• Journal of Korea Multimedia Society
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• v.7 no.3
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• pp.388-398
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• 2004

This paper focuses on the reduction method of message traffic occurred when multiple participants collaborate in the distributed virtual environment. It is referred to as filtering method of update message to minimize data traffic exchanged in the virtual environment, and it is the essential process to improve the scalability of the virtual environment. Spatial partitioning method, a popular filtering technique, divides the whole environment into smaller sub-parts in order to make it small the regions to be maintained consistently. However, it is less flexible and adaptable because the information of area of interest must be configured before simulation. In this paper, the concept of dynamic area of interest is proposed, which is highly adaptable by applying dynamic environmental elements to AOI management. It uses multiple layering and multiple consistency algorithms for dynamic management, and makes it possible to consume system resource efficiently. For performance evaluation, experiments are performed with virtual avatars, measuring message traffic. Finally, the proposed model could be applied to the AOI management systems which accommodate massive users like MMORPG, or virtual communities.

• The KIPS Transactions:PartC
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• v.13C no.6 s.109
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• pp.767-774
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• 2006

In order to support overlay multicast with scalability and reliability, in this paper, we introduced a new multicast tree construction method and a regional multicast. The architecture we introduce efficiently transmits streaming data to the users from multicast source in an environment in which non-multicast network and multicast network. The new multicast tree construction method enables the connection with a remote relay which is an optimum condition in case there is no relay in subnet. Besides, by defining a new service type to traffic class of IPv6 header, a selective adoption or FEC and a distinctive transmission became possible. In order to verify the effect of the solution we suggested, we embodied an environment which is similar to the actual service environment by a simulator and tested it. The result of the test shows that the proposed method is more efficient than the traditional unicast approach method and the existing overlay multicast.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.40 no.6
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• pp.459-468
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• 2003

This paper proposes a novel low-cost and high-speed Reed-Solomon (RS) decoder based on a new degree computationless modified Euclid´s (DCME) algorithm. This architecture has quite low hardware complexity compared with conventional modified Euclid´s (ME) architectures, since it can remove completely the degree computation and comparison circuits. The architecture employing a systolic away requires only the latency of 2t clock cycles to solve the key equation without initial latency. In addition, the DCME architecture using 3t＋2 basic cells has regularity and scalability since it uses only one processing element. The RS decoder has been synthesized using the 0.25${\mu}{\textrm}{m}$. Faraday CMOS standard cell library and operates at 200MHz and its data rate suppots up to 1.6Gbps. For tile (255, 239, 8) RS code, the gate counts of the DCME architecture and the whole RS decoder excluding FIFO memory are only 21,760 and 42,213, respectively. The proposed RS decoder can reduce the total fate count at least 23% and the total latency at least 10% compared with conventional ME architectures.

• Journal of Broadcast Engineering
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• v.25 no.5
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• pp.709-722
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• 2020

Point Cloud which is a cluster of numerous points can express 3D object beyond the 2D plane. Each point contains 3D coordinate and color data basically, reflectance or etc. additionally. Point Cloud demand research and development much higher effective compression technology. Video-based Point Cloud Compression (V-PCC) technology in development and standardization based on the established video codec. Despite its high effective compression technology, point cloud service will be limited by terminal spec and network conditions. 2D video had the same problems. To remedy this kind of problem, 2D video is using Scalable High efficiency Video Coding (SHVC), Dynamic Adaptive Streaming over HTTP (DASH) or diverse technology. This paper proposed a density scalability method using SHVC codec in V-PCC.

• Journal of the Korea Society for Simulation
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• v.22 no.2
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• pp.1-10
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• 2013

Modeling and simulation techniques construct experimental environment considering battlefields and are able to analyze performance of components of weapon system that closely resemble reality. However, developed model has low scalability and not cared reusability because it has been used only in a limited range of domain. In this paper, we develop a verification tool to verify reusability of developed component for dynamic reconfiguration and to judge scalability of it and a management tool to control data of it effectively. In addition, dynamic reconfiguration architecture of guided weapon systems designed in the previous study has been applied to SAM(Surface to Air Missile) System Simulator, and we study effectiveness of the developed component. Thus the user can configure various guided weapon systems through simulation application of dynamic reconfiguration architecture of component.

