Dynamic clustering and management of mobile wireless sensor networks
- Submitting institution
-
Manchester Metropolitan University
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 2335
- Type
- D - Journal article
- DOI
-
10.1016/j.comnet.2017.02.001
- Title of journal
- Computer Networks
- Article number
- -
- First page
- 62
- Volume
- 117
- Issue
- -
- ISSN
- 1389-1286
- Open access status
- Not compliant
- Month of publication
- February
- Year of publication
- 2017
- URL
-
https://e-space.mmu.ac.uk/618157/
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
5
- Research group(s)
-
D - Smart Infrastructure
- Citation count
- 55
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This paper proposes a novel solution for efficient data collection and mobility management in mobile ad-hoc networks, which has important applications in areas such as autonomous vehicles and swarm robotics control. Others latterly applied this idea to self-organised nodes in coherent communication systems (Shi et al., 2019 – 10.1109/TVT.2019.2954653) and it was used as a baseline for new clustering mechanisms (Akabane et al., 2019 – 10.3390/s19163558). Simulation code published on the author’s website, confirms the accuracy of the performance results and allowed others to further address the problem of minimising clustering latency and energy consumption (Wang, et al., 2018 –10.1088/1742-6596/1064/1/012067.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -