Tanja: A framework to Conserve Energy in WSN
Zouhair A. Sadouq1, Mounia Seraoui2, Mohamed Essaaidi3
1Z.A. Sadouq, Information and Telecommunication Systems Laboratory, Abdelmalek  Essaadi University, Tetuan. Morocco.
2M. Seraoui, Electrical Department at EMI, Mohamed V – AGDAL University, Rabat, Morocco.
3M. Essaaidi, Higher National School of  IT ENSIAS, Rabat, Morocco.
Manuscript received on January 22, 2013. | Revised Manuscript received on February 09, 2013. | Manuscript published on February 28, 2013. | PP: 40-45 | Volume-2 Issue-3, February 2013.  | Retrieval Number: C0987022313 /2013©BEIESP

Open Access | Ethics and Policies | Cite
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Nowadays, Wireless Sensor Networks raise a growing interest among industries and civil organizations where monitoring and recognition of physical phenomena are a priority. Their possible applications are extremely versatile. WSN represent a significant technology that attracts more and more considerable research attention in recent years. It has emerged as a result of recent advances in low-power digital and analog circuitry, low-power RF design and sensor technology. In this paper we propose a new framework for modeling Wireless Sensor Networks that supports WSN to handle real-time network management by using a hierarchical framework based on general features identified through a careful analysis of existing sensor networks. Our framework is based on the GSM model. In fact, it’s an energy optimization approach based on cross-layer for wireless sensor networks, joining optimal design of the physical, medium access control, and routing layer. It can be considered as a special kind of clustering architecture that extends the network life by efficiently using every node’s energy and distributes management tasks to support the scalability of the management system in densely deployed sensor networks. However, it is more systematic, more robust and more scalable. In our solution we propose dynamic construction of clustering. The network is partitioned into clusters or cells. A cluster is composed with nodes, where every node can play one of three roles: source or sensing role as a slave, router, or a master as a cluster head and a gateway to the external world. We address the energy-consumption efficiency as a major design challenge in succeeding the vision of self-organized WSN. This approach focuses on the computation of optimal transmission power, routing, and duty-cycle schedule that optimize the WSNs energy-efficiency and by the way, reduces node energy consumption and contributes to extending the lifetime of the entire network.
Keywords: Energy consumption-efficiency, GSM model, Self-configuration, WSN.