Scalable reliable on-demand media streaming protocols

This thesis considers the problem of delivering streaming media, on-demand, to potentially large numbers of concurrent clients. The problem has motivated the development in prior work of scalable protocols based on multicast or broadcast. However, previous protocols do not allow clients to efficiently: 1) recover from packet loss; 2) share bandwidth fairly with competing flows; or 3) maximize the playback quality at the client for any given client reception rate characteristics. In this work, new protocols, namely Reliable Periodic Broadcast (RPB) and Reliable Bandwidth Skimming (RBS), are developed that efficiently recover from packet loss and achieve close to the best possible server bandwidth scalability for a given set of client characteristics. To share bandwidth fairly with competing traffic such as TCP, these protocols can employ the Vegas Multicast Rate Control (VMRC) protocol proposed in this work. The VMRC protocol exhibits TCP Vegas-like behavior. In comparison to prior rate control protocols, VMRC provides less oscillatory reception rates to clients, and operates without inducing packet loss when the bottleneck link is lightly loaded. The VMRC protocol incorporates a new technique for dynamically adjusting the TCP Vegas threshold parameters based on measured characteristics of the network. This technique implements fair sharing of network resources with other types of competing flows, including widely deployed versions of TCP such as TCP Reno. This fair sharing is not possible with the previously defined static Vegas threshold parameters. The RPB protocol is extended to efficiently support quality adaptation. The Optimized Heterogeneous Periodic Broadcast (HPB) is designed to support a range of client reception rates and efficiently support static quality adaptation by allowing clients to work-ahead before beginning playback to receive a media file of the desired quality. A dynamic quality adaptation technique is developed and evaluated which allows clients to achieve more uniform playback quality given time-varying client reception rates

Design and implementation of a consonant broadcasting architecture for large-scale video streaming.

Liu Wing Chun.Thesis submitted in: July 2003.Thesis (M.Phil.)--Chinese University of Hong Kong, 2004.Includes bibliographical references (leaves 55-57).Abstracts in English and Chinese.Acknowledgement --- p.IAbstract --- p.II摘要 --- p.IIIChapter Chapter 1 --- Introduction --- p.1Chapter Chapter 2 --- Related Works --- p.5Chapter 2.1 --- Fixed-Segment Fixed-Bandwidth Schemes --- p.6Chapter 2.2 --- Variable-Segment Fixed-Bandwidth Schemes --- p.7Chapter 2.3 --- Fixed-Segment Variable-Bandwidth Schemes --- p.8Chapter 2.4 --- Variable-Segment Variable-Bandwidth Schemes --- p.9Chapter 2.5 --- Performance Bounds of Periodic Broadcastings --- p.10Chapter Chapter 3 --- Consonant Broadcasting --- p.12Chapter 3.1 --- Type-I Channels --- p.14Chapter 3.2 --- Type-II Channels --- p.15Chapter 3.3 --- Client Buffer --- p.17Chapter Chapter 4 --- Performance Evaluation --- p.19Chapter 4.1 --- Startup Latency versus Network Bandwidth --- p.20Chapter 4.2 --- Startup Latency versus Client Access Bandwidth --- p.22Chapter 4.3 --- Client Buffer Requirement --- p.24Chapter Chapter 5 --- Grouped Consonant Broadcasting --- p.25Chapter 5.1 --- Bandwidth Partitioning and Reception Schedule --- p.26Chapter 5.2 --- Client Buffer Requirement --- p.28Chapter 5.3 --- Performance Tradeoffs --- p.30Chapter Chapter 6 --- Implementation and Benchmarking --- p.34Chapter 6.1 --- Practical Issues --- p.35Chapter 6.2 --- Experimental Results --- p.36Chapter Chapter 7 --- Dynamic Consonant Broadcasting --- p.39Chapter 7.1 --- Virtual Transmission Schedules --- p.40Chapter 7.2 --- Dynamic Broadcasting Schedules --- p.42Chapter 7.3 --- Performance Evaluation --- p.44Chapter Chapter 8 --- Variable-bit-rate Video Streaming --- p.46Chapter 8.1 --- Transmission Schedules --- p.46Chapter 8.2 --- Playback Continuity --- p.48Chapter 8.3 --- Performance Evaluation --- p.50Chapter Chapter 9 --- Conclusions --- p.53Bibliography --- p.5

Smart PIN: performance and cost-oriented context-aware personal information network

The next generation of networks will involve interconnection of heterogeneous individual networks such as WPAN, WLAN, WMAN and Cellular network, adopting the IP as common infrastructural protocol and providing virtually always-connected network. Furthermore, there are many devices which enable easy acquisition and storage of information as pictures, movies, emails, etc. Therefore, the information overload and divergent content’s characteristics make it difficult for users to handle their data in manual way. Consequently, there is a need for personalised automatic services which would enable data exchange across heterogeneous network and devices. To support these personalised services, user centric approaches for data delivery across the heterogeneous network are also required. In this context, this thesis proposes Smart PIN - a novel performance and cost-oriented context-aware Personal Information Network. Smart PIN's architecture is detailed including its network, service and management components. Within the service component, two novel schemes for efficient delivery of context and content data are proposed: Multimedia Data Replication Scheme (MDRS) and Quality-oriented Algorithm for Multiple-source Multimedia Delivery (QAMMD). MDRS supports efficient data accessibility among distributed devices using data replication which is based on a utility function and a minimum data set. QAMMD employs a buffer underflow avoidance scheme for streaming, which achieves high multimedia quality without content adaptation to network conditions. Simulation models for MDRS and QAMMD were built which are based on various heterogeneous network scenarios. Additionally a multiple-source streaming based on QAMMS was implemented as a prototype and tested in an emulated network environment. Comparative tests show that MDRS and QAMMD perform significantly better than other approaches

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