Scalable map-based tasking for urban scale multi-purpose sensor networks

Zoom [1] is a map-based approach for tasking sensor networks where sensing tasks are encoded into 2D task maps. The location of a pixel in the map corresponds to a physical location. The pixel value encodes information necessary for a node to discover and perform its corresponding sensing tasks. Although Zoom is very intuitive and scalable with the number of nodes, it does not scale well with the number of tasks with overlapping sensing regions. We propose and evaluate a new approach to encode sensing tasks for Zoom to reduce the size of encoded task maps. The key idea is that although the total number of tasks might be large, the number tasks being requested over a geographical region at a specific time can be small. Therefore, a fewer number of bits can be used to encode the IDs of the tasks being requested to reduce the size of encoded task maps. Our evaluation based on simulation shows that the new multiplexing approach can significantly reduce the size of encoded task maps.