Integrating Wireless Sensor Networks with the Grid
IEEE Internet Computing
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
An Integrated and Flexible Scheduler for Sensor Grids
UIC '07 Proceedings of the 4th international conference on Ubiquitous Intelligence and Computing
DCOSS '08 Proceedings of the 4th IEEE international conference on Distributed Computing in Sensor Systems
A Sensor Grid Infrastructure for Large-Scale Ambient Intelligence
PDCAT '08 Proceedings of the 2008 Ninth International Conference on Parallel and Distributed Computing, Applications and Technologies
A Distributed Architecture of Sensing Web for Sharing Open Sensor Nodes
GPC '09 Proceedings of the 4th International Conference on Advances in Grid and Pervasive Computing
A Sensor Grid Framework for Acoustic Surveillance Applications
NCM '09 Proceedings of the 2009 Fifth International Joint Conference on INC, IMS and IDC
A large-scale service-oriented sensor grid infrastructure
CCNC'09 Proceedings of the 6th IEEE Conference on Consumer Communications and Networking Conference
Providing service-oriented abstractions for the wireless sensor grid
GPC'07 Proceedings of the 2nd international conference on Advances in grid and pervasive computing
Truthful resource allocation in selfish sensor web
MSN'07 Proceedings of the 3rd international conference on Mobile ad-hoc and sensor networks
A generic architecture for sensor data integration with the grid
SAG'04 Proceedings of the First international conference on Scientific Applications of Grid Computing
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Sensor devices such as video cameras, infrared sensors and microphones are being widely exploited in grid application. The paper deals with multi-layer optimization in service oriented sensor grid to optimize utility function of sensor grid, subject to resource constraints at resource layer, service composition constraints at service layer and user preferences constraints at application layer respectively. The multi-layer optimization problem can be decomposed into three subproblems: sensor grid resource allocation problem, service composing problem, and user satisfaction degree maximization problem, all of which interact through the optimal variables for capacities of sensor grid resources and service demand. The proposed algorithm decomposes global sensor grid optimization problem into a sequence of three sub-problems at three layers via an iterative algorithm. The simulations are conducted to validate the efficiency of the multi-layer optimization algorithm. The experiments compare the performance of the multi-layer global optimization approach with application layer local optimization and resource layer local optimization approach respectively.