• Journal of Internet Computing and Services
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• v.3 no.3
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• pp.67-74
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• 2002

Asynchronous transfer mode (ATM) can be efficiently used to transport packet data services. The switching system will support voice and packet data services simultaneously from end to end applications. To guarantee quality of service (QoS) of the offered services, source rate to send packet data is needed to control the network overload condition. Most existing control algorithms are shown to provide the threshold-based feedback control technique. However, real-time voice calls can be dynamically connected and released during data services in the network. If the feedback control information delays, quality of the serviced voice can be degraded due to a time delay between source and destination in the high speed link, An adaptive algorithm based on the optimal least mean square error technique is presented for the predictive feedback control technique. The algorithm attempts to predict a future buffer size from weight (slope) adaptation of unknown functions, which are used for feedback control. Simulation results are presented, which show the effectiveness of the algorithm.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.8 no.5
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• pp.429-437
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• 2015

DDoS attacks have been used for paralyzing popular Internet services. Especially, amplification attacks have grown dramatically in recent years. Defending against amplification attacks is challenging since the attacks usually generate extremely hugh amount of traffic and attack traffic is coming from legitimate servers, which is hard to differentiate from normal traffic. Moreover, some of protocols used by amplification attacks are widely adopted in IoT devices so that the number of servers susceptible to amplification attacks will continue to increase. This paper studies on the analysis of amplification attack mechanisms in detail and proposes defense methodologies for scenarios where attackers, abused servers or victims are in a monitoring network.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.93-111
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• 2013

As Internet and information technology (IT) continues to develop and evolve, the issue of big data has emerged at the foreground of scholarly and industrial attention. Big data is generally defined as data that exceed the range that can be collected, stored, managed and analyzed by existing conventional information systems and it also refers to the new technologies designed to effectively extract values from such data. With the widespread dissemination of IT systems, continual efforts have been made in various fields of industry such as R&D, manufacturing, and finance to collect and analyze immense quantities of data in order to extract meaningful information and to use this information to solve various problems. Since IT has converged with various industries in many aspects, digital data are now being generated at a remarkably accelerating rate while developments in state-of-the-art technology have led to continual enhancements in system performance. The types of big data that are currently receiving the most attention include information available within companies, such as information on consumer characteristics, information on purchase records, logistics information and log information indicating the usage of products and services by consumers, as well as information accumulated outside companies, such as information on the web search traffic of online users, social network information, and patent information. Among these various types of big data, web searches performed by online users constitute one of the most effective and important sources of information for marketing purposes because consumers search for information on the internet in order to make efficient and rational choices. Recently, Google has provided public access to its information on the web search traffic of online users through a service named Google Trends. Research that uses this web search traffic information to analyze the information search behavior of online users is now receiving much attention in academia and in fields of industry. Studies using web search traffic information can be broadly classified into two fields. The first field consists of empirical demonstrations that show how web search information can be used to forecast social phenomena, the purchasing power of consumers, the outcomes of political elections, etc. The other field focuses on using web search traffic information to observe consumer behavior, identifying the attributes of a product that consumers regard as important or tracking changes on consumers' expectations, for example, but relatively less research has been completed in this field. In particular, to the extent of our knowledge, hardly any studies related to brands have yet attempted to use web search traffic information to analyze the factors that influence consumers' purchasing activities. This study aims to demonstrate that consumers' web search traffic information can be used to derive the relations among brands and the relations between an individual brand and product attributes. When consumers input their search words on the web, they may use a single keyword for the search, but they also often input multiple keywords to seek related information (this is referred to as simultaneous searching). A consumer performs a simultaneous search either to simultaneously compare two product brands to obtain information on their similarities and differences, or to acquire more in-depth information about a specific attribute in a specific brand. Web search traffic information shows that the quantity of simultaneous searches using certain keywords increases when the relation is closer in the consumer's mind and it will be possible to derive the relations between each of the keywords by collecting this relational data and subjecting it to network analysis. Accordingly, this study proposes a method of analyzing how brands are positioned by consumers and what relationships exist between product attributes and an individual brand, using simultaneous search traffic information. It also presents case studies demonstrating the actual application of this method, with a focus on tablets, belonging to innovative product groups.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.41 no.4
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• pp.35-44
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• 2004

Recently announced TCP Vegas predicts the degree of congestion in the network and then control the congestion window size. Thus it shows better performance than TCP Reno. however, TCP vegas does not assume any network model, its congestion window control is very limited. Because or this limitation, TCP vegas still can not adapt to fast changing available bandwidth. In this paper, we introduce a new TCP algorithm which adapts to fast changing available bandwidth well. To devise such a TCP, we model the end to end network of TCP connection as a queueing system and finds congestion window size which can utilize the available bandwidth sufficiently but not make the network congested. The simulation results show that our algorithm adapts to the avaliable bandwidth faster than TCP vegas and as a results, when the available bandwidth is changing rapidly, our algorithm not only operates more stably than TCP Vegas, but also it shows higher thruput than TCP Vegas.

