Congestion detection strategies in wireless sensor networks: A comparative study with testbed experiments

Kafi, Mohamed Amine; Djenouri, Djamel; Othman, Jalel Ben; Ouadjaout, Abdelraouf; Badache, Nadjib

Abstract

© 2014 The Authors. Event based applications of Wireless Sensor Networks (WSNs) are prone to traffic congestion, where unpredicted event detection yields simultaneous generation of traffic at spatially co-related nodes, and its propagation towards the sink. This results in loss of information and waste energy. Early congestion detection is thus of high importance in such WSN applications to avoid the propagation of such a problem and to reduce its consequences. Different detection metrics are used in the congestion control literature. However, a comparative study that investigates the different metrics in real sensor motes environment is missing. This paper focuses on this issue and compares some detection metrics in a testbed network with MICAz motes. Results show the effectiveness of each method in different scenarios and concludes that the combination of buffer length and channel load constitute the better candidate for early and fictive detection.

• Presentation Conference Type: Conference Paper (published)
• Conference Name: The 5th International Conference on Emerging Ubiquitous Systems and Pervasive Networks (EUSPN-2014)
• Acceptance Date: Jul 1, 2014
• Online Publication Date: Sep 17, 2014
• Publication Date: 2014
• Deposit Date: Mar 10, 2020
• Journal: Procedia Computer Science
• Print ISSN: 1877-0509
• Publisher: Elsevier
• Volume: 37
• Pages: 168-175
• Series Number: Procedia Computer Science
• DOI: https://doi.org/10.1016/j.procs.2014.08.026
• Public URL: https://uwe-repository.worktribe.com/output/5638868
• Additional Information: This article is maintained by: Elsevier; Article Title: Congestion Detection Strategies in Wireless Sensor Networks: A Comparative Study with Testbed Experiments; Journal Title: Procedia Computer Science; CrossRef DOI link to publisher maintained version: https://doi.org/10.1016/j.procs.2014.08.026; Content Type: article; Copyright: Copyright © 2014 The Authors. Published by Elsevier B.V.