Our Publications

by Haowen Chan, Mark Luk, and Adrian Perrig
Abstract:
Sensor network localization continues to be an important research challenge. The goal of localization is to assign geographic coordinates to each node in the sensor network. Localization schemes for sensor network systems should work with inexpensive off-the-shelf hardware, scale to large networks, and also achieve good accuracy in the presence of irregularities and obstacles in the deployment area. We present a novel approach for localization that can satisfy all of these desired properties. Recent developments in sensor network clustering algorithms have resulted in distributed algorithms that produce highly regular clusters. We propose to make use of this regularity to inform our localization algorithm. The main advantages of our approach are that our protocol requires only three randomly-placed nodes that know their geographic coordinates, and does not require any ranging or positioning equipment (i.e., no signal strength measurement, ultrasound ranging, or directional antennas are needed). So far, only the DV-Hop localization mechanism worked with the same assumptions \citeNicNat01. We show that our proposed approach may outperform DV-Hop in certain scenarios, in particular when there exist large obstacles in the deployment field, or when the deployment area is free of obstacles but the number of anchors is limited.
Reference:
Using Clustering Information for Sensor Network Localization. Haowen Chan, Mark Luk, and Adrian Perrig. In Proceedings of the IEEE Conference on Distributed Computing in Sensor Systems (DCOSS 2005) 2005.
Bibtex Entry:
@InProceedings{ChLuPe2005,
    author =       {Haowen Chan and Mark Luk and Adrian Perrig},
    title =        {Using Clustering Information for Sensor Network Localization},
    url = {/publications/papers/clusterlocalize.pdf},
    booktitle =    {Proceedings of the IEEE Conference on Distributed Computing in Sensor Systems (DCOSS 2005)},
    year =         2005,
    month =        jun,
    abstract =     {Sensor network localization continues to be an
                  important research challenge. The goal of
                  localization is to assign geographic coordinates to
                  each node in the sensor network. Localization
                  schemes for sensor network systems should work with
                  inexpensive off-the-shelf hardware, scale to large
                  networks, and also achieve good accuracy in the
                  presence of irregularities and obstacles in the
                  deployment area. We present a novel approach for
                  localization that can satisfy all of these desired
                  properties. Recent developments in sensor network
                  clustering algorithms have resulted in distributed
                  algorithms that produce highly regular clusters. We
                  propose to make use of this regularity to inform our
                  localization algorithm. The main advantages of our
                  approach are that our protocol requires only three
                  randomly-placed nodes that know their geographic
                  coordinates, and does not require any ranging or
                  positioning equipment (i.e., no signal strength
                  measurement, ultrasound ranging, or directional
                  antennas are needed).  So far, only the DV-Hop
                  localization mechanism worked with the same
                  assumptions~\cite{NicNat01}. We show that our
                  proposed approach may outperform DV-Hop in certain
                  scenarios, in particular when there exist large
                  obstacles in the deployment field, or when the
                  deployment area is free of obstacles but the number
                  of anchors is limited.}
}