Research Article
Coordinate-Free Boundary Nodes Identification by Angle Comparison in Wireless Sensor Networks
@INPROCEEDINGS{10.1007/978-3-319-78078-8_1, author={Linna Wei and Xiaoxiao Song and Xiao Zheng}, title={Coordinate-Free Boundary Nodes Identification by Angle Comparison in Wireless Sensor Networks}, proceedings={Quality, Reliability, Security and Robustness in Heterogeneous Systems. 13th International Conference, QShine 2017, Dalian, China, December 16 -17, 2017, Proceedings}, proceedings_a={QSHINE}, year={2018}, month={4}, keywords={Boundary node identification Coordinate-free method Angle comparison Coverage problem Wireless sensor networks}, doi={10.1007/978-3-319-78078-8_1} }
- Linna Wei
Xiaoxiao Song
Xiao Zheng
Year: 2018
Coordinate-Free Boundary Nodes Identification by Angle Comparison in Wireless Sensor Networks
QSHINE
Springer
DOI: 10.1007/978-3-319-78078-8_1
Abstract
Identifying the boundary nodes of a wireless sensor network (WSN) is one of the prerequisites for healing coverage holes, which belongs to the main problems of QoS in a network. Most of the existing solutions for this problem rely on the usage of coordinates or a relatively even distribution of sensors on the underlying network. However, as equipping localization devices on sensors usually means considerably higher cost, coordinates are often unavailable in low-budget networks. And it is often hard to guarantee the distribution of nodes. Therefore, identifying the boundary nodes without coordinates still faces difficulties. In this paper, we propose a distributed algorithm to solve this problem. In our method, a checking node first finds out all the potential triangles that with vertices from the 1-hop neighbors of the node. Then, the sensor keeps triangles containing it by calculating angles. At last, triangles with gap edges are identified by angle comparison to avoid wrong identification of a boundary node which has a U shaped ring locates beside. Illustrated simulation results show the performance effectiveness of our method, especially in networks with random and uneven sensor deployment.