The topics addressed in this book are crucial for both the academic community and industry, since the vehicular network has become an essential building block for intelligent transportation systems. The systematic principle of this book provides valuable guidance on the deployment and implementation of V2X-enabled road-safety applications. In addition, this book carries out structured technologies from the MAC layer to the link and network layer, which can provide a general introduction for interested readers with a comprehensive understanding of applying vehicular networks in enhancing road safety, and offers a systematized view for researchers and practitioners in the field of vehicular networks to help them optimize and improve the desired vehicular communication systems. Road safety has always been the first priority for daily commuters on the road. Vehicular networks can be an effective solution to enhance road safety, via which vehicles can exchange cooperative awareness messages rapidly, contributing to better situation awareness and maneuvering cooperation. However, with the fast-changing network topology, intermittent wireless link, and dynamic traffic density, it is challenging to achieve satisfying network performance. This book introduces the background of vehicular networks, provides a comprehensive overview of networking techniques in supporting road-safety applications, states the technical motivations per the MAC, link, and network layer, and proposes/designs vehicular networking technologies at the corresponding layer respectively to guarantee low-latency and reliable V2X communications for road-safety applications. By extending the proposed networking technologies to support all types of vehicular services, this book also outlines open issues and research directions in future 5G and beyond vehicular networks.

The topics addressed in this book are crucial for both the academic community and industry, since the vehicular network has become an essential building block for intelligent transportation systems. The systematic principle of this book provides valuable guidance on the deployment and implementation of V2X-enabled road-safety applications. In addition, this book carries out structured technologies from the MAC layer to the link and network layer, which can provide a general introduction for interested readers with a comprehensive understanding of applying vehicular networks in enhancing road safety, and offers a systematized view for researchers and practitioners in the field of vehicular networks to help them optimize and improve the desired vehicular communication systems. Road safety has always been the first priority for daily commuters on the road. Vehicular networks can be an effective solution to enhance road safety, via which vehicles can exchange cooperative awareness messages rapidly, contributing to better situation awareness and maneuvering cooperation. However, with the fast-changing network topology, intermittent wireless link, and dynamic traffic density, it is challenging to achieve satisfying network performance. This book introduces the background of vehicular networks, provides a comprehensive overview of networking techniques in supporting road-safety applications, states the technical motivations per the MAC, link, and network layer, and proposes/designs vehicular networking technologies at the corresponding layer respectively to guarantee low-latency and reliable V2X communications for road-safety applications. By extending the proposed networking technologies to support all types of vehicular services, this book also outlines open issues and research directions in future 5G and beyond vehicular networks.

With the advancement of wireless technology, vehicular ad hoc networks (VANETs) are emerging as a promising approach to realizing "smart cities" and addressing many important transportation problems such as road safety, efficiency, and convenience. This brief provides an introduction to the large trace data set collected from thousands of taxis and buses in Shanghai, the largest metropolis in China. It also presents the challenges, design issues, performance modeling and evaluation of a wide spectrum of VANET research topics, ranging from realistic vehicular mobility models and opportunistic routing, to real-time vehicle tracking and urban sensing applications. In addition to the latest research and techniques, the reader will also learn the trace-driven methodologies and tools of performance modeling and analysis, network protocol design and optimization, and network simulation, thus keeping pace with the fast moving VANET research and development.

Welcome to the proceedings of the 2008 IFIP International Conference on Network and Parallel Computing (NPC 2008) held in Shanghai, China. NPC has been a premier conference that has brought together researchers and pr- titioners from academia, industry and governments around the world to advance the theories and technologies of network and parallel computing. The goal of NPC is to establish an international forum for researchers and practitioners to present their - cellent ideas and experiences in all system fields of network and parallel computing. The main focus of NPC 2008 was on the most critical areas of network and parallel computing, network technologies, network applications, network and parallel archit- tures, and parallel and distributed software. In total, the conference received more than 140 papers from researchers and prac- tioners. Each paper was reviewed by at least two internationally renowned referees and selected based on its originality, significance, correctness, relevance, and clarity of presentation. Among the high-quality submissions, only 32 regular papers were accepted by the conferences. All of the selected conference papers are included in the conference proceedings. After the conference, some high-quality papers will be r- ommended to be published in the special issue of international journals. We were delighted to host three well-known international scholars offering the k- note speeches, Sajal K. Das from University Texas at Arlington USA, Matt Mutka from Michigan State University and David Hung-Chang Du from University of M- nesota University of Minnesota.

