Exploring the design space of cooperative streaming multicast

Video streaming over the Internet is rapidly rising in popularity, but the availability and quality of video content is currently limited by the high bandwidth costs and infrastructure needs of server-based solutions. Recently, however, cooperative end-system multicast (CEM) has emerged as a promising paradigm for content distribution in the Internet, because the bandwidth overhead of disseminating content is shared among the participants of the CEM overlay network. In this thesis, we identify the dimensions in the design space of CEMs, explore the design space, and seek to understand the inherent tradeoffs of different design choices. In the first part of the thesis, we study the control mechanisms for CEM overlay maintenance. We demonstrate that the control task of neighbor acquisition in CEMs can be factored out into a separate control overlay that provides a single primitive: a configurable anycast for peer selection. The separation of control from data overlay avoids the efficiency tradeoffs that afflict some of the current systems. The anycast primitive can be used to build and maintain different data overlay organizations like single-tree, multi-tree, mesh-based, and hybrids, by expressing appropriate policies. We built SAAR, a reusable, shared control overlay for CEMs, that efficiently implements this anycast primitive, and thereby, efficiently serves the control needs for CEMs. In the second part of the thesis, we focus on techniques for data dissemination. We built a common framework in which different CEM data delivery techniques can be faithfully compared. A systematic empirical comparison of CEM design choices demonstrates that there is no single approach that is best in all scenarios. In fact, our results suggest that every CEM protocol is inherently limited in certain aspects of its performance. We distill our observations into a novel model that explains the inherent tradeoffs of CEM design choices and provides bounds on the practical performance limits of any future CEM protocol. In particular, the model asserts that no CEM design can simultaneously achieve all three of low overhead, low lag, and high streaming quality

Network coding-based channel quality indicator reporting for two-way multi-relay networks

This paper considers channel quality indicator (CQI) reporting for data exchange in a two-way multi-relay network. We first propose an efficient CQI reporting scheme based on network coding, where two terminals are allowed to simultaneously estimate the CQI of the distant terminal-relay link without suffering from additional overhead. In addition, the transmission time for CQI feedback at the relays is reduced by half while the increase in complexity and the loss of performance are negligible. This results in a system throughput improvement of 16.7% with our proposed CQI reporting. Upper and lower bounds of the mean square error (MSE) of the estimated CQI are derived to study performance behaviour of our proposed scheme. It is found that the MSE of the estimated CQI increases proportionally with the square of the cardinality of CQI level sets although an increased number of CQI levels would eventually lead to a higher data rate transmission. On the basis of the derived bounds, a low-complexity relay selection (RS) scheme is then proposed. Simulation results show that, in comparison with optimal methods, our suboptimal bound-based RS scheme achieves satisfactory performance while reducing the complexity at least three times in case of large number of relays

Partial network coding: Theory and application for continuous sensor data collection

Abstract — Wireless sensor networks have been widely used for surveillance in harsh environments. In many such applications, the environmental data are continuously sensed, and data collection by a server is only performed occasionally. Hence, the sensor nodes have to temporarily store the data, and provide easy and on-hand access for the most updated data when the server approaches. Given the expensive server-to-sensor communications, the large amount of sensors and the limited storage space at each tiny sensor, continuous data collection becomes a challenging problem. In this paper, we present partial network coding (PNC) as a generic tool for the above applications. PNC generalizes the existing network coding (NC) paradigm, an elegant solution for ubiquitous data distribution and collection. Yet, PNC enables efficient storage replacement for continuous data, which is a major deficiency of the conventional NC. We prove that the performance of PNC is quite close to NC, except for a sublinear overhead on storage and communications. We then address a set of practical concerns toward PNC-based continuous data collection in sensor networks. Its feasibility and superiority are further demonstrated through simulation results. I

QoE in Pull Based P2P-TV Systems: Overlay Topology Design Tradeoff

Abstract—This paper presents a systematic performance anal-ysis of pull P2P video streaming systems for live applications, providing guidelines for the design of the overlay topology and the chunk scheduling algorithm. The contribution of the paper is threefold: 1) we propose a realistic simulative model of the system that represents the effects of access bandwidth heterogeneity, latencies, peculiar characteristics of the video, while still guaranteeing good scalability properties; 2) we propose a new latency/bandwidth-aware overlay topology design strategy that improves application layer performance while reducing the underlying transport network stress; 3) we investigate the impact of chunk scheduling algorithms that explicitly exploit properties of encoded video. Results show that our proposal jointly improves the actual Quality of Experience of users and reduces the cost the transport network has to support. I

Data aggregation techniques in sensor networks: A survey

Wireless sensor networks consist of sensor nodes with sensing and communication capabilities. We focus on data aggregation problems in energy constrained sensor networks. The main goal of data aggregation algorithms is to gather and aggregate data in an energy efficient manner so that network lifetime is enhanced. In this paper, we present a survey of data aggregation algorithms in wireless sensor networks. We compare and contrast different algorithms on the basis of performance measures such as lifetime, latency and data accuracy. We conclude with possible future research directions