• Journal of the Korea Society of Computer and Information
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• v.16 no.4
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• pp.111-117
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• 2011

In this paper, we propose an QoS aware multi-layer MAC(QAML-MAC) protocol in a wireless sensor networks. Since the proposed protocol is based on the sleep-awake architecture, which save node's energy to prolong the entire network lifetime. For this purpose the QAML-MAC first classifies incoming data according to their transmission urgency and then saves them. The protocol also adapts the cross-layer concept to re-arrange the order of transmission with the same destination. So the delay can be decreased, which can not be obtained with the previous related protocols. And high priority data such as real-time multimedia or critical value in the field monitoring applications can be transmitted quickly, Furthermore the proposed protocol has advantage of decreasing transmitted data collisions using multiple layers of idle listening when there is no high-priority data. So energy consumptions of sensor nodes can be saved and the network lifetime can be prolonged.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.3C
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• pp.281-292
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• 2008

A main application of sensor networks are to monitor and to send information about a possibly hostile environment to a powerful base station connected to a wired network. To conserve power from each sensor, intermediate network nodes should aggregate results from individual sensors. However, it can make it that a single compromised sensor can render the network useless, or worse, mislead the operator into trusting a false reading. In this paper, we propose a protocol to give us a key aggregation mechanism that intermediate network nodes could aggregate data more safely. The proposed protocol is more helpful at multi-tier network architecture in secure sessions established between sensor nodes and gateways. From simulation study, we compare the amount of the energy consumption overhead, the time of key transmission and the ratio of of key process between the proposed method and LHA-SP. The simulation result of proposed protocol is low 3.5% a lord of energy consumption than LHA-SP, the time of key transmission and the ration of key process is get improved result of each 0.3% and 0.6% than LHA-SP.

• The KIPS Transactions:PartC
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• v.16C no.2
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• pp.237-244
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• 2009

The congestion in wireless sensor network increases the ratio of data loss and causes the delay of data. The existing congestion protocols for wireless sensor network reduces the amount of transmission by control the sampling frequency of the sensor nodes related to the congestion when the congestion has occurred and was detected. However, the control method of sampling frequency is not applicable on the situation which is sensitive to the temporal data loss. In the paper, we propose a new congestion control, ACT - Adaptive Congestion conTrol. The ACT monitors the network traffic with the queue usage and detects the congestion based on the multi level threshold of queue usage. Given network congestion, the ACT increases the efficiency of network by adaptive flow control method which adjusts the frequency of packet transmission and guarantees the fairness of packet transmission between nodes. Furthermore, ACT increases the quality of data by using the variable compression method. Through experiment, we show that ACT increases the network efficiency and guarantees the fairness to sensor nodes compared with existing method.

• International Journal of Control, Automation, and Systems
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• v.5 no.2
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• pp.200-207
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• 2007

The passive direction finding cross localization method is widely adopted in passive tracking, therefore there will exist masses of false intersection points. Eliminating these false intersection points correctly and quickly is a key technique in passive localization. A new method is proposed for passive locating and tracking multi-jammer target in this paper. It not only solves the difficulty of determining the number of targets when masses of false intersection points existing, but also solves the initialization problem of elastic network. Thus this method solves the problem of multi-jammer target correlation and the elimination of static false intersection points. The method which dynamically establishes multiple hypothesis trajectory trees solves the problem of eliminating the remaining false intersection points. Simulation results show that computational burden of the method is lower, the elastic network can more quickly find all or most of the targets and have a more probability of locking the real targets. This method can eliminate more false intersection points.

• KIPS Transactions on Computer and Communication Systems
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• v.4 no.1
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• pp.11-14
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• 2015

WSN (Wireless Sensor Network) based on low-power is one of the core technologies in the ubiquitous society. In this paper, we present a border surveillance and control system in WSN environment. The system consists of static sensor node, mobile sensor node, static gateway, mobile gateway, server and mobile application. Mobile applications are divided into user mode and manager mode. So users monitor border surveillance through mobile phone and get information of border network environment without time and space constraints. In manager mode, for the flexible operation of nodes, manager can update to the software remotely and adjust the position of the mobile node. And also we implement a suitable multi-hop routing protocol for scalable low-power sensor nodes and confirm that the system operates well in WSN environment.

