Geometric structures for designing sensor network middleware services
Unlike traditional networks where topologies are logical and are treated as arbitrary graphs, wireless sensor networks exhibit certain spatial characteristics that are suitable for geometric modeling. We exploit the geometry of wireless sensor networks to design middleware services for querying, tracking, clustering and even object classification.
In Glance, we have used geometric ideas to design a lightweight querying service for static events in sensor networks that can be appropriately tuned to be efficient under different publishing and querying rates. We have used properties of logarithmic spirals to design Trail, a network tracking service for mobile objects. In order to be scalable, it is important that algorithms for querying and tracking in large scale sensor networks are distributed and local. Queries should not have to be answered by one or more centralized locations. At the same time events and tracks should not be published network-wide either. Even the faults in the network should be handled in a local manner. In both Glance and Trail, we have designed querying and publishing strategies by which the locality properties are satisfied.
By exploiting the double-band nature of the wireless radio model, FLOC is a fast and local clustering service that partitions a multi-hop wireless network into non-overlapping and approximately equal-sized clusters in O(1) time. By using FLOC as a building block, we have designed an efficient snapshot service for wireless sensor networks in which a global state snapshot of the system is delivered to potentially all nodes with latency, frequency and error that decrease linearly with distance.
We have also used network based estimation of the spatial characteristics of the sensing region [influence field] in order to classify objects monitored by a wireless sensor network.
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