• Proceedings of the Korean Information Science Society Conference
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• 2003.04d
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• pp.76-78
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• 2003

최근 유ㆍ무선이 혼합된 이동 네트워크환경에서 시간과 장소에 구분 없이 인터넷에 접속하기를 원하는 모바일 사용자의 요구는 증가되고 있다. 사용자에게 효율적인 서비스를 제공하기에는 멀티캐스트 전송 기술이 적합하다. IETF Mobile IP에서는 모바일 호스트에 멀티캐스트를 지원하기 위해 HA 기반인 Bi-directional Tunneling과 FA 기반이 Remote Subscription 기법을 제시하였다. 그외 MoM, RBMOM 및 MobiCast 프로토콜 등의 연구들이 이동하는 모바일 호스트에게 멀티캐스트를 지원하는 기법을 제안하였으나, 멀티캐스트 트리 재구성 및 핸드오프 등의 문제점은 여전히 남아 있다. 본 논문에서는 BS의 beacon 신호로 모바일 호스트의 이동성을 예측하여 Smooth-Handoff를 지원하는 기법을 제안하였다. 또한 BS의 패킷 트래픽 측정을 통해 중복 수신되는 패킷을 방지하여 신뢰성 있는 멀티캐스트 전송 서비스를 지원하는 기법을 제안한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2000.04a
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• pp.340-345
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• 2000

본 논문에서는 대용량 통신처리시스템의 트래픽 처리 능력 예측을 위해 실제 네트워크 구축 상황과 서비스 상황을 모의로 만들어 줄 수 있는 테스터 소프트웨어 개발을 목적으로, 리눅스환경에서 Network Traffic Generator, Remote노드에 사용될 패킷 귀한 프로그램, Statistcal Analyzer, GTK+ 라이브러리를 이용한 GUI, Network Traffic Generator와 Statistical Analyzer를 하나의 프로그램 안에서 동시에 동작하도록 하는 Thread 사용 기법이 연구되었다. 이를 이용하여 대용량 통신 처리시스템의 성능 규격의 정확한 확인을 통해 가용 가능한 가입자 노드의 용량을 결정할 수 있으며, 상용현장시험이 가능하고 또한 설치 규격을 제공할 수 있다.

• Proceedings of the Korea Information Processing Society Conference
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• 2012.04a
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• pp.540-543
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• 2012

최근에 녹색 IT의 일환으로 IT 장비에서 소비하는 에너지 크기를 감소시킴으로써 발생하는 탄소발생률을 줄이고, 장비 운용 비용을 낮추는 연구가 각광을 받고 있다. 그에 따라 본 논문에서는 차세대 통신망의 강력한 후보로 예상되는 광 버스트 스위칭 망에서 에너지 절감 기법 중 하나인 저 전력대기 방식을 사용할 때 발생하는 에너지 소비량에 대한 수식 모델을 제안한다. 제안된 수식 모델에서는 입력되는 트래픽 패턴을 고려하여 가져갈 수 있는 상태천이확률을 구하고 이에 따른 에너지 소비량을 예측해 볼 수 있다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.42 no.1
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• pp.128-139
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• 2017

Vehicular Ad hoc Network (VANET) is one of technologies to realize various ITS services for safe driving and efficient traffic control. However, data delivery in VANETs is complicated due to high mobility and unreliable wireless transmission. In this paper, we develop a novel forwarding scheme to deliver packets in a reliable and timely manner. The proposed forwarding scheme uses traffic statistics to predict the encounter of two vehicles, and optimize its forwarding decision by taking into consideration the probability of successful transmission between them at the encounter place. We evaluate our scheme through simulations and show that our proposed scheme provides reliable data delivery in VANETs.

• The Transactions of the Korea Information Processing Society
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• v.3 no.4
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• pp.697-708
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• 1996

In this paper, we study reactive congestion control with priority in ATM network. The priority schemes for buffer access, partial buffer sharing have been investigated in order to improve the utilization of ATM network resources the network and to satisfy the most demanding traffic class. We consider in this paper a discrete-time queueing model for partial buffer sharing with two Markov modulated Poisson inputs. This model can be used to analyze the the effects of the partial buffer sharing priority scheme on system performance for realistic cases of bursty services. Explicit formulae are derived for the number of cells in the system and the loss probabilities for the traffic. Congestion may still occur because of unpredictable statistical fluctuation of traffic sources even when preventive control is performed in the network. In this Paper, we study reactive congestion control, in which each source changes its cell emitting rate a daptively to the traffic load at the switching node. Our intention is that,by incorporating such a congcstion control method in ATM network,more efficient congsestion control is established. We develope an analytical model,and carry out an approximateanalysis of reactive congestion con-trol with priority.Numerical results show that several orders of magnitude improvement in the loss probability can be achieved for the high priority class with little impact on the low priority class performance.And the results show that the reactive congestion control with priority are very effective in avoiding congestion and in achieving the statistical gain.

• Journal of Advanced Navigation Technology
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• v.18 no.5
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• pp.461-467
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• 2014

Active queue management (AQM) algorithms run on routers and detect incipient congestion by typically monitoring the instantaneous or average queue size. When the average queue size exceeds a certain threshold, AQM algorithms infer congestion on the link and notify the end systems to back off by proactively dropping some of the packets arriving at a router or marking the packets to reduce transmission rate at the sender. Among the existing AQM algorithms, random early detection (RED) is well known as the representative queue-based management scheme by randomizing packet dropping. To reduce the number of timeouts in TCP and queuing delay, maintain high link utilization, and remove bursty traffic biases, the RED considers an average queue size as a degree of congestions. However, RED do not well in the specified networks conditions due to the fixed parameters($P_{max}$ and $TH_{min}$) of RED. This paper addresses a extended RED to be adapted in various networks conditions. By sensing network state, $P_{max}$ and $TH_{min}$ can be automatically changed to proper value and then RED do well in various networks conditions.