• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.21 no.10
• /
• pp.1840-1848
• /
• 2017

Linear wireless sensor networks typically construct a network topology with a high reliability through sequential 1:1 mapping among sensor nodes, so that they are used in various surveillance applications of major national infrastructures. Most existing techniques for identifying sensor nodes in those networks are using GPS, AOA, and RSSI mechanisms. However, GPS or AOA based node identification techniques affect the size or production cost of the nodes so that it is not easy to construct practical sensor networks. RSSI based techniques may have a high deviation regrading location identification according to propagation environments and equipment quality so that complexity of error correction algorithm may increase. We propose a timestamps based sequential localization algorithm that uses transmit and receive timestamps in a message between sensor nodes without using GPS, AOA, and RSSI techniques. The algorithms for distance measurement between each node are expected to measure distance within up to 1 meter in case of an crystal oscillator of 300MHz or more.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.26 no.1
• /
• pp.47-53
• /
• 2003

이 논문은 환(環)을 형성하는 부분네트웍들로 이루어진 sparse network의 특수한 형태에서 최단거리 결정을 위한 효율적인 앨고리즘을 제안한다. 제시된 앨고리즘은 소위 비환(非換) 형태의 sparse network에 대한 최단거리 결정 앨고리즘의 확장이라 할 수 있다. 도우넛 형태를 갖는 sparse network에 대해 최단거리 결정을 위한 접근법으로 하나는 정점제거 방법이고, 다른 하나는 선분제거 방법이다. 여기서 제안된 앨고리즘은 일반적인 n-degree circular sparse network으로 확대될 수 있다.

• Journal of the Korea Society of Computer and Information
• /
• v.20 no.11
• /
• pp.63-68
• /
• 2015

In this paper, we propose a new energy efficient scheme which can prolong the life of sensor networks, it should be able to reduce the number of sensing. We use the concept of safe zone for manage the appropriate range of properties. We measure the distance between the sensed temperature value and the center of the zone, and calculate the next sensing interval based on this distance. We name our proposed scheme "VIS". To assess the performance of the proposed scheme the actual temperature data was collected using the sensor node. The algorithm was implemented through the programming and was evaluated in a variety of settings. Experimental results show that the proposed algorithm is to significantly reduce the number of sensing in terms of energy efficiency while having the ability to know the state of the sensor nodes periodically. Our VIS algorithm can be useful in applications which will require the ability of control to the temperature within a proper range.

• Journal of KIISE:Information Networking
• /
• v.34 no.5
• /
• pp.370-378
• /
• 2007

In wireless sensor networks (WSNs), thousands of sensors are often deployed in a hostile environment. In such an environment, WSNs can be applied to various applications by using the absolute or relative location information of the sensors. Until now, the time-of-arrival (TOA) based localization method has been considered most accurate. In the TOA method, however, inaccuracy in distance estimation is caused by clock drift and clock skew between sensor nodes. To solve this problem, several numbers of periodic time synchronization methods were suggested while these methods introduced overheads to the packet traffic. In this paper, we propose a new localization method based on multiple round-trip times (RTOA) of a signal which gives more accurate distance and location estimation even in the presence of clock skew between sensor nodes. Our experimental results show that the Proposed RTOA method gives up to 93% more accurate location estimation.

• The KIPS Transactions:PartC
• /
• v.13C no.6 s.109
• /
• pp.741-748
• /
• 2006

Due to the continuous development of sensor technology, Wireless Sensor Networks are rapidly growing and are expected to be applied to various applications. One of the most important factors in Wireless Sensor Networks is energy-efficient management of network resources. For this purpose, a lot of researches have been ongoing in the development of energy-efficient routing protocol. In this paper, a cluster head selection algorithm considering node density in addition to the cluster head selection algorithm of LEACH-C is proposed and simulated. This algorithm gives nearly the same computational speed compared to that of LEACH-C and shows improvement of network lifetime about 11% better than LEACH-C. The simulation result shows that consideration of density as well as distance between nodes in cluster head selection can be more energy-efficient than considering only the distance between nodes as LEACH-C in energy usage of Wireless Sensor Networks.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.17 no.3
• /
• pp.29-45
• /
• 2017

