Abstract
Wireless sensor networks represent a class of ad hoc networks for which the localization problem is emphasized since the collected data are usually not usable without location information. Range based localization techniques estimate locations of unknown nodes using information about distance from the anchor nodes, often estimating that distance by radio signal strength. Such distance estimation contains noise and determining node locations from such data is a hard optimization problem for which swarm intelligence stochastic population based algorithms have been used successfully. In this paper we propose localization algorithm based on recent fireworks swarm intelligence metaheuristic. We tested our approach using standard benchmark data and compared it to other algorithms from literature. Our fireworks based localization algorithm proved to be superior considering most performance indicators that included average localization error with different number of radio signal strength measurements, different number of nodes, different number of anchors and different radio signal strength noise levels.
Original language | English |
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Title of host publication | Proceedings of 2016 5th International Conference on Multimedia Computing and Systems, ICMCS 2016 |
Publisher | IEEE Computer Society |
Pages | 223-229 |
Number of pages | 7 |
ISBN (Electronic) | 9781509051465 |
DOIs | |
Publication status | Published - 2016 |
Event | 5th International Conference on Multimedia Computing and Systems, ICMCS 2016 - Marrakech, Morocco Duration: 29 Sept 2016 → 1 Oct 2016 |
Conference
Conference | 5th International Conference on Multimedia Computing and Systems, ICMCS 2016 |
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Country/Territory | Morocco |
City | Marrakech |
Period | 29/09/16 → 1/10/16 |
Keywords
- fireworks algorithm
- localization problem
- nature inspired algorithms
- swarm intelligence
- wireless sensor networks