A paracasting model for concurrent access to replicated content

We propose a framework to study how to download effectively a copy of the same document from a set of replicated servers. A generalized application-layer anycasting, known as paracasting, has been proposed to advocate concurrent access of a subset of replicated servers to satisfy cooperatively a client's request. Each participating server satisfies the request in part by transmitting a subset of the requested file to the client. The client can recover the complete file when different parts of the file sent from the participating servers are received. This framework allows us to estimate the average time to download a file from the set of homogeneous replicated servers, and the request blocking probability when each server can accept and serve a finite number of concurrent. requests. Our results show that the file download time drops when a request is served concurrently by a larger number of homogeneous replicated servers, although the performance improvement quickly saturates when the number of servers used increases. If the total number of requests that a server can handle simultaneously is finite, the request blocking probability increases with the number of replicated servers used to serve a request concurrently. Therefore, paracasting is effective in using a small number of servers, say, up to four, to serve a request concurrently.published_or_final_versio

Multi-path streaming and dynamic end-point adaptation.

Tung, Tak Fu.Thesis (M.Phil.)--Chinese University of Hong Kong, 2002.Includes bibliographical references (leaves 66-68).Abstracts in English and Chinese.Chapter 1 --- Introduction to Multi-path Streaming and Dynamic End-point Adaptation --- p.1Chapter 1.1 --- Multi-path Streaming --- p.2Chapter 1.2 --- Dynamic End-point Adaptation --- p.4Chapter 2 --- Related Work --- p.6Chapter 3 --- Path Loss Model --- p.10Chapter 3.1 --- Bursty Loss --- p.10Chapter 3.2 --- Gilbert Model --- p.11Chapter 3.2.1 --- Discrete-time Gilbert Model --- p.11Chapter 3.2.2 --- Continuous-time Gilbert Model --- p.12Chapter 4 --- Loss RecoveryChapter 4.1 --- Automatic Repeat Request (ARQ) --- p.17Chapter 4.2 --- Forward Error Correction (FEC) --- p.18Chapter 5 --- Connection Adaptation --- p.23Chapter 5.1 --- Path Quality --- p.23Chapter 5.2 --- Effect of Shared Congestion Point --- p.24Chapter 5.2.1 --- Point-of-Congestion Detection --- p.25Chapter 5.3 --- Load Distribution --- p.27Chapter 6 --- Analytical Evaluation --- p.28Chapter 6.1 --- Performance Analysis of SP vs. Multi-path Streaming (without FEC) --- p.29Chapter 6.2 --- Performance Analysis of SP vs. Multi-path Streaming (with FEC) --- p.36Chapter 7 --- Experiments and Simulations --- p.42Chapter 7.1 --- Effect of Correlated Bursty Losses on Video Quality --- p.42Chapter 7.2 --- Analytical Model Based Evaluation --- p.44Chapter 7.2.1 --- Data Loss Rate --- p.44Chapter 7.2.2 --- Data Loss Rate as a function of FEC parameters --- p.46Chapter 7.2.3 --- Conditional Error Burst Length --- p.48Chapter 7.2.4 --- Lag-1 Autocorrelation --- p.49Chapter 7.2.5 --- Effects of Load Distribution Among Senders --- p.50Chapter 7.2.6 --- Sensitivity Analysis --- p.51Chapter 7.2.7 --- Effects of Shared Points of Congestion on Various Perfor- mance Metrics --- p.53Chapter 7.3 --- Simulation Model Based Evaluation --- p.55Chapter 7.3.1 --- Simulation Setup --- p.55Chapter 7.3.2 --- Data Loss Rate --- p.57Chapter 7.3.3 --- Data Loss Rate as a function of FEC parameters --- p.58Chapter 7.3.4 --- Conditional Error Burst Length --- p.59Chapter 7.3.5 --- Lag-1 Autocorrelation --- p.60Chapter 7.3.6 --- Effects of Load Distribution among Senders --- p.61Chapter 7.3.7 --- Sensitivity Analysis --- p.62Chapter 7.3.8 --- Effects of Shared Points of Congestion on Various Perfor- mance Metrics --- p.63Chapter 8 --- Conclusion --- p.6

A system for improving the quality of real-time services on the internet

Real-time Internet services are becoming more popular every day, and Voice over Internet Protocol (VOIP) is arguably the most popular of these, despite the quality and reliability problems that are so characteristic of VOIP. This thesis proposes to apply a routing technique called Fully Redundant Dispersity Routing to VOIP and shows how this mitigates these problems to deliver a premium service that is more equal to traditional telephony than VOIP is currently.Fully Redundant Dispersity Routing uses the path diversity readily available in the Internet to route complete copies of the data to be communicated over multiple paths. This allows the effect of a failure on a path to be reduced, and possibly even masked completely, by the other paths. Significantly, rather than expecting changes of the Internet that will improve real-time service quality, this approach simply changes the manner in which real-time services use the Internet, leaving the Internet itself to stay the way it is.First, real VOIP traffic in a commercial call centre is measured (1) to establish a baseline of current quality characteristics against which the effects of Fully Redundant Dispersity Routing may be measured, and (2) as a source of realistic path characteristics. Simulations of various Fully Redundant Dispersity Routing systems that adopt the measured VOIP traffic characteristics then (1) show how this routing technique mitigates quality and reliability problems, and (2) quantify the quality deliverable with the VOIP traffic characteristics measured. For example, quantifying quality as a Mean Opinion Score (MOS) estimated from the measurements with the International Telecommunication Union’s E-model, slightly more than 1 in every 23 of the VOIP telephone calls measured in the call centre is likely to be perceived to be of a quality with which humans would be less than very satisfied. Simulations carried out for this thesis show that using just two paths adopting the same measurements, Fully Redundant Dispersity Routing may increase quality to reduce that proportion to slightly less than 1 in every 10 000 VOIP telephone calls

