Abstract
Wireless sensor networks (WSNs), with a wide range of applications in smart cities (e.g. environmental monitoring, intelligent traffic management, healthcare), have energy self-sufficiency as one of the main bottlenecks in their implementation. Thanks to the recent advances in energy harvesting (EH), i.e., capturing energy from ambient renewable sources, it is now a promising solution for low-power and low-rate WNSs. In this paper, we consider two open problems of practical importance to the data quality optimization problem. In this paper, first the probabilistic energy causality constraint for the online consideration of the EH scenarios is proposed. Our realistic assumptions consider causal energy state information, instead of the non-causal cases and the ones based on offline prediction studied in literature. In addition, we propose a novel EH-aware routing protocol, based on opportunistic relaying. This routing protocol is shown to have significant benefits in finding the best path with no prior knowledge of the topology and with minimal overhead, making it an efficient protocol for EH-WSNs.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Ozel, O., Tutuncuoglu, K., Yang, J., Ulukus, S., Yener, A.: Transmission with energy harvesting nodes in fading wireless channels: optimal policies. IEEE J. Sel. Areas Commun. 29(8), 1732–1743 (2011)
Li, H., Xu, J., Zhang, R., Cui, S.: A general utility optimization framework for energy harvesting based wireless communications. IEEE Commun. Mag. 53(4), 79–85 (2015)
Dang, N., Bozorgzadeh, E., Venkatasubramanian, N.: QuARES: quality-aware data collection in energy harvesting sensor networks. In: 2011 International on Green Computing Conference and Workshops (IGCC), pp. 1–9, 25–28 July 2011
Hasenfratz, D., Meier, A., Moser, C., Chen, J.J., Thiele, L.: Analysis, comparison, and optimization of routing protocols for energy harvesting wireless sensor networks. In: 2010 IEEE International Conference on Sensor Networks, Ubiquitous, and Trustworthy Computing (SUTC), pp. 19–26, 7–9 June 2010
Eu, Z.A., Tan, H.-P., Seah, W.K.: Opportunistic routing in wireless sensor networks powered by ambient energy harvesting. Comput. Netw. 54(17), 2943–2966 (2010)
Eu, Z.A., Seah, W.K., Tan, H.-P.: A study of MAC schemes for wireless sensor networks powered by ambient energy harvesting. In: Proceedings of the 4th Annual International Conference on Wireless Internet, p. 78. ICST (Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering) (2008)
Zhang, B., Simon, R., Aydin, H.: Maximal utility rate allocation for energy harvesting wireless sensor networks. In: 14th ACM International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems (2011)
Fan, K.W., Zheng, Z., Sinha, P.: Steady and fair rate allocation for rechargeable sensors in perpetual sensor networks. In: Proceedings of the 6th ACM Conference on Embedded Network Sensor Systems, pp. 239–252. ACM (2008)
Dang, N., Roshanaei, M., Bozorgzadeh, E., Venkatasubramanian, N.: Adapting data quality with multihop routing for energy harvesting wireless sensor networks. In: 2013 International on Green Computing Conference (IGCC), pp. 1–6, 27–29 June 2013
Wei, S., Guan, W., Liu, K.J.R.: Outage probability optimization with equal and unequal transmission rates under energy harvesting constraints. In: Global Communications Conference, GLOBECOM 2013, pp. 2520–2525. IEEE, 9–13 December 2013
Seah, W.K.G., Eu, Z.A., Tan, H.: Wireless sensor networks powered by ambient energy harvesting (WSN-HEAP) - survey and challenges. In: 1st International Conference on Wireless Communication, Vehicular Technology, Information Theory and Aerospace & Electronic Systems Technology, Wireless VITAE 2009, pp. 1–5, 17–20 May 2009
Yang, J., Ulukus, S.: Transmission completion time minimization in an energy harvesting system. In: 2010 44th Annual Conference on Information Sciences and Systems (CISS), pp. 1–6, 17–19 March 2010
Boyd, S., Vandenberghe, L.: Convex Optimization. Cambridge University Press, Cambridge (2004)
Bletsas, A., Khisti, A., Reed, D.P., Lippman, A.: A simple cooperative diversity method based on network path selection. IEEE J. Sel. Areas Commun. 24(3), 659–672 (2006)
Grant, M., Boyd, S., Ye, Y.: CVX: Matlab software for disciplined convex programming (2008)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
About this paper
Cite this paper
Shafieirad, H., Adve, R.S., ShahbazPanahi, S. (2016). Large Scale Energy Harvesting Sensor Networks with Applications in Smart Cities. In: Leon-Garcia, A., et al. Smart City 360°. SmartCity 360 SmartCity 360 2016 2015. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 166. Springer, Cham. https://doi.org/10.1007/978-3-319-33681-7_18
Download citation
DOI: https://doi.org/10.1007/978-3-319-33681-7_18
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-33680-0
Online ISBN: 978-3-319-33681-7
eBook Packages: Computer ScienceComputer Science (R0)