article

Energetic sustainability of routing algorithms for energy-harvesting wireless sensor networks

Authors:

Emanuele Lattanzi,

Edoardo Regini,

Andrea Acquaviva,

Alessandro BoglioloAuthors Info & Claims

Computer Communications, Volume 30, Issue 14-15

Pages 2976 - 2986

https://doi.org/10.1016/j.comcom.2007.05.035

Published: 01 October 2007 Publication History

Abstract

A new class of wireless sensor networks that harvest power from the environment is emerging because of its intrinsic capability of providing unbounded lifetime. While a lot of research has been focused on energy-aware routing schemes tailored to battery-operated networks, the problem of optimal routing for energy harvesting wireless sensor networks (EH-WSNs) has never been explored. The objective of routing optimization in this context is not extending network lifetime, but maximizing the workload that can be autonomously sustained by the network. In this work we present a methodology for assessing the energy efficiency of routing algorithms for networks whose nodes drain power from the environment. We first introduce the energetic sustainability problem, then we define the maximum energetically sustainable workload (MESW) as the objective function to be used to drive the optimization of routing algorithms for EH-WSNs. We propose a methodology that makes use of graph algorithms and network simulations for evaluating the MESW starting from a network topology, a routing algorithm and a distribution of the environmental power available at each node. We present a tool flow implementing the proposed methodology and we show comparative results achieved on several routing algorithms. Experimental results highlight that routing strategies that do not take into account environmental power do not provide optimal results in terms of workload sustainability. Using optimal routing algorithms may lead to sizeable enhancements of the maximum sustainable workload. Moreover, optimality strongly depends on environmental power configurations. Since environmental power sources change over time, our results prompt for a new class of routing algorithms for EH-WSNs that are able to dynamically adapt to time-varying environmental conditions.

References

[1]

Akkaya, K. and Younis, M., A survey of routing protocols in wireless sensor networks. Elsevier Ad Hoc Network Journal. v33. 325-349.

[2]

M. Bhardwaj, A. Chandrakasan, Bounding the lifetime of sensor networks via optimal role assignments, in: Proceedings of IEEE InfoCom, 2002, pp. 1587-1596.

[3]

A. Bogliolo, E. Lattanzi, A. Acquaviva, Energetic sustainability of environmentally powered wireless sensor networks, in: Proceedings of PE-WASUN, 2006.

[4]

Amirtharajah, R., Collier, J., Siebert, J., Zhou, B. and Chandrakasan, A., DSPs for energy harvesting sensors: applications and architectures. IEEE Pervasive Computing. v4 i3. 72-79.

[5]

J. Chang, L. Tassiulas, Routing for maximum system lifetime in wireless ad-hoc networks, in: Proceedings of Annual Allerton Conference on Communication, Control, and Computing, 1999.

[6]

Floreen, P., Kaski, P., Kohonen, J. and Orponen, P., Exact and approximate balanced data gathering in energy-constrained sensor networks. Theoretical Computer Science. v1 i344. 30-46.

[7]

Ford, L.R. and Fulkerson, D.R., Flows in Networks. 1962. Princeton University Press.

[8]

J. Hsu, J. Friedman, V. Raghunathan, A. Kansal, M.B. Srivastava, Heliomote: enabling self-sustained wireless sensor networks through solar energy harvesting, in: Proceedings of ACM/IEEE ISLPED, 2005.

[9]

Kansal, A. and Srivastava, M.B., Distributed energy harvesting for energy neutral sensor networks. IEEE Pervasive Computing. v4 i1. 69-70.

[10]

A. Kansal, M.B. Srivastava, Energy harvesting aware power management, in: N. Bulusu, S. Jha (Eds.), Wireles Sensor Networks: A Systems Perspective, Artech House, 2005, pp. 1-10 (Chapter 9).

[11]

Intanagonwiwat, C., Govindan, R., Estrin, D., Heidemann, J. and Silva, F., Directed diffusion for wireless sensor networking. ACM/IEEE Transactions on Networking. v1 i1. 2-16.

[12]

Mhatre, V. and Rosenberg, C., Energy and cost optimizations in wireless sensor networks: a survey. In: Girard, A., Sanso, B., Vazquez-Abad, F. (Eds.), Performance Evaluation and Planning Methods for the Next Generation Internet, Kluwer Academic Publishers. pp. 1-23.

[13]

OMNet++ Discrete Event Simulation System, <http://www.omnetpp.org/>.

[14]

Paradiso, J.A. and Starner, T., Energy scavenging for mobile and wireless electronics. IEEE Pervasive Computing. v4 i1. 18-27.

[15]

V. Raghunathan, A. Kansal, J. Hsu, J. Friedman, M.B. Srivastava, Design considerations for solar energy harvesting wireless embedded systems, in: Proceedings of IEEE/ACM International Conference on Information Processing in Sensor Networks, pp. 457-462, 2005.

