• Journal of Communications and Networks
• /
• v.12 no.6
• /
• pp.624-631
• /
• 2010

Effective traffic matrix estimation is the basis of efficient traffic engineering, and therefore, quality of service provision support in IP networks. In this study, traffic matrix estimation is investigated in IP networks and an Elman neural network-based traffic matrix inference (ENNTMI) method is proposed. In ENNTMI, the conventional Elman neural network is modified to capture the spatio-temporal correlations and the time-varying property, and certain side information is introduced to help estimate traffic matrix in a network accurately. The regular parameter is further introduced into the optimal equation. Thus, the highly ill-posed nature of traffic matrix estimation is overcome effectively and efficiently.

• Journal of Korea Multimedia Society
• /
• v.21 no.11
• /
• pp.1244-1253
• /
• 2018

The color of traffic light is sensitive to various illumination conditions. Especially it loses the hue information when oversaturation happens on the lighting area. This paper proposes a traffic light recognition method robust to these illumination variations. The method consists of two steps of traffic light detection and recognition. It just uses the intensity and saturation in the first step of traffic light detection. It delays the use of hue information until it reaches to the second step of recognizing the signal of traffic light. We utilized a deep learning technique in the second step. We designed a deep convolutional neural network(DCNN) which is composed of three convolutional networks and two fully connected networks. 12 video clips were used to evaluate the performance of the proposed method. Experimental results show the performance of traffic light detection reporting the precision of 93.9%, the recall of 91.6%, and the recognition accuracy of 89.4%. Considering that the maximum distance between the camera and traffic lights is 70m, the results shows that the proposed method is effective.

• Journal of Korea Society of Industrial Information Systems
• /
• v.17 no.1
• /
• pp.31-38
• /
• 2012

Next generation cellular applications and smart phone usage generate very heavy wireless data traffic. It becomes ineluctable for mobile network operators to have multiple core network entities such as Serving Gateway and Packet Data Network Gateway in 4G-LTE to share this high traffic generated. A typical configuration consists of multiple serving gateways behind a load-balancer which would determine which serving gateway would service a end-users'request. Such hardware is expensive, has a rigid policy set, and is a single point of failure. Another perspective of today's increasingly high data traffic is that besides it is being widely accepted that the high bandwidth L TE provides is creating bottlenecks for service providers by the increasing user bandwidth demands without creating any corresponding revenue improvements, a hidden problem that is also passively advancing on the newly emerging 4G-LTE that may need more immediate attention is the network signaling traffic, also known as the control-plane traffic that is generated by the applications developed for smartphones and tablets. With this as starting point, in this paper, we propose a solution, by a new approach considering OpenFlow switch connected to a controller, which gains flexibility in policy, costs less, and has the potential to be more robust to failure with future generations of switches. This also solves the problem of scaling the control-plane traffic that is imperative to preserve revenue and ensure customer satisfaction. Thus, with the proposed architecture with OpenFlow, mobile network operators could manipulate the traffic generated by the control-plane signaling separated from the data-plane, besides also reducing the cost in installing multiple core-network entities.

• Journal of Institute of Control, Robotics and Systems
• /
• v.18 no.8
• /
• pp.719-724
• /
• 2012

A traffic detection system is a device that collects traffic information around an intersection. Most existing traffic detection systems provide very limited traffic information for signal control due to the restriction of vehicle detection area. A signal control scheme determines the transition among signal phases and the time that a phase lasts for. However, the existing signal control scheme do not resolve the traffic congestion effectively since they use restricted traffic information. In this paper, a new traffic detection system with a zone division signal control scheme is proposed to provide correct and detail traffic information and decrease the vehicle's waiting time at the intersection. The traffic detection system obtains traffic information in a way of vehicle-to-roadside communication between vehicles and sensor network. A new signal control scheme is built to exploit the sufficient traffic information provided by the proposed traffic detection system efficiently. Simulation results show that the proposed signal control scheme has 121 % and 56 % lower waiting time and delay time of vehicles at an intersection than other fuzzy signal control scheme.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.8 no.4
• /
• pp.1307-1323
• /
• 2014

