SART: speeding up query processing in sensor networks with an autonomous range tree structure

We consider the problem of constructing efficient P2P overlays for sensornets providing "Energy-Level Application and Services". In this context, assuming that a sensor is responsible for executing some program task but unfortunately it's energy-level is lower than a pre-defined threshold. Then, this sensor should be able to introduce a query to the whole system in order to discover efficiently another sensor with the desired energy level, in which the task overhead must be eventually forwarded. In this way, the "Life-Expectancy" of the whole network could be increased. Sensor nodes are mapped to peers based on their energy level. As the energy levels change, the sensor nodes would have to move from one peer to another and this operation is very crucial for the efficient scalability of the proposed system. Similarly, as the energy level of a sensor node becomes extremely low, that node may want to forward it's task to another node with the desired energy level. The method presented in presents a novel P2P overlay for Energy Level discovery in a sensornet. However, this solution is not dynamic, since requires periodical restructuring. In particular, it is not able to support neither join of sensor_nodes with energy level out of the ranges supported by the existing p2p overlay nor leave of empty overlay_peers to which no sensor_nodes are currently associated. On this purpose and based on the efficient P2P method presented in [16], we design a dynamic P2P overlay for Energy Level discovery in a sensornet, the so-called SART (Sensors' Autonomous Range Tree). The adaptation of the P2P index presented in guarantees the best-known dynamic query performance of the above operation. We experimentally verify this performance, via the D-P2P-Sim simulator.