Abstract
In wired networks, monitor-based network tomography has been proved to be an effective technology for network internal state measurements. Existing wired network tomography approaches assume that the network topology is relatively static. However, the network topology of sensor networks are usually changing over time due to wireless dynamics. In this paper, we study the problem to assign a number of sensor nodes as monitors in large scale sensor networks, so that the end-to-end measurements among monitors can be used to identify hop-by-hop link metrics. We propose RoMA, a Robust Monitor Assignment algorithm to assign monitors in large scale sensor networks with dynamically changing topology. RoMA includes two components, confidence-based robust topology generation and cost-minimized monitor assignment. We implement RoMA and evaluate its performance based on a deployed large scale sensor network. Results show that RoMA achieves high identifiability with dynamically changing topology and is able to assign monitors with minimum cost.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Lawrence, E., Michailidis, G., Nair, V.N., Xi, B.: Network tomography: a review and recent developments. In: Frontiers in Statistics (2006)
Ma, L., He, T., Leung, K.K., Swami, A., Towsley, D.: Identifiability of link metrics based on end-to-end path measurements. In: Proceedings of ACM IMC (2013)
Ma, L., He, T., Leung, K.K., Towsley, D., Swami, A.: Efficient identification of additive link metrics via network tomography. In: Proceedings of IEEE ICDCS (2013)
Ma, L., He, T., Leung, K.K., Swami, A., Towsley, D.: Link identifiability in communication networks with two monitors. In: Proceedings of IEEE Globecom (2013)
Gao, Y., Dong, W., Chen, C., Bu, J., Guan, G., Zhang, X., Liu, X.: Pathfinder: robust path reconstruction in large scale sensor networks with lossy links. In: Proceedings of ICNP (2013)
Downey, A.B.: Using pathchar to estimate internet link characteristics. In: Proceedings of ACM SIGCOMM (1999)
Jin, G., Yang, G., Crowley, B.R., Agarwal, D.A.: Network characterization service (NCS). In: Proceedings of IEEE HPDC (2001)
Bejerano, Y., Rastogi, R.: Robust monitoring of link delays and faults in IP networks. IEEE/ACM Trans. Netw. 14(5), 1092–1103 (2006)
Kumar, R., Kaur, J.: Practical beacon placement for link monitoring using network tomography. IEEE J. Sel. Areas Commun. 24(12), 2196–2209 (2006)
Horton, J.D., Lpez-Ortiz, A.: On the number of distributed measurement points for network tomography. In: Proceedings of ACM IMC (2003)
Chen, Y., Bindel, D., Song, H., Katz, R.H.: An algebraic approach to practical and scalable overlay network monitoring. In: Proceedings of ACM SIGCOMM (2004)
Gurewitz, O., Sidi, M.: Estimating one-way delays from cyclic-path delay measurements. In: Proceedings of IEEE INFOCOM (2001)
Gopalan, A., Ramasubramanian, S.: On identifying additive link metrics using linearly independent cycles and paths. IEEE/ACM Trans. Netw. 20(3), 906–916 (2012)
Gao, Y., Dong, W., Chen, C., Bu, J., Chen, T., Xia, M., Liu, X., Xu, X.: Domo: passive per-packet delay tomography in wireless ad-hoc networks. In: Proceedings of IEEE ICDCS (2014)
Dong, W., Zhang, X., Wang, J., Gao, Y., Chen, C., Bu, J.: Accurate and robust time reconstruction for deployed sensor networks. In: Proceedings of ACM SIGMETRICS (poster) (2014)
Tarjan, R.E.: Depth-first search and linear graph algorithms. SIAM J. Comput. 1(2), 146–160 (1972)
Hopcroft, J.E., Tarjan, R.E.: Dividing a graph into triconnected components. SIAM J. Comput. 2(3), 135–158 (1973)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Liu, X., Gao, Y., Wu, W., Dong, W. (2015). Robust Monitor Assignment for Large Scale Sensor Network Tomography. In: Sun, L., Ma, H., Fang, D., Niu, J., Wang, W. (eds) Advances in Wireless Sensor Networks. CWSN 2014. Communications in Computer and Information Science, vol 501. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-46981-1_48
Download citation
DOI: https://doi.org/10.1007/978-3-662-46981-1_48
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-662-46980-4
Online ISBN: 978-3-662-46981-1
eBook Packages: Computer ScienceComputer Science (R0)