• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.3
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• pp.857-872
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• 2014

Recent researches reveal that great benefit can be achieved for data gathering in wireless sensor networks (WSNs) by employing mobile data collectors. In order to balance the energy consumption at sensor nodes and prolong the network lifetime, a multi-track large-scale mobile data collection mechanism (MTDCM) is proposed in this paper. MTDCM is composed of two phases: the Energy-balance Phase and the Data Collection Phase. In this mechanism, the energy-balance trajectories, the sleep-wakeup strategy and the data collection algorithm are determined. Theoretical analysis and performance simulations indicate that MTDCM is an energy efficient mechanism. It has prominent features on balancing the energy consumption and prolonging the network lifetime.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.22 no.5
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• pp.999-1007
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• 2012

Multi-precision multiplication over public key cryptography should be considered for performance enhancement due to its computational complexity. Particularly, embedded device is not suitable to execute high complex computation, public key cryptography, because of its limited computational power and capacity. To overcome this flaw, research on multi-precision multiplication with fast computation and small capacity is actively being conducted. In the paper, we explore the cutting-edge technology of multi-precision multiplication for efficient implementation of public key cryptography over sensor network. This survey report will be used for further research on implementation of public key cryptography over sensor network.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.10a
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• pp.465-468
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• 2007

An intelligent home network system using low-power and low-cost sensor nodes was designed and implemented. In Intelligent Home Network System, active home appliances control is composed of RSSI (Received Signal Strength Indicator) based user indoor location tracking, dynamic multi-hop routing, and learning integration remote-control. Through the remote-control learning, home appliances can be controlled in wireless network environment. User location information for intelligent service is calculated using RSSI based Triangle measurement method, and then the received location information is passed to Smoothing Algorithm to reduce error rate. In order to service Intelligent Home Network, moreover, the sensor node is designed to be held by user. The gathered user data is transmitted through dynamic multi-hop routing to server, and real-time user location & environment information are displayed on monitoring program.

• The Journal of the Korea Contents Association
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• v.6 no.12
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• pp.136-146
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• 2006

In Wireless Sensor Network(WSN) a sensor node transfers sensing data to the base-node through multi-hop because of the limited transmission range. Also because of the limited energy of the sensor node, the sensor nodes are required to consume their energy evenly to prolong the lifetime of the network. LMPR is a routing protocol for WSN, LMPR configures the network autonomously based on level which is the depth from the base-node, and distributes the transmission and computation load of the network to each sensor node. This paper implements LMPR on TinyOS and experiments on the performance of LMPR in WSN. As the result, the average of the received rate of LMPR is 91.39% and LMPR distributes the load of the transmission and computation about 4.6 times compare to the shortest cost routing protocol. We expect LMPR evenly distributes the transmission and computation load of the network to each node, and the lifetime of the network will be longer than it used to be.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.1
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• pp.193-214
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• 2017

In this paper, we study the problem of network utility maximization in a CSMA based multi-hop wireless network. Existing work in this aspect typically adopted continuous time Markov model for performance modelling, which fails to consider the channel conflict impact in actual CSMA networks. To maximize the utility of a CSMA based wireless network with channel conflict, in this paper, we first model its weighted network capacity (i.e., network capacity weighted by link queue length) and then propose a distributed link scheduling algorithm, called CSMA based Maximal-Weight Scheduling (C-MWS), to maximize the weighted network capacity. We derive the upper and lower bounds of network utility based on C-MWS. The derived bounds can help us to tune the C-MWS parameters for C-MWS to work in a distributed wireless network. Simulation results show that the joint optimization based on C-MWS can achieve near-optimal network utility when appropriate algorithm parameters are chosen and also show that the derived utility upper bound is very tight.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.22 no.2
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• pp.142-147
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• 2008

In wireless sensor networks, one of the most important issue is improvement of network lifetime with an efficient energy consumption. we repose effective multi-hop routing algorithm which increases the number of nodes alive at any time. In our algorithm we use the dynamic selection of cluster head and short distance transmission method. We simulated the proposed algorithm by using Network Simulator 2 and compared its performance with LEACH. The experimental result shows that the number of the nodes alive is increased up to 39.71[%] during the simulation time.

• Journal of Sensor Science and Technology
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• v.18 no.6
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• pp.409-416
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• 2009

A lot of valuable-piece of information are acquisited through ubiquitous sensor network(USN) system composed of man-made sensors. The telemetry system used for communicating to access informations between nature and human-beings monitors and estimates the status of infrastructure, utilities and natural environments to prevent hidden disasters, improving quality of life and productivity in multi-directional views. That would be the reason of USN subsistence. This paper will be a review on how to build long-term USN system. Therefore, this paper focuses on reviewing the sensor interface and the sensor network interface and its significance as the foundation stone for varying USN service profiles and showing its development example, and finally proposing a few of things to set up future-oriented USN open system.

• The KIPS Transactions:PartA
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• v.18A no.4
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• pp.159-164
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• 2011

In this paper, we suggest the active multi-agent middleware for the sensor network application. For this, firstly we design and implement the active rule based mobile agent middleware. The mobile agent in the proposed system visits the destination sensor nodes according to the migration list offered by the meta table in the name space of the naming agent, acquires and transmits sensor data according to the purpose and needs through the active rules, and directly executes the actions corresponding to the optional events(changed sensor data and/or time etc.). And then, we show the potential applicability of the active rule based mobile agent middleware in various active sensor networks through the interaction with the rule base system and context database system.

• International journal of advanced smart convergence
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• v.5 no.1
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• pp.59-65
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• 2016

In this paper, we're compared network protocol which is network lifetime longer when using LEACH Protocol, SEP, and TEEN in a heterogeneous Wireless Sensor Network with a Large Sensor Area. Also, we propose a method of divided layer the wide-area sensor filed and transmitting a multi-hop to improve the network lifetime. And we're compared network protocol which is network lifetime more improved apply the proposed method to LEACH Protocol, SEP, and TEEN. We tried to compare results, TEEN showed the best network lifetime. Apply the proposed method to divided the sensor field, L-TEEN (Layered TEEN)'s network lifetime rates of improvement is highest.

• Smart Structures and Systems
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• v.5 no.4
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• pp.415-426
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• 2009

This study focuses on the concept of multi-scale wireless sensor networks for damage detection in civil infrastructure systems by first over viewing the general network philosophy and attributes in the areas of data acquisition, data reduction, assessment and decision making. The data acquisition aspect includes a scalable wireless sensor network acquiring acceleration and strain data, triggered using a Restricted Input Network Activation scheme (RINAS) that extends network lifetime and reduces the size of the requisite undamaged reference pool. Major emphasis is given in this study to data reduction and assessment aspects that enable a decentralized approach operating within the hardware and power constraints of wireless sensor networks to avoid issues associated with packet loss, synchronization and latency. After over viewing various models for data reduction, the concept of a data-driven Bivariate Regressive Adaptive INdex (BRAIN) for damage detection is presented. Subsequent examples using experimental and simulated data verify two major hypotheses related to the BRAIN concept: (i) data-driven damage metrics are more robust and reliable than their counterparts and (ii) the use of heterogeneous sensing enhances overall detection capability of such data-driven damage metrics.