Network-lifetime maximization of wireless sensor networks

Yetgin, Halil, Cheung, Kent Tsz Kan, El-Hajjar, Mohammed and Hanzo, Lajos (2015) Network-lifetime maximization of wireless sensor networks IEEE Access, 3, pp. 2191-2226. (doi:10.1109/ACCESS.2015.2493779).


[img] PDF access-hanzo-2493779-proof.pdf - Accepted Manuscript
Available under License Other.

Download (15MB)
[img] PDF 07322190.pdf - Version of Record
Available under License Other.

Download (21MB)


Network lifetime (NL) maximization techniques have attracted a lot of research attention owing to their importance for extending the duration of the operations in the battery-constrained wireless sensor networks (WSNs). In this paper, we consider a two-stage NL maximization technique conceived for a fully-connected WSN, where the NL is strictly dependent on the source node’s (SN) battery level, since we can transmit information generated at the SN to the destination node (DN) via alternative routes, each having a specific route lifetime (RL) value. During the first stage the RL of the alternative routes spanning from SN to DN is evaluated, where the RL is defined as the earliest time, at which a sensor node lying in the route fully drains its battery charge. The second stage involves the summation of these RL values, until the SN’s battery is fully depleted, which constitutes the lifetime of the WSN considered. Each alternative route is evaluated using cross-layer optimization of the power allocation, scheduling and routing operations for the sake of NL maximization for a predetermined per-link target signal-to-interference-plus-noise ratio (SINR) values. Therefore, we propose the optimal but excessive-complexity algorithm, namely the exhaustive search algorithm (ESA) and a near-optimal single objective genetic algorithm (SOGA) exhibiting a reduced complexity in a fully connected WSN. We demonstrate that in a high-complexity WSN, the SOGA is capable of approaching the ESA’s NL within a tiny margin of 3.02% at a 2.56 times reduced complexity. We also show that our NL maximization approach is powerful in terms of prolonging the NL, while striking a trade-off between the NL and the quality of service (QoS) requirements.

Item Type: Article
Digital Object Identifier (DOI): doi:10.1109/ACCESS.2015.2493779
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Organisations: Southampton Wireless Group
ePrint ID: 381434
Date :
Date Event
9 October 2015Accepted/In Press
9 November 2015e-pub ahead of print
17 November 2015Published
Date Deposited: 12 Oct 2015 10:35
Last Modified: 17 Apr 2017 05:13
Further Information:Google Scholar

Actions (login required)

View Item View Item