This book constitutes the refereed joint proceedings of four international workshops held in conjunction with the 8th Asia-Pacific Web Conference, APWeb 2006, in Harbin, China in January 2006. The 88 revised full papers and 58 revised short papers presented are very specific and contribute to enlarging the spectrum of the more general topics treated in the APWeb 2006 main conference.

This volume contains papers selected for presentation at the 7th Asia Pacific Conference on Web Technology (APWeb 2005), which was held in Shanghai, China during March 29 April 1, 2005. APWeb is an international conference series on WWW technologies and is the primary forum for researchers and practitioners from both academia and industry to exchange knowledge on WWW-related technologies and new advanced applications. APWeb 2005 received 420 submissions from 21 countries and regions worldwide, including China, Korea, Australia, Japan, Taiwan, France, UK, Canada, USA, India, Hong Kong, Brazil, Germany, Thailand, Singapore, Turkey, Spain, Greece, Belgium, New Zealand, and UAE. After a thorough review process for each submission by the Program Committee members and expert reviewers recommended by PC members, APWeb 2005 accepted 71 regular research papers (acceptance ratio 16.9%) and 22 short papers (acceptance ratio 5.2%). This volume also includes 6 keynote papers and 11 invited demo papers. The keynote lectures were given by six leading experts: Prof. Ah Chung Tsoi (Australia Research Council), Prof. Zhiyong Liu (National Nature Science Foundation of China), Prof. John Mylopoulos (University of Toronto), Prof. Ramamohanarao (Rao) Kotagiri (University of Melbourne), Prof. Calton Pu (Georgia Tech), and Prof. Zhiwei Xu (Chinese Academy of Sciences)."

Grid and cooperative computing has emerged as a new frontier of information tech- logy. It aims to share and coordinate distributed and heterogeneous network resources forbetterperformanceandfunctionalitythatcanotherwisenotbeachieved.Thisvolume contains the papers presented at the 2nd International Workshop on Grid and Coope- tive Computing, GCC 2003, which was held in Shanghai, P.R. China, during December 7-10, 2003. GCC is designed to serve as a forum to present current and future work as well as to exchange research ideas among researchers, developers, practitioners, and usersinGridcomputing, Webservicesandcooperativecomputing, includingtheoryand applications. For this workshop, we received over 550 paper submissions from 22 countries and regions. All the papers were peer-reviewed in depth and qualitatively graded on their relevance, originality, signi?cance, presentation, and the overall appropriateness of their acceptance. Any concerns raised were discussed by the program committee. The or- nizing committee selected 176 papers for conference presentation (full papers) and 173 submissions for poster presentation (short papers).The papers included herein represent the forefront of research from China, USA, UK, Canada, Switzerland, Japan, Aust- lia, India, Korea, Singapore, Brazil, Norway, Greece, Iran, Turkey, Oman, Pakistan and other countries. More than 600 attendees participated in the technical section and the exhibition of the worksho

Grid and cooperative computing has emerged as a new frontier of information tech- logy. It aims to share and coordinate distributed and heterogeneous network resources forbetterperformanceandfunctionalitythatcanotherwisenotbeachieved.Thisvolume contains the papers presented at the 2nd International Workshop on Grid and Coope- tive Computing, GCC 2003, which was held in Shanghai, P.R. China, during December 7-10, 2003. GCC is designed to serve as a forum to present current and future work as well as to exchange research ideas among researchers, developers, practitioners, and usersinGridcomputing,Webservicesandcooperativecomputing,includingtheoryand applications. For this workshop, we received over 550 paper submissions from 22 countries and regions. All the papers were peer-reviewed in depth and qualitatively graded on their relevance, originality, signi?cance, presentation, and the overall appropriateness of their acceptance. Any concerns raised were discussed by the program committee. The or- nizing committee selected 176 papers for conference presentation (full papers) and 173 submissions for poster presentation (short papers).The papers included herein represent the forefront of research from China, USA, UK, Canada, Switzerland, Japan, Aust- lia, India, Korea, Singapore, Brazil, Norway, Greece, Iran, Turkey, Oman, Pakistan and other countries. More than 600 attendees participated in the technical section and the exhibition of the workshop.

