• The Journal of Korean Institute of Communications and Information Sciences
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• v.17 no.8
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• pp.796-804
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• 1992

This paper presents a design of a backbone network which uses a rigister-Insertion ring structure, The introduction of a high speed register in sertton backbone ring enables high performance inter-network 4ommunicatlons In a simple and modular structure at low cost and Its concurrent communications.. Two or more bridge nodes can be used to construct a register Insertion backbone ring network. The high bandwidth of the backbone ring sup ports heavy traffic for Inter-segment Eornrnunicatlons. The bridge node does both local address filtering to block data entering the ring and remote address filtering to block data entering the local LAN segment . Title local address greatly reduces the rate on the backbone ring and the remote address filterlng greatly reduces the traffic rate on each LAN segment. An feature makes the network the network reconflguratlon simpler and transparent to users. A throughput analysis Is used to deterrune the bandwidth of the backbone rlr)g transmission medium.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.5
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• pp.1284-1294
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• 2010

The ZigBee is one of the most important technologies for composing USN. It is one of the IEEE 802.15.4 standards to support personal area networks. It uses a hierarchical routing or an on-demand route discovery strategy as an address allocation method. A hierarchical routing doesn't use a routing table but only uses a child node or a parent node as an intermediate node for data delivery. Therefore, the ZigBee network's topology greatly affects the overall network performance. In this paper, we propose a more trustworthy algorithm than only using the depth and widely variable LQI during network formation, and moreover we propose an algorithm to measure network's trustworthiness. We simulate our algorithm using the NS-2 and implement our network using the MG2400 ZigBee module for verifying performance.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.6 no.1
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• pp.14-24
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• 2002

In this paper, a design of the pulsewidth-modulation(PWM) neural network with both retrieving and learning function is proposed. In the designed PWM neural system, the input and output signals of the neural network are represented by PWM signals. In neural network, the multiplication is one of the most commonly used operations. The multiplication and summation functions are realized by using the PWM technique and simple mixed-mode circuits. Thus, the designed neural network only occupies the small chip area. By applying some circuit design techniques to reduce the nonideal effects, the designed circuits have good linearity and large dynamic range. Moreover, the delta learning rule can easily be realized. To demonstrate the learning capability of the realized PWM neural network, the delta learning nile is realized. The circuit with one neuron, three synapses, and the associated learning circuits has been designed. The HSPICE simulation results on the two learning examples on AND function and OR function have successfully verified the function correctness and performance of the designed neural network.

• Journal of the Korea Institute of Military Science and Technology
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• v.22 no.3
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• pp.369-381
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• 2019

As tactical networks are gradually shifting toward IP-based flexible operation for diversified battlefield services, QoS(Quality-of-Service) coordination for service differentiation becomes essential to overcome the heterogeneous and scarce networking resources limitations. QoS coordination for tactical network traffic should be able to monitor and react the dynamic changes in underlying network topology and service priorities. In this paper, by adopting the emerging cloud-native service mesh concept into tactical network context, we study the feasibility of intelligent QoS coordination by employing tactical service mesh(TSM) as an additional layer to support enhanced traffic quality monitoring and control. The additional TSM layer can leverage distributed service-mesh proxies at tactical mesh WAN(Wide Area Network) nodes so that service-aware differentiated QoS coordination can be effectively designed and integrated with TSM-assisted traffic monitoring and control. Also, by validating the feasibility of TSM layer for QoS coordination with miniaturized experimental setup, we show the potential of the proposed approach with several approximated battlefield traffics over a simulated TSM-enabled tactical network.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.11
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• pp.2091-2098
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• 2006

