Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/6086
Title: A GRASP Meta-Heuristic for Evaluating the Latency and Lifetime Impact of Critical Nodes in Large Wireless Sensor Networks
Authors: Sembroiz, David
Ojaghi, Behnam
Careglio, Davide
Ricciardi, Sergio
Keywords: internet of things
MIP
WSN
ILP
optimization
GRASP
meta-heuristics
latency
lifetime
Issue Date: 2019
Publisher: Mdpi
Abstract: Wireless Sensor Networks (WSN) have lately been gaining momentum thanks to the hardware improvements and standardization software efforts. Moreover, the appearance of Internet of Things (IoT) and its reliance on sensors are helping to widely extend the usage of WSNs. However, such networks present drawbacks, mainly because of limited sensor batteries and their vulnerability against physical attacks due to the lack of protection and security. Additionally, not all the sensors inside the network have the same responsibility in terms of traffic handling. In this paper, we firstly analyze the fact that some nodes are more critical than others, considering the most critical node the one that, once incapacitated, causes the most deterioration on the network performance. Such performance is analyzed using two metrics, namely network latency and lifetime. We present a result comparison between a Mixed Integer Programming (MIP) model and a Greedy Randomized Adaptive Search Procedure (GRASP) meta-heuristic for small networks. For bigger networks, GRASP meta-heuristic results are presented to understand how the network degrades as the number of both critical and network nodes increase, by distributing them into two different areas: fixed and incremental to maintain node density.
URI: https://doi.org/10.3390/app9214564
https://hdl.handle.net/20.500.11851/6086
ISSN: 2076-3417
Appears in Collections:Bilgisayar Mühendisliği Bölümü / Department of Computer Engineering
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

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