• ETRI Journal
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• v.27 no.5
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• pp.497-503
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• 2005

In this paper, we present a performance analysis for an MPEG-4 video codec based on the on-chip network communication architecture. The existing on-chip buses of system-on-a-chip (SoC) have some limitation on data traffic bandwidth since a large number of silicon IPs share the bus. An on-chip network is introduced to solve the problem of on-chip buses, in which the concept of a computer network is applied to the communication architecture of SoC. We compared the performance of the MPEG-4 video codec based on the on-chip network and Advanced Micro-controller Bus Architecture (AMBA) on-chip bus. Experimental results show that the performance of the MPEG-4 video codec based on the on-chip network is improved over 50% compared to the design based on a multi-layer AMBA bus.

• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.354-356
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• 2006

In this paper, the position control performance of networked control systems is analyzed when time delay through the network is considered. Integrating a control system into a network has great advantages over the traditional control system which uses point to point connection: it allows remarkable reduction in wiring, makes it easy to install and maintain the system, and improves compability. However, a networked control system has the critical defect that network uncertainties, such as time delay, can degrade the control system's performance. Therefore, the major concern of a networked control system is analyzing the effect of network uncertainties. This paper is concerned with PID controller performance for stability region, critical stability region and unstability region under the time delay in the Controller Area Network.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.9
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• pp.5998-6008
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• 2015

The value of social network and entrepreneurial orientation has widely been acknowledged as a critical resource of business success. However, the previous studies did not specify each role and conceptually have examined them as separate antecedents of firm performance. This study develops propositions concerning network capabilities and investigates the moderating effects of network structures (degree centrality, closeness centrality, and betweenness centrality) on the relationship between entrepreneurial orientation and firm performance. This research conducted with a sample of 115 small consulting companies in Korea. The findings indicate that closeness centrality moderates the relationship between proactiveness and performance. Also, the combination of betweenness centrality and proactiveness exerts a positive impact on performance. Accordingly, degree centrality enhances the influence of innovativeness on performance. In particular, betweenness centrality exacerbates the influence of risk-taking on performance against our expectation. Overall, these findings conclude the synergistic effects of network capability and entrepreneurial orientation on firm performance. Finally, practical implications and academic propositions are presented regarding the way firms could most effectively utilize entrepreneurial orientation and network capability to maximize firm performance.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.6C
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• pp.562-570
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• 2002

The network-wide performance management is crucial for maintaining the quality of network services, which requires the collection and monitoring the performance data at individual network nodes. Most of the public networks, however, are composed of diverse, heterogeneous network nodes that are managed by various types of proprietary management systems with a conventional operator console and embedded management functions, which makes it difficult to implement the integrated performance management systems. Even though the developments of TMN (Telecommunication Management Network) based management systems are being attempted, the little work has been done in performance management area. In this paper, we propose the performance monitoring architecture for ATM switches using the 0₃ object model and describe how to implement the TMN-based performance prosy agent for ATM switching systems. The proposed performance proxy agent provides the TMN standard performance management interfaces by translating the proprietary performance management functions, which eventually leads to network-wide integrated performance management.

• International Journal of Automotive Technology
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• v.7 no.6
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• pp.687-695
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• 2006

This paper presents a network-based traction control system(TCS), where several electric control units(ECUs) are connected by a controller area network(CAN) communication system. The control system consists of four ECUs: the electric throttle controller, the transmission controller, the engine controller and the traction controller. In order to validate the traction control algorithm of the network-based TCS and evaluate its performance, a Hardware-In-the-Loop Simulation(HILS) environment was developed. Herein we propose a new concept of the HILS environment called the network-based HILS(Net-HILS) for the development and validation of network-based control systems which include smart sensors or actuators. In this study, we report that we have designed a network-based TCS, validated its algorithm and evaluated its performance using Net-HILS.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.2
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• pp.280-286
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• 2009

