• Journal of Internet Computing and Services
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• v.9 no.6
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• pp.99-107
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• 2008

Wireless sensor networks (WSN) based on low-power technologies become important portion of ubiquitous systems. In this paper, we introduce a WSN-based welfare management system as one of the WSN applications. Especially, we implement S-MAC (Sensor Medium Access control) protocol on our system that saves both cost and power consumption, and we evaluate system performances using the TOSSIM simulator. Sensors and a small database server are placed in the house of participant, which collects and stores some environment conditions of the house. The small servers are connected to each others by wireless ad-hoc network.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.8
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• pp.725-730
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• 2012

In this paper, we propose the localization algorithm for the cooperative behavior of the swarm robots based on WSN (Wireless Sensor Network). The proposed method is as follows: First, we measure positions of the L-bot (Leader robot) and F-bots (Follower robots) by using the APIT (Approximate Point In Triangle) and the RSSI (Received Signal Strength Indication). Second, we measure relative positions of the F-bots against the pre-measured position of the L-bot by using trilateration. Then, to revise a position error caused by noise of the wireless signal, we use the particle filter. Finally, we show the effectiveness and feasibility of the proposed method though some simulations.

• Electronics and Telecommunications Trends
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• v.34 no.3
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• pp.55-64
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• 2019

In drone-assisted wireless sensor networks, drones collect data from sensors in an energy-efficient manner and quickly distribute urgent information to sensor nodes. This article introduces recent communication and security schemes for drone-assisted wireless sensor networks. For the communication schemes, we introduce data collection optimization schemes, drone position and movement optimization schemes, and drone flight path optimization schemes. For the security schemes, we introduce authentication and key management schemes, cluster formation schemes, and cluster head election schemes. Then, we present some enhancement methodologies for these communication and security schemes. As a conclusion, we present some interesting future work items.

• Journal of Korea Multimedia Society
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• v.24 no.1
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• pp.67-74
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• 2021

As IoT(Internet Of Things) devices like a smart sensor have constrained power sources, a power strategy is critical in WSN(Wireless Sensor Networks). Therefore, it is necessary to figure out the residual power of each sensor node for managing power strategies in WSN, which, however, requires additional data transmission, leading to more power consumption. In this paper, a residual power estimation method was proposed, which uses ignorantly small amount of power consumption in the resource-constrained wireless networks including WSN. A residual power prediction is possible with the least data transmission by using Machine Learning method with some training data in this proposal. The performance of the proposed scheme was evaluated by machine learning method, simulation, and analysis.

• International Journal of Computer Science & Network Security
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• v.22 no.7
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• pp.91-102
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• 2022

With the evolution of wireless sensor network (WSN) technology, the routing policy has foremost importance in the Internet of Things (IoT). A systematic routing policy is one of the primary mechanics to make certain the precise and robust transmission of wireless sensor networks in an energy-efficient manner. In an IoT environment, WSN is utilized for controlling services concerning data like, data gathering, sensing and transmission. With the advantages of IoT potentialities, the traditional routing in a WSN are augmented with decision-making in an energy efficient manner to concur finer optimization. In this paper, we study how to combine IoT-based deep learning classifier with routing called, Kriging Regressive Deep Belief Neural Learning (KR-DBNL) to propose an efficient data packet routing to cope with scalability issues and therefore ensure robust data packet transmission. The KR-DBNL method includes four layers, namely input layer, two hidden layers and one output layer for performing data transmission between source and destination sensor node. Initially, the KR-DBNL method acquires the patient data from different location. Followed by which, the input layer transmits sensor nodes to first hidden layer where analysis of energy consumption, bandwidth consumption and light intensity are made using kriging regression function to perform classification. According to classified results, sensor nodes are classified into higher performance and lower performance sensor nodes. The higher performance sensor nodes are then transmitted to second hidden layer. Here high performance sensor nodes neighbouring sensor with higher signal strength and frequency are selected and sent to the output layer where the actual data packet transmission is performed. Experimental evaluation is carried out on factors such as energy consumption, packet delivery ratio, packet loss rate and end-to-end delay with respect to number of patient data packets and sensor nodes.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.5
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• pp.747-754
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• 2023

Energy-efficient routing protocol is an important task in a wireless sensor network that is used for monitoring and control by wirelessly collecting information obtained from sensor nodes deployed in various environments. Various routing techniques have been studied for this, but it is also necessary to consider WSN environments with specific situations and conditions. In particular, due to topographical characteristics or specific obstacles, a hole where sensor nodes are not deployed may exist in most WSN environments, which may result in inefficient routing or routing failures. In this case, the geographical routing-based hall bypass routing method using GPS functions will form the most efficient path, but sensors with GPS functions have the disadvantage of being expensive and consuming energy. Therefore, we would like to find the boundary node of the hole in a WSN environment with holes through minimal sensor function and propose hole bypass routing through boundary line formation.

