Wireless integrated network sensors
Communications of the ACM
Processing complex aggregate queries over data streams
Proceedings of the 2002 ACM SIGMOD international conference on Management of data
Wireless sensor networks: a survey
Computer Networks: The International Journal of Computer and Telecommunications Networking
Timing-sync protocol for sensor networks
Proceedings of the 1st international conference on Embedded networked sensor systems
A resource--efficient time estimation for wireless sensor networks
Proceedings of the 2004 joint workshop on Foundations of mobile computing
Fine-grained network time synchronization using reference broadcasts
OSDI '02 Proceedings of the 5th symposium on Operating systems design and implementationCopyright restrictions prevent ACM from being able to make the PDFs for this conference available for downloading
Estimating clock uncertainty for efficient duty-cycling in sensor networks
Proceedings of the 3rd international conference on Embedded networked sensor systems
IEEE Transactions on Signal Processing
Gaussian sum particle filtering
IEEE Transactions on Signal Processing
A tutorial on particle filters for online nonlinear/non-GaussianBayesian tracking
IEEE Transactions on Signal Processing
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The maximum likelihood estimators (MLEs) for the clock phase offset assuming a two-way message exchange mechanism between the nodes of a wireless sensor network were recently derived assuming Gaussian and exponential network delays. However, the MLE performs poorly in the presence of non-Gaussian or nonexponential network delay distributions. Currently, there is a need to develop clock synchronization algorithms that are robust to the distribution of network delays. This paper proposes a clock offset estimator based on the composite particle filter (CPF) to cope with the possible asymmetries and non-Gaussianity of the network delay distributions. Also, a variant of the CPF approach based on the bootstrap sampling (BS) is shown to exhibit good performance in the presence of reduced number of observations. Computer simulations illustrate that the basic CPF and its BSbased variant present superior performance than MLE under general random network delay distributions such as asymmetric Gaussian, exponential, Gamma, Weibull as well as various mixtures.