Convergecast Algorithms for Wake-up Transceivers

Amir Bannoura, Leonhard Reindl, Christian Schindelhauer


New transceiver and receiver hardware technology allow the usage of special wake-up signals, which are able to awake neighbored sensor nodes from the sleep. However, such messages need more energy ew than those standard message transmissions em, when nodes are awake. Furthermore, the distance range rw is also smaller than the distance range rm of standard messages. Therefore, it does not completely replace duty-cycling for the convergecast problem in wireless sensor networks. We present a theoretical and practical discussion of energyefficient algorithms for the convergecast problem. First, we present a model based on the current technology and show that without constraints on the delivery times wake-up signals are obsolete, when arbitrary long sleeping times are allowed. The wake-up graph Gw and the message graph Gm are modeled by planar rwand rm-disk-graphs. Then, we give a competitive analysis for the general case, where we discuss an online D-convergecast algorithms bounded by competitive energy ratios. Finally, we present simulation results for these algorithmic ideas in the plane by considering the energy efficiency and the latency of data delivery.


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Paper Citation

in Harvard Style

Bannoura A., Reindl L. and Schindelhauer C. (2016). Convergecast Algorithms for Wake-up Transceivers . In Proceedings of the 5th International Confererence on Sensor Networks - Volume 1: SENSORNETS, ISBN 978-989-758-169-4, pages 137-143. DOI: 10.5220/0005795601370143

in Bibtex Style

author={Amir Bannoura and Leonhard Reindl and Christian Schindelhauer},
title={Convergecast Algorithms for Wake-up Transceivers},
booktitle={Proceedings of the 5th International Confererence on Sensor Networks - Volume 1: SENSORNETS,},

in EndNote Style

JO - Proceedings of the 5th International Confererence on Sensor Networks - Volume 1: SENSORNETS,
TI - Convergecast Algorithms for Wake-up Transceivers
SN - 978-989-758-169-4
AU - Bannoura A.
AU - Reindl L.
AU - Schindelhauer C.
PY - 2016
SP - 137
EP - 143
DO - 10.5220/0005795601370143