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ZigBee-based long-thin wireless sensor networks: address assignment and routing schemes
(2013)
Pan, Meng-Shiuan
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Tseng, Yu-Chee
;
資訊工程學系
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Department of Computer Science
Although Wireless Sensor Networks (WSNs) have been extensively researched, its deployment is still a big concern. This paper makes two contributions to this issue. First, we promote a new concept of Long-Thin (LT) topology for WSNs, where a network may have a number of linear paths of nodes as backbones connecting to each other. These backbones are to extend the network to the intended coverage areas. At the first glance, a LT WSN only seems to be a special case of numerous WSN topologies. However, we observe, from real deployment experiences, that such a topology is quite general in many applications and deployments. The second contribution is that we show that the address assignment and thus the tree routing scheme defined in the original ZigBee specification may work poorly, if not fail, in a LT topology. We then propose simple, yet efficient, address assignment and routing schemes for a LT WSN. Simulation results are reported.
k-Angle Object Coverage Problem in a Wireless Sensor Network
(2012-12-01)
Tseng, Yu-Chee
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Chen, Po-Yu
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Chen, Wen-Tsuen
;
資訊工程學系
;
Department of Computer Science
One of the fundamental issues in sensor networks is the coverage problem, which reflects how well a field is monitored or tracked by sensors. Various versions of this problem have been studied, such as object, area, barrier, and hole coverage problems. In this paper, we define a new k-angle object coverage problem in a wireless sensor network. Each sensor can only cover a limited angle and range, but can freely rotate to any direction to cover a particular angle. Given a set of sensors and a set of objects at known locations, the goal is to use the least number of sensors to k-angle-cover the largest number of objects such that each object is monitored by at least k sensors satisfying some angle constraint. We propose centralized and distributed polynomial-time algorithms to solve this problem. Simulation results show that our algorithms can be effective in maximizing coverage of objects. A prototype system is developed to demonstrate the usefulness of angle coverage.
Data Compression by Temporal and Spatial Correlations in a Body-Area Sensor Network: A Case Study in Pilates Motion Recognition
(2011-10-01)
Wu, Chun-Hao
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Tseng, Yu-Chee
;
資訊工程學系
;
Department of Computer Science
We consider a body-area sensor network (BSN) consisting of multiple small, wearable sensor nodes deployed on a human body to track body motions. Concerning that human bodies are relatively small and wireless packets are subject to more serious contention and collision, this paper addresses the data compression problem in a BSN. We observe that, when body parts move, although sensor nodes in vicinity may compete strongly with each other, the transmitted data usually exist some levels of redundancy and even strong temporal and spatial correlations. Unlike traditional data compression approaches for large-scale and multihop sensor networks, our scheme is specifically designed for BSNs, where nodes are likely fully connected and overhearing among sensor nodes is possible. In our scheme, an offline phase is conducted in advance to learn the temporal and spatial correlations of sensing data. Then, a partial ordering of sensor nodes is determined to represent their transmission priorities so as to facilitate data compression during the online phase. We present algorithms to determine such partial ordering and discuss the design of the underlying MAC protocol to support our compression model. An experimental case study in Pilates exercises for patient rehabilitation is reported. The results show that our schemes reduce more than 70 percent of overall transmitted data compared with previous approaches.
Non-Location-Based Mobile Sensor Relocation in a Hybrid Static-Mobile Wireless Sensor Network
(2009)
Wu, Fang-Jing
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Hsu, Hsiu-Chi
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Tseng, Yu-Chee
;
Huang, Chi-Fu
;
資訊工程學系
An inherent concern for a wireless sensor network (WSN) is the unbalanced energy consumption problem, where sensors closer to the sink are more likely to exhaust their energy faster than other nodes. To mitigate this problem, this paper considers including some resource-rich mobile nodes, called mobile data-pumps, to conduct data relaying from static sensors to the sink. The network thus becomes a two-tier network, with the original static sensors at the low tier and data-pumps at both low and high tiers. We propose a novel distributed navigation protocol that does not rely on any location information of sensor nodes to relocate data-pumps to meet both goals of connectivity and load balance. The main idea is a concept called virtual Voronoi cells, which can help data-pumps to locally balance their loads using the underlaying low-tier topology and thus significantly balance energy consumption of sensors. Simulation results are presented to verify the effectiveness of our result.
