• Journal of the Korean Institute of Telematics and Electronics A
• /
• v.32A no.4
• /
• pp.15-23
• /
• 1995

In this paper, we evaluate the performance of a transient queueing approximation when it is applied to modeling computer communication networks. An operational computer network that uses the ISO IS-IS(Intermediate System-Intermediate System) routing protocol is modeled as a Jackson network. The primary goal of the approximation pursued in the study was to provide transient queue statistics comparable in accuracy to the results from conventional Monte Carlo simulations. A closure approximation of the M/M/1 queueing system was extended to the general Jackson network in order to obtain transient queue statistics. The performance of the approximation was compared to a discrete event simulation under nonstationary conditions. The transient results from the two simulations are compared on the basis of queue size and computer execution time. Under nonstationary conditions, the approximations for the mean and variance of the number of packets in the queue erer fairly close to the simulation values. The approximation offered substantial speed improvements over the discrete event simulation. The closure approximation provided a good alternative Monte Carlo simulation of the computer networks.

• Proceedings of the Korean Society of Computer Information Conference
• /
• 2012.01a
• /
• pp.105-108
• /
• 2012

Wireless mesh networks are considered a promising solution to last mile broadband. The unique characteristics of WMN impose unique requirements on designing routing protocols and metrics for WMN. However, existing routing schemes that are designed for single-channel multi-hop wireless networks may lead to inefficient routing paths in multichannel. This paper focuses on the routing problem for multi-radio multichannel WMNs. We list the challenges in designing routing algorithms for multi-radio multichannel WMNs. Then we examine the requirements and considerations for designing routing metrics according to the characteristics of multi-radio multichannel WMNs. Finally we survey and investigate the existing routing metrics in terms of their ability to satisfy these requirements.

• Journal of the Korea Society of Computer and Information
• /
• v.23 no.10
• /
• pp.181-188
• /
• 2018

In this paper, we tried to investigate whether the influence of 'I' in a heterogeneous network of physical network and virtual network can be quantitatively measurable. To do this, we used Networked Community(NC) methodology to devise a concrete model of influence assessment in heterogeneous network. In order to test the model, we conducted an experiment with Donald J. Trump and his surroundings to evaluate the effectiveness of this influence assessment model. Experimentation included the measurement of impacts on the physical and virtual networks, and the impact on the networked community. Using Trump's case, we found that analyzing only one of the two networks can not accurately analyze the impact on others.

• Proceedings of the KIEE Conference
• /
• 2005.07c
• /
• pp.2327-2329
• /
• 2005

In this paper, we identify the memory effects of the RF high-power base station amplifiers with Vector Signal Analyzer (VSA). It is found that the model of power- amplifier using Tapped Delayed Neural - Networks with back-propagation algorithm shows very accurate modeling performance. Based on this behavioral modeling, we conducted inverse compensation process which also uses Neural Networks.

• International Journal of Computer Science & Network Security
• /
• v.22 no.7
• /
• pp.240-244
• /
• 2022

The common goals of designing a routing algorithm are not only to reduce control packet overhead, maximize throughput and minimize the end-to-end delay, but also take into consideration the energy consumption. Scalability is an important factor in designing an efficient routing protocol for wireless sensor networks (WSN's). Three metrics (power consumption, time of transmission and packet loss rate) are used in order to compare three routing protocols which are AODV, DSDV and LEACH.

• International Journal of Computer Science & Network Security
• /
• v.22 no.10
• /
• pp.237-245
• /
• 2022

The prominence of IoTs (Internet of Things) and exponential advancement of computer networks has resulted in massive essential applications. Recognizing various cyber-attacks or anomalies in networks and establishing effective intrusion recognition systems are becoming increasingly vital to current security. MLTs (Machine Learning Techniques) can be developed for such data-driven intelligent recognition systems. Researchers have employed a TFDNNs (Tensor Flow Deep Neural Networks) and DCNNs (Deep Convolution Neural Networks) to recognize pirated software and malwares efficiently. However, tuning the amount of neurons in multiple layers with activation functions leads to learning error rates, degrading classifier's reliability. HTFDNNs ( Hybrid tensor flow DNNs) and MRNs (Modified Residual Networks) or Resnet CNNs were presented to recognize software piracy and malwares. This study proposes HTFDNNs to identify stolen software starting with plagiarized source codes. This work uses Tokens and weights for filtering noises while focusing on token's for identifying source code thefts. DLTs (Deep learning techniques) are then used to detect plagiarized sources. Data from Google Code Jam is used for finding software piracy. MRNs visualize colour images for identifying harms in networks using IoTs. Malware samples of Maling dataset is used for tests in this work.

