Abstract
The use of Wireless Sensor Networks (WSN) in a wide variety of application domains has been intensively pursued lately while Future Internet designers consider WSN as a network architecture paradigm that provides abundant real-life real-time information which can be exploited to enhance the user experience. The wealth of applications running on WSNs imposes different Quality of Service requirements on the underlying network with respect to delay, reliability and loss. At the same time, WSNs present intricacies such as limited energy, node and network resources. To meet the application’s requirements while respecting the characteristics and limitations of the WSN, appropriate routing metrics have to be adopted by the routing protocol. These metrics can be primary (e.g. expected transmission count) to capture a specific effect (e.g. link reliability) and achieve a specific goal (e.g. low number of retransmissions to economize resources) or composite (e.g. combining latency with remaining energy) to satisfy different applications needs and WSNs requirements (e.g. low latency and energy consumption at the same time). In this paper, (a) we specify primary routing metrics and ways to combine them into composite routing metrics, (b) we prove (based on the routing algebra formalism) that these metrics can be utilized in such a way that the routing protocol converges to optimal paths in a loop-free manner and (c) we apply the proposed approach to the RPL protocol specified by the ROLL group of IETF for such low power and lossy link networks to quantify the achieved performance through extensive computer simulations.
Similar content being viewed by others
References
Mainwaring, A., et al. (2002). Wireless sensor networks for habitat monitoring. International Workshop on Wireless Sensor Networks and Applications (ACM).
Viswanathan, H., Chen, B., & Pompili, D. (2012). Research challenges in computation, communication, and context awareness for ubiquitous healthcare. IEEE Communications Magazine, 50(5), 92–99.
Mols, D. (2009). Making measurement count. Control Engineering Europe Journal, 24–26.
Ledeczi, A., Nadas, A., Volgyesi, P., Balogh, G., Kusy, B., Sallai, J., et al. (2005). Contersniper system for urban warfare. ACM Transactions on Sensor Networks, 1(2), 153–177.
Sarakis, L., Zahariadis, T., Leligou, H., & Dohler, M., (2012). A Framework for Service Provisioning in Virtual Sensor Networks. EURASIP Journal on Wireless Communications and Networking. doi:10.1186/1687-1499-2012-135.
Akkaya, K., & Younis, M. (2005). A survey on routing protocols for wireless sensor networks. Elsevier Journal of Ad Hoc Networks, 3, 325–349.
Boukerche, A., Turgut, B., Aydin, N., Ahmad, M. Z., Bölöni, L., & Turgut, D. (2011). Routing protocols in ad hoc networks: A survey. Computer Networks, 55, 3032–3080.
Baumann, R., Heimlicher, S., Strasser, M., & Weibel, A., (2007). A survey on routing metrics. TIK Report 262, ETH-Zentrum, Computer Engineering and Networks Laboratory.
Anastasi, G., Conti, M., Di Francesco, M., & Passarella, A. (2009). Energy conservation in wireless sensor networks: A survey. Ad Hoc Networks, 7(3), 537–568.
IETF, RFC6551. Vasseur, J. P., et al. (2012). Routing metrics used for path calculation in low power and lossy networks. http://tools.ietf.org/html/rfc6551. Accessed 8 November 2012.
Javaid, N., Javaid, A., Ali Khan, I., & Djouani, K., (2009). Performance study of ETX based wireless routing metrics. In 2nd IEEE International Conference on Computer, Control and Communication.
Leligou, H.C., Trakadas, P., Maniatis, S., Karkazis, P., & Zahariadis, T. (2010). Combining trust with location information for routing in wireless sensor networks. Wireless Communications and Mobile Computing Journal. doi:10.1002/wcm.1038.
Gouda, M. G., & Schneider, M. (2003). Maximizable routing metrics. IEEE/ACM Transactions on Networking, 11(4), 663–675.
Yan, C., Hu, J., Shen, L., & Song, T., (2009). RPLRE: A routing protocol based on LQI and residual energy for wireless sensor networks. In 1st International Conference on Information Science and Engineering, ICISE2009, pp. 2714–2717.
Sobrinho, J. L. (2002). Algebra and algorithms for QoS path computation and hop-by-hop routing in the Internet. IEEE/ACM Transactions on Networking, 10(4), 541–550.