• The Journal of Society for e-Business Studies
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• v.15 no.4
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• pp.49-58
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• 2010

The wireless sensor network technology becomes one of core technologies to make it possible to implement various e-business applications. Energy efficiency is an important issue in wireless sensor networks. IEEE 802.15.4, a representative international standard for wireless sensor networks, provides the beacon enabled mode for energy-efficient communication. However, the beacons may conflict each other when the network is of multi-hop topology such as mesh or cluster-tree topology with beacon-enabled mode. The beacon conflict causes the failure of synchronization between sensor nodes, and affects other nodes in the network in that unsynchronized nodes cannot participate in communication. In this paper, we suggest an energy-efficient beacon scheduling for the wireless sensor networks. Nodes can save their energy duringperiod and prevent beacon conflict using beacon scheduling. We implement the scheduling using QualNet, and evaluate the performance under mesh topology networks. It turns out that the proposed scheduling may improve the energy efficiency in the networks.

• Journal of information and communication convergence engineering
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• v.20 no.1
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• pp.22-30
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• 2022

The reinforcement learning algorithm has proven its potential in solving sequential decision-making problems under uncertainties, such as finding paths to route data packets in wireless sensor networks. With reinforcement learning, the computation of the optimum path requires careful definition of the so-called reward function, which is defined as a linear function that aggregates multiple objective functions into a single objective to compute a numerical value (reward) to be maximized. In a typical defined linear reward function, the multiple objectives to be optimized are integrated in the form of a weighted sum with fixed weighting factors for all learning agents. This study proposes a reinforcement learning -based routing protocol for wireless sensor network, where different learning agents prioritize different objective goals by assigning weighting factors to the aggregated objectives of the reward function. We assign appropriate weighting factors to the objectives in the reward function of a sensor node according to its hop-count distance to the sink node. We expect this approach to enhance the effectiveness of multi-objective reinforcement learning for wireless sensor networks with a balanced trade-off among competing parameters. Furthermore, we propose SDN (Software Defined Networks) architecture with multiple controllers for constant network monitoring to allow learning agents to adapt according to the dynamics of the network conditions. Simulation results show that our proposed scheme enhances the performance of wireless sensor network under varied conditions, such as the node density and traffic intensity, with a good trade-off among competing performance metrics.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.1
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• pp.105-122
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• 2011

The fundamental design goal of wireless sensor MAC protocols is to minimize unnecessary power consumption of the sensor nodes, because of its stringent resource constraints and ultra-power limitation. In existing MAC protocols in wireless sensor networks (WSNs), duty cycling, in which each node periodically cycles between the active and sleep states, has been introduced to reduce unnecessary energy consumption. Existing MAC schemes, however, use a fixed duty cycling regardless of multi-hop communication and traffic fluctuations. On the other hand, there is a tradeoff between energy efficiency and delay caused by duty cycling mechanism in multi-hop communication and existing MAC approaches only tend to improve energy efficiency with sacrificing data delivery delay. In this paper, we propose two different MAC schemes (ADS-MAC and ELA-MAC) using closed-loop control in order to achieve both energy savings and minimal delay in wireless sensor networks. The two proposed MAC schemes, which are synchronous and asynchronous approaches, respectively, utilize an adaptive timer and a successive preload frame with closed-loop control for adaptive duty cycling. As a result, the analysis and the simulation results show that our schemes outperform existing schemes in terms of energy efficiency and delivery delay.

• Journal of Korea Society of Industrial Information Systems
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• v.29 no.4
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• pp.35-42
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• 2024

In this study, we propose a method for real-time recognition and analysis of dog behavior using a motion sensor and deep learning techonology. The existing home CCTV (Closed-Circuit Television) that recognizes dog behavior has privacy and security issues, so there is a need for new technologies to overcome them. In this paper, we propose a system that can analyze and care for a dog's behavior based on the data measured by the motion sensor. The study compares the MLP (Multi-Layer Perceptron) and CNN (Convolutional Neural Network) models to find the optimal model for dog behavior analysis, and the final model, which has an accuracy of about 82.19%, is selected. The model is lightened to confirm its potential for use in embedded environments.

• Journal of Korea Society of Industrial Information Systems
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• v.11 no.5
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• pp.11-17
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• 2006

Recently, IT industry by digital technique is improved gradually. Therefore many electronic appliance became the digital, and this is magnified gradually. The development of embedded home automation system combined embedded and internet technique is taking many interest. Specially in the times of the ubiquitous, excellent economically home automation system is preferred even in general family. Therefore, in this paper, we escape from monotonic control of home automation and draw a plan intelligent home automation to be developed.