In this paper, it proposes a protocol of resource adaptive data dissemination for sensor nodes in a wireless sensor network. In general, each sensor node used in a wireless sensor network delivers the required information to the final destination by conducting cooperative works such as sensing, processing, and communicating each other using the battery power of a independent sensor node. So, a protocol used for transferring the acquired information to users through the wireless sensor network can minimize the power consumption of energy resource given to a sensor node. Especially, it is very important to minimize the total amount of power consumption with a method for handling the problems on implosion. data delivery overlapping, and excessive message transfer caused by message broadcasting. In this paper, for the maintaining of the shortest path between sensor nodes, maximizing of the life time of a sensor node and minimizing of communication cost, it presents a method for selecting the representative transfer node for an event arising area based on the negotiation scheme and maintaining optimal transfer path using hop and energy information. Finally, for the performance evaluation, we compare the proposed protocol to existing directed diffusion and SPIN protocol. And, with the simulation results, we show that the proposed protocol enhances the performance on the power consumption rate when the number of overall sensor nodes in a sensor network or neighbor sensor nodes in an event area are increased and on the number of messages disseminated from a sensor node.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.1
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• pp.193-198
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• 2020

The various uses of the Convolutional Neural Network technology are accelerating the evolution of the computing area, but the opposite is causing serious hardware performance shortages. Neural network accelerators, next-generation memory device technologies, and high-bandwidth memory architectures were proposed as countermeasures, but they are difficult to actively introduce due to the problems of versatility, technological maturity, and high cost, respectively. This study proposes DRAM-based main memory technology that enables read operations to be completed without waiting until the end of the refresh operation using pre-stored XOR bit values, even when the refresh operation is performed in the main memory. The results showed that the proposed technique improved performance by 5.8%, saved energy by 1.2%, and improved EDP by 10.6%.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.5
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• pp.38-48
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• 2017

Link attributes, such as speed, occupancy, and flow, are essential factors for transportation planning and operation. It is, therefore, one of the most important decision-making problems in intelligent transport system (ITS) to determine the optimal location of a sensor for collecting the information on link attributes. This paper aims to develop a model to determine the optimal location of a sensor to minimize the variability of traffic information on whole networks. To achieve this, a network sensor location model (NSLM) is developed to reflect discrete characteristics of data collection. The variability indices of traffic information are calculated based on the summation of diagonal elements of the variance-covariance matrix. To assess the applicability of the developed model, speed data collected from the dedicated short range communication (DSRC) systems were used in Daegu metropolitan area. The developed model in this study contributes to the enhancement of investment efficiency and the improvement of information accuracy in intelligent transport system (ITS).

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.4
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• pp.679-686
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• 2020

With global data totals expected to grow to 175 ZB by 2025, data processing capabilities in the network area are becoming more important. In particular, data centers are becoming more stubborn as data usage increases, and the load generated by incoming data should be appropriately distributed to reduce costs and efficiently operate. The SDN technology, which emerged to overcome the limitations of the existing network system, removes rigidity of the Legacy system by separating H/W and S/W from the network equipment, and can be effectively applied to load balancing in the data center using S/W-based flexibility. In this paper, we propose ways to increase efficiency by classifying data received from users by type by utilizing SDN technology, and transmitting and processing classified data in order of response speed of servers in the data center.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.2
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• pp.308-316
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• 2015

In this paper, we carried out performance comparison of four routing protocols that had been proposed for mobile ad hoc networks using the NS-3 network simulator. Those four routing protocols consist of two proactive routing protocols, DSDV(destination-sequenced distance vector) and OLSR(optimized link state routing), and two reactive routing protocols, AODV(ad-hoc on-demand distance vector) and DSR(dynamic source routing). Two performance metrics, system throughput and packet delivery ratio, are adopted and performance evaluation was carried out in a square communication area where each communicating mobile node moves independently. Numerical results show that the AODV routing protocol provides the best performance among those four routing protocols.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.3
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• pp.165-171
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• 2019

The study of the computer architecture has shown that major improvements in price-to-energy performance stems from domain-specific hardware development. This paper analyzes the tensor processing unit (TPU) ASIC which can accelerate the reasoning of the artificial neural network (NN). The core device of the TPU is a MAC matrix multiplier capable of high-speed operation and software-managed on-chip memory. The execution model of the TPU can meet the reaction time requirements of the artificial neural network better than the existing CPU and the GPU execution models, with the small area and the low power consumption even though it has many MAC and large memory. Utilizing the TPU for the tensor flow benchmark framework, it can achieve higher performance and better power efficiency than the CPU or CPU. In this paper, we analyze TPU, simulate the Python modeled OpenTPU, and synthesize the matrix multiplication unit, which is the key hardware.