• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.5 no.5
• /
• pp.923-930
• /
• 2001

In this paper, in order to improve the performance of TCP short traffic services in wireless Internet environments, the Split-ACKs(SPACK) scheme is proposed. In wireless networks, unlike wired networks, packet losses will occur more often due to high bit error rates. Therefore, each packet loss over wireless links results in congestion control procedure of TCP being invoked at the source. This causes severe end-to-end performance degradation of TCP. In this paper, to alleviate the TCP performance, the SPACK method, split acknowledgement packets in the base station, is proposed. Using computer simulation, the performance of TCP using SPACK is analyzed and shows better performance than traditional TCP protocol.

• Journal of the Semiconductor & Display Technology
• /
• v.10 no.3
• /
• pp.83-87
• /
• 2011

TCP works well in wired networks where packet losses mainly occur due to congestion in data traffic. In wireless networks TCP does not differentiate packet losses from transmission errors or from congestion, which could lead to degrade the network performance. Several methods have been proposed to improve TCP performance over wireless links. Among them the Snoop module working at the base station is the popular method. In this paper, it is shown that the performance of Snoop largely depends upon the transmission link errors and the amount of data traffic. Also, our research shows that the local retransmission timeout value of Snoop can affect throughput. From the simulation results we suggest how to effectively use the Snoop algorithm considering data traffic and transmission link errors. It is expected that the proposed adaptive method will contribute to improving the network performance reducing the burden of the processes for data traffic.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.9 no.4
• /
• pp.87-97
• /
• 2009

A Mobile Ad hoc Network (MANET) is characterized by multi-hop wireless connectivity, frequently changing network topology with mobile nodes and the efficiency of the dynamic routing protocol plays an important role in the performance of the network. In this paper, the performance of five routing protocols for MANET is compared by using OPNET modeler: AODV, DSR, GRP, OLSR and TORA. The various performance metrics are examined, such as packet delivery ratio, end-to-end delay and routing overhead with varying data traffic, number of nodes and mobility. In our simulation results, OLSR shows the best performance in terms of data delivery ratio in static networks, while AODV has the best performance in mobile networks with moderate data traffic. When comparing proactive protocols (OLSR, GRP) and reactive protocols (AODV, DSR) with varying data traffic in the static networks, proactive protocols consistently presents almost constant overhead while the reactive protocols show a sharp increase to some extent. When comparing each of proactive protocols in static and mobile networks, OLSR is better than GRP in the delivery ratio while overhead is more. As for reactive protocols, DSR outperforms AODV under the moderate data traffic in static networks because it exploits caching aggressively and maintains multiple routes per destination. However, this advantage turns into disadvantage in high mobility networks since the chance of the cached routes becoming stale increases.

• Smart Media Journal
• /
• v.13 no.6
• /
• pp.24-34
• /
• 2024

If the future can be predicted from network traffic data, which is a time series, it can achieve effects such as efficient resource allocation, prevention of malicious attacks, and energy saving. Many models based on statistical and deep learning techniques have been proposed, and most of these studies have focused on improving model structures and learning algorithms. Another approach to improving the prediction performance of the model is to obtain a good-quality data. With the aim of obtaining a good-quality data, this paper applies a dense sampling technique that augments time series data to the application of network traffic prediction and analyzes the performance improvement. As a dataset, UNSW-NB15, which is widely used for network traffic analysis, is used. Performance is analyzed using RMSE, MAE, and MAPE. To increase the objectivity of performance measurement, experiment is performed independently 10 times and the performance of existing sparse sampling and dense sampling is compared as a box plot. As a result of comparing the performance by changing the window size and the horizon factor, dense sampling consistently showed a better performance.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.26 no.11
• /
• pp.1630-1636
• /
• 2022

The results of current method of traffic sign detection gets hindered by environmental conditions and the traffic sign's condition as well. Therefore, in this paper, we propose a method of improving detection performance of damaged traffic signs by utilizing Hopfield Network and Fuzzy Max-Min Neural Network. In this proposed method, the characteristics of damaged traffic signs are analyzed and those characteristics are configured as the training pattern to be used by Fuzzy Max-Min Neural Network to initially classify the characteristics of the traffic signs. The images with initial characteristics that has been classified are restored by using Hopfield Network. The images restored with Hopfield Network are classified by the Fuzzy Max-Min Neural Network onces again to finally classify and detect the damaged traffic signs. 8 traffic signs with varying degrees of damage are used to evaluate the performance of the proposed method which resulted with an average of 38.76% improvement on classification performance than the Fuzzy Max-Min Neural Network.

