Imperial College London
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ProfessorJulieMcCann

Faculty of Engineering, Department of Computing

Vice-Dean (Research) for the Faculty of Engineering
 
 
 
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Contact

 

+44 (0)20 7594 8375j.mccann Website

 
 
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Assistant

 

Miss Teresa Ng +44 (0)20 7594 8300

 
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Location

 

260ACE ExtensionSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{Bezerra:2022:10.1145/3466639,
author = {Bezerra, P and Chen, P-Y and McCann, JA and Yu, W},
doi = {10.1145/3466639},
journal = {ACM Transactions on Sensor Networks},
title = {Adaptive monitor placement for near real-time node failure localisation in wireless sensor networks},
url = {http://dx.doi.org/10.1145/3466639},
volume = {18},
year = {2022}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - As sensor-based networks become more prevalent, scaling to unmanageable numbers or deployed in difficult to reach areas, real-time failure localisation is becoming essential for continued operation. Network tomography, a system and application-independent approach, has been successful in localising complex failures (i.e., observable by end-to-end global analysis) in traditional networks.Applying network tomography to wireless sensor networks (WSNs), however, is challenging. First, WSN topology changes due to environmental interactions (e.g., interference). Additionally, the selection of devices for running network monitoring processes (monitors) is an NP-hard problem. Monitors observe end-to-end in-network properties to identify failures, with their placement impacting the number of identifiable failures. Since monitoring consumes more in-node resources, it is essential to minimise their number while maintaining network tomography’s effectiveness. Unfortunately, state-of-the-art solutions solve this optimisation problem using time-consuming greedy heuristics.In this article, we propose two solutions for efficiently applying Network Tomography in WSNs: a graph compression scheme, enabling faster monitor placement by reducing the number of edges in the network, and an adaptive monitor placement algorithm for recovering the monitor placement given topology changes. The experiments show that our solution is at least 1,000× faster than the state-of-the-art approaches and efficiently copes with topology variations in large-scale WSNs.
AU  - Bezerra,P
AU  - Chen,P-Y
AU  - McCann,JA
AU  - Yu,W
DO  - 10.1145/3466639
PY  - 2022///
SN  - 1550-4859
TI  - Adaptive monitor placement for near real-time node failure localisation in wireless sensor networks
T2  - ACM Transactions on Sensor Networks
UR  - http://dx.doi.org/10.1145/3466639
UR  - https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000841447200002&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
UR  - https://dl.acm.org/doi/10.1145/3466639
UR  - http://hdl.handle.net/10044/1/99470
VL  - 18
ER  -
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