| Summary: | 碩士 === 國立交通大學 === 電信工程研究所 === 107 === Node-to-node delay variation (DV) needs to be controlled for latency-sensitive network communications,
the packet delay variation (PDV) is also a major error source in a packet-based synchronization system.
The PDV at the queue buffer in each switching hub along the master-to-slave route presents a
considerable uncertainty in the clock recovery system. The network delay statistics are needed not only for timing
synchronization application but for network resource allocation in a software defined network.
In this thesis, we consider a general parametric network delay model, which enables us to deal with
a general class of network traffics. We assume that the packet delay follows a mixed-Weibull distribution.
The mixing coefficients along with component Weibull parameters allow the model to describe a very wide range
of statistical delay behaviors. For this model-based method, we invoke the concept of moment matching to
perform joint mixing coefficients, unknown parameters and clock offset estimation. We apply the cross
entropy (CE) method for the associated multi-variable optimization problem. The CE method is modified to
deal with larger uncertainty dimension cases. Still it may fail when the model degenerates (i.e., a subset
of the mixing coefficients becomes very small). To overcome this shortcoming, we add a Kullback-Leibler (KL) divergence
based model identification step by dividing the mixing combinations into seven models. The KL divergence is
used to measure the similarity between the sampled delay distribution and the quantized model distribution.
By using moment-matching and forcing the lower-order sample moments to be equal to the ensemble moments,
we seek the optimal model parameters that give the least higher-order moment mismatches. An alternative
approach is to minimize both lower-order and higher-order moment mismatches which can be formulated as
a multi-object optimization problem. Based on this idea, we employ the NSGA-II algorithm to minimize
the mismatches of the second-order and third-order moments simultaneously. Note that our methods can be used
to estimate either or both node clock offset and routing delays.
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