Sobrinho, J. (2003). Network routing with path vector protocols: Theory and applications. PLoS One, 200, 49–60.
Sobrinho, J. L. (2005). An Algebraic Theory of Dynamic Network Routing. IEEE/ACM Transactions on Networking, 13(5), 1160–1173.
Yang, Y., & Wang, J. (2005). Designing routing metrics for mesh networks. Wi-Mesh 2005. Santa Clara, CA.
Yang, Y., & Wang, J. (2008). Design guidelines for routing metrics in multihop wireless networks. IEEE INFOCOM, 2008, 1615–1623.
IETF, RFC6550. RPL: IPv6 Routing protocol for low power and lossy networks. http://tools.ietf.org/rfc/rfc6550.txt. Accessed 8 November 2012.
Kalpana, G., Kumar, D., Ranjani, K., & SenthilKumar, G. (2011). Interference aware routing metrics for wireless mesh networks: A survey. International Journal of Research and Reviews in Wireless Communications, 1(3), 43–50.
Siraj, M., & Abu Bakar, K. (2012). A load balancing interference aware routing metric (LBIARM) for multi hop wireless mesh network. International Journal of the Physical Sciences, 7(3), 456–461. doi:10.5897/IJPS11.1522.
Singh, S., Woo, & M., Raghavendra, C. (1998). Power-aware routing in mobile ad hoc networks. In Proceedings of Fourth Annual International Conference on Mobile Computing and Networking.
Kannhavong, B., Nakayama, H., Nemoto, Y., Kato, N., & Jamalipour, A. (2007). A survey of routing attacks in mobile ad hoc networks. IEEE Wireless Communications, 14(5), 85–90.
Zahariadis, T., Leligou, H., Trakadas, P., & Voliotis, S. (2010). Trust management in wireless sensor networks. European Transaction on Telecommunicatiοns, 21(4), 386–395. doi:10.1002/ett.1413.
Marmol, F. G., & Perez, G. M. (2010). Providing trust in wireless sensor networks using a bio-inspired technique. Telecommunication Systems, 46(2), 163–180.
Zahariadis, T., Leligou, H., Karkazis, P., Trakadas, P., Papaefstathiou, I., Vangelatos, C., et al. (2010). Design and implementation of a trust-aware routing protocol for large WSNs. International Journal of Network Security and Its Applications, 2(3), 52–68.
Sun, Y., Han, Z., & Ray Liu, K. J. (2008). Defense of trust management vulnerabilities in distributed networks. IEEE Communications Magazine, 25(2), 112–119.
Zahariadis, T., & Trakadas, P., (2012). Design guidelines for routing metrics composition in LLN. http://tools.ietf.org/html/draft-zahariadis-roll-metrics-composition-03, Accessed 8 November 2012.
IETF, RFC6552. Thubert, P., (2012). Objective function zero for the routing protocol for low-power and lossy networks. http://tools.ietf.org/html/rfc6552. Accessed 8 November 2012.
IETF, RFC6719 Gnawali, O., & Levis, P., (2012). The minimum rank with hysteresis objective function, http://tools.ietf.org/html/rfc6719, Accessed 8 November 2012.
J-Sim official web site. (2005). J-Sim Official, NSF DARPA/IPTO, MURI/AFOSR, Cisco Systems, Inc., Ohio State University, University of Illinois at Urbana-Champaign, http://sites.google.com/site/jsimofficial. Accessed 8 November 2012.
Karkazis, P., Trakadas, P., Zahariadis, T., Hatziefremidis, A., & Leligou, H. C. (2012). RPL modeling in J-Sim platform. In 9th International Conference on Networked Sensing Systems.
http://www.ee.teihal.gr/professors/voliotis/digilab_site/RPL_for_JSIM_Home.html OR http://code.google.com/p/rpl-jsim-platform/.
Acknowledgment
The work presented in this paper was partially supported by the EU-funded Project FP7 ICT-257245 VITRO project.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Karkazis, P., Trakadas, P., Leligou, H.C. et al. Evaluating routing metric composition approaches for QoS differentiation in low power and lossy networks. Wireless Netw 19, 1269–1284 (2013). https://doi.org/10.1007/s11276-012-0532-2
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11276-012-0532-2