In recent years, the proliferation of available video content and the popularity of the Internet have encouraged service providers to develop new ways of distributing content to clients. Increasing video scaling ratios and advanced digital signal processing techniques have led to Internet Video-on-Demand applications, but these currently lack efficiency and quality. Scalable Video on Demand: Adaptive Internet-based Distribution examines how current video compression and streaming can be used to deliver high-quality applications over the Internet. In addition to analysing the problems of client heterogeneity and the absence of Quality of Service in the Internet, this book: assesses existing products and encoding formats; presents new algorithms and protocols for optimised on-line video streaming architectures; includes real-world application examples and experiments; sets out a practical ‘toolkit’ for Dynamically Reconfigurable Multimedia Distribution Systems. Written by an expert in the field of video distribution, Scalable Video on Demand: Adaptive Internet-based Distribution provides a novel approach to the design and implementation of Video-on-Demand systems for Software Engineers and researchers. It will also be useful for graduate students following Electronic Engineering and Computer Science courses.

Continuous media streaming systems will shape the future of information infrastructure. The challenge is to design systems and networks capable of supporting millions of concurrent users. Key to this is the integration of fault-tolerant mechanisms to prevent individual component failures from disrupting systems operations. These are just some of the hurdles that need to be overcome before large-scale continuous media services such as video-on-demand can be deployed with maximum efficiency. The author places the subject in context, drawing together findings from the past decade of research whilst examining the technology’s present status and its future potential. The approach adopted is comprehensive, covering topics – notably the scalability and fault-tolerance issues - that previously have not been treated in depth. Provides an accessible introduction to the technology, presenting the basic principles for media streaming system design, focusing on the need for the correct and timely delivery of data. Explores the use of parallel server architectures to tackle the two key challenges of scalability and fault-tolerance. Investigates the use of network multicast streaming algorithms to further increase the scalability of very-large-scale media streaming systems. Illustrates all findings using real-world examples and case studies gleaned from cutting-edge worldwide research. Combining theory and practice, this book will appeal to industry specialists working in content distribution in general and continuous media streaming in particular. The introductory materials and basic building blocks complemented by amply illustrated, more advanced coverage provide essential reading for senior undergraduates, postgraduates and researchers in these fields.

While the demand for video streaming services has risen rapidly in recent years, supporting video streaming service to a large number of receivers still remains a challenging task. Issues of video streaming in the Internet, such as scalability, and reliability are still under extensive research. Recently proposed network contexts such as overlay networks, and mobile ad hoc networks pose even tougher challenges. This thesis focuses on supporting scalable video streaming applications under various network environments. More specifically, this thesis investigates the following problems: i) Server selection in replicated batching video on demand (VoD) systems: we find out that, to optimize the user perceived latency, it is vital to consider the server state information and channel allocation schemes when making server selection decisions. We develop and evaluate a set of server selection algorithms that use increasingly more information. ii) Scalable live video streaming with time shifting and video patching: we consider the problem of how to enable continuous live video streaming to a large group of clients in cooperative but unreliable overlay networks. We design a server-based architecture which uses a combined technique of time-shifting video server and P2P video patching. iii) A Cooperative patching architecture in overlay networks: We design a cooperative patching architecture which shifts video patching responsibility completely to the client side. An end-host retrieves lost data from other end-hosts within the same multicast group. iv) V3: a vehicle to vehicle video streaming architecture: We propose V3, an architecture to provide live video streaming service to driving vehicles through vehicle-to-vehicle (V2V) networks. V3 incorporates a novel signaling mechanism to continuously trigger video sources to send video data back to the receiver. It also adopts a store-carry-and-forward approach to transmit video data in a partitioned network environment. We also develop a multicasting framework that enables live video streaming applications from multiple sources to multiple receivers in V2V networks. A message integration scheme is used to suppress the signaling overhead, and a two-level tree-based routing approach is adopted to forward the video data.

"This book spans a number of interdependent and emerging topics in streaming media, offering a comprehensive collection of topics including media coding, wireless/mobile video, P2P media streaming, and applications of streaming media"--Provided by publisher.

A friendly, framework-agnostic tutorial that will help you grok how streaming systems work—and how to build your own! In Grokking Streaming Systems you will learn how to: Implement and troubleshoot streaming systems Design streaming systems for complex functionalities Assess parallelization requirements Spot networking bottlenecks and resolve back pressure Group data for high-performance systems Handle delayed events in real-time systems Grokking Streaming Systems is a simple guide to the complex concepts behind streaming systems. This friendly and framework-agnostic tutorial teaches you how to handle real-time events, and even design and build your own streaming job that’s a perfect fit for your needs. Each new idea is carefully explained with diagrams, clear examples, and fun dialogue between perplexed personalities! About the technology Streaming systems minimize the time between receiving and processing event data, so they can deliver responses in real time. For applications in finance, security, and IoT where milliseconds matter, streaming systems are a requirement. And streaming is hot! Skills on platforms like Spark, Heron, and Kafka are in high demand. About the book Grokking Streaming Systems introduces real-time event streaming applications in clear, reader-friendly language. This engaging book illuminates core concepts like data parallelization, event windows, and backpressure without getting bogged down in framework-specific details. As you go, you’ll build your own simple streaming tool from the ground up to make sure all the ideas and techniques stick. The helpful and entertaining illustrations make streaming systems come alive as you tackle relevant examples like real-time credit card fraud detection and monitoring IoT services. What's inside Implement and troubleshoot streaming systems Design streaming systems for complex functionalities Spot networking bottlenecks and resolve backpressure Group data for high-performance systems About the reader No prior experience with streaming systems is assumed. Examples in Java. About the author Josh Fischer and Ning Wang are Apache Committers, and part of the committee for the Apache Heron distributed stream processing engine. Table of Contents PART 1 GETTING STARTED WITH STREAMING 1 Welcome to Grokking Streaming Systems 2 Hello, streaming systems! 3 Parallelization and data grouping 4 Stream graph 5 Delivery semantics 6 Streaming systems review and a glimpse ahead PART 2 STEPPING UP 7 Windowed computations 8 Join operations 9 Backpressure 10 Stateful computation 11 Wrap-up: Advanced concepts in streaming systems

Streaming data is a big deal in big data these days. As more and more businesses seek to tame the massive unbounded data sets that pervade our world, streaming systems have finally reached a level of maturity sufficient for mainstream adoption. With this practical guide, data engineers, data scientists, and developers will learn how to work with streaming data in a conceptual and platform-agnostic way. Expanded from Tyler Akidau’s popular blog posts "Streaming 101" and "Streaming 102", this book takes you from an introductory level to a nuanced understanding of the what, where, when, and how of processing real-time data streams. You’ll also dive deep into watermarks and exactly-once processing with co-authors Slava Chernyak and Reuven Lax. You’ll explore: How streaming and batch data processing patterns compare The core principles and concepts behind robust out-of-order data processing How watermarks track progress and completeness in infinite datasets How exactly-once data processing techniques ensure correctness How the concepts of streams and tables form the foundations of both batch and streaming data processing The practical motivations behind a powerful persistent state mechanism, driven by a real-world example How time-varying relations provide a link between stream processing and the world of SQL and relational algebra