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Network-lifetime maximization of wireless sensor networks

Network-lifetime maximization of wireless sensor networks
Network-lifetime maximization of wireless sensor networks
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.
2191-2226
Yetgin, Halil
61dca21c-f273-4e17-81e7-16abcfb4cd32
Cheung, Kent Tsz Kan
77118f8f-b4ed-4e01-a747-9bb3a3809ad8
El-Hajjar, Mohammed
3a829028-a427-4123-b885-2bab81a44b6f
Hanzo, Lajos
66e7266f-3066-4fc0-8391-e000acce71a1
Yetgin, Halil
61dca21c-f273-4e17-81e7-16abcfb4cd32
Cheung, Kent Tsz Kan
77118f8f-b4ed-4e01-a747-9bb3a3809ad8
El-Hajjar, Mohammed
3a829028-a427-4123-b885-2bab81a44b6f
Hanzo, Lajos
66e7266f-3066-4fc0-8391-e000acce71a1

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

Record type: Article

Abstract

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.

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More information

Accepted/In Press date: 9 October 2015
e-pub ahead of print date: 9 November 2015
Published date: 17 November 2015
Organisations: Southampton Wireless Group

Identifiers

Local EPrints ID: 381434
URI: https://eprints.soton.ac.uk/id/eprint/381434
PURE UUID: 9d738e13-e266-43af-9f48-384cad76c3d8
ORCID for Mohammed El-Hajjar: ORCID iD orcid.org/0000-0002-7987-1401
ORCID for Lajos Hanzo: ORCID iD orcid.org/0000-0002-2636-5214

Catalogue record

Date deposited: 12 Oct 2015 10:35
Last modified: 06 Jun 2018 13:15

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