Crowdsourced Live Streaming over the Cloud

Empowered by today's rich tools for media generation and distribution, and the convenient Internet access, crowdsourced streaming generalizes the single-source streaming paradigm by including massive contributors for a video channel. It calls a joint optimization along the path from crowdsourcers, through streaming servers, to the end-users to minimize the overall latency. The dynamics of the video sources, together with the globalized request demands and the high computation demand from each sourcer, make crowdsourced live streaming challenging even with powerful support from modern cloud computing. In this paper, we present a generic framework that facilitates a cost-effective cloud service for crowdsourced live streaming. Through adaptively leasing, the cloud servers can be provisioned in a fine granularity to accommodate geo-distributed video crowdsourcers. We present an optimal solution to deal with service migration among cloud instances of diverse lease prices. It also addresses the location impact to the streaming quality. To understand the performance of the proposed strategies in the realworld, we have built a prototype system running over the planetlab and the Amazon/Microsoft Cloud. Our extensive experiments demonstrate that the effectiveness of our solution in terms of deployment cost and streaming quality

Optimized Adaptive Streaming Representations based on System Dynamics

Adaptive streaming addresses the increasing and heterogenous demand of multimedia content over the Internet by offering several encoded versions for each video sequence. Each version (or representation) has a different resolution and bit rate, aimed at a specific set of users, like TV or mobile phone clients. While most existing works on adaptive streaming deal with effective playout-control strategies at the client side, we take in this paper a providers' perspective and propose solutions to improve user satisfaction by optimizing the encoding rates of the video sequences. We formulate an integer linear program that maximizes users' average satisfaction, taking into account the network dynamics, the video content information, and the user population characteristics. The solution of the optimization is a set of encoding parameters that permit to create different streams to robustly satisfy users' requests over time. We simulate multiple adaptive streaming sessions characterized by realistic network connections models, where the proposed solution outperforms commonly used vendor recommendations, in terms of user satisfaction but also in terms of fairness and outage probability. The simulation results further show that video content information as well as network constraints and users' statistics play a crucial role in selecting proper encoding parameters to provide fairness a mong users and to reduce network resource usage. We finally propose a few practical guidelines that can be used to choose the encoding parameters based on the user base characteristics, the network capacity and the type of video content

Delivering Live Multimedia Streams to Mobile Hosts in a Wireless Internet with Multiple Content Aggregators

We consider the distribution of channels of live multimedia content (e.g., radio or TV broadcasts) via multiple content aggregators. In our work, an aggregator receives channels from content sources and redistributes them to a potentially large number of mobile hosts. Each aggregator can offer a channel in various configurations to cater for different wireless links, mobile hosts, and user preferences. As a result, a mobile host can generally choose from different configurations of the same channel offered by multiple alternative aggregators, which may be available through different interfaces (e.g., in a hotspot). A mobile host may need to handoff to another aggregator once it receives a channel. To prevent service disruption, a mobile host may for instance need to handoff to another aggregator when it leaves the subnets that make up its current aggregator�s service area (e.g., a hotspot or a cellular network).\ud In this paper, we present the design of a system that enables (multi-homed) mobile hosts to seamlessly handoff from one aggregator to another so that they can continue to receive a channel wherever they go. We concentrate on handoffs between aggregators as a result of a mobile host crossing a subnet boundary. As part of the system, we discuss a lightweight application-level protocol that enables mobile hosts to select the aggregator that provides the �best� configuration of a channel. The protocol comes into play when a mobile host begins to receive a channel and when it crosses a subnet boundary while receiving the channel. We show how our protocol can be implemented using the standard IETF session control and description protocols SIP and SDP. The implementation combines SIP and SDP�s offer-answer model in a novel way

Survey of End-to-End Mobile Network Measurement Testbeds, Tools, and Services

Mobile (cellular) networks enable innovation, but can also stifle it and lead to user frustration when network performance falls below expectations. As mobile networks become the predominant method of Internet access, developer, research, network operator, and regulatory communities have taken an increased interest in measuring end-to-end mobile network performance to, among other goals, minimize negative impact on application responsiveness. In this survey we examine current approaches to end-to-end mobile network performance measurement, diagnosis, and application prototyping. We compare available tools and their shortcomings with respect to the needs of researchers, developers, regulators, and the public. We intend for this survey to provide a comprehensive view of currently active efforts and some auspicious directions for future work in mobile network measurement and mobile application performance evaluation.Comment: Submitted to IEEE Communications Surveys and Tutorials. arXiv does not format the URL references correctly. For a correctly formatted version of this paper go to http://www.cs.montana.edu/mwittie/publications/Goel14Survey.pd

A Marketplace for Efficient and Secure Caching for IoT Applications in 5G Networks

As the communication industry is progressing towards fifth generation (5G) of cellular networks, the traffic it carries is also shifting from high data rate traffic from cellular users to a mixture of high data rate and low data rate traffic from Internet of Things (IoT) applications. Moreover, the need to efficiently access Internet data is also increasing across 5G networks. Caching contents at the network edge is considered as a promising approach to reduce the delivery time. In this paper, we propose a marketplace for providing a number of caching options for a broad range of applications. In addition, we propose a security scheme to secure the caching contents with a simultaneous potential of reducing the duplicate contents from the caching server by dividing a file into smaller chunks. We model different caching scenarios in NS-3 and present the performance evaluation of our proposal in terms of latency and throughput gains for various chunk sizes