment. Utility function is used to specify each QoS dimension; we formulate the problem of energy and QoS tradeoff by utility optimization. The work is different from the classical energy aware scheduling, which usually takes the consumed energy as the constraints; our utility model regards consumed energy as one of the components of measure of the utility values, which indicates the tradeoff of application satisfaction and consumed energy. It is a more accurate utility model for abstracting the energy characteristics and QoS requirement for mobile users and resources in mobile grid. The paper also proposes a distributed energy---QoS tradeoff algorithm. The performance evaluation of our energy---QoS tradeoff algorithm is evaluated and compared with other energy and deadline constrained scheduling algorithm.