Cross-layer network lifetime optimisation considering transmit and signal processing power in wireless sensor networks

Article

Yetgin, H., Cheung, K.T.K., El-Hajjar, M. and Hanzo, L. 2014. Cross-layer network lifetime optimisation considering transmit and signal processing power in wireless sensor networks. IET Wireless Sensor Systems. 4 (4), pp. 176-182. https://doi.org/10.1049/iet-wss.2014.0049
TypeArticle
TitleCross-layer network lifetime optimisation considering transmit and signal processing power in wireless sensor networks
AuthorsYetgin, H., Cheung, K.T.K., El-Hajjar, M. and Hanzo, L.
Abstract

Maintaining high energy efficiency is essential for increasing the lifetime ot wireless sensor networks (WSNs), where the battery of the sensor nodes cannot be routinely replaced. Nevertheless, the energy budget of the WSN strictly relies on the communication parameters, where the choice of both the transmit power as well as of the modulation and coding schemes (MCSs) plays a significant role in maximising the network lifetime (NL). In this paper, we optimise the NL of WNSs by analysing the impact of the physical layer parameters as well as of the signal processing power (SPP) Psp on the NL. We characterise the underlying trade-offs between the NL and bit error ratio (BER) performance for a predetermined set of target signal-to-interference-plus-noise ratio (SINR) values and for different MCSs using periodic transmit-time slot (TS) scheduling in interference-limited WSNs. For a per-link target BER requirement (PLBR) of 10−3, our results demonstrate that a ‘continuous-time’ NL in the range of 0.58 – 4.99 years is achieved depending on the MCSs, channel configurations, and SPI.

Sustainable Development Goals11 Sustainable cities and communities
Middlesex University ThemeSustainability
PublisherWiley
The Institution of Engineering and Technology (IET)
JournalIET Wireless Sensor Systems
ISSN2043-6386
Electronic2043-6394
Publication dates
Online01 Dec 2014
Print01 Dec 2014
Publication process dates
Submitted06 Jun 2014
Accepted16 Oct 2014
Deposited15 Apr 2024
Output statusPublished
Digital Object Identifier (DOI)https://doi.org/10.1049/iet-wss.2014.0049
LanguageEnglish
Permalink -

https://repository.mdx.ac.uk/item/11z15q

Log in to edit
  • 21
    total views
  • 0
    total downloads
  • 2
    views this month
  • 0
    downloads this month

