• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 2003년도 ICCAS
• /
• pp.1767-1770
• /
• 2003

This paper proposes an efficient network architecture for reflective memory system (RMS). Using this architecture, the time for broadcasting a shared-data to all nodes can be significantly shortened. The device named topology conversion switch (TCS) is implemented to realize the network architecture. The implemented TCS is applied to the ethernet based real time control network (ERCnet) to evaluate the performance.

• 한국정보처리학회:학술대회논문집
• /
• 한국정보처리학회 2002년도 춘계학술발표논문집 (상)
• /
• pp.19-22
• /
• 2002

기존의 광선로 특성 데이터에 대한 관리는 대부분 수작업에 의존하였기 때문에 처리 절차가 제대로 정립되어 있지 않고 사용의 어려움이 많았다. 이로 인해 선로 자원의 사용이 원활하지 못하였고, 최적의 땅 구축하는데 많은 시간이 소요되는 등 많은 문제점들이 도출되었다. 따라서, 이러한 문제점을 해결하기 위해 본 논문에서는 수작업에 의존했던 황 선로의 특성 정보 데이터를 데이터베이스화하고, 구축된 데이터베이스를 통해 최적의 광통신망 설계를 지원할 수 있도록 망 설계 처리 구조를 제안한다.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제5권1호
• /
• pp.52-67
• /
• 2011

Network coding is a newly developed technology that can cause considerable improvements in network throughput. COPE is the first network coding approach for wireless mesh networks and it is based on opportunistic Wireless Network Coding (WNC). It significantly improves throughput of multi-hop wireless networks utilizing network coding and broadcast features of wireless medium. In this paper we propose a new method, called FENC, for opportunistic WNC that improves the network throughput. In addition, its complexity is lower than other opportunistic WNC approaches. FENC utilizes division and conquer method to find an optimal network coding. The numerical results show that the proposed opportunistic algorithm improves the overall throughput as well as network coding approach.

• 한국컴퓨터정보학회논문지
• /
• 제22권3호
• /
• pp.131-138
• /
• 2017

New drug development is time-consuming and costly. Hence, it is necessary to repurpose old drugs for finding new indication. We suggest the way that repurposing old drug using massive literature data and biological network. We supposed a disease-drug relationship can be available if signal pathways of the relationship include significant genes identified in literature data. This research is composed of three steps-identifying significant gene using co-occurrence in literature; analyzing the shortest path on biological network; and scoring a relationship with comparison between the significant genes and the shortest paths. Based on literatures, we identify significant genes based on the co-occurrence frequency between a gene and disease. With the network that include weight as possibility of interaction between genes, we use shortest paths on the network as signal pathways. We perform comparing genes that identified as significant gene and included on signal pathways, calculating the scores and then identifying the candidate drugs. With this processes, we show the drugs having new possibility of drug repurposing and the use of our method as the new method of drug repurposing.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제17권3호
• /
• pp.896-915
• /
• 2023

The network function virtualization (NFV) uses virtualization technology to separate software from hardware. One of the most important challenges of NFV is the resource management of virtual network functions (VNFs). According to the dynamic nature of NFV, the resource allocation of VNFs must be changed to adapt to the variations of incoming network traffic. However, the significant delay may be happened because of the reallocation of resources. In order to balance the performance between delay and quality of service, this paper firstly made a compromise between VNF migration and energy consumption. Then, the long short-term memory (LSTM) was utilized to forecast network traffic. Also, the asymmetric loss function for LSTM (LO-LSTM) was proposed to increase the predicted value to a certain extent. Finally, an experiment was conducted to evaluate the performance of LO-LSTM. The results demonstrated that the proposed LO-LSTM can not only reduce migration times, but also make the energy consumption increment within an acceptable range.