• 제어로봇시스템학회:학술대회논문집
• /
• 2005.06a
• /
• pp.1846-1850
• /
• 2005

This paper presents a constrained-based routing (CBR) algorithm called, Dynamic Possible Path per Link (D-PPL) routing algorithm, for MultiProtocol Label Switching (MPLS) networks. In MPLS on-line routing, future traffics are unknown and network resource is limited. Therefore many routing algorithms such as Minimum Hop Algorithm (MHA), Widest Shortest Path (WSP), Dynamic Link Weight (DLW), Minimum Interference Routing Algorithm (MIRA), Profiled-Based Routing (PBR), Possible Path per Link (PPL) and Residual bandwidth integrated - Possible Path per Link (R-PPL) are proposed in order to improve network throughput and reduce rejection probability. MIRA is the first algorithm that introduces interference level avoidance between source-destination node pairs by integrating topology information or address of source-destination node pairs into the routing calculation. From its results, MIRA improves lower rejection probability performance. Nevertheless, MIRA suffer from its high routing complexity which could be considered as NP-Complete problem. In PBR, complexity of on-line routing is reduced comparing to those of MIRA, because link weights are off-line calculated by statistical profile of history traffics. However, because of dynamic of traffic nature, PBR maybe unsuitable for MPLS on-line routing. Also, both PPL and R-PPL routing algorithm we formerly proposed, are algorithms that achieve reduction of interference level among source-destination node pairs, rejection probability and routing complexity. Again, those previously proposed algorithms do not take into account the dynamic nature of traffic load. In fact, future traffics are unknown, but, amount of previous traffic over link can be measured. Therefore, this is the motivation of our proposed algorithm, the D-PPL. The D-PPL algorithm is improved based on the R-PPL routing algorithm by integrating traffic-per-link parameters. The parameters are periodically updated and are dynamically changed depended on current incoming traffic. The D-PPL tries to reserve residual bandwidth to service future request by avoid routing through those high traffic-per-link parameters. We have developed extensive MATLAB simulator to evaluate performance of the D-PPL. From simulation results, the D-PPL improves performance of MPLS on-line routing in terms of rejection probability and total throughput.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.23 no.8
• /
• pp.1926-1940
• /
• 1998

This paper is the part II of research results on the performance evaluation of fully interconnected ATM switch, and includes the performance evaluation results for bursty traffic and nonuniform distribution. The switch model is a fyully interconnected switch type proposed by ETRI and is the proper architecutre for a small-sized switch element. The proposed switch consists of two steps of buffering scheme in the switch fabric in order to effectively absorb the effect of bursty nature of ATM traffic. The switch uses bit addressing method for addressing shcmeme and thus it is easy to implement multicasting function without adding additional functional block. In order to incorporate the bursty nature of traffic in ATM networks, we use IBP(Interrupted Bernoulli Process) model as an input traffic model as well as random traffic model which has been used as a traditional traffic model. In order to design the various scenarios for simulation, we considered both uniform and nonuniform output distribution, and also implemented multicast function. In this paper, we presented the simulation results in diverse environments and evaluated the performance of the switch.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.11 no.10
• /
• pp.4887-4907
• /
• 2017

Accurate traffic flow forecasting is critical to the development and implementation of city intelligent transportation systems. Therefore, it is one of the most important components in the research of urban traffic scheduling. However, traffic flow forecasting involves a rather complex nonlinear data pattern, particularly during workday peak periods, and a lot of research has shown that traffic flow data reveals a seasonal trend. This paper proposes a new traffic flow forecasting model that combines seasonal relevance vector regression with the hybrid chaotic simulated annealing method (SRVRCSA). Additionally, a numerical example of traffic flow data from The Transportation Data Research Laboratory is used to elucidate the forecasting performance of the proposed SRVRCSA model. The forecasting results indicate that the proposed model yields more accurate forecasting results than the seasonal auto regressive integrated moving average (SARIMA), the double seasonal Holt-Winters exponential smoothing (DSHWES), and the relevance vector regression with hybrid Chaotic Simulated Annealing method (RVRCSA) models. The forecasting performance of RVRCSA with different kernel functions is also studied.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 1993.06a
• /
• pp.907-910
• /
• 1993

This paper describes the use of fuzzy control and decision making to simulate the control of traffic flow at an intersection. To show the value of fuzzy logic as an alternative method for control of traffic environments. A traffic environment includes the lanes to and from an intersection, the intersection, vehicle traffic, and signal lights in the intersection. To test the fuzzy logic controller, a computer simulation was constructed to model a traffic environment. A typical cross intersection was chosen for the traffic environment, and the performance of the fuzzy logic controller was compared with the performance of two different types of conventional control. In the hardware verifications, fuzzy logic was used to control acceleration of a model train on a circular path. For the software experiment, the fuzzy logic controller proved better than conventional control methods, especially in the case of highly uneven traffic flow between different directions. On the hardware si e of the research, the fuzzy acceleration control system showed a marked improvement in smoothness of ride over crisp control.

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.18 no.2
• /
• pp.9-16
• /
• 2022

The nodes constituting the vehicle ad hoc network (VANET) are vehicles moving along the road and road side units (RSUs) installed around the road. The vehicle ad hoc network is used to collect the status, speed, and location information of vehicles driving on the road, and to communicate with vehicles, vehicles, and RSUs. Today, as the number of vehicles continues to increase, urban roads are suffering from traffic jams, which cause various problems such as time, fuel, and the environment. In this paper, we propose a method to solve traffic congestion problems on urban roads and demonstrate that the method can be applied to solve traffic congestion problems through performance evaluation using two typical protocols of vehicle ad hoc networks, AODV and GPSR. The performance evaluation used ns-2 simulator, and the average number of traffic jams and the waiting time due to the average traffic congestion were measured. Through this, we demonstrate that the vehicle ad hoc-based traffic congestion management technique proposed in this paper can be applied to urban roads in smart cities.