• Journal of information and communication convergence engineering
• /
• v.8 no.5
• /
• pp.554-559
• /
• 2010

Recently, various in-vehicle networks have been developed respectively in order to accomplish their own purpose such as CAN and MOST. Various electronic devices for vehicle are controllable by the advent of networks attached to the vehicle. However, the networks also come with a variety of unique features in each network-specific communication which creates difficulty using and supporting the interoperable services among the networks. To solve this problem, each network needs a standard integration framework. In this paper, a framework is proposed and implemented. It consists of a standard protocol using XML to improve compatibility and portability. The framework makes each network interoperable by applying unique information and messages of the network in the XML standard document. The results obtained by implementation show that the framework supports the efficient communication of data between heterogeneous invehicle networks.

• Journal of Communications and Networks
• /
• v.12 no.2
• /
• pp.181-190
• /
• 2010

A multitude of overlay network designs for resilient routing, multicasting, quality of service, content distribution, storage, and object location have been proposed. Overlay networks offer several attractive features, including ease of deployment, flexibility, adaptivity, and an infrastructure for collaboration among hosts. In this paper, we explore cooperation among co-existing, possibly heterogeneous, overlay networks. We discuss a spectrum of cooperative forwarding and information sharing services, and investigate the associated scalability, heterogeneity, and security problems. Motivated by these services, we design Synergy, a utility-based overlay internetworking architecture that fosters overlay cooperation. Our architecture promotes fair peering relationships to achieve synergism. Results from Internet experiments with cooperative forwarding overlays indicate that our Synergy prototype improves delay, throughput, and loss performance, while maintaining the autonomy and heterogeneity of individual overlay networks.

• Journal of Information Processing Systems
• /
• v.7 no.1
• /
• pp.29-42
• /
• 2011

Wireless sensor networks are composed of a large number of sensor nodes with limited energy resources. One critical issue in wireless sensor networks is how to gather sensed information in an energy efficient way, since their energy is limited. The clustering algorithm is a technique used to reduce energy consumption. It can improve the scalability and lifetime of wireless sensor networks. In this paper, we introduce a clustering protocol with mode selection (CPMS) for wireless sensor networks. Our scheme improves the performance of BCDCP (Base Station Controlled Dynamic Clustering Protocol) and BIDRP (Base Station Initiated Dynamic Routing Protocol) routing protocol. In CPMS, the base station constructs clusters and makes the head node with the highest residual energy send data to the base station. Furthermore, we can save the energy of head nodes by using the modes selection method. The simulation results show that CPMS achieves longer lifetime and more data message transmissions than current important clustering protocols in wireless sensor networks.

• ETRI Journal
• /
• v.44 no.6
• /
• pp.977-990
• /
• 2022

This study proposes a novel method for identifying the primary conspirators involved in terrorist activities. To map the information related to terrorist activities, we gathered information from different sources of real cases involving terrorist attacks. We extracted useful information from available sources and then mapped them in the form of terrorist networks, and this mapping provided us with insights in these networks. Furthermore, we came up with a novel centrality measure for identifying the primary conspirators of a terrorist attack. Because the leaders of terrorist attacks usually direct conspirators to conduct terrorist activities, we designed a novel algorithm that can identify such leaders. This algorithm can identify terrorist attack leaders even if they have less connectivity in networks. We tested the effectiveness of the proposed algorithms on four real-world datasets and conducted an experimental evaluation, and the proposed algorithms could correctly identify the primary conspirators and leaders of the attacks in the four cases. To summarize, this work may provide information support for security agencies and can be helpful during the trials of the cases related to terrorist attacks.