With advances in microelectronic and wireless communication technologies, smartphones have computer-like capabilities in terms of computing power and communication bandwidth. They allow users to use advanced applications that used to be run on computers only. Web browsing, email fetching, gaming, social networking, and multimedia streaming are examples of wide-spread smartphone applications. Unsurprisingly, network-related applications are dominant in the realm of smartphones. Users love to be connected while they are mobile. Streaming applications, as a part of network-related applications, are getting increasingly popular. Mobile TV, video on demand, and video sharing are some popular streaming services in the mobile world. Thus, the expected operational time of smartphones is rising rapidly. On the other hand, the enormous growth of smartphone applications and services adds up to a significant increase in complexity in the context of computation and communication needs, and thus there is a growing demand for energy in smartphones. Unlike the exponential growth in computing and communication technologies, the growth in battery technologies is not keeping up with the rapidly growing energy demand of these devices. Therefore, the smartphone's utility has been severely constrained by its limited battery lifetime. It is very important to conserve the smartphone's battery power. Even though hardware components are the actual energy consumers, software applications utilize the hardware components through the operating system. Thus, by making smartphone applications energy-efficient, the battery lifetime can be extended. With this view, this work focuses on two main problems: i) developing an energy testing methodology for smartphone applications, and ii) evaluating the energy cost and designing an energy-friendly downloader for smartphone streaming applications. The detailed contributions of this thesis are as follows: (i) it gives a generalized framework for energy performance testing and shows a detailed flowchart that application developers can easily follow to test their applications; (ii) it evaluates the energy cost of some popular streaming applications showing how the download strategy that an application developer adopts may adversely affect the energy savings; (iii) it develops a model of an energy-friendly downloader for streaming applications and studies the effects of the downloader's parameters regarding energy consumption; and finally, (iv) it gives a mathematical model for the proposed downloader and validates it by means of experiments.

Peer-to-peer streaming has emerged as a killer application in today's Internet, delivering a large variety of live multimedia content to millions of users at any given time with low server cost. Though successfully deployed, the efficiency and optimality of the current peer-to-peer streaming protocols are still less than satisfactory. In this thesis, we investigate optimizing solutions to enhance the performance of the state-of-the-art mesh-based peer-to-peer streaming systems, utilizing both theoretical performance modeling and extensive real-world measurements. First, we model peer-to-peer streaming applications in both the single-overlay and multi-overlay scenarios, based on the solid foundation of optimization and game theories. Using these models, we design efficient and fully decentralized solutions to achieve performance optimization in peer-to-peer streaming. Then, based on a large volume of live measurements from a commercial large-scale peer-to-peer streaming application, we extensively study the real-world performance of peer-to-peer streaming over a long period of time. Highlights of our measurement study include the topological characterization of large-scale streaming meshes, the statistical characterization of inter-peer bandwidth availability, and the investigation of server capacity utilization in peer-to-peer streaming. Utilizing in-depth insights from our measurements, we design practical algorithms that advance the performance of key protocols in peer-to-peer live streaming. We show that our optimizing solutions fulfill their design objectives in various realistic scenarios, using extensive simulations and experiments.

This dissertation was motivated by the exponential growth in bandwidth capacity of the Internet, coupled with the immense growth of broadband adoption by the public. This has led to the development of a wide variety of new online services. Chief amongst the emerging applications is the delivery of multimedia contents to the end users via the network on-demand. It is the “on-demand” aspect that has led to problems which, despite the advances in hardware technology and network capacity, have hampered wide scale adoption of multimedia delivery. The focus of this dissertation was to address these problems, namely: scalability, cost-effectiveness, and network quality of service for timely presentation of multimedia contents. We proposed an architecture, which we referred to as “Delayed-Multicast”, to address the scalability problem. The new architecture introduced buffers within the network to reduce demands on core network bandwidth and server load. A feasibility study of the architecture was conducted through the use of a prototype. It was found that such a system is within reach by demonstrating the prototype using cheap, common-of-the-shelf (COTS) components, and with help of freely available system software such Linux with real-time support. The introduction of buffers within the network led to the requirement of how to minimize buffer space. We developed an optimal algorithm for allocating buffer space in a single level caching layout (i.e. only one buffer in the transmission path from the server to the end user). For the case of multi-levels network caching, we thoroughly examined different optimization problems from an algorithmic perspective. These problems included how to minimize total system memory, and minimize the maximum memory used per node. We proved that determining the optimal buffer allocation in many of these iv v cases is an NP-complete problem. Consequently, we developed heuristics to handle multi-level caching and showed through simulations that the heuristics greatly help in minimizing buffer space and network bandwidth requirement. An important aspect of the heuristics was how to handle the case when the arrival times of client requests were not known a priori. For these “online” problems we also proposed heuristics that can significantly reduce overall system resource requirements. If the cost of buffer space was also taken into account along with the cost of network bandwidth, a different optimization problem was how to minimize the total system cost. Here, we also proposed heuristics, which in simulations show that the total system cost can be significantly reduced. Besides the problems associated with resource allocation, in terms of buffer space and bandwidth, we also examined the problem of how to provision the necessary network quality of service on-demand. Most current networks rely on best-effort delivery which is ill suited for the delivery of multimedia traffic. We proposed a solution which relied on the use of a programmable network plane, that is present in many current routers, to dynamically alter the priority of flows within the network in real-time. We also demonstrated the effectiveness of the flow prioritization on an actual Nortel router. Finally, we examined the problem of how to admit and achieve fair bandwidth allocation for the end-users within a Differentiated Service (DiffServ) network. Diff- Serv is an IETF standard that aims to provide a “better than best-effort” network in a scalable manner, and is used widely, especially within the same autonomous domain for prioritization different classes of traffic. However, there are open problems on how to provide fair bandwidth allocation amongst competing flows. We proposed an edge-aware resource discovery loop, which as the name suggests, sent packets to gather information about the internal states of the core network. With this information, we proposed a price-based admission control algorithm for use within the DiffServ network that would allow fair admission, effective congestion control, and fair bandwidth allocation amongst different traffic flows.

Thesis (Ph.D.)--Hong Kong University of Science and Technology, 2008. / Vita. Includes bibliographical references (leaves 113-120). Also available in electronic version.

Thesis (M.A.). / Written for the Dept. of Art History and Communication Studies [Communications Graduate Program]. Title from title page of PDF (viewed 2008/05/12). Includes bibliographical references.

Thesis (Ph. D.)--Computing, Georgia Institute of Technology, 2007. / Committee Chair: Dovrolis, Constantine; Committee Member: Ammar, Mostafa; Committee Member: Schwan, Karsten; Committee Member: Steenkiste, Peter; Committee Member: Zegura, Ellen.

Thesis (Ph.D.)--Hong Kong University of Science and Technology, 2008. / Includes bibliographical references (leaves 91-96). Also available in electronic version.

Thesis (M.Phil.)--Hong Kong University of Science and Technology, 2008. / Includes bibliographical references (leaves 70-75). Also available in electronic version.

Thesis (M.Eng.(Computer Engineering))--University of Pretoria, 2008. / Summaries in Afrikaans and English. Includes bibliographical references (leaves [152]-159).

Zugl.: München, Techn. Univ., Diss., 2007 / Hergestellt on demand