• Journal of Korea Multimedia Society
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• v.19 no.9
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• pp.1690-1697
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• 2016

In a beacon-enabled Zigbee network, the slotted CSMA/CA mechanism based on the super frame structure fairly provides communication chance for each node and makes a reasonable usage of the available energy. In the case of wireless nano sensors that are implanted into the target human body area for detecting disease symptoms or virus, such a nano-network requires a similar type of channel sharing and transmission of short length event-driven data. In this paper, for nano-network's in-body applications, we aim to design conceptually a new super frame derived from the existing beacon-enabled Zigbee MAC protocol. And we analyze the efficiency of the proposed super frame in the aspect of practical deployment.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.11
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• pp.4065-4083
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• 2021

Super-resolution can improve the clarity of low-resolution (LR) images, which can increase the accuracy of high-level compute vision tasks. Portable devices have low computing power and storage performance. Large-scale neural network super-resolution methods are not suitable for portable devices. In order to save the computational cost and the number of parameters, Lightweight image processing method can improve the processing speed of portable devices. Therefore, we propose the Enhanced Information Multiple Distillation Network (EIMDN) to adapt lower delay and cost. The EIMDN takes feedback mechanism as the framework and obtains low level features through high level features. Further, we replace the feature extraction convolution operation in Information Multiple Distillation Block (IMDB), with Ghost module, and propose the Enhanced Information Multiple Distillation Block (EIMDB) to reduce the amount of calculation and the number of parameters. Finally, coordinate attention (CA) is used at the end of IMDB and EIMDB to enhance the important information extraction from Spaces and channels. Experimental results show that our proposed can achieve convergence faster with fewer parameters and computation, compared with other lightweight super-resolution methods. Under the condition of higher peak signal-to-noise ratio (PSNR) and higher structural similarity (SSIM), the performance of network reconstruction image texture and target contour is significantly improved.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.3
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• pp.602-612
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• 2015

Current IEEE 802.11p which is suggested for vehicle to vehicle communication supports one hop communication. Thus, it has a limitation to carry out efficient data dissemination. In this thesis, we suggest LTE-D2D based vehicle network to provide efficient data dissemination in the vehicle environment. In this network architecture, we use name based message with IP packet options and we put the intermediate vehicle node called 'super vehicle node' and each normal vehicle node in the cell requests data to the super vehicle node. The super vehicle node responses data to the normal vehicle node. Performance analysis is based mathematical modeling. We compare LTE cellular network to LTE-D2D based vehicle network about throughput according to packet delivery time.

• Journal of information and communication convergence engineering
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• v.8 no.3
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• pp.295-300
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• 2010

Recent researches of network structure are moving to high-level networks because there are already many research results of low-level network. Especially, current network services has been changed to the multimedia service using multicast routing such as IPTV(Internet Protocol Television) service. And then previous multicast services were provider oriented. So previous multicast structures were organized server/client model. But future multicast services will make user oriented services. Therefore there will be many service providers in the future. At this point, we study P2P network for supporting multi provider. So we research load balancing and contents lookup protocols in P2P network. In this paper, we propose network protocol and system based on super peer P2P for load balancing and efficiently service search. And we considered mobile environment for mobile IPTV.

• Journal of the Korean Professional Engineers Association
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• v.29 no.5
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• pp.99-103
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• 1996

In this paper we discuss Gigabit information communication service utilizing Gigabit information super-highway, multimedia data processing technology for the services, multimedia communication protocol for transmitting multimedia data and construction of Gigabit information communication network which can be accessed everywhere and present items which should be tactically prepared for high-level information society of the 21 st century.

