• Journal of information and communication convergence engineering
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• v.8 no.2
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• pp.129-135
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• 2010

Wireless sensor networks (WSNs) are an emerging technology and offers economically viable monitoring solution to many challenging applications. However, deploying new technology in hostile environment, without considering security in mind has often proved to be unreasonably unsecured. Apparently, security techniques face many critical challenges in WSNs like data security and secrecy due to its hostile deployment nature. In order to resolve security in WSNs, we propose a novel and efficient secure framework called TriSec: a secure data framework for wireless sensor networks to attain high level of security. TriSec provides data confidentiality, authentication and data integrity to sensor networks. TriSec supports node-to-node encryption using PingPong-128 stream cipher based-privacy. A new PingPong-MAC (PP-MAC) is incorporated with PingPong stream cipher to make TriSec framework more secure. PingPong-128 is fast keystream generation and it is very suitable for sensor network environment. We have implemented the proposed scheme on wireless sensor platform and our result shows their feasibility.

• ETRI Journal
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• v.33 no.6
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• pp.924-934
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• 2011

Sensor networks play an important role in making the dream of ubiquitous computing a reality. With a variety of applications, sensor networks have the potential to influence everyone's life in the near future. However, there are a number of issues in deployment and exploitation of these networks that must be dealt with for sensor network applications to realize such potential. Localization of the sensor nodes, which is the subject of this paper, is one of the basic problems that must be solved for sensor networks to be effectively used. This paper proposes a probabilistic support vector machine (SVM)-based method to gain a fairly accurate localization of sensor nodes. As opposed to many existing methods, our method assumes almost no extra equipment on the sensor nodes. Our experiments demonstrate that the probabilistic SVM method (PSVM) provides a significant improvement over existing localization methods, particularly in sparse networks and rough environments. In addition, a post processing step for PSVM, called attractive/repulsive potential field localization, is proposed, which provides even more improvement on the accuracy of the sensor node locations.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.4
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• pp.846-851
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• 2007

The wireless sensor network is one of the most practical and cost-effective solutions for monitoring systems covering wild and wide area such as wildfire monitoring. However, the RF distance between sensor nodes is very short due to the need of low power consumption of the sensor node, so the number of sensor nodes to be deployed in the target area is more than tens of thousands. In this paper, we design and analyze the deployment issues as well as re-deployment problem occurred when the battery is exhausted. We also propose the needs and solutions for coverage problem in dynamic deployment. By the experimental evaluations, we analyze the packet success ratio between sensor nodes under various environments such as obstacles and variable distances.

• ETRI Journal
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• v.39 no.2
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• pp.222-233
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• 2017

Debugging in distributed environments, such as wireless sensor networks (WSNs), which consist of sensor nodes with limited resources, is an iterative and occasionally laborious process for programmers. In sensor networks, it is not easy to find unintended bugs that arise during development and deployment, and that are due to a lack of visibility into the nodes and a dearth of effective debugging tools. Most sensor network debugging tools are not provided with effective facilities such as real-time tracing, remote debugging, or a GUI environment. In this paper, we present a hybrid debugging framework (HDF) that works on WSNs. This framework supports query-based monitoring and real-time tracing on sensor nodes. The monitoring supports commands to manage/control the deployed nodes, and provides new debug commands. To do so, we devised a debugging device called a Docking Debug-Box (D2-Box), and two program agents. In addition, we provide a scalable node monitor to enable all deployed nodes for viewing. To transmit and collect their data or information reliably, all nodes are connected using a scalable node monitor applied through the Internet. Therefore, the suggested framework in theory does not increase the network traffic for debugging on WSNs, and the traffic complexity is nearly O(1).

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.10a
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• pp.373-376
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• 2008

Wireless sensor networks consist of thousands of sensor nodes that have low power, low footprint and low computational capacities. So the burning issues in the design and deployment of these sensor nodes in the practical application areas include the energy conservation and network lifetime. Efficient routing schemes can help reduce the energy consumption and thus increase the network lifetime. This paper deals with the comparative analysis of popular routing protocols such as LEACH, LEACH-C, MTE, and PEGASIS. The protocols are compared by using performance me tries such as system lifetime, the time for first node death, and total system energy.