Exploiting Multi-Spatial Correlations of Motion Data in a Body Sensor Network
(2012-05-01)
Wu, Chun-Hao
;
Tseng, Yu-Chee
;
資訊工程學系
;
Department of Computer Science
Human body motions usually exhibit a high degree of coherence and correlation in patterns. This allows exploiting spatial correlations of motion data being captured by a body sensor network. Since human bodies are relatively small, earlier work has shown how to compress motion data by allowing a node to overhear at most kappa = 1 node's transmission and exploit the correlation with its own data for data compression. In this work, we consider multi-spatial correlations by extending kappa = 1 to kappa > 1 and constructing a partial-ordering directed acyclic graph (DAG) to represent the compression dependencies among sensor nodes. While a minimum-cost tree for kappa = 1 can be found in polynomial time, we show that finding a minimum-cost DAG is NP-hard even for kappa = 2. We then propose an efficient heuristic and verify its performance by real sensing data.
Cyber-Physical Handshake
(2011-08-01)
Wu, Fang-Jing
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Chu, Feng-I
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Tseng, Yu-Chee
;
資訊工程學系
;
Department of Computer Science
While sensor-enabled devices have greatly enriched human interactions in our daily life, discovering the essential knowledge behind sensing data is a critical issue to connect the cyber world and the physical world. This motivates us to design an innovative sensor-aided social network system, termed cyber-physical handshake. It allows two users to naturally exchange personal information with each other after detecting and authenticating the handshaking patterns between them. This work describes our design of detection and authentication mechanisms to achieve this purpose and our prototype system to facilitate handshake social behavior.
Indoor Localization: Automatically Constructing Today's Radio Map by iRobot and RFIDs
(2009)
Yeh, Lun-Wu
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Hsu, Ming-Shiou
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Lee, Yueh-Feng
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Tseng, Yu-Chee
;
資訊工程學系
For outdoor localization, GPS already provides a satisfactory solution. For indoor localization, however, a globally usable solution is still missing. One promising direction that is proposed recently is the fingerprinting-based solution. It involves a training phase to collect the radio signal strength (RSS) patterns in fields where localization is needed into a database (called radio map). The radio signal could be from WiFi access points, GSM base stations, or other RF-based networks. Then, during the positioning phase, an object which is interested in its own location can collect its current RSS pattern and compare it against the radio map established in the training phase to identify its possible location. We present an interesting system based a robot and numerous cheap RFID tags deployed on the ground to automate the training process and, more importantly, to frequently update radio maps to reflect the current RSS patterns. This not only significantly reduces human labors but also improves positioning accuracy.
Using event detection latency to evaluate the coverage of a wireless sensor network
(2007-10-15)
Wang, You-Chiun
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Cheng, Kai-Yang
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Tseng, Yu-Chee
;
資訊工程學系
;
Department of Computer Science
A wireless sensor network (WSN) consists of many tiny and low-power devices deployed in a sensing field. One of the major tasks of a WSN is to monitor the surrounding environment and to detect events occurring in the sensing field. Given an event appearing in a WSN, the event detection latency is to model the time that it takes for the WSN to be aware of the event. In this work, we analyze the latency using a probabilistic approach under an any-sensor-detection and a k-sensor-detection models, where k > 1 is an integer. Such an analysis can be used as an index to evaluate a WSN's coverage and thus can help guide the deployment of a WSN. We also develop simulations to verify our analytical results. (C) 2007 Elsevier B.V. All rights reserved.
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
;
資訊工程學系
;
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.
Distributed deployment schemes for mobile wireless sensor networks to ensure multilevel coverage
(2008-09-01)
Wang, You-Chiun
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Tseng, Yu-Chee
;
資訊工程學系
;
Department of Computer Science
One of the key research issues in wireless sensor networks (WSNs) is how sensors can efficiently be deployed to cover an area. In this paper, we solve the k-coverage sensor deployment problem to achieve multilevel (k) coverage of the area of interest I. We consider two subproblems: the k-coverage placement problem and the distributed dispatch problem. The placement problem asks how the minimum number of sensors required and their locations in I can be determined to guarantee that I is k-covered and the network is connected, while the dispatch problem asks how mobile sensors can be scheduled to move to the designated locations according to the result computed by the placement strategy if they are not in the current positions such that the energy consumption due to movement is minimized. Our solutions to the placement problem consider both the binary and probabilistic sensing models and allow an arbitrary relationship between the communication distance and the sensing distance of sensors, thereby relaxing the limitations of existing results. For the dispatch problem, we propose a competition-based scheme and a pattern-based scheme. The competition-based scheme allows mobile sensors to bid for their closest locations, while the pattern-based scheme allows sensors to derive the target locations on their own. Our proposed schemes are efficient in terms of the number of sensors required and are distributed in nature. Simulation results are presented to verify their effectiveness.

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