With the exhaustion of global IPv4 addresses, IPv6 technologies have attracted increasing attentions, and have been deployed widely. Meanwhile, new applications running over IPv6 networks will change the traditional traffic characteristics obtained from IPv4 networks. Traditional models obtained from IPv4 cannot be used for IPv6 network monitoring directly and there is a need to investigate those changes. In this paper, we explore the flow features of IPv6 traffic and compare its difference with that of IPv4 traffic from flow level. Firstly, we analyze the differences of the general flow statistical characteristics and users' behavior between IPv4 and IPv6 networks. We find that there are more elephant flows in IPv6, which is critical for traffic engineering. Secondly, we find that there exist many one-way flows both in the IPv4 and IPv6 traffic, which are important information sources for abnormal behavior detection. Finally, in light of the challenges of analyzing massive data of large-scale network monitoring, we propose a group flow model which can greatly reduce the number of flows while capturing the primary traffic features, and perform a comparative measurement analysis of group users' behavior dynamic characteristics. We find there are less sharp changes caused by abnormity compared with IPv4, which shows there are less large-scale malicious activities in IPv6 currently. All the evaluation experiments are carried out based on the traffic traces collected from the Northwest Regional Center of CERNET (China Education and Research Network), and the results reveal the detailed flow characteristics of IPv6, which are useful for traffic management and anomaly detection in IPv6.

• Journal of Communications and Networks
• /
• v.14 no.3
• /
• pp.310-318
• /
• 2012

Detecting intrusion attacks accurately and rapidly in wireless networks is one of the most challenging security problems. Intrusion attacks of various types can be detected by the change in traffic flow that they induce. Wireless industrial networks based on the wireless networks for industrial automation-process automation (WIA-PA) standard use a superframe to schedule network communications. We propose an intrusion detection system for WIA-PA networks. After modeling and analyzing traffic flow data by time-sequence techniques, we propose a data traffic prediction model based on autoregressive moving average (ARMA) using the time series data. The model can quickly and precisely predict network traffic. We initialized the model with data traffic measurements taken by a 16-channel analyzer. Test results show that our scheme can effectively detect intrusion attacks, improve the overall network performance, and prolong the network lifetime.

• Proceedings of the KOR-KST Conference
• /
• 2000.02a
• /
• pp.89-115
• /
• 2000

Traffic signal setting policies and traffic assignment procedures are mutually dependent. The combined signal control and traffic assignment problem deals with this interaction. With the total travel time minimization objective, gradient based local search methods are implemented. Deterministic user equilibrium is the selected user route choice rule, Webster's delay curve is the link performance function, and green time per cycle ratios are decision variables. Three implemented solution codes resulting in six variations include intersections operating under multiphase operation with overlapping traffic movements. For reference, the iterative approach is also coded and all codes are tested in four example networks at five demand levels. The results show the numerical gradient estimation procedure performs best although the simplified local searches show reducing the large network computational burden. Demand level as well as network size affects the relative performance of the local and iterative approaches. As demand level becomes higher, (1) in the small network, the local search tends to outperform the iterative search and (2) in the large network, vice versa.

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.5 no.3
• /
• pp.107-115
• /
• 2009

Traditionally, simulation method is used to test and evaluate the performance of communication protocol or functional elements for mobile communication service. In this paper, wireless network simulator is implemented using the C++ object-oriented programming language. This simulator can simulate wireless data services, like as ad-hoc networks, by considering the user's mobility. In this paper, the simulator includes network traffic model to reflect wireless data service and traffic source model to represent a user's mobility similar to real service environment and traffic characteristics can be reflected on the simulation, and also more accurate simulation results can be got through that. In addition, by using object-oriented techniques, new service feature or environment can be easily added or changed so that the developed mobile communication simulator can reflect the real service environment all the time. This simulator can be used in adjusting the characteristics of wireless data hosts following the mobility of the user, and also can be used in building new wireless ad-hoc network routing protocols.

• The Korean Journal of Applied Statistics
• /
• v.20 no.2
• /
• pp.219-227
• /
• 2007

The time series models have been used to analyze and predict the network traffic. In this paper, we compare the performance of the time series models for prediction of network traffic. The feasibility study showed that a class of nonlinear time series models can be outperformed than the linear time series models to predict the network traffic.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2000.10a
• /
• pp.267-271
• /
• 2000

Traffic analysis during past years used the Poisson distribution or Markov model, assuming an exponential distribution of packet queue arrival. Recent studies, however, have shown aperiodic and burst characteristics of network traffics. Such characteristics of data traffic enable the scalability of network, QoS, optimized design, when we analyze new traffic model having a self-similar characteristic. This paper analyzes the self-similar characteristics of a small-scale mixed traffic in a network simulation, the real network Traffic.