Using Data Compression for Delay Constrained Applications in Wireless Sensor Networks

International audienceData compression is a technique used to save energy in Wireless Sensor Networks by reducing the quantity of data transmitted and the number of transmission. Actually, the main cause of energy consumption in WSN is data transmission. There exist critical applications such as delay constrained activities in which the data have to arrive quickly to the Sink for rapid analysis. In this article, we explore the use of data compression algorithms for delay constrained applications by evaluating a recent data compression algorithm for WSN named K-RLE with optimal parameters on an ultra-low power microcontroller from TI MSP430 series. The relevance of the parameter K for the lossy algorithm K-RLE led us to propose and compare two methods to characterize K: the Standard deviation and the Allan deviation. The last one allow us to control the percentage of data modified. Experimental results show that data compression is an energy efficient technique which can also perform in certain cases the global data transfer time (compression plus transmission time) compared to direct transmission

A dynamic clustering construction for wireless sensor networks

International audienceResearch in sensor networks has focused on development of energy efficient and secure infrastructures. In this article, we introduce a new approach to organize sensor networks in clusters in order to reduce energy dissipation. Our contribution is an heuristic to define the number of clusters and also an efficient manner to choose cluster heads by minimizing the distance between the cluster heads and its cluster nodes. Inspired from LEACH, a well-known TDMA cluster-based sensor network architecture, we introduce a new method for building and maintaining clusters using the paradigm of a soccer team. In this work, a new algorithm called OH-Kmeans, based on the Kmeans algorithm, is used to find dynamically the number of clusters and form them guaranteeing direct transmission between the cluster heads and cluster nodes

Conception d une architecture hiérarchique de réseau de capteurs pour le stockage et la compression de données

Les récentes avancées dans les divers domaines liés à la micro-électronique, à l'informatique et aux réseaux sans fil ont donné naissance à de nouvelles thématiques de recherche. Les réseaux de capteurs issus de ces nouveaux progrès technologiques constituent un axe de recherche très fertile. En effet, la capacité réduite des noeuds en teme de calcul, de mémoire et d'énergie génère de nombreuses problématiques intéressantes. Le but de cette thèse est la conception d'une architecture hiérarchique de réseaux de capteurs capables de s'adapter à différents contextes en prenant en compte les contraintes énergétiques et en permettant de fournir des informations riches comme le multimédia à l'utilisateur final. Nous proposons une architecture hiérarchique avec les différents noeuds qui la composent et les technologies sans fil qui les relient. L'économie d'énergie étant un fil conducteur de notre travail et le module de transmission la principale source d'énergie, nous proposons deux nouveaux algorithmes de compression de données permettant d'optimiser l'utilisation du canal de communication. nous présentons également une solution pour le stockage de grandes quantités d'informations sur les noeuds en integrant le système de fichiers FAT16 sous TinyOS-2.xRecent advances in various aeras related to micro-electronics, computer science and wireless networks have resulted in the development of new research topics. Sensor networks are one of them. The particularity of this new research direction is the reduced performances of nodes in terms of computation, memory and energy. The purpose of this thesis is the definition of a new hierarchical architecture of sensor networks usable in different contexts by taking into account the sensors constraints and providing a high quality data such as multimedia to the end-users.We present our hierachical architecture with different nodes and the wireless technologies that connect them. Because of the high consumtpionof data transmission, we have developped two data compression algortithms in order to optimize the use of the channel by reducing data transmitted. We also present a solution for storing large amount of data on nodes by integrating the file system FAT16 under TinyOS-2.x.BESANCON-BU Sciences Staps (250562103) / SudocSudocFranceF