• Journal of Sensor Science and Technology
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• v.22 no.4
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• pp.268-275
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• 2013

Efficient energy management becomes a critical design issue for complex WSN (Wireless Sensor Network). Most of complex WSN employ the sleep mode to reduce the energy dissipation. However, it should cause the reduction of sensing coverage. This paper presents new wake-up algorithm for reducing energy consumption in complex WSN. The proposed wake-up algorithm is devised using geometric probability. It determined which node will be waked-up among the nodes having overlapped sensing coverage. The only one sensor node will be waked-up and it is ready to sense the event occurred uniformly. The simulation results show that the lifetime is increased by 15% and the sensing coverage is increased by 20% compared to the other scheduling methods. Consequently, the proposed wake-up algorithm can eliminate the power dissipation in the overlapped sensing coverage. Thus, it can be applicable for the various WSN suffering from the limited power supply.

• Journal of Communications and Networks
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• v.15 no.4
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• pp.422-429
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• 2013

Advances in wireless sensor network (WSN) technology have enabled small and low-cost sensors with the capability of sensing various types of physical and environmental conditions, data processing, and wireless communication. In the WSN, the sensor nodes have a limited transmission range and their processing and storage capabilities as well as their energy resources are limited. A triple umpiring system has already been proved for its better performance in WSNs. The clustering technique is effective in prolonging the lifetime of the WSN. In this study, we have modified the ad-hoc on demand distance vector routing by incorporating signal-to-noise ratio (SNR) based dynamic clustering. The proposed scheme, which is an efficient and secure routing protocol for wireless sensor networks through SNR-based dynamic clustering (ESRPSDC) mechanisms, can partition the nodes into clusters and select the cluster head (CH) among the nodes based on the energy, and non CH nodes join with a specific CH based on the SNR values. Error recovery has been implemented during the inter-cluster routing in order to avoid end-to-end error recovery. Security has been achieved by isolating the malicious nodes using sink-based routing pattern analysis. Extensive investigation studies using a global mobile simulator have shown that this hybrid ESRP significantly improves the energy efficiency and packet reception rate as compared with the SNR unaware routing algorithms such as the low energy aware adaptive clustering hierarchy and power efficient gathering in sensor information systems.

• Convergence Security Journal
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• v.15 no.3_1
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• pp.75-82
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• 2015

Recently, lot of researches on multi-level protocol have been done to balance the sensor node energy consumption of WSN and to improve the node efficiency to extend the life of the entire network. Especially in multi-hop protocol, a variety of models have been studied to improve energy efficiency and apply it in real system. In multi-hop protocol, we assume that energy consumption can be adjusted based on the distance between the sensor nodes. However, according to the physical property of the actual WSN, it's hard to establish this. In this paper, we propose low-power sub-cluster protocol to improve the energy efficiency based on the spread of distance. Compared with the previous protocols, the proposed protocol is energy efficient and can be effectively used in the wireless sensing network.

• 한국방재학회:학술대회논문집
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• 2007.02a
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• pp.429-432
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• 2007

For smart structure technologies, the interests in wireless sensor networks for structural health monitoring are growing. The wireless sensor networks reduce the installation of the wire embedded in the whole structure and save the costs. But the wireless sensor networks have lots of limits and there are lots of researches and developments of wireless sensor and the network for data process. Most of the researches of wireless sensor network is applying to the civil engineering structure and the researches for the highrise building are required. And strain-based SHM gives the local damage information of the structures which acceleration-based SHM can not. In this paper, concept of wireless sensor network for structural health monitoring of highrise building is suggested. And verifying the feasibility of the strain-based SHM a strain sensor board has developed and tested by experiments.