Cooperative Interval Caching in Clustered Multimedia Servers

In this project, we design a cooperative interval caching (CIC) algorithm for clustered video servers, and evaluate its performance through simulation. The CIC algorithm describes how distributed caches in the cluster cooperate to serve a given request. With CIC, a clustered server can accommodate twice (95%) more number of cached streams than the clustered server without cache cooperation. There are two major processes of CIC to find available cache space for a given request in the cluster: to find the server containing the information about the preceding request of the given request; and to find another server which may have available cache space if the current server turns out not to have enough cache space. The performance study shows that it is better to direct the requests of the same movie to the same server so that a request can always find the information of its preceding request from the same server. The CIC algorithm uses scoreboard mechanism to achieve this goal. The performance results also show that when the current server fails to find cache space for a given request, randomly selecting a server works well to find the next server which may have available cache space. The combination of scoreboard and random selection to find the preceding request information and the next available server outperforms other combinations of different approaches by 86%. With CIC, the cooperative distributed caches can support as many cached streams as one integrated cache does. In some cases, the cooperative distributed caches accommodate more number of cached streams than one integrated cache would do. The CIC algorithm makes every server in the cluster perform identical tasks to eliminate any single point of failure, there by increasing availability of the server cluster. The CIC algorithm also specifies how to smoothly add or remove a server to or from the cluster to provide the server with scalability

Self-Optimization of Internet Services with Dynamic Resource Provisioning

Self-optimization through dynamic resource provisioning is an appealing approach to tackle load variation in Internet services. It allows to assign or release resources to/from Internet services according to the varying load. However, dynamic resource provisioning raises several challenges among which: (i) How to plan a good capacity of an Internet service, i.e.~a necessary and sufficient amount of resource to handle the Internet service workload, (ii) How to manage both gradual load variation and load peaks in Internet services, (iii) How to prevent system oscillations in presence of potentially concurrent dynamic resource provisioning, and (iv) How to provide generic self-optimization that applies to different Internet services such as e-mail services, streaming servers or e-commerce web systems. This paper precisely answers these questions. It presents the design principles and implementation details of a self-optimization autonomic manager. It describes the results of an experimental evaluation of the self-optimization manager with a realistic e-commerce multi-tier web application running in a Linux cluster of computers. The experimental results show the usefulness of self-optimization in terms of end-user's perceived performance and system's operational costs, with a negligible overhead

ATM network impairment to video quality

Includes bibliographical reference

Flexi-WVSNP-DASH: A Wireless Video Sensor Network Platform for the Internet of Things

abstract: Video capture, storage, and distribution in wireless video sensor networks (WVSNs) critically depends on the resources of the nodes forming the sensor networks. In the era of big data, Internet of Things (IoT), and distributed demand and solutions, there is a need for multi-dimensional data to be part of the Sensor Network data that is easily accessible and consumable by humanity as well as machinery. Images and video are expected to become as ubiquitous as is the scalar data in traditional sensor networks. The inception of video-streaming over the Internet, heralded a relentless research for effective ways of distributing video in a scalable and cost effective way. There has been novel implementation attempts across several network layers. Due to the inherent complications of backward compatibility and need for standardization across network layers, there has been a refocused attention to address most of the video distribution over the application layer. As a result, a few video streaming solutions over the Hypertext Transfer Protocol (HTTP) have been proposed. Most notable are Apple’s HTTP Live Streaming (HLS) and the Motion Picture Experts Groups Dynamic Adaptive Streaming over HTTP (MPEG-DASH). These frameworks, do not address the typical and future WVSN use cases. A highly flexible Wireless Video Sensor Network Platform and compatible DASH (WVSNP-DASH) are introduced. The platform's goal is to usher video as a data element that can be integrated into traditional and non-Internet networks. A low cost, scalable node is built from the ground up to be fully compatible with the Internet of Things Machine to Machine (M2M) concept, as well as the ability to be easily re-targeted to new applications in a short time. Flexi-WVSNP design includes a multi-radio node, a middle-ware for sensor operation and communication, a cross platform client facing data retriever/player framework, scalable security as well as a cohesive but decoupled hardware and software design.Dissertation/ThesisDoctoral Dissertation Electrical Engineering 201

Localized Application for Video Capture for a Multimedia Sensor Node with Name-Based Segment Streaming

abstract: The Internet of Things (IoT) has become a more pervasive part of everyday life. IoT networks such as wireless sensor networks, depend greatly on the limiting unnecessary power consumption. As such, providing low-power, adaptable software can greatly improve network design. For streaming live video content, Wireless Video Sensor Network Platform compatible Dynamic Adaptive Streaming over HTTP (WVSNP-DASH) aims to revolutionize wireless segmented video streaming by providing a low-power, adaptable framework to compete with modern DASH players such as Moving Picture Experts Group (MPEG-DASH) and Apple’s Hypertext Transfer Protocol (HTTP) Live Streaming (HLS). Each segment is independently playable, and does not depend on a manifest file, resulting in greatly improved power performance. My work was to show that WVSNP-DASH is capable of further power savings at the level of the wireless sensor node itself if a native capture program is implemented at the camera sensor node. I created a native capture program in the C language that fulfills the name-based segmentation requirements of WVSNP-DASH. I present this program with intent to measure its power consumption on a hardware test-bed in future. To my knowledge, this is the first program to generate WVSNP-DASH playable video segments. The results show that our program could be utilized by WVSNP-DASH, but there are issues with the efficiency, so provided are an additional outline for further improvements.Dissertation/ThesisMasters Thesis Computer Engineering 201

Design and performance analysis of a super-scalar video-on-demand system.

