research-article

On meeting lifetime goals and providing constant application quality

Authors:

Andreas Lachenmann,

Klaus Herrmann,

Kurt Rothermel,

Pedro José MarrónAuthors Info & Claims

ACM Transactions on Sensor Networks (TOSN), Volume 5, Issue 4

Article No.: 36, Pages 1 - 36

https://doi.org/10.1145/1614379.1614388

Published: 27 November 2009 Publication History

Abstract

Most work in sensor networks tries to maximize network lifetime. However, for many applications the required lifetime is known in advance. Therefore, application quality should rather be maximized for that given time.Levels, the approach presented in this article, is a programming abstraction for energy-aware sensor network applications that helps to meet such a user-defined lifetime goal by deactivating optional functionality.

With this programming abstraction, the application developer defines so-called energy levels. Functionality in energy levels is deactivated if the required lifetime cannot be met otherwise. The runtime system uses data about the energy consumption of different levels to compute an optimal level assignment that maximizes each node's quality for the time remaining.

As described in this paper, Levels includes a completely distributed coordination algorithm that balances energy level assignments and keeps the application quality of the network roughly constant over time. In this approach, each node computes its schedule based on those of its neighbors.

As the evaluation shows, applications using Levels can accurately meet given lifetime goals with only small fluctuations in application quality. In addition, the runtime overhead both for computation and for communication is negligible.

References

[1]

Camacho, E. F. and Bordons, C. 2004. Model Predictive Control 2nd Ed. Advanced Textbooks in Control and Signal Processing. Springer-Verlag.

[2]

Cardei, M. and Wu, J. 2006. Energy-efficient coverage problems in wireless ad-hoc sensor networks. Comput. Comm. 29, 4, 413--420.

Digital Library

[3]

Cerpa, A. and Estrin, D. 2002. ASCENT: Adaptive self-configuring sensor networks topologies. In Proceedings of the 21st Annual Joint Conference of the IEEE Computer and Communications Societies. Vol. 3. 1278--1287.

[4]

Chvátal, V. 1983. Linear Programming. W. H. Freeman and Company.

[5]

Dunkels, A., Österlind, F., Tsiftes, N., and He, Z. 2007. Software-based on-line energy estimation for sensor nodes. In Proceedings of the 4th Workshop on Embedded Networked Sensors.

Digital Library

[6]

Duracell Batteries. 2001. Duracell Plus alkaline-manganese dioxide battery. http://www.mdsbattery.co.uk/datasheets/duracell/MN1500PL.pdf.

[7]

Dutta, P., Feldmeier, M., Paradiso, J., and Culler, D. 2008. Energy metering for free: Augmenting switching regulators for real-time monitoring. In Proceedings of the International Conference on Information Processing in Sensor Networks. 283--294.

Digital Library

[8]

Flinn, J. and Satyanarayanan, M. 1999. Energy-aware adaptation for mobile applications. In Proceedings of the 17th ACM Symposium on Operating Systems Principles. 48--63.

Digital Library

[9]

Gay, D., Levis, P., von Behren, R., Welsh, M., Brewer, E., and Culler, D. 2003. The nesC language: A holistic approach to networked embedded systems. In Proceedings of the Conference on Programming Language Design and Implementation. 1--11.

Digital Library

[10]

Giusti, A., Murphy, A. L., and Picco, G. P. 2007. Decentralized scattering of wake-up times in wireless sensor networks. In Proceedings of the 4th European Conference on Wireless Sensor Networks. 245--260.

Digital Library

[11]

Huang, C.-F., Lo, L.-C., Tseng, Y.-C., and Chen, W.-T. 2006. Decentralized energy-conserving and coverage-preserving protocols for wireless sensor networks. ACM Trans. Sens. Netw. 2, 2, 182--187.

Digital Library

[12]

Jiang, X., Dutta, P., Culler, D., and Stoica, I. 2007. Micro power meter for energy monitoring of wireless sensor networks at scale. In Proceedings of the 6th International Conference on Information Processing in Sensor Networks: Track on Sensor Platforms, Tools and Design Methods. 186--195.

Digital Library

[13]

Kim, S., Pakzad, S., Culler, D., Demmel, J., Fenves, G., Glaser, S., and Turon, M. 2007. Health monitoring of civil infrastructures using wireless sensor networks. In Proceedings of the 6th International Conference on Information Processing in Sensor Networks. 254--263.

Digital Library

[14]

Kirkpatrick, S., Gelatt Jr., C. D., and Vecchi, M. P. 1983. Optimization by simulated annealing. Science 220, 4598, 671--680.

[15]

Lachenmann, A., Marrón, P. J., Minder, D., and Rothermel, K. 2007. Meeting lifetime goals with energy levels. In Proceedings of the 5th ACM Conference on Embedded Networked Sensor Systems. 131--144.

Digital Library

[16]

Landsiedel, O., Wehrle, K., and Götz, S. 2005. Accurate prediction of power consumption in sensor networks. In Proceedings of the 2nd Workshop on Embedded Networked Sensors.

Digital Library

[17]

Liu, T., Sadler, C. M., Zhang, P., and Martonosi, M. 2004. Implementing software on resource-constrained mobile sensors: Experiences with Impala and ZebraNet. In Proceedings of the International Conference on Mobile Systems, Applications, and Services. 256--269.

