Leila Azouz Saidane

Work place: National School of Computer Science, University of Manouba, 2010, La Manouba, Tunisia

E-mail: leila.saidane@ensi-uma.tn

Website:

Research Interests: Computer Architecture and Organization, Systems Architecture, Image Compression, Image Manipulation, Network Architecture, Image Processing, Multimedia Information System, Data Structures and Algorithms

Biography

Pr. Leila Azouz Saïdane is a Professor at the National School of Computer Science (ENSI), at The University of Manouba, in Tunisia. She was the Director of this school, the Chairperson of the PhD Commission and the supervisor of the Master’s Degree program in Networks and Multimedia Systems at ENSI. She is the responsible of RAMSIS group of CRISTAL Research Laboratory (Center of Research in Network and System Architecture, Multimedia and Image Processing) at ENSI. She collaborated on several international projects. She is author and co-author of several papers in refereed journals, magazines and international conferences.

Author Articles
Performance Evaluation of Unslotted CSMA/CA for Wireless Sensor Networks: Energy Consumption Analysis and Cross Layer Routing

By Ines El Korbi Leila Azouz Saidane

DOI: https://doi.org/10.5815/ijcnis.2017.06.01, Pub. Date: 8 Jun. 2017

The IEEE 802.15.4 standard is considered as the most notorious MAC layer for wireless sensor networks (WSNs) in both centralized and distributed context. For instance, in multi hop environment, the beaconless IEEE 802.15.4 is used. Several works evaluated the performance of the beaconless IEEE 802.15.4 in terms of average delay, average energy consumption, throughput etc. But, none of the existing studies derived accurate energy consumption bounds of this MAC layer. In this paper, our contribution is twofold. We first propose a comprehensive energy consumption analysis of the unslotted CSMA/CA algorithm. The results are validated through simulation. Then, we exploit our analysis to propose a cross layer routing scheme that enhances the native PEGASIS protocol. Our scheme called Average Energy Enhanced PEGASIS (AE2-PEGASIS) considers the average energy consumption at the MAC layer when constructing the routes to the sink.

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