Graph Signal Processing: Overview, Challenges and Applications

Research in Graph Signal Processing (GSP) aims to develop tools for processing data defined on irregular graph domains. In this paper we first provide an overview of core ideas in GSP and their connection to conventional digital signal processing. We then summarize recent developments in developing basic GSP tools, including methods for sampling, filtering or graph learning. Next, we review progress in several application areas using GSP, including processing and analysis of sensor network data, biological data, and applications to image processing and machine learning. We finish by providing a brief historical perspective to highlight how concepts recently developed in GSP build on top of prior research in other areas.Comment: To appear, Proceedings of the IEE

Characterisation of real GPRS traffic with analytical tools

With GPRS and UMTS networks lunched, wireless multimedia services are commercially becoming the most attractive applications next to voice. Because of the nature of bursty, packet-switched schemes and multiple data rates, the traditional Erlang approach and Poisson models for characterising voice-centric services traffic are not suitable for studying wireless multimedia services traffic. Therefore, research on the characterisation of wireless multimedia services traffic is very challenging. The typical reference for the study of wireless multimedia services traffic is wired Internet services traffic. However, because of the differences in network protocol, bandwidth, and QoS requirements between wired and wireless services, their traffic characterisations may not be similar. Wired network Internet traffic shows self-similarity, long-range dependence and its file sizes exhibit heavy-tailedness. This paper reports the use of existing tools to analyse real GPRS traffic data to establish whether wireless multimedia services traffic have similar properties as wired Internet services traffic

Empirical mode decomposition-based facial pose estimation inside video sequences

We describe a new pose-estimation algorithm via integration of the strength in both empirical mode decomposition (EMD) and mutual information. While mutual information is exploited to measure the similarity between facial images to estimate poses, EMD is exploited to decompose input facial images into a number of intrinsic mode function (IMF) components, which redistribute the effect of noise, expression changes, and illumination variations as such that, when the input facial image is described by the selected IMF components, all the negative effects can be minimized. Extensive experiments were carried out in comparisons to existing representative techniques, and the results show that the proposed algorithm achieves better pose-estimation performances with robustness to noise corruption, illumination variation, and facial expressions

The Dynamics of Internet Traffic: Self-Similarity, Self-Organization, and Complex Phenomena

The Internet is the most complex system ever created in human history. Therefore, its dynamics and traffic unsurprisingly take on a rich variety of complex dynamics, self-organization, and other phenomena that have been researched for years. This paper is a review of the complex dynamics of Internet traffic. Departing from normal treatises, we will take a view from both the network engineering and physics perspectives showing the strengths and weaknesses as well as insights of both. In addition, many less covered phenomena such as traffic oscillations, large-scale effects of worm traffic, and comparisons of the Internet and biological models will be covered.Comment: 63 pages, 7 figures, 7 tables, submitted to Advances in Complex System

Driving Rhythm Method for Driving Comfort Analysis on Rural Highways

Driving comfort is of great significance for rural highways, since the variation characteristics of driving speed are comparatively complex on rural highways. Earlier studies about driving comfort were usually based on the actual geometric road alignments and automobiles, without considering the driver’s visual perception. However, some scholars have shown that there is a discrepancy between actual and perceived geometric alignments, especially on rural highways. Moreover, few studies focus on rural highways. Therefore, in this paper the driver’s visual lane model was established based on the Catmull-Rom spline, in order to describe the driver’s visual perception of rural highways. The real vehicle experiment was conducted on 100 km rural highways in Tibet. The driving rhythm was presented to signify the information during the driving process. Shape parameters of the driver’s visual lane model were chosen as input variables to predict the driving rhythm by BP neural network. Wavelet transform was used to explore which part of the driving rhythm is related to the driving comfort. Then the probabilities of good, fair and bad driving comfort can be calculated by wavelets of the driving rhythm. This work not only provides a new perspective into driving comfort analysis and quantifies the driver’s visual perception, but also pays attention to the unique characteristics of rural highways.</p

Performance Analysis of Multicast Mobility in a Hierarchical Mobile IP Proxy Environment

Mobility support in IPv6 networks is ready for release as an RFC, stimulating major discussions on improvements to meet real-time communication requirements. Sprawling hot spots of IP-only wireless networks at the same time await voice and videoconferencing as standard mobile Internet services, thereby adding the request for multicast support to real-time mobility. This paper briefly introduces current approaches for seamless multicast extensions to Mobile IPv6. Key issues of multicast mobility are discussed. Both analytically and in simulations comparisons are drawn between handover performance characteristics, dedicating special focus on the M-HMIPv6 approach.Comment: 11 pages, 7 figure