Lifetime and latency aware data collection in wireless sensor networks

A Wireless Sensor Network (WSN) consists of a set of sensor nodes deployed in the environment where we intend to collect physical information such as temperatures. All the senor nodes are connected wirelessly, and work cooperatively to fulfill some specified tasks. Sensor nodes are typically battery powered. As a result, the network lifetime becomes a major optimization objective in the design of a WSN. Another important optimisation objective is to minimize the maximum latency of data collection for time-critical applications. In this thesis, we study the problem of lifetime and latency aware data collection in a static WSN with only one base station. We propose two novel routing structures, namely, k-tree and k-DAG, to balance the loads of the neighbouring sensor nodes of the base station to prolong the lifetime of the network while providing the maximum latency guarantee. Firstly, we investigate the lifetime aware data collection problem by using ktree. A k-tree is a spanning tree with the base station as the root such that the path from each sensor node to the base station is at most k hops longer than the shortest path from this sensor node to the base station. We propose a distributed algorithm for constructing a k-tree such that the loads of the base station s children are balanced. Secondly, we study the lifetime aware data collection problem by using k-DAG. A k-DAG is a spanning Directed Acyclic Graph (DAG) with the base station as the only source node such that the path length of any path from each sensor node to the base station is not k hops longer than its shortest path length to the base station. We present a distributed algorithm for constructing a k-DAG such that the loads of the base station s children are balanced. In addition, we propose an efficient distributed naming scheme to assign a unique ID to each sensor node for efficient point-to-point communication. We have implemented all of our algorithms by Cooja simulator. The simulation results show that our approaches significantly increase the network lifetime by up to 82%

Multi-path multimedia streaming system: adaptation and optimization.

Chow Lik Hang.Thesis (M.Phil.)--Chinese University of Hong Kong, 2003.Includes bibliographical references (leaves 100-102).Abstracts in English and Chinese.Chapter 1 --- Introduction --- p.1Chapter 1.1 --- Multimedia Streaming Background --- p.2Chapter 1.2 --- Streaming over the Internet --- p.2Chapter 1.3 --- Traditional Approaches --- p.4Chapter 1.4 --- Document Road-map --- p.6Chapter 2 --- Related Work --- p.8Chapter 3 --- Our Multi-path Streaming Approach --- p.11Chapter 3.1 --- Potential Benefits --- p.14Chapter 3.2 --- Performance Metrics --- p.15Chapter 3.3 --- Visual Quality of Data --- p.15Chapter 3.3.1 --- Experiment: Effect of Correlated Bursty Losses on Video Quality --- p.16Chapter 4 --- Performance Evaluation using Gilbert Model --- p.18Chapter 4.1 --- Mathematical analysis --- p.18Chapter 4.1.1 --- Model --- p.19Chapter 4.1.2 --- Performance Analysis of SP vs. Multi-path Streaming (without FEC) --- p.20Chapter 4.1.3 --- Performance Analysis of SP vs. Multi-path Streaming (with FEC) --- p.26Chapter 4.2 --- Analytical Model Based Evaluation --- p.32Chapter 5 --- Functional Gilbert Model and Optimization --- p.45Chapter 5.1 --- Functional Gilbert Model --- p.45Chapter 5.2 --- Optimal Traffic Splitting --- p.48Chapter 5.2.1 --- Optimization Based on Achieved Loss Rate --- p.49Chapter 5.2.2 --- Optimization Based on Lag-1 Autocorrelation --- p.54Chapter 5.3 --- Experiments --- p.58Chapter 5.3.1 --- Type A Experiment: Without an Erasure Code --- p.59Chapter 5.3.2 --- Type B Experiment: with an Erasure Code --- p.62Chapter 6 --- NS Simulations --- p.68Chapter 6.1 --- Simulation Setup --- p.68Chapter 6.2 --- Simulation Result --- p.70Chapter 7 --- Quantization of Traffic Splitting Vector --- p.80Chapter 8 --- Prototype Implementation and Experiments --- p.86Chapter 8.1 --- Multi-path Streaming Prototype --- p.86Chapter 8.2 --- Experiments --- p.87Chapter 9 --- Other Design Issues and Considerations --- p.93Chapter 9.1 --- Requirements and Overheads --- p.93Chapter 9.2 --- Share Point of Congestion (SPOC) --- p.96Chapter 10 --- Conclusion --- p.98Bibliography --- p.10