• Journal of Intelligence and Information Systems
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• v.22 no.4
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• pp.1-18
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• 2016

Collaborative Filtering (CF) predicts the focal user's preference for particular item based on user's preference rating data and recommends items for the similar users by using them. It is a popular technique for the personalization in e-commerce to reduce information overload. However, it has some limitations including sparsity and scalability problems. In this paper, we use a method to integrate social network information into collaborative filtering in order to mitigate the sparsity and scalability problems which are major limitations of typical collaborative filtering and reflect the user's qualitative and emotional information in recommendation process. In this paper, we use a novel recommendation algorithm which is integrated with collaborative filtering by using Social SVD++ algorithm which considers social network information in SVD++, an extension algorithm that can reflect implicit information in singular value decomposition (SVD). In particular, this study will evaluate the performance of the model by reflecting the real-world user's social network information in the recommendation process.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.9B
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• pp.1390-1398
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• 2010

We present the concept of applying Wireless Mesh Networking (WMN) technology into Smart Grid, which is recently rising as a potential technology in various areas thanks to its advantages such as low installation costs, high scalability, and high flexibility. Smart Grid is an intelligent, next-generation electrical power network that can maximize energy efficiency by monitoring utility information in real-time and controlling the flow of electricity with IT communications technology converged to the existing power grid. WMNs must be designed for Smart Grid communication systems considering not only the high level of reliability, QoS support and mass-data treatment but also the properties of the traditional power grid. In addition, it is essential to design techniques based on international standards to support interoperability and scalability. In this paper, we evaluate the performance of IEEE 802.11s based Smart Grid Mesh Networks by conducting preliminary simulation studies with the ns-3 simulator. We also outline some challenging issues that should be reviewed when considering WMNs as the candidate for Smart Grid communication infrastructure.

• Journal of KIISE:Information Networking
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• v.36 no.4
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• pp.263-274
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• 2009

Decentralized group key management mechanisms offer beneficial solutions to enhance the scalability and reliability of a secure multicast framework by confining the impact of a membership change in a local area. However, many of the previous decentralized solutions reveal the plaintext to the intermediate relaying proxies, or require the key distribution center to coordinate secure group communications between subgroups. In this study, we propose a decentralized group key management scheme that features a mechanism allowing a service provider to deliver the group key to valid members in a distributed manner using the proxy cryptography. In the proposed scheme, the key distribution center is eliminated while data confidentiality of the transmitted message is provided during the message delivery process. The proposed scheme can support a secure group communication in dynamic network environments where there is no trusted central controller for the whole network and the network topology changes frequently.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.7
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• pp.2257-2285
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• 2022

Cyber-physical systems (CPS) have been growing exponentially due to improved cloud-datacenter infrastructure-as-a-service (CDIaaS). Incremental expandability (scalability), Quality of Service (QoS) performance, and reliability are currently the automation focus on healthy Tier 4 CDIaaS. However, stable QoS is yet to be fully addressed in Cyber-physical data centers (CP-DCS). Also, balanced agility and flexibility for the application workloads need urgent attention. There is a need for a resilient and fault-tolerance scheme in terms of CPS routing service including Pod cluster reliability analytics that meets QoS requirements. Motivated by these concerns, our contributions are fourfold. First, a Distributed Non-Recursive Cloud Model (DNRCM) is proposed to support cyber-physical workloads for remote lab activities. Second, an efficient QoS stability model with Routh-Hurwitz criteria is established. Third, an evaluation of the CDIaaS DCN topology is validated for handling large-scale, traffic workloads. Network Function Virtualization (NFV) with Floodlight SDN controllers was adopted for the implementation of DNRCM with embedded rule-base in Open vSwitch engines. Fourth, QoS evaluation is carried out experimentally. Considering the non-recursive queuing delays with SDN isolation (logical), a lower queuing delay (19.65%) is observed. Without logical isolation, the average queuing delay is 80.34%. Without logical resource isolation, the fault tolerance yields 33.55%, while with logical isolation, it yields 66.44%. In terms of throughput, DNRCM, recursive BCube, and DCell offered 38.30%, 36.37%, and 25.53% respectively. Similarly, the DNRCM had an improved incremental scalability profile of 40.00%, while BCube and Recursive DCell had 33.33%, and 26.67% respectively. In terms of service availability, the DNRCM offered 52.10% compared with recursive BCube and DCell which yielded 34.72% and 13.18% respectively. The average delays obtained for DNRCM, recursive BCube, and DCell are 32.81%, 33.44%, and 33.75% respectively. Finally, workload utilization for DNRCM, recursive BCube, and DCell yielded 50.28%, 27.93%, and 21.79% respectively.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.9
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• pp.399-406
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• 2023

Cloud computing has been evolved to support edge computing architecture that combines fog management layer with edge servers. The main reason why it is received much attention is low communication latency for real-time IoT applications. At the same time, various cloud task scheduling techniques based on artificial intelligence have been proposed. Artificial intelligence-based cloud task scheduling techniques show better performance in comparison to existing methods, but it has relatively high scheduling time. In this paper, we propose a deep learning-based dynamic scheduling with multi-agents supporting scalability in edge computing environments. The proposed method shows low scheduling time than previous artificial intelligence-based scheduling techniques. To show the effectiveness of the proposed method, we compare the performance between previous and proposed methods in a scalable experimental environment. The results show that our method supports real-time IoT applications with low scheduling time, and shows better performance in terms of the number of completed cloud tasks in a scalable experimental environment.