OPTICS Based Coverage in Wireless Sensor Network

TL;DR

This paper introduces an OPTICS-based clustering approach to optimize sensor placement in wireless sensor networks, reducing the number of sensors needed for effective coverage by identifying dense regions and eliminating overlaps.

Contribution

It proposes a novel application of the OPTICS clustering algorithm for coverage optimization in wireless sensor networks, including a decision tree for minimal coverage.

Findings

Reduces sensor count for coverage

Effectively identifies dense regions and outliers

Minimizes overlap in sensor deployment

Abstract

This paper deals with the coverage problem of wireless sensor network. We use the density based clustering technique - OPTICS to cover a target region with less number of sensor nodes. OPTICS works well to identify the outliers, core points and it obtains the denser regions. We define a level of acceptance to find next appropriate sensor in the region. We eliminate overlapped area and obtain a decision tree to minimally cover up the target region.