• Journal of the Institute of Electronics Engineers of Korea TC
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• v.39 no.6
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• pp.277-284
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• 2002

In this paper the authors explore the effect of bandwidth sharing to the utility of the customer for the best-effort Internet services and draw a basis for the pricing principle in Internet Protocol networks. Especially, we investigate the behavior of a customer's utility in case an arbitrary amount of additional bandwidth is allowed to each customer for the elastic traffic, which is the typical example of the non-real time Internet data traffic. After drawing the utility curve, which will be proved to follow the concave curve, we will apply it to the pricing of Internet traffic. Finally, via numerical experiments, we will illustrate the validity and implication of the proposed method.

• Proceedings of the IEEK Conference
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• 2000.11a
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• pp.41-44
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• 2000

Because of internet's growth, today's network has a serious bandwidth problem. WDM(Wavelength Division Multiplexing) is a solution of this problem. In the WDM networks, QoS(Quality of Service) is as important as bandwidth. And today's voice over IP technology makes a lot of delay-sensitive internet traffic. De]ay-sensitive internet traffic is growing up, so more QoS is needed. We proposed effective solution to assign QoS.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.11
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• pp.4246-4267
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• 2020

As the network goes deep into all aspects of people's lives, the number and the complexity of network traffic is increasing, and traffic classification becomes more and more important. How to classify them effectively is an important prerequisite for network management and planning, and ensuring network security. With the continuous development of deep learning, more and more traffic classification begins to use it as the main method, which achieves better results than traditional classification methods. In this paper, we provide a comprehensive review of network traffic classification based on deep learning. Firstly, we introduce the research background and progress of network traffic classification. Then, we summarize and compare traffic classification based on deep learning such as stack autoencoder, one-dimensional convolution neural network, two-dimensional convolution neural network, three-dimensional convolution neural network, long short-term memory network and Deep Belief Networks. In addition, we compare traffic classification based on deep learning with other methods such as based on port number, deep packets detection and machine learning. Finally, the future research directions of network traffic classification based on deep learning are prospected.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.5
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• pp.995-1003
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• 2004

A number of Internet application services are used with the development of Internet backbone nowadays. Well-known services such as WWW, ]n, email are provided at first time. Tremendous unwell-known services are presented according to the demands of various contents. After analyzing PDU information of the packet using unwell-known port travelling on the internet, searching internet service type and its statistical data is provided with internet traffic analyst as very useful information. This paper presents the mechanism to extract the internet application services operated on (un)well-known port of UDP or TCP used occasionally through netflow and tcpdump method introduced by ethereal and the operation scheme of the service. Afterwards to get the detailed statistics of the analyzed application service, the agent and the server environment, the agent gathering raw data traffics and the server adapting the traffic received from the agent BNF(Backus-Naur Form) method, is also introduced. Adapting the presented mechanism eve. LAN of Andong national university, the internet traffic service type and the detailed statistics of the analyzed application services which provides with internet traffic analyst are presented as very useful information.

• International Journal of Internet, Broadcasting and Communication
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• v.8 no.1
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• pp.53-63
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• 2016

This paper applies WiMedia UWB network into a wireless ship area network (WSAN) so as to support high-quality multimedia services on board and reliable instrument control information as well, since the need for mixed high-quality video traffic and shipboard control data traffic is essential for a high-cost valued digital ship. Thus, in this paper, prioritized contention access (PCA) and distributed reservation protocol (DRP) based on WiMedia UWB (ECMA-368) MAC protocols are combined and proposed to such mixed traffic environment, by varying the portions of superframe according to traffic type. It is shown that the proposed WiMedia UWB MAC protocol can provide reliable mixed video and shipboard control data traffic as well.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.11
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• pp.3584-3602
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• 2022

NFV realizes flexible and rapid software deployment and management of network functions in the cloud network, and provides network services in the form of chained virtual network functions (VNFs). However, using VNFs to provide quality guaranteed services is still a challenge because of the inherent difficulty in intelligently scaling VNFs to handle traffic fluctuations. Most existing works scale VNFs with fixed-capacity instances, that is they take instances of the same size and determine a suitable deployment location without considering the cloud network resource distribution. This paper proposes a traffic forecasted assisted proactive VNF scaling approach, and it adopts the instance capacity adaptive to the node resource. We first model the VNF scaling as integer quadratic programming and then propose a proactive adaptive VNF scaling (PAVS) approach. The approach employs an efficient traffic forecasting method based on LSTM to predict the upcoming traffic demands. With the obtained traffic demands, we design a resource-aware new VNF instance deployment algorithm to scale out under-provisioning VNFs and a redundant VNF instance management mechanism to scale in over-provisioning VNFs. Trace-driven simulation demonstrates that our proposed approach can respond to traffic fluctuation in advance and reduce the total cost significantly.

