• 제목/요약/키워드: Network Traffic Flow Management

검색결과 112건 처리시간 0.022초

통계 시그니쳐 기반 트래픽 분석 시스템의 성능 향상 (Performance Improvement of the Statistic Signature based Traffic Identification System)

  • 박진완;김명섭
    • 정보처리학회논문지C
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    • 제18C권4호
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    • pp.243-250
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    • 2011
  • 네트워크의 고속화와 다양한 서비스의 등장으로 오늘날의 네트워크 트래픽은 복잡 다양해지고 있다. 효율적인 네트워크 관리를 위해서는 네트워크에서 발생하는 트래픽에 대한 다양한 분석이 필요하다. QoS, SLA와 같은 정책을 적용하기 위해서는 트래픽 분석 중에서도 트래픽 분류의 중요성이 크다. 현재까지 트래픽 분류에 관한 연구가 활발히 진행되어 왔는데 최근에는 플로우의 통계 정보를 이용한 트래픽 분류 방법론이 많이 연구되고 있다. 본 논문에서는 기존 연구에서 제안한 페이로드 크기 분포를 이용한 트래픽 분류 방법의 문제점인 낮은 분석률 및 정확도를 향상시키는 방법을 제안한다. 본 논문에서 제안하는 방법은 PSD 충돌로 인해 분류하지 못하는 트래픽을 IP와 port정보를 이용하여 추가적으로 분류하여 분석률을 향상시키고 기존 분류 방법에서 트래픽 분류를 위해 사용되던 플로우와 시그니쳐 사이의 거리 측정 방법을 벡터 거리 측정에서 패킷 별 거리 측정으로의 변경으로 통해 분류 방법의 정확도를 향상시킨다. 제안한 방법은 학내 망에서의 실험을 통해 기존 알고리즘에 비해 향상된 알고리즘의 성능을 검증한다.

ATM 망의 가상경로 루팅 최적화 (Virtual Path Routing Optimization in ATM Network)

  • 박구현
    • 한국경영과학회지
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    • 제20권1호
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    • pp.35-54
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    • 1995
  • Routing in ATM network is set up by combination of both virtual path routing and virtual channel routing. While virtual channel is similar concept to virtual circuit of data networks, virtual path is a special concept which is not used in traditional data networks. Virtual path can rearrange in structure and size by simply changing virtual path routing tables and giving the network the capability to eash allocate network resources according to the demand needs. This paper provides reconfiguration models of virtual path network which give the bandwidth of link and the routing path for each traffic class. The reconfiguration models are network optimization problems of multicommodity network flow type. The numerical examples are also included.

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인터넷 응용 트래픽 분석을 위한 행위기반 시그니쳐 추출 방법 (Behavior Based Signature Extraction Method for Internet Application Traffic Identification)

  • 윤성호;김명섭
    • 한국통신학회논문지
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    • 제38B권5호
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    • pp.368-376
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    • 2013
  • 최근 급격한 인터넷의 발전으로 효율적인 네트워크관리를 위해 응용 트래픽 분석의 중요성이 강조되고 있다. 본 논문에서는 기존 분석 방법의 한계점을 보완하기 위하여 행위기반 시그니쳐를 이용한 응용 트래픽 분석 방법을 제안한다. 행위기반 시그니쳐는 기존에 제안된 다양한 트래픽 특징을 조합하여 사용할 뿐만 아니라, 복수 개 플로우들의 첫 질의 패킷을 분석 단위로 사용한다. 제안한 행위기반 시그니쳐의 타당성을 검증하기 위해 국내외 응용 5종을 대상으로 정확도를 측정결과, 모든 응용에서 100% Precision을 나타내었다.

Integrating Granger Causality and Vector Auto-Regression for Traffic Prediction of Large-Scale WLANs

  • Lu, Zheng;Zhou, Chen;Wu, Jing;Jiang, Hao;Cui, Songyue
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제10권1호
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    • pp.136-151
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    • 2016
  • Flexible large-scale WLANs are now widely deployed in crowded and highly mobile places such as campus, airport, shopping mall and company etc. But network management is hard for large-scale WLANs due to highly uneven interference and throughput among links. So the traffic is difficult to predict accurately. In the paper, through analysis of traffic in two real large-scale WLANs, Granger Causality is found in both scenarios. In combination with information entropy, it shows that the traffic prediction of target AP considering Granger Causality can be more predictable than that utilizing target AP alone, or that of considering irrelevant APs. So We develops new method -Granger Causality and Vector Auto-Regression (GCVAR), which takes APs series sharing Granger Causality based on Vector Auto-regression (VAR) into account, to predict the traffic flow in two real scenarios, thus redundant and noise introduced by multivariate time series could be removed. Experiments show that GCVAR is much more effective compared to that of traditional univariate time series (e.g. ARIMA, WARIMA). In particular, GCVAR consumes two orders of magnitude less than that caused by ARIMA/WARIMA.

