The predictability of network traffic is a significant interest in many domains such as congestion control, admission control, and network management. An accurate traffic prediction model should have the ability to capture prominent traffic characteristics, such as long-range dependence (LRD) and self-similarity in the large time scale, multifractal in small time scale. In this paper we propose...

We propose a dynamic vehicular routing algorithm with traffic prediction for improved routing performance. The primary idea of our algorithm is to use real-time as well as predictive traffic information provided by a central routing controller. In order to evaluate the performance, we develop a microtraffic simulator that provides road networks created from real maps, routing algorithms, and ve...

The predictability of network traffic is a significant interest in many domains such as congestion control, admission control, and network management. An accurate traffic prediction model should have the ability to capture prominent traffic characteristics, such as long-range dependence (LRD) and self-similarity in the large time scale, multifractal in small time scale. In this paper we propose...

Security data fusion is fundamental and essential for intelligent traffic systems. A dynamic data fusion scheme is proposed to guarantee the security and accuracy of sensed data. It is used to collect and manage multi-source traffic messages. It improves K-neighbor nonparametric regression method on the basis of repeated occurrence feature of traffic flow state mode. Double-screening for neighb...

This paper presents a model for traffic volume prediction which can be effectively used for transportation planning, management and security assessment at any time. Fuzzy logic is applied in order to realize effective and efficient traffic prediction. In this paper, 'day' of a week and 'time' of a day are taken as inputs for proposed model and the output will be the predicte...

To support real-time applications, for instance Voice-over-IP, network infrastructure has to provide high bandwidth as well as short endto-end latency. To cope with both, network processors (NP) are selected. Current NP support transmission rates of OC-48. However, due to sequential packet layer processing, processing delay is not optimized. To solve this problem, speculative packet processing ...

The rapid proliferation of Global Position Service (GPS) devices and mounting number of traffic monitoring systems employed by municipalities have opened the door for advanced traffic control and personalized route planning. Most state of the art traffic management and information systems focus on data analysis, and very little has been done in the sense of prediction. In this article, we devis...

This paper investigates the long-term prediction of MPEG video traffic. Predicting such traffic over a long horizon is important for today’s fast networks and internet multimedia services. In comparison with short-term prediction, long-term prediction of video traffic is yet to be explored especially for MPEG-4 coded videos despite its effectiveness in a number of important network-edge applica...

In this paper, we consider the temporal pattern in traffic flow time series, and implement a deep learning model for traffic flow prediction. Detrending based methods decompose original flow series into trend and residual series, in which trend describes the fixed temporal pattern in traffic flow and residual series is used for prediction. Inspired by the detrending method, we propose DeepTrend...