Ad hoc sensor network is characterized by decentralized structure and ad hoc deployment. Sensor networks have all basic features of ad hoc network except different degrees such as lower mobility and more stringent energy requirements. Existing protocols provide different tradeoffs among some desirable characteristics such as fault tolerance, distributed computation, robustness, scalability and reliability. wireless protocols suggested so far are very limited, generally focusing on communication to a single base station or on aggregating sensor data. The main reason having such restrictions is due to maximum lifetime to maintain network activities. The network lifetime is an important design metric in ad hoc networks. Since every node does a router role, it is not possible for other nodes to communicate with each other if some nodes do not work due to energy lack. In this paper, we suggest an experimental ad-hoc on-demand distance vector routing protocol to optimize the communication of energy of the network nodes.The load distribution avoids the choice of exhausted nodes at the route selection phase, thus balances the use of energy among nodes and maximizing the network lifetime. In transmission control phase, there is a balance between the choice of a high transmission power that lead to increase in the range of signal transmission thus reducing the number of hops and lower power levels that reduces the interference on the expense of network connectivity.

• Convergence Security Journal
• /
• v.13 no.6
• /
• pp.69-76
• /
• 2013

A lot of researches have been done to improve the energy efficiency of Wireless Sensor Networks. But all the current researches are based on the idea of direct communication between cluster head and sink node. Previous results assume that node can intelligently regulate signal energy according to the distance between nodes. It is difficult to implement algorithms based on this assumption. We present a multi-level routing algorithm from the sink node to all other nodes which have fixed radio wave radius. We also show the energy saving efficiency and the implementation in real WSN using the simulation result.

• Journal of Communications and Networks
• /
• v.15 no.2
• /
• pp.164-172
• /
• 2013

We consider the problem of secure and robust clustering for quantized target tracking in wireless sensor networks (WSN) where the observed system is assumed to evolve according to a probabilistic state space model. We propose a new method for jointly activating the best group of candidate sensors that participate in data aggregation, detecting the malicious sensors and estimating the target position. Firstly, we select the appropriate group in order to balance the energy dissipation and to provide the required data of the target in the WSN. This selection is also based on the transmission power between a sensor node and a cluster head. Secondly, we detect the malicious sensor nodes based on the information relevance of their measurements. Then, we estimate the target position using quantized variational filtering (QVF) algorithm. The selection of the candidate sensors group is based on multi-criteria function, which is computed by using the predicted target position provided by the QVF algorithm, while the malicious sensor nodes detection is based on Kullback-Leibler distance between the current target position distribution and the predicted sensor observation. The performance of the proposed method is validated by simulation results in target tracking for WSN.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2011.10a
• /
• pp.493-496
• /
• 2011

Currently in the development of community wireless technology is gaining interest in location-based services and as a result, the importance of the location information is a growing trend. To calculate the location information is being suggested several ways, among them Trilateration is representative. Trilateration is three beacon nodes, the distance between the location in which you want to calculate with information. Beacon from a node to know where to get information when the distance between the obstacle and the distance error caused by the surrounding environment, which leads to the exact location can not be obtained. Currently due to distance error, location information has a variety of algorithms to reduce the error. However, a systematic analysis of these algorithms is not progress. This paper analyzes the location-aware technologies, and the error the distance of the location information to reduce errors in the various aspects of the algorithm for the systematic and empirical comparison was evaluated through the analysis.

• Journal of the Korea Society of Computer and Information
• /
• v.24 no.7
• /
• pp.61-69
• /
• 2019

In this paper, a classification method of random graph models is proposed and it is based on centralities of the random graphs. Similarity between two random graphs is measured for the classification of random graph models. The similarity between two random graph models $G^{R_1}$ and $G^{R_2}$ is defined by the distance of $G^{R_1}$ and $G^{R_2}$, where $G^{R_2}$ is a set of random graph $G^{R_2}=\{G_1^{R_2},...,G_p^{R_2}\}$ that have the same number of nodes and edges as random graph $G^{R_1}$. The distance($G^{R_1},G^{R_2}$) is obtained by comparing centralities of $G^{R_1}$ and $G^{R_2}$. Through the computational experiments, we show that it is possible to compare random graph models regardless of the number of vertices or edges of the random graphs. Also, it is possible to identify and classify the properties of the random graph models by measuring and comparing similarities between random graph models.