Seminaire LIA: Optimized Monitoring of Internet of Things Networks

Séminaire ce Mercredi à 11h30.

Intervenant: Basma Mostafa

Title: Optimized Monitoring of Internet of Things Networks


The emergence of the Internet of Things (IoT) is introducing more and more services and applications such as smart cities. IoT networks tend to experience unexpected communication problems during deployment, because resource-constrained embedded devices are unreliable by nature for a variety of reasons, such as uncertain radio connectivity and battery drain. Despite the fact that IoT networks are dynamic and vulnerable, the offered services need the continuous availability of defined network components. To that end, monitoring techniques for detecting, localizing and remedying network failures in IoT will definitely develop in significance. The objective of our work is to contribute to the optimization of IoT network monitoring for fault tolerance and quality of service purposes. We aim at the designing of optimized, efficient algorithms for monitoring of communicant elements in IoT networks. Additional monitoring will increase the network load; however, the added cost for link monitoring could be tolerated, especially for critical-time IoT applications. This is because monitoring will help in accelerating link recovery, and decreasing node unreachability times. Nevertheless, the monitoring algorithms must be optimized in order to minimize the energy requirements and the monitoring load. In previous work, we proposed a polynomial-time algorithm that aimed to achieve distributed probe/monitor placement with minimal computational complexity. The proposed algorithm works in tandem with RPL. The problem was modeled as a Minimum Vertex Cover Problem (VCP). Furthermore, we developed another optimization model for scheduling of the monitoring role of the nodes in IoT networks to maximize the lifetime of the resource-constrained embedded devices while minimizing the overall cost of monitoring in the network. The multi-phase model was tested on randomly generated instances and results proved to be very promising.

Short biography:

Basma Mostafa is an Assistant Lecturer of Operations Research and Decision Support at the Faculty of Computers and Information (FCI), Cairo University where she received her Bachelor degree as well as her Master's degree in using Data Mining and Metaheuristics for Feature Selection. Currently, she is working on monitoring IoT networks in her PhD thesis in a co-supervision between Cairo University, University of Montpellier and University of Avignon. Her research interests center on Operations Research; Combinatorial Optimization; Metaheuristics; and Machine Learning.  

Mercredi, 12 Juillet, 2017 - 11:30 to 12:30

Laboratoire Informatique d'Avignon

Université d'Avignon et des Pays de Vaucluse
339 chemin des Meinajaries, Agroparc BP 91228, 84911 Avignon cedex 9
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