This book investigates compressive sensing techniques to provide a robust and general framework for network data analytics. The goal is to introduce a compressive sensing framework for missing data interpolation, anomaly detection, data segmentation and activity recognition, and to demonstrate its benefits. Chapter 1 introduces compressive sensing, including its definition, limitation, and how it supports different network analysis applications. Chapter 2 demonstrates the feasibility of compressive sensing in network analytics, the authors we apply it to detect anomalies in the customer care call dataset from a Tier 1 ISP in the United States. A regression-based model is applied to find the relationship between calls and events. The authors illustrate that compressive sensing is effective in identifying important factors and can leverage the low-rank structure and temporal stability to improve the detection accuracy. Chapter 3 discusses that there are several challenges in applying compressive sensing to real-world data. Understanding the reasons behind the challenges is important for designing methods and mitigating their impact. The authors analyze a wide range of real-world traces. The analysis demonstrates that there are different factors that contribute to the violation of the low-rank property in real data. In particular, the authors find that (1) noise, errors, and anomalies, and (2) asynchrony in the time and frequency domains lead to network-induced ambiguity and can easily cause low-rank matrices to become higher-ranked. To address the problem of noise, errors and anomalies in Chap. 4, the authors propose a robust compressive sensing technique. It explicitly accounts for anomalies by decomposing real-world data represented in matrix form into a low-rank matrix, a sparse anomaly matrix, an error term and a small noise matrix. Chapter 5 addresses the problem of lack of synchronization, and the authors propose a data-driven synchronization algorithm. It can eliminate misalignment while taking into account the heterogeneity of real-world data in both time and frequency domains. The data-driven synchronization can be applied to any compressive sensing technique and is general to any real-world data. The authors illustrates that the combination of the two techniques can reduce the ranks of real-world data, improve the effectiveness of compressive sensing and have a wide range of applications. The networks are constantly generating a wealth of rich and diverse information. This information creates exciting opportunities for network analysis and provides insight into the complex interactions between network entities. However, network analysis often faces the problems of (1) under-constrained, where there is too little data due to feasibility and cost issues in collecting data, or (2) over-constrained, where there is too much data, so the analysis becomes unscalable. Compressive sensing is an effective technique to solve both problems. It utilizes the underlying data structure for analysis. Specifically, to solve the under-constrained problem, compressive sensing technologies can be applied to reconstruct the missing elements or predict the future data. Also, to solve the over-constraint problem, compressive sensing technologies can be applied to identify significant elements To support compressive sensing in network data analysis, a robust and general framework is needed to support diverse applications. Yet this can be challenging for real-world data where noise, anomalies and lack of synchronization are common. First, the number of unknowns for network analysis can be much larger than the number of measurements. For example, traffic engineering requires knowing the complete traffic matrix between all source and destination pairs, in order to properly configure traffic and avoid congestion. However, measuring the flow between all source and destination pairs is very expensive or even infeasible. Reconstructing data from a small number of measurements is an underconstrained problem. In addition, real-world data is complex and heterogeneous, and often violate the low-level assumptions required by existing compressive sensing techniques. These violations significantly reduce the applicability and effectiveness of existing compressive sensing methods. Third, synchronization of network data reduces the data ranks and increases spatial locality. However, periodic time series exhibit not only misalignment but also different frequencies, which makes it difficult to synchronize data in the time and frequency domains. The primary audience for this book is data engineers, analysts and researchers, who need to deal with big data with missing anomalous and synchronization problems. Advanced level students focused on compressive sensing techniques will also benefit from this book as a reference.