Urban traffic analysis is crucial for traffic forecasting systems, urban planning and, more recently, various mobile and network applications. In this paper, we analyse urban traffic with network and statistical methods. Our analysis is based on one big bus dataset containing 45 million bus arrival samples in Helsinki. We mainly address following questions: 1. How can we identify the areas that...

Traffic classification plays an important role in many aspects of network management such as identifying type of the transferred data, detection of malware applications, applying policies to restrict network accesses and so on. Basic methods in this field were using some obvious traffic features like port number and protocol type to classify the traffic type. However, recent changes in applicat...

Int J Network Mgmt 2016; 1–15 Summary Various traffic identification methods have been proposed with the focus on application‐level traffic analysis. Header signature–based identification using the 3‐tuple (Internet Protocol address, port number, and L4 protocol) within a packet header has garnered a lot of attention because it overcomes the limitations faced by the payload‐based method, such a...

the congestion pricing has been discussed as a practical tool for traffic management on urban transport networks. the traffic congestion is defined as an external diseconomy on the network in transport economics. it has been proposed that the congestion pricing would be used to reduce the traffic on the network. this paper investigates the cordon-based second-best congestion-pricing problems on...

The encryption of network traffic complicates legitimate network monitoring, traffic analysis, and network forensics. In this paper, we present real-time lightweight identification of HTTPS clients based on network monitoring and SSL/TLS fingerprinting. Our experiment shows that it is possible to estimate the User-Agent of a client in HTTPS communication via the analysis of the SSL/TLS handshak...

The identification of network applications that create traffic flows is vital to the areas of network management and surveillance. Current popular methods such as port number and payload-based identification are inadequate and exhibit a number of shortfalls. A potential solution is the use of machine learning techniques to identify network applications based on payload independent statistical f...

Prediction of traffic is very crucial for its management. Because of human involvement in the generation of this phenomenon, traffic signal is normally accompanied by noise and high levels of non-stationarity. Therefore, traffic signal prediction as one of the important subjects of study has attracted researchers’ interests. In this study, a combinatorial approach is proposed for traffic signal...

the paper discusses the current state of research concerning railway network timetabling and traffic management. timetable effectiveness is governed by frequency, regularity, accurate running, recovery and layover times, as well as minimal headway, buffer times and waiting times. analytic (queuing) models and stochastic microsimulation are predominantly used for estimation of waiting times and ...

A key aspect of traffic classification is the early identification of individual flows which may utilise strategies such as ephemeral ports and transport later encryption to ‘hide’ on the network. This paper focuses on P2P and HTTP – the two main producers of network traffic – to determine the characteristics of their individual flows. We propose a heuristic based classification system to disti...

Owing to the enormous growth of VoIP applications, an effective means of identifying VoIP is now essential for managing a number of network traffic issues, such as reserving bandwidth for VoIP traffic, assigning high priority for VoIP flows, or blocking VoIP calls to certain destinations. Because the protocols, port numbers, and codecs used by VoIP services are shifting toward proprietary, encr...