Convergecast Algorithms for Wake-up Transceivers

Amir Bannoura, Leonhard Reindl, Christian Schindelhauer

2016

Abstract

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.

References

  1. Bannoura, A., Ortolf, C., Reindl, L., and Schindelhauer, C. (2015). The wake up dominating set problem. Theoretical Computer Science, 8243(0):35 - 50.
  2. Cardei, M. and Wu, J. (2006). Energy-efficient coverage problems in wireless ad-hoc sensor networks. Computer Communications, 29(4):413 - 420. Current areas of interest in wireless sensor networks designs.
  3. Cheng, X., Huang, X., Li, D., Wu, W., and Du, D.-Z. (2003). A polynomial-time approximation scheme for the minimum-connected dominating set in ad hoc wireless networks. Networks, 42(4):202-208.
  4. Choi, H., Wang, J., and Hughes, E. A. (2009). Scheduling for information gathering on sensor network. Wirel. Netw., 15(1):127-140.
  5. Clark, B. N., Colbourn, C. J., and Johnson, D. S. (1991). Unit disk graphs. Discrete Math., 86(1-3):165-177.
  6. Fakcharoenphol, J., Rao, S., and Talwar, K. (2004). A tight bound on approximating arbitrary metrics by tree metrics. Journal of Computer and System Sciences, 69(3):485 - 497. Special Issue on {STOC} 2003.
  7. Gamm, G., Sippel, M., Kostic, M., and Reindl, L. (2010). Low power wake-up receiver for wireless sensor nodes. In Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP), 2010 Sixth International Conference on, pages 121-126.
  8. Gandham, S., Zhang, Y., and Huang, Q. (2006). Distributed minimal time convergecast scheduling in wireless sensor networks. In Distributed Computing Systems, 2006. ICDCS 2006. 26th IEEE International Conference on, pages 50-50.
  9. Ghosh, A. and Das, S. K. (2008). Coverage and connectivity issues in wireless sensor networks: A survey. Pervasive and Mobile Computing, 4(3):303 - 334.
  10. Gu, L. and Stankovic, J. (2004). Radio-triggered wakeup capability for sensor networks. In Real-Time and Embedded Technology and Applications Symposium, 2004. Proceedings. RTAS 2004. 10th IEEE, pages 27- 36.
  11. Kesselman, A. and Kowalski, D. (2005). Fast distributed algorithm for convergecast in ad hoc geometric radio networks. In Wireless On-demand Network Systems and Services, 2005. WONS 2005. Second Annual Conference on, pages 119-124.
  12. Lichtenstein, D. (1982). Planar formulae and their uses. SIAM Journal on Computing, 11(2):329-343.
  13. Lu, G., Sadagopan, N., Krishnamachari, B., and Goel, A. (2005). Delay efficient sleep scheduling in wireless sensor networks. In INFOCOM 2005. 24th Annual Joint Conference of the IEEE Computer and Communications Societies. Proceedings IEEE, volume 4, pages 2470-2481 vol. 4.
  14. Shang, W., Wan, P., and Hu, X. (2010). Approximation algorithm for minimal convergecast time problem in wireless sensor networks. Wireless Networks, 16(5):1345-1353.
  15. Yu, Y., Krishnamachari, B., and Prasanna, V. (2004). Energy-latency tradeoffs for data gathering in wireless sensor networks. In INFOCOM 2004. Twentythird AnnualJoint Conference of the IEEE Computer and Communications Societies, volume 1, page 255.
  16. Zhang, H., Osterlind, F., Soldati, P., Voigt, T., and Johansson, M. (2015). Time-optimal convergecast with separated packet copying: Scheduling policies and performance. Vehicular Technology, IEEE Transactions on, 64(2):793-803.
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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

@conference{sensornets16,
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,},
year={2016},
pages={137-143},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005795601370143},
isbn={978-989-758-169-4},
}


in EndNote Style

TY - CONF
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