동적구조를 갖는 대기행렬 모형: Speed-Flow-Density 다이어그램을 중심으로 (A Study on the Queueing Process with Dynamic Structure for Speed-Flow-Density Diagram)

  • 박유성;전새봄
    • 응용통계연구
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    • 제23권6호
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    • pp.1179-1190
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    • 2010
  • 교통 혼잡을 해결하기 위해, 도로 교통망의 흐름을 정확히 파악하고 이를 효율적으로 관리하는 것은 가장 중요하면서도 효율적인 방안이다. 일반적으로 교통 흐름에 대한 연구로 대기행렬 모형이 이용된다. 특히, 속도, 통행량, 교통밀도에 대한 S-F-D(Speed-Flow-Density) 다이어그램은 도로의 현황을 파악하는데 매우 유용한 도구이다. 그러나 우리나라의 경우, 이러한 교통 속성들 간에 구조적인 변화를 볼 수 있었다. 이에 따라 본 연구에서는 대기 행렬 모형내에 구조변화를 포함함으로써 정체 시 도로 상황이 구조적으로 변화하는 현상을 모형에 반영하여, 국내 고속도로의 현황을 보다 잘 파악할 수 있는 새로운 S-F-D 다이어그램을 제안한다. 각 구간에 대한 최적의 대기행렬 모형을 찾기 위해 뉴튼-랩슨 방법으로 최적화 모수를 추정하고, 이를 바탕으로 최적속도와 밀도를 산출하여 요일별 시간별 도로의 이용현황 및 효율성을 파악하고자 한다.

CSCF 노드 관리를 이용한 응용 서비스 구현 (The Implementation of Application Services Using CSCFs of Management)

  • 이재오;조재형
    • 인터넷정보학회논문지
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    • 제13권2호
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    • pp.33-40
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    • 2012
  • 최근 네트워크간의 통합으로 인하여 네트워크 통합 관리 시스템 중 하나인 IMS (IP Multimedia Subsystem)의 사용이 증가하고, 이로 인해 네트워크 트래픽이 증가하고 있다. 따라서 IMS에서의 자원을 효율적으로 관리하기 위하여 네크워크 관리 시스템의 기능이 점차 커지고 있다. 특히 IMS 노드에 트래픽은 유동적이기 때문에 이것을 효과적으로 관리하기 위해서는 적절한 동적 라우팅 구조가 필요하다. 따라서 본 논문에서는 IMS 노드간의 트래픽을 제어하기위한 동적 알고리즘 구조를 제안하고, IMS의 대표적인 응용서비스인 Presence Service와 PoC (Push to talk over Cellular)를 이용하여 본 알고리즘의 성능을 측정한다.

Big Data Based Dynamic Flow Aggregation over 5G Network Slicing

  • Sun, Guolin;Mareri, Bruce;Liu, Guisong;Fang, Xiufen;Jiang, Wei
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제11권10호
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    • pp.4717-4737
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    • 2017
  • Today, smart grids, smart homes, smart water networks, and intelligent transportation, are infrastructure systems that connect our world more than we ever thought possible and are associated with a single concept, the Internet of Things (IoT). The number of devices connected to the IoT and hence the number of traffic flow increases continuously, as well as the emergence of new applications. Although cutting-edge hardware technology can be employed to achieve a fast implementation to handle this huge data streams, there will always be a limit on size of traffic supported by a given architecture. However, recent cloud-based big data technologies fortunately offer an ideal environment to handle this issue. Moreover, the ever-increasing high volume of traffic created on demand presents great challenges for flow management. As a solution, flow aggregation decreases the number of flows needed to be processed by the network. The previous works in the literature prove that most of aggregation strategies designed for smart grids aim at optimizing system operation performance. They consider a common identifier to aggregate traffic on each device, having its independent static aggregation policy. In this paper, we propose a dynamic approach to aggregate flows based on traffic characteristics and device preferences. Our algorithm runs on a big data platform to provide an end-to-end network visibility of flows, which performs high-speed and high-volume computations to identify the clusters of similar flows and aggregate massive number of mice flows into a few meta-flows. Compared with existing solutions, our approach dynamically aggregates large number of such small flows into fewer flows, based on traffic characteristics and access node preferences. Using this approach, we alleviate the problem of processing a large amount of micro flows, and also significantly improve the accuracy of meeting the access node QoS demands. We conducted experiments, using a dataset of up to 100,000 flows, and studied the performance of our algorithm analytically. The experimental results are presented to show the promising effectiveness and scalability of our proposed approach.