• JSTS:Journal of Semiconductor Technology and Science
• /
• 제4권4호
• /
• pp.258-262
• /
• 2004

Storage over Ethernet (SoE) is a network storage architecture that allows direct attachment of existing ATA/ATAPI devices to Ethernet without a separate server. Unlike SAN, no server computer intervenes between the storage and the client hosts. We propose a SoE disk controller (SoEDC) amenable to low-cost, single-chip implementation that processes a simplified L3/L4 protocol and converts commands between Ethernet and ATA/ATAPI, while the rest of the complex tasks are performed by the remote hosts. Thanks to simple architecture and protocol, the SoEDC implemented on a single $4mm{\times}4mm$ chip in 0.18um CMOS technology achieves maximum throughput of 55MB/s on Gigabit Ethernet, which is comparable to that of a high-performance disk storage locally attached to a host computer.

• International Journal of Control, Automation, and Systems
• /
• 제6권3호
• /
• pp.351-363
• /
• 2008

This paper is concerned with tasking and guidance of networked airborne sensors to achieve fault-tolerant sensing. The sensors are coordinated to locate hostile transmitters by intercepting and processing their signals. Faults occur when some sensor-carrying vehicles engaged in target location missions are lost. Faults effectively change the network architecture and therefore degrade the network performance. The first objective of the paper is to optimally allocate a finite number of sensors to targets to maximize the network life and availability. To that end allocation policies are solved from relevant Markov decision problems. The sensors allocated to a target must continue to adjust their trajectories until the estimate of the target location reaches a prescribed accuracy. The second objective of the paper is to establish a criterion for vehicle guidance for which fault-tolerant sensing is achieved by incorporating the knowledge of vehicle loss probability, and by allowing network reconfiguration in the event of loss of vehicles. Superior sensing performance in terms of location accuracy is demonstrated under the established criterion.

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 2002년도 추계학술대회 논문집 전력기술부문
• /
• pp.65-68
• /
• 2002

Distributed Generators (DG) are rapidly increasing and most of them are interconnected with distribution network to supply power into the network. Therefore, DG may make significant impacts on distribution system operation. protection, and control with respect to the voltage regulation, voltage flicker, harmonics, fault current levels, the losses of the network, etc. These impacts would be demerits for both of DG and distribution networks. And the operation of DG may be influenced by the abnormal grid condition such as disturbances occurred in the neighboring distribution feeders as well as the feeder directly connected with DG. This paper describes the influence of fault occurred in the interconnected power network on the DG operation and the impact of DG on the network load during the interruptions of utility power.

• ETRI Journal
• /
• 제42권5호
• /
• pp.686-699
• /
• 2020

In this paper, we propose a supervised-learning-based spatial performance prediction (SLPP) framework for next-generation heterogeneous communication networks (HCNs). Adaptive asset placement, dynamic resource allocation, and load balancing are critical network functions in an HCN to ensure seamless network management and enhance service quality. Although many existing systems use measurement data to react to network performance changes, it is highly beneficial to perform accurate performance prediction for different systems to support various network functions. Recent advancements in complex statistical algorithms and computational efficiency have made machine-learning ubiquitous for accurate data-based prediction. A robust network performance prediction framework for optimizing performance and resource utilization through a linear discriminant analysis-based prediction approach has been proposed in this paper. Comparison results with different machine-learning techniques on real-world data demonstrate that SLPP provides superior accuracy and computational efficiency for both stationary and mobile user conditions.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 2004년도 ICCAS
• /
• pp.820-824
• /
• 2004

Personal Robot System in developing, have a module architecture, each module are connected through heterogeneors network systems like Ethernet, WLAN (802.11), IEEE1394 (Firewire), Bluetooth, USB, CAN, or RS-232C. In developing personal robot system we think that the key of robot performance is interoperability among modules. Each network protocol are well connected in the view of network system for the interoperability. So we make a bridging architecture that can routing, converting, transporting data packets with matcing each network's properties. Furthermore we suggest a advanced design scheme for realtime / non-realtime and control signal (short, requiring hard-realtime) / multimedia data (large, requiring soft-realtime). By some application systems, we could test performance, interoperability and stability. In this paper, we show our design concept, middleware architecture, and some applications systems using this middleware.