The NGN(Next-Generation Network) structure has been considered from various points of view as all If wireless-wired integration network and its performance is one of the main issue in these days. In this paper, various wired and wireless integrated networks with voice service are designed and simulated to obtain problems and factors affects the network performance using OPnet simulator. The characteristics only showed in the wired and wireless integrated networks are measured and analyzed compared with the single networks such as a wired or wireless networks. Especially, in the wired and wireless integrated networks showed degrading performance even if there are few transmissions in the network and furthermore, the various networks of increasing numbers of the nodes and transmission are simulated and evaluated.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.4C
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• pp.282-294
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• 2002

The modern telecommunication networks are composed of various network-type and are managed by various management technologies, such as TMN, SNMP, TINA etc. Furthermore, the network user's needs of real-time multimedia services are rapidly increasing. In order to guarantee the user-requested quality-of-service(QoS) and keep the network utilization at maximum, it is required to manage the network performance continuously after the network is deployed. The performance management function should provide the useful information for the network expansion and the capacity reallocation in the future. In this paper, we propose a DPE-based performance management architecture for the integrated management of the heterogeneous network elements with TMN and SNMP. We propose an approach to provide the Intranet traffic monitoring and analysis function using layered network management concept and distributed processing technology. The proposed architecture has been designed and implemented based on multiprocess and multithread structure to support concurrent processing. To manage the traffic according to the Intranet service categories, we implemented an ITMA(Intelligent Traffic Monitoring Agent) with packet capture library. With the proposed architecture, we could measure and analyze the real Intranet traffic of Yeungnam University.

• ETRI Journal
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• v.42 no.5
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• pp.686-699
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• 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.

• Journal of the Korean Physical Society
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• v.73 no.10
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• pp.1589-1595
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• 2018

Similarity index measures the topological proximity of node pairs in a complex network. Numerous similarity indices have been defined and investigated, but the dependency of structure on the performance of similarity indices has not been sufficiently investigated. In this study, we investigated the relationship between the performance of similarity indices and structural properties of a network by employing a two-state random network. A node in a two-state network has binary types that are initially given, and a connection probability is determined from the state of the node pair. The performances of similarity indices are affected by the number of links and the ratio of intra-connections to inter-connections. Similarity indices have different characteristics depending on their type. Local indices perform well in small-size networks and do not depend on whether the structure is intra-dominant or inter-dominant. In contrast, global indices perform better in large-size networks, and some such indices do not perform well in an inter-dominant structure. We also found that link prediction performance and the performance of similarity are correlated in both model networks and empirical networks. This relationship implies that link prediction performance can be used as an approximation for the performance of the similarity index when information about node type is unavailable. This relationship may help to find the appropriate index for given networks.

• The Transactions of the Korea Information Processing Society
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• v.13 no.2
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• pp.48-59
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• 2024

As functions that support virtualization on their own in hardware are developed, user applications having various workloads are operating efficiently in the virtualization system. SR-IOV is a virtualization support function that takes direct access to PCI devices, thus giving a high I/O performance by minimizing the need for hypervisor or operating system interventions. With SR-IOV, network I/O acceleration can be realized in virtualization systems that have relatively long I/O paths compared to bare-metal systems and frequent context switches between the user area and kernel area. To take performance advantages of SR-IOV, network resource management policies that can derive optimal network performance when SR-IOV is applied to an instance such as a virtual machine(VM) or container are being actively studied.This paper evaluates and analyzes the network performance of SR-IOV implementing I/O acceleration is compared with Virtio in terms of 1) network delay, 2) network throughput, 3) network fairness, 4) performance interference, and 5) multi-network. The contributions of this paper are as follows. First, the network I/O process of Virtio and SR-IOV was clearly explained in the virtualization system, and second, the evaluation results of the network performance of Virtio and SR-IOV were analyzed based on various performance metrics. Third, the system overhead and the possibility of optimization for the SR-IOV network in a virtualization system with high VM density were experimentally confirmed. The experimental results and analysis of the paper are expected to be referenced in the network resource management policy for virtualization systems that operate network-intensive services such as smart factories, connected cars, deep learning inference models, and crowdsourcing.