• Journal of the Korean Geographical Society
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• v.45 no.6
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• pp.788-805
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• 2010

The present USN (Ubiquitous Sensor Networks) node deployment practices have many limitations in terms of positional connectivity. The aim of this research was to minimize a redundancy of USN route nodes, by integrating spatially weighted parameters such as visibility, proximity to cell center, road density, building density and cell overlapping ratio into a comprehensive GIS database. This spatially weighted approach made it possible to reduce the number of route nodes (11) required in the study site as compared to that of the grid network method (24). The field test for RSSI (Received Signal Strength Indicator) indicates that the spatially weighted deployment could comply with the quality assurance standard for node connectivity, and that reduced route nodes do not show a significant degree of signal fluctuation for different site conditions. This study demonstrated that the spatially weighted deployment can be used to minimize a redundancy of USN route nodes in a routine manner, and the quantitative evidence removing a redundancy of USN route nodes could be utilized as major tools to ensure the strong signal in the USN, that is frequently encountered in real applications.

• Journal of Korea Multimedia Society
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• v.12 no.10
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• pp.1478-1485
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• 2009

A sensor network which is composed of a large number of sensors that perform various sensing is applied in a variety of fields. The sensor networks can be widely used for various application area like as home automation, fire detection and security area. Development of new sensor to have appropriate functions and deployment of networks for suitable application are served actively. In this paper, we design and implement a system that monitors various factory facilities by deploying sensor network at a working place which threatens the worker's safety. A sensor node reports its sensing data like as temperature and humidity to monitor facilities to a sink node. And the server which is connect to the sink node gathers and provides information by user interface. In addition, digital data which are generated at a work place can be transferred via the sensor network to increase the efficiency of works. The proposed sensor network provides the convenience of working, since it is deployed at a garbage collection company to monitor a temperature and humidity of garbage and to transmit data about the weight of trucks which enters the company.

• Journal of information and communication convergence engineering
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• v.16 no.1
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• pp.6-11
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• 2018

It is important to find the random estimation points in wireless sensor network. A link quality indicator (LQI) is part of a network management service that is suitable for a ZigBee network and can be used for localization. The current quality of the received signal is referred as LQI. It is a technique to demodulate the received signal by accumulating the magnitude of the error between ideal constellations and the received signal. This proposed model accepts any number of random estimation point in the network and calculated its nearest anchor centroid node pair. Coordinates of the LQI sphere are calculated from the pair and are added iteratively to the initially estimated point. With the help of the LQI and weighted centroid localization, the proposed system finds the position of target node more accurately than the existing system by solving the problems related to higher error in terms of the distance and the deployment of nodes.

• Journal of KIISE:Information Networking
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• v.33 no.3
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• pp.193-200
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• 2006

The security feature is essential in wireless sensor network such as intrusion detection or obstacle observation. Sensor nodes must have shared secret between nodes to support security such as privacy. Many methods which provide key pre-distribution need too many keys or support poor security. To solve this problem, probabilistic key pre-distribution is proposed. This method needs a few keys and use probabilistic method to share keys. However, this method does not guarantee key sharing between nodes, and neighbor nodes nay not communicate each other. It leads to waste of network resource such as inefficient routing, extra routing protocol. In this paper, we propose new key distribution method using quorum system which needs a few keys and guarantee key sharing between nodes. We also propose extension of the method which needs fewer keys and guarantee key sharing when node deployment knowledge is well known.

• Smart Structures and Systems
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• v.10 no.3
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• pp.271-298
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• 2012

Researchers have made significant progress in recent years towards realizing effective structural health monitoring (SHM) utilizing wireless smart sensor networks (WSSNs). These efforts have focused on improving the performance and robustness of such networks to achieve high quality data acquisition and distributed, in-network processing. One of the primary challenges still facing the use of smart sensors for long-term monitoring deployments is their limited power resources. Periodically accessing the sensor nodes to change batteries is not feasible or economical in many deployment cases. While energy harvesting techniques show promise for prolonging unattended network life, low power design and operation are still critically important. This research presents the WiSeMote: a new, fully integrated ultra-low power wireless smart sensor node and a flexible base station, both designed for long-term SHM deployments. The power consumption of the sensor nodes and base station has been minimized through careful hardware selection and the implementation of power-aware network software, without sacrificing flexibility and functionality.