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Traffic-Adaptive and Link-Quality-Aware Communication in Wireless Sensor Networks

Type of publication Peer-reviewed
Publikationsform Original article (peer-reviewed)
Publication date 2013
Author Philipp Hurni,
Project Traffic Adaptivity in Wireless Sensor Networks
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Original article (peer-reviewed)

Journal PIK - Praxis der Informationsverarbeitung und Kommunikation
Volume (Issue) 36(1)
Page(s) 3 - 8
Title of proceedings PIK - Praxis der Informationsverarbeitung und Kommunikation
DOI 10.1515/pik-2012-0138


This paper is a summary of the main contributions of the PhD thesis published in [1]. The main research contributions of the thesis are driven by the research question how to design simple, yet efficient and robust run-time adaptive resource allocation schemes within the communication stack of Wireless Sensor Network (WSN) nodes. The thesis addresses several problem domains with contributions on different layers of the WSN communication stack. The main contributions can be summarized as follows: First, a a novel run-time adaptive MAC protocol is introduced, which stepwise allocates the power-hungry radio interface in an on-demand manner when the encountered traffic load requires it. Second, the thesis outlines a methodology for robust, reliable and accurate software-based energy-estimation, which is calculated at network runtime on the sensor node itself. Third, the thesis evaluates several Forward Error Correction (FEC) strategies to adaptively allocate the correctional power of Error Correcting Codes (ECCs) to cope with timely and spatially variable bit error rates. Fourth, in the context of TCP-based communications in WSNs, the thesis evaluates distributed caching and local retransmission strategies to overcome the performance degrading effects of packet corruption and transmission failures when transmitting data over multiple hops. The performance of all developed protocols are evaluated on a self-developed real-world WSN testbed and achieve superior performance over selected existing approaches, especially where traffic load and channel conditions are suspect to rapid variations over time.