Export as

Related outputs

Smart infrastructures: Artificial Intelligence-Enabled lifecycle automation
Fortuna, C., Yetgin, H. and Mohorčič, M. 2023. Smart infrastructures: Artificial Intelligence-Enabled lifecycle automation. IEEE Industrial Electronics Magazine. 17 (2), pp. 37-47. https://doi.org/10.1109/MIE.2022.3165673
HANNA: Human-friendly provisioning and configuration of smart devices
Fortuna, C., Yetgin, H., Ogrizek, L., Municio, E., Marquez-Barja, J.M. and Mohorcic, M. 2023. HANNA: Human-friendly provisioning and configuration of smart devices. Engineering Applications of Artificial Intelligence. 126 (Part A). https://doi.org/10.1016/j.engappai.2023.106745
Multi-source multi-destination hybrid infrastructure-aided traffic aware routing in V2V/I networks
Ivanescu, T., Yetgin, H., Merrett, G.V. and El-Hajjar, M. 2022. Multi-source multi-destination hybrid infrastructure-aided traffic aware routing in V2V/I networks. IEEE Access. 10, pp. 119956-119969. https://doi.org/10.1109/access.2022.3221446
Machine learning for wireless link quality estimation: A survey
Cerar, G., Yetgin, H., Mohorčič, M. and Fortuna, C. 2021. Machine learning for wireless link quality estimation: A survey. IEEE Communications Surveys and Tutorials. 23 (2), pp. 696-728. https://doi.org/10.1109/COMST.2021.3053615
Twin-component near-pareto routing optimization for AANETs in the North-Atlantic Region relying on real flight statistics
Cui, J., Yetgin, H., Liu, D., Zhang, J., Ng, S.X. and Hanzo, L. 2021. Twin-component near-pareto routing optimization for AANETs in the North-Atlantic Region relying on real flight statistics. IEEE Open Journal of Vehicular Technology. 2, pp. 346-364. https://doi.org/10.1109/OJVT.2021.3095467
Minimum-delay routing for integrated aeronautical ad hoc networks relying on real flight data in the North-Atlantic Region
Cui, J., Liu, D., Zhang, J., Yetgin, H., Ng, S.X., Maunder, R. and Hanzo, L. 2021. Minimum-delay routing for integrated aeronautical ad hoc networks relying on real flight data in the North-Atlantic Region. IEEE Open Journal of Vehicular Technology. 2, pp. 310-320. https://doi.org/10.1109/OJVT.2021.3089543
Time-to-provision evaluation of IoT devices using automated zero-touch provisioning
Boskov, I., Yetgin, H., Vučnik, M., Fortuna, C. and Mohorčič, M. 2020. Time-to-provision evaluation of IoT devices using automated zero-touch provisioning. 2020 IEEE Global Communications Conference. Taipei, Taiwan 07 - 11 Dec 2020 IEEE. https://doi.org/10.1109/GLOBECOM42002.2020.9348119
On designing a machine learning based wireless link quality classifier
Cerar, G., Yetgin, H., Mohorčič, M. and Fortuna, C. 2020. On designing a machine learning based wireless link quality classifier. IEEE 31st Annual International Symposium on Personal, Indoor and Mobile Radio Communications. London, UK 31 Aug - 03 Sep 2020 IEEE. https://doi.org/10.1109/PIMRC48278.2020.9217171
Security, usability, and biometric authentication scheme for electronic voting using multiple keys
Ahmad, M., Rehman, A.U., Ayub, N., Alshehri, MD., Khan, M.A., Hameed, A. and Yetgin, H. 2020. Security, usability, and biometric authentication scheme for electronic voting using multiple keys. International Journal of Distributed Sensor Networks. 16 (7). https://doi.org/10.1177/1550147720944025
Learning to detect anomalous wireless links in IoT networks
Cerar, G., Yetgin, H., Bertalanic, B. and Fortuna, C. 2020. Learning to detect anomalous wireless links in IoT networks. IEEE Access. 8, pp. 212130-212155. https://doi.org/10.1109/ACCESS.2020.3039333
Analysis and optimization of unmanned aerial vehicle swarms in logistics: An intelligent delivery platform
Kuru, K., Ansell, D., Khan, W. and Yetgin, H. 2019. Analysis and optimization of unmanned aerial vehicle swarms in logistics: An intelligent delivery platform. IEEE Access. 7, pp. 15804-15831. https://doi.org/10.1109/ACCESS.2019.2892716
Transformation to advanced mechatronics systems within new industrial revolution: a navel framework in Automation of Everything (AoE)
Kuru, K. and Yetgin, H. 2019. Transformation to advanced mechatronics systems within new industrial revolution: a navel framework in Automation of Everything (AoE). IEEE Access. 7, pp. 41395-41415. https://doi.org/10.1109/ACCESS.2019.2907809
Whitelisting in RFDMA networks
Šolc, T., Yetgin, H., Gale, T., Mohorčič, M. and Fortuna, C. 2019. Whitelisting in RFDMA networks. IEEE Access. 7, pp. 159284-159299. https://doi.org/10.1109/ACCESS.2019.2950754
A survey of network lifetime maximization techniques in wireless sensor networks
Yetgin, H., Cheung, K.T.K., El-Hajjar, M. and Hanzo, L. 2017. A survey of network lifetime maximization techniques in wireless sensor networks. IEEE Communications Surveys and Tutorials. 19 (2), pp. 828-854. https://doi.org/10.1109/COMST.2017.2650979
Network-lifetime maximization of wireless sensor networks
Yetgin, H., Cheung, K.T.K., El-Hajjar, M. and Hanzo, L. 2015. Network-lifetime maximization of wireless sensor networks. IEEE Access. 3, pp. 2191-2226. https://doi.org/10.1109/ACCESS.2015.2493779
Cross-layer network lifetime maximization in interference-limited WSNs
Yetgin, H,, Cheung, K.T.K., El-Hajjar, M. and Hanzo, L. 2015. Cross-layer network lifetime maximization in interference-limited WSNs. IEEE Transactions on Vehicular Technology. 64 (8), pp. 3795-3803. https://doi.org/10.1109/TVT.2014.2360361
Multi-objective routing optimization using evolutionary algorithms
Yetgin, H., Cheung, K.T.K. and Hanzo, L. 2012. Multi-objective routing optimization using evolutionary algorithms. 2012 IEEE Wireless Communications and Networking Conference. Paris, France 01 - 04 Apr 2012 IEEE. pp. 3030-3034 https://doi.org/10.1109/WCNC.2012.6214324