Digital Library

[18]

Madden, S. R., Franklin, M. J., Hellerstein, J. M., and Hong, W. 2005. TinyDB: An acquisitional query processing system for sensor networks. ACM Trans. Datab. Syst. 30, 1, 122--173.

Digital Library

[19]

Marrón, P. J., Saukh, O., Krüger, M., and Grosse, C. 2005. Sensor network issues in the Sustainable Bridges project. In Proceedings of the European Projects Session of EWSN.

[20]

Polastre, J., Hill, J., and Culler, D. 2004. Versatile low power media access for wireless sensor networks. In Proceedings of the International Conference on Embedded Networked Sensor Systems. 95--107.

Digital Library

[21]

Polastre, J., Szewczyk, R., and Culler, D. 2005. Telos: Enabling ultra-low power wireless research. In Proceedings of the International Conference on Information Processing in Sensor Networks; Special Track on Platform Tools and Design Methods for Network Embedded Sensors.

Digital Library

[22]

Rao, R., Vrudhula, S., and Rakhmatov, D. N. 2003. Battery modeling for energy-aware system design. Computer 36, 12, 77--87.

Digital Library

[23]

Shnayder, V., Hempstead, M., Chen, B.-r., Werner-Allen, G., and Welsh, M. 2004. Simulating the power consumption of large-scale sensor network applications. In Proceedings of the 2nd International Conference on Embedded Networked Sensor Systems. 188--200.

Digital Library

[24]

Simon, G., Maróti, M., Ákos Lédeczi, Balogh, G., Kusy, B., Nádas, A., Pap, G., Sallai, J., and Frampton, K. 2004. Sensor network-based countersniper system. In Proceedings of the 2nd International Conference on Embedded Networked Sensor Systems. 1--12.

Digital Library

[25]

Sorber, J., Kostadinov, A., Garber, M., Brennan, M., Corner, M. D., and Berger, E. D. 2007. Eon: A language and runtime system for perpetual systems. In Proceedings of the 5th International Conference on Embedded Networked Sensor Systems. 161--174.

Digital Library

[26]

Titzer, B., Lee, D., and Palsberg, J. 2005. Avrora: Scalable sensor network simulation with precise timing. In Proceedings of the 4th International Conference on Information Processing in Sensor Networks. 477--482.

Digital Library

[27]

Tolle, G., Polastre, J., Szewczyk, R., Culler, D., Turner, N., Tu, K., Burgess, S., Dawson, T., Buonadonna, P., Gay, D., and Hong, W. 2005. A macroscope in the redwoods. In Proceedings of the 3rd International Conference on Embedded Networked Sensor Systems. 51--63.

Digital Library

[28]

Werner-Allen, G., Lorincz, K., Johnson, J., Lees, J., and Welsh, M. 2006. Fidelity and yield in a volcano monitoring sensor network. In Proceedings of the Symposium on Operating Systems Design and Implementation.

Digital Library

[29]

Ye, F., Zhong, G., Cheng, J., Lu, S., and Zhang, L. 2003. PEAS: A robust energy conserving protocol for long-lived sensor networks. In Proceedings of the International Conference on Distributed Computing Systems. 28--37.

Digital Library

[30]

Zeng, H., Ellis, C. S., Lebeck, A. R., and Vahdat, A. 2002. ECOSystem: Managing energy as a first class operating system resource. In Proceedings of the International Conference on Architectural Support for Programming Languages and Operating Systems. 123--132.

Digital Library

Cited By

Peng YLi ZZhang WQiao D(2012)LB-MAC: A Lifetime-Balanced MAC Protocol for Sensor NetworksWireless Algorithms, Systems, and Applications10.1007/978-3-642-31869-6_23(272-291)Online publication date: 2012
https://doi.org/10.1007/978-3-642-31869-6_23
El Kouche AAl-Awami LHassanein H(2011)Dynamically Reconfigurable Energy Aware Modular Software (DREAMS) Architecture for WSNs in Industrial EnvironmentsProcedia Computer Science10.1016/j.procs.2011.07.0355(264-271)Online publication date: 2011
https://doi.org/10.1016/j.procs.2011.07.035

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On meeting lifetime goals and providing constant application quality

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Published In

cover image ACM Transactions on Sensor Networks

ACM Transactions on Sensor Networks Volume 5, Issue 4

November 2009

264 pages

ISSN:1550-4859

EISSN:1550-4867

DOI:10.1145/1614379

Issue’s Table of Contents

Copyright © 2009 ACM.

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Association for Computing Machinery

New York, NY, United States

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ACM Journals for the Design of Smart and Connected Systems

Publication History

Published: 27 November 2009

Accepted: 01 October 2008

Revised: 01 October 2008

Received: 01 February 2008

Published in TOSN Volume 5, Issue 4

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Cited By

Peng YLi ZZhang WQiao D(2012)LB-MAC: A Lifetime-Balanced MAC Protocol for Sensor NetworksWireless Algorithms, Systems, and Applications10.1007/978-3-642-31869-6_23(272-291)Online publication date: 2012
https://doi.org/10.1007/978-3-642-31869-6_23
El Kouche AAl-Awami LHassanein H(2011)Dynamically Reconfigurable Energy Aware Modular Software (DREAMS) Architecture for WSNs in Industrial EnvironmentsProcedia Computer Science10.1016/j.procs.2011.07.0355(264-271)Online publication date: 2011
https://doi.org/10.1016/j.procs.2011.07.035

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