Models and algorithms for wireless sensor networks (smart dust)

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Abstract

Recent rapid developments in micro-electro-mechanical systems (MEMS), wireless communications and digital electronics have already led to the development of tiny, low-power, low-cost sensor devices, Such devices integrate sensing, limited data processing and restricted communication capabilities. Each sensor device individually might have small utility, however the effective distributed co-ordination of large numbers of such devices can lead to the efficient accomplishment of large sensing tasks. Large numbers of sensors can be deployed in areas of interest (such as inaccessible terrains or disaster places) and use self-organization and collaborative methods to form an ad-hoc network. We note however that the efficient and robust realization of such large, highly-dynamic, complex, non-conventional networking environments is a challenging technological and algorithmic task, because of the unique characteristics and severe limitations of these devices. This talk will present and discuss several important aspects of the design, deployment and operation of sensor networks. In particular, we provide a brief description of the technical specifications of state-of-the-art sensor, a discussion of possible models used to abstract such networks, a discussion of some key algorithmic design techniques (like randomization, adaptation and hybrid schemes), a presentation of representative protocols for sensor networks, for important problems including data propagation, collision avoidance and energy balance and an evaluation of crucial performance properties (correctness, efficiency, fault-tolerance) of these protocols, both with analytic and simulation means. © Springer-Verlag Berlin Heidelberg 2006.

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APA

Nikoletseas, S. (2006). Models and algorithms for wireless sensor networks (smart dust). In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3831 LNCS, pp. 64–83). https://doi.org/10.1007/11611257_7

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