Abstract
The integration of wireless sensor networks and grid computing is an emerging and promising area of research. Sensor grids extend the grid computing paradigm to the sharing of sensor resources in wireless sensor networks. By combining the complementary strengths of sensor networks and grid computing, sensor grids can support applications that require real-time information from the physical environment and vast amount of computational and storage resources.
One of the major challenges in the design of sensor grids is how to efficiently schedule sensor jobs across the collection of sensor resources in a sensor grid. In this paper, we design an integrated and flexible scheduler for a sensor grid testbed. The scheduler makes use of several scheduling and load balancing algorithms to suit the characteristics of sensor jobs. We performed extensive evaluations to characterize the behaviour and performance of these scheduling and load balancing algorithms. Our performance results indicate that the sensor grid scheduler can provide a good tradeoff betweeen performance objectives such as sensor resource utilization, sensor job throughput, and sensor grid lifetime.