Browsing by Author "Yao, Chien"

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A filter-based self-similar trace synthesizer
(2007-05-01)
Yao, Chien
;
Hua, Kai-Lung
;
Chen, Po-Ning
;
Chen, Jin-Yuan
;
Chiang, Tihao
Recent empirical studies have shown that modern computer network traffic is much more appropriately modelled by long-range dependent self-similar processes than traditional short-range dependent processes such as Poisson. Thus, if its selfsimilar nature is not considered in the synthesis of experimental network data, incorrect performance assessments for network systems may result. This raises the need of a self-similar trace synthesizing algorithm with long-range dependence. In this paper, we propose and examine the feasibility of a filter-based method for the synthesis of self-similar network traces. The proposed approach can alleviate the problems encountered by conventional synthesizers, such as random midpoint displacement and Paxson's spectrum fitting, which cannot generate self-similar traces on the fly and may give negative numbers. Additionally, the extended range of self-similarity of the filtered approach can be easily managed by the filter truncation window; therefore, a trace that faithfully matches the measured behavior of true network traffic, where the self-similar nature only lasts beyond a certain range but disappears as the considered aggregated window is much further extended, can be generated.
Fault-tolerance analysis of a wireless sensor network with distributed classification codes
(2006)
Chen, Po-Ning
;
Wang, Tsang-Yi
;
Han, Yunghsiang S.
;
Varshney, Pramod K.
;
Yao, Chien
In this work, we analyze the performance of a wireless sensor network with distributed classification codes, where independence across sensors, including local observations, local classifications and sensor-fusion link noises, is assumed. In terms of large deviations technique, we establish the necessary and sufficient condition under which the minimum Hamming distance fusion error vanishes as the number of sensors tends to infinity. With the necessary and sufficient condition and the upper performance bounds, the relation between the fault-tolerance capability of a distributed classification code and its pair-wise Hamming distances is characterized.
Performance analysis and code design for minimum hamming distance fusion in wireless sensor networks
(2007-05-01)
Yao, Chien
;
Chen, Po-Ning
;
Wang, Tsang-Yi
;
Han, Yunghsiang S.
;
Varshney, Pramod K.
Distributed classification fusion using error-correcting codes (DCFECC) has recently been proposed for wireless sensor networks operating in a harsh environment. It has been shown to have a considerably better capability against unexpected sensor faults than the optimal likelihood fusion. In this paper, We analyze the performance of a DCFECC code with minimum Hamming distance fusion. No assumption on identical distribution for local observations, as well as common marginal distribution for the additive noises of the wireless links, is made. In addition, sensors are allowed to employ their own local classification rules. Upper bounds on the probability of error that are valid for any finite number of sensors are derived based on large deviations technique. A necessary and sufficient. condition under which the minimum Hamming distance fusion error vanishes as the number of sensors tends to infinity is also established. With the necessary and sufficient condition and the upper error bounds, the relation between the fault-tolerance capability of a DCFECC code and its pair-wise Hamming distances is characterized, and can be used together with any code search criterion in finding the code with the desired fault-tolerance capability. Based on the above results, we further propose a code search criterion of much less complexity than the minimum Hamming distance fusion error criterion adopted earlier by the authors. This makes the code construction with acceptable fault-tolerance capability for a network with over a hundred of sensors practical. Simulation results show that the code determined based on the new criterion of much less complexity performs almost identically to the best code that minimizes the minimum Hamming distance fusion error. Also simulated and discussed are them performance trends of the codes searched based on the new simpler criterion with respect to the network size and the number of hypotheses.