Data-Based Cluster-Tree Formation Scheme for Large-Scale Wireless Sensor Networks

• Type: Article in International Conference Proceedings Book
• Date: 2018

Authors

Andrade, ATC (Author) Other; Siedersberger, D (Author) Other; Montez, C (Author) Other; Moraes, R (Author) Other; Leao, E (Author) Other; Francisco Vasques (Author) FEUP

Conference proceedings International

Title: Proceedings - IEEE 16th International Conference on Industrial Informatics, INDIN 2018

Pages: 175-180

16th IEEE International Conference on Industrial Informatics, INDIN 2018

18 July 2018 through 20 July 2018

Indexing

ISI Web of Knowledge - 6 Citations

Scopus - 6 Citations

Other information

Authenticus ID: P-00P-TEN

DOI: 10.1109/indin.2018.8471938

Abstract (EN): Topology formation in wireless sensor networks is usually done assuming just either the geographical proximity between nodes or the signal strength of communication. In this paper, a heuristic called DbCTF is proposed to guide the formation of cluster-tree networks, which also considers data clustering techniques. The use of DbCTF allows the setup of a data-based topology in the cluster-tree, and also the prioritisation of monitored regions in which relevant events may be occurring. The performance of DbCTF has been compared with a state-of-the-art algorithm, for the specific case of a classical WSN laboratory experiment. The simulation assessment revealed that the cluster-tree formed by DbCTF was able to reduce by more than 20% the average communication delay of message streams conveying critical data, and was also able to increase by more than 35% the average lifetime of the network.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 6