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

• Tipo: Artigo em Livro de Atas de Conferência Internacional
• Data: 2018

Autores

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

Ata de Conferência Internacional

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

Páginas: 175-180

16th IEEE International Conference on Industrial Informatics, INDIN 2018

18 July 2018 through 20 July 2018

Indexação

ISI Web of Knowledge - 6 Citações

Scopus - 6 Citações

Outras Informações

ID Authenticus: 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.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 6