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Tuft: Tree Based Heuristic Data Dissemination for Mobile Sink Wireless Sensor Networks.
- Source :
- IEEE Transactions on Mobile Computing; Apr2022, Vol. 21 Issue 4, p1520-1536, 17p
- Publication Year :
- 2022
-
Abstract
- Wireless sensor networks (WSNs) with a static sink suffer from concentrated data traffic in the vicinity of the sink, which increases the burden on the nodes surrounding the sink, and impels them to deplete their batteries faster than other nodes in the network. Mobile sinks solve this corollary by providing a more balanced traffic dispersion, by shifting the traffic concentration with the mobility of the sink. However, it brings about a new expenditure to the network, where prior to delivering data, nodes are obligated to procure the sink's current position. This paper proposes Tuft, a novel hierarchical tree structure that is able to avert the overhead cost from delivering the fresh sink's position while maintaining a uniform dispersion of data traffic concentration. Tuft appropriates the mobility of the sink to its advantage, to increase the uniformity of energy consumption throughout the network. Moreover, we propose Tuft-Cells, a distributed dissemination protocol that models data routing as a multi-criteria decision making (MCDM) in three steps. To begin with, each criterion constitutes a random variable defined by a mass function. Each of these cirterion serves a proportionately distinguishable alternative, and hence, may conflict. Therefore, the analytic hierarchy process (AHP) quantifies the relationship between criteria. Finally, the final forwarding decision is derived by a weighted aggregation. Tuft is compared with state-of-the-art protocols, and the performance evaluation illustrates that our protocol adheres to the requirements of WSNs, in terms of energy consumption, and success ratio, considering the additional overhead cost brought by the mobility of the sink. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 15361233
- Volume :
- 21
- Issue :
- 4
- Database :
- Complementary Index
- Journal :
- IEEE Transactions on Mobile Computing
- Publication Type :
- Academic Journal
- Accession number :
- 155735797
- Full Text :
- https://doi.org/10.1109/TMC.2020.3022403