Work place: Computer Science Departement, Laboratoire de Recherche en Informatique (LARI), Université Mouloud Mammeri de Tizi Ouzou, Algeria
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Research Interests: Computer systems and computational processes, Computer Architecture and Organization, Embedded System, Computer Networks, Data Structures and Algorithms
Biography
Dr. Daoui Mehammed born in 1972. He received his engineering degree on computer science in 1997 and his PhD in 2009. Actually, is an assistant Professor at computer science department of Mouloud Mammeri University, Tizi Ouzou, ALGERIA. He is a research member at the Laboratory (LARI) of the Computer Science Department. His areas of interest include mobile networks (Cellular, Ad hoc and sensors networks), embedded systems and computer architecture.
By Malika BELKADI Rachida AOUDJIT Mehammed DAOUI Mustapha LALAM
DOI: https://doi.org/10.5815/ijitcs.2014.01.06, Pub. Date: 8 Dec. 2013
In wireless sensor networks, it is crucial to design and employ energy-efficient communication protocols, since nodes are battery-powered and thus their lifetimes are limited. Such constraints combined with a great number of applications used in these networks, pose many challenges (limited energy, low security…) to the design and management of wireless sensor networks. These challenges necessitate a great attention. In this paper, we present a new version of Directed Diffusion routing protocol which provides both security and energy efficiency together in wireless sensor networks.
[...] Read more.By Malika BELKADI Rachida AOUDJIT Mehammed DAOUI Mustapha LALAM
DOI: https://doi.org/10.5815/ijcnis.2013.09.05, Pub. Date: 8 Jul. 2013
This work presents a mobile location management technique based on the clustering. This technique can be implemented on next generation mobile networks by exploiting the data available on the users (age, function, address, workplace… etc), existing infrastructure (roads, location of base stations… etc) and the users' displacements history.
The simulations are carried out using a realistic model of movements. The results show that our strategy requires a minimum number of location messages compared to the static and dynamic location management techniques.
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