[16]

E. Shih, S. Cho, N. Ickes, R. Min, A. Sinha, A. Wang, A. Chandrakasan, Physical layer driven protocol and algorithm design for energy-efficient wireless sensor networks, in: Proceedings of ACM SIGMOBILE, 2001.

[17]

Sinha, A. and Chandrakasan, A., Dynamic power management in wireless sensor networks. IEEE Design and Test of Computers. v18 i2. 62-74.

[18]

R. Shah, J. Rabaey, Energy aware routing for low energy ad-hoc sensor networks, in: Proceedings of IEEE Wireless Communication and Networking Conference, vol. 1, pp. 350-355, 2002.

[19]

Tilak, S., A taxonomy of wireless microsensor networks model. ACM Mobile Computing and Communication Review. v6. 28-36.

[20]

T. Voigt, H. Ritter, J. Schiller, Utilizing solar power in wireless sensor networks, in: Proceedings of IEEE Conference on Local Computer Networks, 2003.

[21]

Voigt, T., Ritter, H., Schiller, J., Dunkels, A. and Alonso, J., Solar-aware clustering in wireless sensor networks. Proceedings of IEEE Symposium on Computers and Communications. 238-243.

[22]

T. Voigt, H. Ritter, J. Schiller, Utilizing solar power in wireless sensor networks, in: The 28th Annual IEEE Conference on Local Computer Networks, LCN 2003, pp. 416, 2003.

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Energetic sustainability of routing algorithms for energy-harvesting wireless sensor networks

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Copyright © Elsevier B.V. © 2007.

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Elsevier Science Publishers B. V.

Netherlands

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Published: 01 October 2007

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Cited By

Monali CBhaskar A(2023)Improved wLEACH Based on Real-time Wind Speed Meteorological DataWireless Personal Communications: An International Journal10.1007/s11277-024-10868-z133:4(2321-2337)Online publication date: 1-Dec-2023
https://dl.acm.org/doi/10.1007/s11277-024-10868-z
Rana BSingh YSingh P(2021)A systematic survey on internet of thingsTransactions on Emerging Telecommunications Technologies10.1002/ett.416632:8Online publication date: 6-Aug-2021
https://dl.acm.org/doi/10.1002/ett.4166
Sharma DOjha ABhondekar A(2019)Heterogeneity consideration in wireless sensor networks routing algorithmsThe Journal of Supercomputing10.1007/s11227-018-2635-875:5(2341-2394)Online publication date: 1-May-2019
https://dl.acm.org/doi/10.1007/s11227-018-2635-8
Edla DLipare ACheruku R(2018)Shuffled Complex Evolution Approach for Load Balancing of Gateways in Wireless Sensor NetworksWireless Personal Communications: An International Journal10.1007/s11277-017-5024-398:4(3455-3476)Online publication date: 1-Feb-2018
https://dl.acm.org/doi/10.1007/s11277-017-5024-3
Azharuddin MJana P(2017)PSO-based approach for energy-efficient and energy-balanced routing and clustering in wireless sensor networksSoft Computing - A Fusion of Foundations, Methodologies and Applications10.1007/s00500-016-2234-721:22(6825-6839)Online publication date: 1-Nov-2017
https://dl.acm.org/doi/10.1007/s00500-016-2234-7
Dimou MKossyvakis TChaikalis CTsoukatos KLiolios CVlachos V(2016)Topology Experimentation in a Zigbee Wireless Sensor NetworkProceedings of the 20th Pan-Hellenic Conference on Informatics10.1145/3003733.3003772(1-6)Online publication date: 10-Nov-2016
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Peng SLow C(2015)Energy neutral directed diffusion for energy harvesting wireless sensor networksComputer Communications10.1016/j.comcom.2015.02.01763:C(40-52)Online publication date: 1-Jun-2015
https://dl.acm.org/doi/10.1016/j.comcom.2015.02.017
Tan QAn WHan YLiu YCi SShao FTang H(2015)Energy harvesting aware topology control with power adaptation in wireless sensor networksAd Hoc Networks10.1016/j.adhoc.2014.11.02227:C(44-56)Online publication date: 1-Apr-2015
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Bouyer AHatamlou A(2014)Hybridization of the LEACH Protocol with Penalized Fuzzy C-Means PFCM and Self-Organization Map SOM Algorithms for Decreasing Energy in Wireless Sensor NetworksInternational Journal of Business Data Communications and Networking10.5555/2903913.290391610:3(46-64)Online publication date: 1-Jul-2014
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Gu YHe LZhu THe T(2014)Achieving energy-synchronized communication in energy-harvesting wireless sensor networksACM Transactions on Embedded Computing Systems10.1145/2544375.254438813:2s(1-26)Online publication date: 27-Jan-2014
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