마코프 재생과정을 이용한 ATM 트랙픽 모델링 및 성능분석 (ATM Traffic Modeling with Markov Renewal Process and Performance Analysis)

  • 정석윤;허선
    • 한국경영과학회지
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    • 제24권3호
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    • pp.83-91
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    • 1999
  • In order to build and manage an ATM network effectively under several types of control methods, it is necessary to estimate the performance of the equipments in various viewpoints, especially of ATM multiplexer. As for the method to model the input stream into the ATM multiplexer, many researches have been done to characterize it by, such as, fluid flow, MMPP(Markov Modulated Poisson Process), or MMDP (Markov Modulated Deterministic Process). We introduce an MRP(Markov Renewal Process) to model the input stream which has proper structure to represent the burst traffic with high correlation. In this paper, we build a model for aggregated heterogeneous ON-OFF sources of ATM traffic by MRP. We make discrete time MR/D/1/B queueing system, whose input process is the superposed MRP and present a performance analysis by finding CLP(Cell Loss Probability). A simulation is done to validate our algorithm.

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신경망, 시계열 분석 및 판단보정 기법을 이용한 교통량 예측 (Traffic-Flow Forecasting using ARIMA, Neural Network and Judgment Adjustment)

  • 장석철;석상문;이주상;이상욱;안병하
    • 한국경영과학회:학술대회논문집
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    • 한국경영과학회/대한산업공학회 2005년도 춘계공동학술대회 발표논문
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    • pp.795-797
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    • 2005
  • During the past few years, various traffic-flow forecasting models, i.e. an ARIMA, an ANN, and so on, have been developed to predict more accurate traffic flow. However, these models analyze historical data in an attempt to predict future value of a variable of interest. They make use of the following basic strategy. Past data are analyzed in order to identify a pattern that can be used to describe them. Then this pattern is extrapolated, or extended, into the future in order to make forecasts. This strategy rests on the assumption that the pattern that has been identified will continue into the future. So ARIMA or ANN models with its traditional architecture cannot be expected to give good predictions unless this assumption is valid; The statistical models in particular, the time series models are deficient in the sense that they merely extrapolate past patterns in the data without reflecting the expected irregular and infrequent future events Also forecasting power of a single model is limited to its accurate. In this paper, we compared with an ANN model and ARIMA model and tried to combine an ARIMA model and ANN model for obtaining a better forecasting performance. In addition to combining two models, we also introduced judgmental adjustment technique. Our approach can improve the forecasting power in traffic flow. To validate our model, we have compared the performance with other models. Finally we prove that the proposed model, i.e. ARIMA + ANN + Judgmental Adjustment, is superior to the other model.

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The development of a ship's network monitoring system using SNMP based on standard IEC 61162-460

  • Wu, Zu-Xin;Rind, Sobia;Yu, Yung-Ho;Cho, Seok-Je
    • Journal of Advanced Marine Engineering and Technology
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    • 제40권10호
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    • pp.906-915
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    • 2016
  • In this study, a network monitoring system, including a secure 460-Network and a 460-Gateway, is designed and developed according with the requirements of the IEC (International Electro-Technical Commission) 61162-460 network standard for the safety and security of networks on board ships. At present, internal or external unauthorized access to or malicious attack on a ship's on board systems are possible threats to the safe operation of a ship's network. To secure the ship's network, a 460-Network was designed and implemented by using a 460-Switch, 460-Nodes, and a 460-Gateway that contains firewalls and a DMZ (Demilitarized Zone) with various application servers. In addition, a 460-firewall was used to block all traffic from unauthorized networks. 460-NMS (Network Monitoring System) is a network-monitoring software application that was developed by using an simple network management protocol (SNMP) SharpNet library with the .Net 4.5 framework and a backhand SQLite database management system, which is used to manage network information. 460-NMS receives network information from a 460-Switch by utilizing SNMP, SNMP Trap, and Syslog. 460-NMS monitors the 460-Network load, traffic flow, current network status, network failure, and unknown devices connected to the network. It notifies the network administrator via alarms, notifications, or warnings in case any network problem occurs. Once developed, 460-NMS was tested both in a laboratory environment and for a real ship network that had been installed by the manufacturer and was confirmed to comply with the IEC 61162-460 requirements. Network safety and security issues onboard ships could be solved by designing a secure 460-Network along with a 460-Gateway and by constantly monitoring the 460-Network according to the requirements of the IEC 61162-460 network standard.