SART: Speeding up Query Processing in Sensor Networks with an Autonomous Range Tree Structure

TL;DR

This paper introduces SART, a dynamic P2P overlay structure for sensor networks that efficiently manages energy level queries, supporting node joins and leaves, and improves query performance through an autonomous range tree design.

Contribution

The paper presents SART, a novel dynamic P2P overlay for energy level discovery in sensor networks, based on an adaptation of an existing efficient P2P method, enabling better support for network changes.

Findings

SART supports dynamic joins and leaves of sensor nodes.

Experimental results show improved query performance.

SART outperforms previous static overlays in energy level management.

Abstract

We consider the problem of constructing efficient P2P overlays for sensornets providing "Energy-Level Application and Services". The method presented in \cite{SOPXM09} 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 \emph{empty} overlay\_peers to which no sensor\_nodes are currently associated. On this purpose and based on the efficient P2P method presented in \cite{SPSTMT10}, 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 \cite{SPSTMT10} guarantees the best-known dynamic query performance of the above operation. We experimentally verify this performance, via the D-P2P-Sim simulator (D-P2P-Sim is publicly available at http://code.google.com/p/d-p2p-sim/).