Lee Chung Hing.Thesis (M.Phil.)--Chinese University of Hong Kong, 2001.Includes bibliographical references (leaves 61-63).Abstracts in English and Chinese.Acknowledgements --- p.iiAbstract --- p.iiiList of Figures --- p.viiChapter 1. --- Introduction --- p.1Chapter 1.1 --- Contributions of This Thesis --- p.3Chapter 1.2 --- Organizations of This Thesis --- p.3Chapter 1.3 --- Publication --- p.4Chapter 2. --- Overview of VoD Systems --- p.5Chapter 2.1 --- True VoD --- p.6Chapter 2.2 --- Near VoD --- p.7Chapter 2.3 --- Related Works --- p.9Chapter 2.3.1 --- Batching --- p.9Chapter 2.3.2 --- Patching --- p.11Chapter 2.3.3 --- Mcache --- p.11Chapter 2.3.4 --- Unified VoD --- p.12Chapter 2.4 --- Discussions --- p.15Chapter 3. --- Super-Scalar Architecture --- p.17Chapter 3.1 --- Transmission Scheduling --- p.20Chapter 3.2 --- Admission Control --- p.21Chapter 3.3 --- Channel Merging --- p.26Chapter 3.4 --- Interactive Control --- p.29Chapter 4. --- Performance Modeling --- p.31Chapter 4.1 --- Waiting Time for Statically-Admitted Clients --- p.32Chapter 4.2 --- Waiting Time for Dynamically-Admitted Clients --- p.33Chapter 4.3 --- Admission Threshold --- p.38Chapter 4.4 --- Channel Partitioning --- p.39Chapter 5. --- Performance Evaluation --- p.40Chapter 5.1 --- Model Validation --- p.40Chapter 5.2 --- Channel Partitioning --- p.42Chapter 5.3 --- Latency Comparisons --- p.44Chapter 5.4 --- Channel Requirement --- p.46Chapter 5.5 --- Performance at Light Loads --- p.47Chapter 5.6 --- Multiplexing Gain --- p.49Chapter 6. --- Implementation and Benchmarking --- p.51Chapter 6.1 --- Implementation Description --- p.51Chapter 6.2 --- Benchmarking --- p.53Chapter 6.2.1 --- Benchmarking Setup --- p.53Chapter 6.2.2 --- Benchmarking Result --- p.55Chapter 7. --- Conclusion --- p.56Appendix --- p.57Bibliography --- p.6

RTSP-based Mobile Peer-to-Peer Streaming System

Peer-to-peer is emerging as a potentially disruptive technology for content distribution in the mobile Internet. In addition to the already well-known peer-to-peer file sharing, real-time peer-to-peer streaming is gaining popularity. This paper presents an effective real-time peer-to-peer streaming system for the mobile environment. The basis for the system is a scalable overlay network which groups peer into clusters according to their proximity using RTT values between peers as a criteria for the cluster selection. The actual media delivery in the system is implemented using the partial RTP stream concept: the original RTP sessions related to a media delivery are split into a number of so-called partial streams according to a predefined set of parameters in such a way that it allows low-complexity reassembly of the original media session in real-time at the receiving end. Partial streams also help in utilizing the upload capacity with finer granularity than just per one original stream. This is beneficial in mobile environments where bandwidth can be scarce

Provider-Controlled Bandwidth Management for HTTP-based Video Delivery

Over the past few years, a revolution in video delivery technology has taken place as mobile viewers and over-the-top (OTT) distribution paradigms have significantly changed the landscape of video delivery services. For decades, high quality video was only available in the home via linear television or physical media. Though Web-based services brought video to desktop and laptop computers, the dominance of proprietary delivery protocols and codecs inhibited research efforts. The recent emergence of HTTP adaptive streaming protocols has prompted a re-evaluation of legacy video delivery paradigms and introduced new questions as to the scalability and manageability of OTT video delivery. This dissertation addresses the question of how to enable for content and network service providers the ability to monitor and manage large numbers of HTTP adaptive streaming clients in an OTT environment. Our early work focused on demonstrating the viability of server-side pacing schemes to produce an HTTP-based streaming server. We also investigated the ability of client-side pacing schemes to work with both commodity HTTP servers and our HTTP streaming server. Continuing our client-side pacing research, we developed our own client-side data proxy architecture which was implemented on a variety of mobile devices and operating systems. We used the portable client architecture as a platform for investigating different rate adaptation schemes and algorithms. We then concentrated on evaluating the network impact of multiple adaptive bitrate clients competing for limited network resources, and developing schemes for enforcing fair access to network resources. The main contribution of this dissertation is the definition of segment-level client and network techniques for enforcing class of service (CoS) differentiation between OTT HTTP adaptive streaming clients. We developed a segment-level network proxy architecture which works transparently with adaptive bitrate clients through the use of segment replacement. We also defined a segment-level rate adaptation algorithm which uses download aborts to enforce CoS differentiation across distributed independent clients. The segment-level abstraction more accurately models application-network interactions and highlights the difference between segment-level and packet-level time scales. Our segment-level CoS enforcement techniques provide a foundation for creating scalable managed OTT video delivery services