• IE interfaces
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• v.15 no.2
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• pp.152-158
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• 2002

The explosive growth of the internet traffic in the last few years has imposed tremendous stress on today's routers, particularly in the core network. Recently, ATM LSRs(Label Switching Router) are potentially capable of providing the highest forwarding capacity in the backbone Internet network. VC merging is a mechanism in an ATM LSR that allows many IP routes to be mapped to the same VC label, and provides a scalable mapping method that can support thousands of destinations. VC merging requires reassembly buffers so that cells belonging to different packets intended for the same destination do not interleave with each other. In this study, we propose an architecture of the ATM LSR which supports VC merging. We propose traffic control scheme called APD(Active Packet Discard) algorithm so that predicts and controls the congestion of the Internet traffic effectively. We study the performance of this algorithm using simulation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.4 no.4
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• pp.671-690
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• 2010

The continuous growth of attacks in the Internet causes to generate a number of rules in security devices such as Intrusion Prevention Systems, firewalls, etc. Policy anomalies in security devices create security holes and prevent the system from determining quickly whether allow or deny a packet. Policy anomalies exist among the rules in multiple security devices as well as in a single security device. The solution for policy anomalies requires complex and complicated algorithms. In this paper, we propose a new method to remove policy anomalies in a single security device and avoid policy anomalies among the rules in distributed security devices. The proposed method classifies rules according to traffic direction and checks policy anomalies in each device. It is unnecessary to compare the rules for outgoing traffic with the rules for incoming traffic. Therefore, classifying rules by in-out traffic, the proposed method can reduce the number of rules to be compared up to a half. Instead of detecting policy anomalies in distributed security devices, one adopts the rules from others for avoiding anomaly. After removing policy anomalies in each device, other firewalls can keep the policy consistency without anomalies by adopting the rules of a trusted firewall. In addition, it blocks unnecessary traffic because a source side sends as much traffic as the destination side accepts. Also we explain another policy anomaly which can be found under a connection-oriented communication protocol.

• Journal of Communications and Networks
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• v.18 no.4
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• pp.559-566
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• 2016

Software defined network (SDN) can effectively improve the performance of traffic engineering and will be widely used in backbone networks. Therefore, new energy-saving schemes must take SDN into consideration; this action is extremely important owing to the rapidly increasing energy consumption in telecom and Internet service provider (ISP) networks. Meanwhile, the introduction of SDN in current networks must be incremental in most cases, for technical and economic reasons. During this period, operators must manage hybrid networks in which SDN and traditional protocols coexist. In this study, we investigate the energy-efficient traffic engineering problem in hybrid SDN/Internet protocol (IP) networks. First, we formulate the mathematical optimization model considering the SDN/IP hybrid routing mode. The problem is NP-hard; therefore, we propose a fast heuristic algorithm named hybrid energy-aware traffic engineering (HEATE) as a solution. In our proposed HEATE algorithm, the IP routers perform shortest-path routing by using distributed open shortest path first (OSPF) link weight optimization. The SDNs perform multipath routing with traffic-flow splitting managed by the global SDN controller. The HEATE algorithm determines the optimal setting for the OSPF link weight and the splitting ratio of SDNs. Thus, the traffic flow is aggregated onto partial links, and the underutilized links can be turned off to save energy. Based on computer simulation results, we demonstrate that our algorithm achieves a significant improvement in energy efficiency in hybrid SDN/IP networks.

• International Journal of Computer Science & Network Security
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• v.21 no.8
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• pp.28-34
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• 2021

Internet Service Providers (ISPs) constantly endeavor to resolve network congestion, in order to provide fast and cheap services to the customers. This study suggests two models based on Markov chain, using three and four access attempts to complete the call. It involves a comparative study of four models to check the relationship between Internet Access sharing traffic, and the possibility of network jamming. The first model is a Markov chain, based on call-by-call attempt, whereas the second is based on two attempts. Models III&IV suggested by the authors are based on the assumption of three and four attempts. The assessment reveals that sometimes by increasing the number of attempts for the same operator, the chances for the customers to complete the call, is also increased due to blocking probabilities. Three and four attempts express the actual relationship between traffic sharing and blocking probability based on Markov using MATLAB tools with initial probability values. The study reflects shouting results compared to I&II models using one and two attempts. The success ratio of the first model is 84.5%, and that of the second is 90.6% to complete the call, whereas models using three and four attempts have 94.95% and 95.12% respectively to complete the call.