Comparative Analysis of Transmission Power Level and Packet Size Optimization Strategies for WSNs

Wireless sensor networks (WSNs) are envisioned to be a widely utilized technology in a smart grid (SG). Maximizing the network lifetime (NL) of WSNs in SG deployments is necessary to provide reliability and efficiency of the services offered to the entities involved. Harsh channel conditions in SG e...

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Bibliographic Details
Published in:IEEE systems journal 2019-09, Vol.13 (3), p.2264-2274
Main Authors: Yildiz, Huseyin Ugur, Kurt, Sinan, Tavli, Bulent
Format: Article
Language:English
Subjects:
Analytical models
Integer programming
Mixed-integer programming (MIP)
network lifetime (NL)
Optimization
packet size optimization
Payloads
Programming
Reliability
Remote sensors
Smart grid
smart grid (SG)
Smart grids
transmission power control
Wireless sensor networks
wireless sensor networks (WSNs)
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Summary:Wireless sensor networks (WSNs) are envisioned to be a widely utilized technology in a smart grid (SG). Maximizing the network lifetime (NL) of WSNs in SG deployments is necessary to provide reliability and efficiency of the services offered to the entities involved. Harsh channel conditions in SG environments have a profound impact on the communication channel utilized by WSNs. Therefore, optimizing the transmission power level (TPL) and data packet size (DPS) is of paramount importance for prolonging the WSN NL. In both TPL and DPS optimizations, two general approaches are followed: utilizing a constant TPL and/or DPS or optimizing TPL and/or DPS for each link. However, the joint optimization of the TPL and DPS for each link has not been investigated in the literature. In this study, we present a mixed-integer programming framework, which utilizes a detailed link-layer abstraction to analyze nine TPL and DPS assignment strategies for WSNs employed in SG environments. The results of our analysis reveal that there is a large margin to be exploited in prolonging the WSN NL by an appropriate selection of the strategy to be used in TPL and DPS optimization.
ISSN:1932-8184
1937-9234
DOI:10.1109/JSYST.2018.2864941