• The KIPS Transactions:PartC
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• 제18C권4호
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• pp.243-250
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• 2011

Nowadays, the traffic type and behavior are extremely diverse due to the appearance of various services on Internet, which makes the need of traffic identification important for efficient operation and management of network. In recent years traffic identification methodology using statistical features of flow has been broadly studied. We also proposed a traffic identification methodology using payload size distribution in our previous work, which has a problem of low completeness. In this paper, we improved the completeness by solving the PSD conflict using IP and port. And we improved the accuracy by changing the distance measurement between flow and statistic signature from vector distance to per-packet distance. The feasibility of our methodology was proved via experimental evaluation on our campus network.

• Journal of the Korean Operations Research and Management Science Society
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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.

• The Journal of Korean Institute of Communications and Information Sciences
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• 제38B권5호
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• pp.368-376
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• 2013

The importance of application traffic identification is emphasized for the efficient network management with recent rapid development of internet. In this paper, we present the application traffic identification method using the behavior based signature to improve the previous limitations. The behavior based signature is made by combining the existing various traffic features, and uses the Inter-Flow unit that is combination of the first request packet of each flow. All signatures have 100% precision when measured the accuracy of 5 applications using at home and abroad to prove the feasibility of the proposed signature.

• 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.

• The Korean Journal of Applied Statistics
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• 제23권6호
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• pp.1179-1190
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• 2010

Management of the existing traffic network and understanding current traffic conditions is the most important and effective way to solve traffic congestion. This research investigates the status of Korea expressway through the Speed-Flow-Density diagram and finds the best suitable queueing model for each area. Dynamic structure in the queueing model enables us to reflect the structural change of the road in case of traffic congestion. To find the best model and estimate the parameters, we use the Newton-Raphson method. Finally, we examine the road efficiency in view of the optimal speed and density using the conditional distribution of speed and density of a S-F-D diagram.

• Journal of Internet Computing and Services
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• 제13권2호
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• pp.33-40
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• 2012

Recently, according to increasing the network traffic in the IMS, the role of Network Management System (NMS) is very important because of limited network resource. NMS can perform two kinds of routing ways with the capability of static or dynamic routing. The way of A dynamic routing is more efficient than static routing one because it can make the flow of traffic changeful among nodes in the IMS. Therefore, in this paper, we suggest a management function of NMS, using a dynamic routing algorithm for managing the CSCFs in the IMS. And then we analyze the algorithm by measuring the performance of PoC, one of the prominent application services to be deployed in the IMS.

• 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.

• Journal of the Korean Operations Research and Management Science Society
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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.

• Proceedings of the Korean Operations and Management Science Society Conference
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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.

• 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.