• Journal of Biosystems Engineering
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• v.23 no.4
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• pp.391-398
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• 1998

Effective use of agricultural informations is crucial for 21 century farming. An interactive agricultural machinery information system was developed. It consisted of databases, knowledge bases, expert systems, a server engine, clients for a multimedia agricultural machinery information system based on Java and distributed objects technology. It is supposed to be served through a nationwide super information communication network for my farmers to utilize it interactively and quickly. Several user-friendly interface programs for users were developed to use texts, static k dynamic images, and expert systems easily. Tools for providing the informations were built with JAVA. Information providers permitted to access to the system such as agricultural machinery companies can easily add or modify the informations using distributed object technology. This system can interact among three groups : prime information provider (or system manager), permitted information providers, and farmers.

• International Journal of Internet, Broadcasting and Communication
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• v.7 no.1
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• pp.42-48
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• 2015

Generally, the current commercial cloud system is hosted by the centralization large datacenter. However, the other clouding forms existed and one of them is the P2P cloud. The P2P Cloud is a distributed systems, is freedom to join and leave and is possible to provide the IaaS. Commonly, P2P Cloud System is based on Pure-P2P System. Since a number of connection paths exist, it has a high reliability and easily scalability of the network. However, there are disadvantages of the slow rate of route because of looking up the all peers in order to search for the peer. In this paper, it proposes the P2P cloud system based on super-peer P2P. Super-peer P2P system has fast routing time, because of searching for cluster unit and it also can has high reliability and high scalability. We designs the super Peer cloud service and proposes the system model and Resource Allocation Algorithm for IaaS in Super peer P2P environment.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.12
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• pp.1604-1611
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• 2020

Light field image captured by a microlens array-based camera has many limitations in practical use due to its low spatial resolution and angular resolution. High spatial resolution images can be easily acquired with a single image super-resolution technique that has been studied a lot recently. But there is a problem in that high angular resolution images are distorted in the process of using disparity information inherent among images, and thus it is difficult to obtain a high-quality angular resolution image. In this paper, we propose light field angular super-resolution that extracts an initial feature map using an dilated convolutional neural network in order to effectively extract the view difference information inherent among images and generates target image using a residual neural network. The proposed network showed superior performance in PSNR and subjective image quality compared to existing angular super-resolution networks.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.10
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• pp.3302-3320
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• 2014

An allocation of sensing and reporting times is proposed to improve the sensing performance by scheduling them in an efficient way for cognitive radio networks with cluster-based cooperative spectrum sensing. In the conventional cooperative sensing scheme, all secondary users (SUs) detect the primary user (PU) signal to check the availability of the spectrum during a fixed sensing time slot. The sensing results from the SUs are reported to cluster heads (CHs) during the reporting time slots of the SUs and the CHs forward them to a fusion center (FC) during the reporting time slots of the CHs through the common control channels for the global decision, respectively. However, the delivery of the local decision from SUs and CHs to a CH and FC requires a time which does not contribute to the performance of spectrum sensing and system throughput. In this paper, a super-allocation technique, which merges reporting time slots of SUs and CHs to sensing time slots of SUs by re-scheduling the reporting time slots, has been proposed to sense the spectrum more accurately. In this regard, SUs in each cluster can obtain a longer sensing duration depending on their reporting order and their clusters except for the first SU belonged to the first cluster. The proposed scheme, therefore, can achieve better sensing performance under -28 dB to -10 dB environments and will thus reduce reporting overhead.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.11
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• pp.1477-1485
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• 2021

Recently, super-resolution has been intensively studied only on upscaling models with integer magnification. However, the need to expand arbitrary magnification is emerging in representative application fields of actual super-resolution, such as object recognition and display image quality improvement. In this paper, we propose a model that can support arbitrary magnification by using the weights of the existing integer magnification model. This model converts super-resolution results into the DCT spectral domain to expand the space for arbitrary magnification. To reduce the loss of high-frequency information in the image caused by the expansion by the DCT spectral domain, we propose a high-frequency attention network for arbitrary magnification so that this model can properly restore high-frequency spectral information. To recover high-frequency information properly, the proposed network utilizes channel attention layers. This layer can learn correlations between RGB channels, and it can deepen the model through residual structures.