Browsing by Author "Kuo, Sheng-Po"

Now showing 1 - 7 of 7

A quorum-based mechanism as an enhancement to clock synchronization protocols for IEEE 802.11 MANETs
(2007-04-01)
Chen, Shu-Min
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Kuo, Sheng-Po
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Tseng, Yu-Chee
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資訊工程學系
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Department of Computer Science
In wireless mobile ad hoc networks (MANETs), it is essential that all mobile hosts (MHs) are synchronized to a common clock to support the power-saving (PS) mechanism. Many protocols have been proposed for clock synchronization in IEEE 802.11 MANETs. However, it is practically impossible for any protocol to completely solve the asynchronism problem especially when connectivity is achieved by multi-hop communication or when a network could be temporarily disconnected. In this work, we propose a quorum-based mechanism, which includes a new structure of beacon intervals for MHs to detect potential asynchronous neighbors and an enhanced beacon transmission rule to assist clock synchronization protocols to discover asynchronous neighbors within bounded time. The proposed mechanism should be regarded as an enhancement to existing clock synchronization protocols. Our simulation results show that the mechanism can effectively relieve the clock asynchronism problem for IEEE 802.11 MANETs.
A scrambling method for fingerprint positioning based on temporal diversity and spatial dependency
(2008-05-01)
Kuo, Sheng-Po
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Tseng, Yu-Chee
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資訊工程學系
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Department of Computer Science
Signal strength fluctuation is one of the major problems in a fingerprint-based localization system. To alleviate this problem, we propose a scrambling method to exploit temporal diversity and spatial dependency of collected signal samples. We present methods on how these properties can be applied to enhance the positioning accuracy of several existing schemes. Simulation studies and experimental results show that the scrambling method can greatly improve positioning accuracy, especially when the tracked object has some degree of mobility.
Cluster-enhanced techniques for pattern-matching localization systems
(2007)
Kuo, Sheng-Po
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Wu, Bing-Jhen
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Peng, Wen-Chih
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Tseng, Yu-Chee
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資訊工程學系
In location-based services, the response time of location determination is critical, especially for real-time applications. This is especially true for pattern-matching localization methods, which rely on comparing tin object's current signal strength pattern against a pre-established location database of signal strength patterns collected in the training phase. In this work, we propose some cluster-enhanced techniques to speed up the positioning process while avoiding the possible positioning errors caused by this accelerated mechanism. Through grouping training locations with similar signal strength patterns together and characterizing them by a single feature vector, we show how to reduce the associated comparison cost so as to accelerate? the pattern-matching process. To deal with signal fluctuations, several clustering strategies allowing overlaps are proposed. Extensive simulation studies are conducted. Experimental results show that compared to the pattern-matching systems without clustering techniques, a reduction of more than 90% in computation cost can be obtained in average without degrading the positioning accuracy.
Detecting movement of beacons in location-tracking wireless sensor networks
(2007)
Kuo, Sheng-Po
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Kuo, Hsiao-Ju
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Tseng, Ya-Chee
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Lee, Yueh-Feng
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資訊工程學系
Localization is a critical issue in wireless sensor networks. In most localization schemes, there are beacons being placed as references to determine the positions of objects or events appearing in the sensing field. The underlying assumption is that beacons are always static. In this work, we define a new Beacon Movement Detection (BMD) problem. Assuming that there are unnoticed changes of locations of some beacons in the system, this problem is concerned about how to automatically monitor such situations and identify these beacons. Removal of such beacons in the positioning engine may improve the localization accuracy. Two schemes are proposed to solve the BMD problem. Finally, we evaluate how these solutions can improve the accuracy of localization schemes in case that there are unnoticed movement of some beacons. Simulation results show that our solutions alleviate 53% the decrease of positioning accuracy caused by the exceptional beacon movement.
Discriminant Minimization Search for Large-Scale RF-Based Localization Systems
(2011-02-01)
Kuo, Sheng-Po
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Tseng, Yu-Chee
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資訊工程學系
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Department of Computer Science
In large-scale fingerprinting localization systems, fine-grained location estimation and quick location determination are conflicting concerns. To achieve finer grained localization, we have to collect signal patterns at a larger number of training locations. However, this will incur higher computation cost during the pattern-matching process. In this paper, we propose a novel discriminant minimization search (DMS)-based localization methodology. Continuous and differentiable discriminant functions are designed to extract the spatial correlation of signal patterns at training locations. The advantages of the DMS-based methodology are threefold. First, with through slope of discriminant functions, the exhaustive pattern-matching process can be replaced by an optimization search process, which could be done by a few quick jumps. Second, the continuity of the discriminant functions helps predict signal patterns at untrained locations so as to achieve finer grained localization. Third, the large amount of training data can be compressed into some functions that can be represented by a few parameters. Therefore, the storage space required for localization can be significantly reduced. To realize this methodology, two algorithms, namely, Newton-PL and Newton-INT, are designed based on the concept of gradient descent search. Simulation and experiment studies show that our algorithms do provide finer grained localization and incur less computation cost.
GeoAds: A middleware architecture for music service with location-aware advertisement
(2007)
Kuo, Sheng-Po
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Lin, Shih-Ching
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Wu, Bing-Jhen
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Tseng, Yu-Chee
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Shen, Chung-Chou
This paper presents a middleware architecture to support location-based services (LBSs) based on heterogeneous localization systems. A GEOINFO gateway is implemented to hide the discrepancy of different localization systems from application developers. Hence, application developers can deploy their LBSs easily without considering the underlying localization techniques. To demonstrate the detailed process and advantages of the proposed architecture, we present a location-based service, called GeoAds, which is a streaming music service with geographical advertisement. This novel integration is expected to attract more mobile users' attention.
The Beacon Movement Detection Problem in Wireless Sensor Networks for Localization Applications
(2009-10-01)
Kuo, Sheng-Po
;
Kuo, Hsiao-Ju
;
Tseng, Yu-Chee
;
資訊工程學系
;
Department of Computer Science
Localization is a critical issue in wireless sensor networks. In most localization systems, beacons are being placed as references to determine the positions of objects or events appearing in the sensing field. The underlying assumption is that beacons are always reliable. In this work, we define a new Beacon Movement Detection (BMD) problem. Assuming that there are unnoticed changes of locations of some beacons in the system, this problem concerns how to automatically monitor such situations and identify such unreliable beacons based on the mutual observations among beacons only. Existence of such unreliable beacons may affect the localization accuracy. After identifying such beacons, we can remove them from the localization engine. Four BMD schemes are proposed to solve the BMD problem. Then, we evaluate how these solutions can improve the accuracy of localization systems in case there are unnoticed movements of some beacons. Simulation results show that our solutions can capture most of the unnoticed beacon movement events and thus can significantly alleviate the degradation of such events.