Abstract
Pervasive computing applications have, in many cases, hard requirements in terms of security. In particular when deploying a Wireless Sensor Network (WSN), security and privacy exigences must be accommodated with the small computational power and especially with the limited energy of the nodes. In some applications nodes may be equipped with energy harvesting devices, especially solar cells, to keep their small batteries charged. The presence of an harvesting device, while enabling the use of WSN in more application fields, represents an additional challenge in the design phase. Given the stochastic nature of most energy harvesting sources, optimizing system performance requires the capability to evaluate the current system conditions runtime.
In this chapter we present a runtime mechanism that optimizes network lifetime and quality of service by adapting network security provisions to the current situation in terms of available energy and recharging rate. By applying our algorithm, network lifetime when the harvester cannot collect energy can be prolonged. The algorithm tries to limit power consumption by suitably changing security settings and by lowering the number of unessential messages sent on the network.
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
Preview
Unable to display preview. Download preview PDF.
References
Akyildiz, I.F., Su, W., Sankarasubramaniam, Y., Cayirci, E.: Wireless Sensor Networks: a Survey. Computer Networks 38, 393–422 (2002)
Alippi, C., Camplani, R., Galperti, C., Roveri, M.: Effective design of WSNs: From the lab to the real world. In: ICST 2008, pp. 1–9 (2008)
Roundy, S., Steingart, D., Frechette, L., Wright, P., Rabaey, J.: Power Sources for Wireless Sensor Networks. In: Karl, H., Wolisz, A., Willig, A. (eds.) EWSN 2004. LNCS, vol. 2920, pp. 1–17. Springer, Heidelberg (2004)
Moser, C., Brunelli, D., Thiele, L., Benini, L.: Real-time scheduling for energy harvesting sensor nodes. Real-Time Syst. 37, 233–260 (2007)
Chandramouli, R., Bapatla, S., Subbalakshmi, K.P., Uma, R.N.: Battery power-aware encryption. ACM Trans. Inf. Syst. Secur. 9, 162–180 (2006)
Mura, M., Fabbri, F., Sami, M.: Modelling the Power Cost of Security in Wireless Sensor Networks: the Case of 802.15.4. In: IEEE ICT 2008 (2008)
Ferrante, A., Piuri, V., Owen, J.: IPSec Hardware Resource Requirements Evaluation. In: NGI 2005, Rome, Italy, EuroNGI (2005)
Keeratiwintakorn, P., Krishnamurthy, P.: Energy Efficient Security Services for Limited Wireless Devices. In: International Symposium on Wireless Pervasive Computing, pp. 1–6 (2006)
Großschädl, J., Szekely, A., Tillich, S.: The energy cost of cryptographic key establishment in wireless sensor networks. In: ASIACCS 2007, pp. 380–382. ACM (2007)
Chigan, C., Li, L., Ye, Y.: Resource-aware self-adaptive security provisioning in mobile ad hoc networks. In: IEEE WCNC, vol. 4, pp. 2118–2124 (2005)
Lighfoot, L., Ren, J., Li, T.: An energy efficient link-layer security protocol for wireless sensor networks. In: 2007 IEEE International Conference on Electro/Information Technology, pp. 233–238 (2007)
Moser, C., Thiele, L., Brunelli, D., Benini, L.: Adaptive power management in energy harvesting systems. In: DATE 2007, pp. 773–778 (2007)
Moser, C., Chen, J.J., Thiele, L.: Reward Maximization for Embedded Systems with Renewable Energies. In: IEEE RTCSA 2008, pp. 247–256 (2008)
Liu, S., Qiu, Q., Wu, Q.: Energy aware dynamic voltage and frequency selection for real-time systems with energy harvesting. In: DATE 2008, pp. 236–241. ACM (2008)
Liu, S., Wu, Q., Qiu, Q.: An adaptive scheduling and voltage/frequency selection algorithm for real-time energy harvesting systems. In: DAC 2009, pp. 782–787 (2009)
Wang, L., Yang, Y., Noh, D.K., Le, H., Abdelzaher, T., Ward, M.: AdaptSens: An Adaptive Data Collection and Storage Service for Solar-Powered Sensor networks. In: RTSS 2009 (2009)
Sean Convery: 49. In: Internetworking Technologies Handbook, 49-1–49-32. Cisco Press (2004) ISBN158705115X
Ravi, S., Raghunathan, A., Kocher, P., Hattangady, S.: Security in embedded systems: Design challenges. Trans. on Embedded Computing Sys. 3, 461–491 (2004)
Mura, M., Paolieri, M., Negri, L., Fabri, F., Sami, M.: Power Modeling and Power Analysis for IEEE 802.15.4: a Concurrent State Machine Approach. In: CCNC 2007 (2007)
Sastry, N., Wagner, D.: Security considerations for IEEE 802.15.4 networks. In: WiSe 2004, pp. 32–42. ACM (2004)
Derin, O., Ferrante, A., Taddeo, A.V.: Coordinated management of hardware and software self-adaptivity. Journal of Systems Architecture 55, 170–179 (2009)
Mura, M., Sami, M.: Code generation from statecharts: Simulation of wireless sensor networks. In: Proceedings of DSD 2008, Parma, Italy (2008)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Taddeo, A.V., Mura, M., Ferrante, A. (2012). Dynamic Adaptation of Security and QoS in Energy-Harvesting Sensors Nodes. In: Obaidat, M.S., Tsihrintzis, G.A., Filipe, J. (eds) e-Business and Telecommunications. ICETE 2010. Communications in Computer and Information Science, vol 222. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25206-8_16
Download citation
DOI: https://doi.org/10.1007/978-3-642-25206-8_16
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-25205-1
Online ISBN: 978-3-642-25206-8
eBook Packages: Computer ScienceComputer Science (R0)