Computer Science

Content distribution, i.e., distributing digital content from one node to another node or multiple nodes, is the most fundamental function of the Internet. Since Amazon’s launch of EC2 in 2006 and Apple’s release of the iPhone in 2007, Internet content distribution has shown a strong trend toward polarization. On the one hand, considerable investments have been made in creating heavyweight, integrated data centers (“heavy-cloud”) all over the world, in order to achieve economies of scale and high flexibility/efficiency of content distribution. On the other hand, end-user devices (“light-end”) have become increasingly lightweight, mobile and heterogeneous, creating new demands concerning traffic usage, energy consumption, bandwidth, latency, reliability, and/or the security of content distribution. Based on comprehensive real-world measurements at scale, we observe that existing content distribution techniques often perform poorly under the abovementioned new circumstances.

Motivated by the trend of “heavy-cloud vs. light-end,” this book is dedicated to uncovering the root causes of today’s mobile networking problems and designing innovative cloud-based solutions to practically address such problems. Our work has produced not only academic papers published in prestigious conference proceedings like SIGCOMM, NSDI, MobiCom and MobiSys, but also concrete effects on industrial systems such as Xiaomi Mobile, MIUI OS, Tencent App Store, Baidu PhoneGuard, and WiFi.com. A series of practical takeaways and easy-to-follow testimonials are provided to researchers and practitioners working in mobile networking and cloud computing. In addition, we have released as much code and data used in our research as possible to benefit the community.

The rise of Android malware poses a significant threat to users’ information security and privacy. Malicious software can inflict severe harm on users by employing various tactics, including deception, personal information theft, and device control. To address this issue, both academia and industry are continually engaged in research and development efforts focused on detecting and countering Android malware.

This book presents challenges, bad/best practices, experiences, tools, gaps, and future directions in the field. This will guide future generations of experts moving forward on DevOps and testing automation for complex CPSs.

This book presents the select proceedings of the 7th International Conference on Data Analytics and Cyber Security (DACS 2024). It covers distinct features of various data analytics, cyber security, and synergies in data analytics and cyber security to resolve physical world problems. The book will be useful for researchers and professionals interested in the broad field of cyber security.

The 28 revised full papers presented were carefully reviewed and selected from 66 submissions. The papers are organized in the topical sections: IoT and cyber security; blockchain security; digital forensic and malware analysis; 5G virtual Infrastructure, cryptography and network security.

The 13-volume set LNCS 14425-14437 constitutes the refereed proceedings of the 6th Chinese Conference on Pattern Recognition and Computer Vision, PRCV 2023, held in Xiamen, China, during October 13–15, 2023.

The 532 full papers presented in these volumes were selected from 1420 submissions. The papers have been organized in the following topical sections: Action Recognition, Multi-Modal Information Processing, 3D Vision and Reconstruction, Character Recognition, Fundamental Theory of Computer Vision, Machine Learning, Vision Problems in Robotics, Autonomous Driving, Pattern Classification and Cluster Analysis, Performance Evaluation and Benchmarks, Remote Sensing Image Interpretation, Biometric Recognition, Face Recognition and Pose Recognition, Structural Pattern Recognition, Computational Photography, Sensing and Display Technology, Video Analysis and Understanding, Vision Applications and Systems, Document Analysis and Recognition, Feature Extraction and Feature Selection, Multimedia Analysis and Reasoning, Optimization and Learning methods, Neural Network and Deep Learning, Low-Level Vision and Image Processing, Object Detection, Tracking and Identification, Medical Image Processing and Analysis.