Securing Media for Adaptive Streaming

This paper describes the ARMS system which enables secure and adaptive rich media streaming to a large-scale, heterogeneous client population. The secure streaming algorithms ensure end-to-end security while the content is adapted and streamed via intermediate, potentially untrusted servers. ARMS streaming is completely standards compliant and to our knowledge is the first such end-to-end MPEG-4-based system

Reflections on security options for the real-time transport protocol framework

The Real-time Transport Protocol (RTP) supports a range of video conferencing, telephony, and streaming video ap- plications, but offers few native security features. We discuss the problem of securing RTP, considering the range of applications. We outline why this makes RTP a difficult protocol to secure, and describe the approach we have recently proposed in the IETF to provide security for RTP applications. This approach treats RTP as a framework with a set of extensible security building blocks, and prescribes mandatory-to-implement security at the level of different application classes, rather than at the level of the media transport protocol

The Road Ahead for Networking: A Survey on ICN-IP Coexistence Solutions

In recent years, the current Internet has experienced an unexpected paradigm shift in the usage model, which has pushed researchers towards the design of the Information-Centric Networking (ICN) paradigm as a possible replacement of the existing architecture. Even though both Academia and Industry have investigated the feasibility and effectiveness of ICN, achieving the complete replacement of the Internet Protocol (IP) is a challenging task. Some research groups have already addressed the coexistence by designing their own architectures, but none of those is the final solution to move towards the future Internet considering the unaltered state of the networking. To design such architecture, the research community needs now a comprehensive overview of the existing solutions that have so far addressed the coexistence. The purpose of this paper is to reach this goal by providing the first comprehensive survey and classification of the coexistence architectures according to their features (i.e., deployment approach, deployment scenarios, addressed coexistence requirements and architecture or technology used) and evaluation parameters (i.e., challenges emerging during the deployment and the runtime behaviour of an architecture). We believe that this paper will finally fill the gap required for moving towards the design of the final coexistence architecture.Comment: 23 pages, 16 figures, 3 table

AngelCast: cloud-based peer-assisted live streaming using optimized multi-tree construction

Increasingly, commercial content providers (CPs) offer streaming solutions using peer-to-peer (P2P) architectures, which promises significant scalabil- ity by leveraging clients’ upstream capacity. A major limitation of P2P live streaming is that playout rates are constrained by clients’ upstream capac- ities – typically much lower than downstream capacities – which limit the quality of the delivered stream. To leverage P2P architectures without sacri- ficing quality, CPs must commit additional resources to complement clients’ resources. In this work, we propose a cloud-based service AngelCast that enables CPs to complement P2P streaming. By subscribing to AngelCast, a CP is able to deploy extra resources (angel), on-demand from the cloud, to maintain a desirable stream quality. Angels do not download the whole stream, nor are they in possession of it. Rather, angels only relay the minimal fraction of the stream necessary to achieve the desired quality. We provide a lower bound on the minimum angel capacity needed to maintain a desired client bit-rate, and develop a fluid model construction to achieve it. Realizing the limitations of the fluid model construction, we design a practical multi- tree construction that captures the spirit of the optimal construction, and avoids its limitations. We present a prototype implementation of AngelCast, along with experimental results confirming the feasibility of our service.Supported in part by NSF awards #0720604, #0735974, #0820138, #0952145, #1012798 #1012798 #1430145 #1414119. (0720604 - NSF; 0735974 - NSF; 0820138 - NSF; 0952145 - NSF; 1012798 - NSF; 1430145 - NSF; 1414119 - NSF

A Novel Framework to Select Intelligent Video Streaming Scheme for Learning Software as a Service

Cloud computing offers many benefits for government, business and educational institutions as exemplified in many cases. Options to deliver video streaming contents for educational purposes over cloud computing infrastructures are highlighted in this study. In such case, parameters that affect video quality directly or indirectly must be taken into account such as bandwidth, jitter and loss of data. Currently, several intelligent schemes to improve video streaming services have been proposed by researchers through different approaches. This study aims to propose a novel framework to select appropriate intelligent video streaming schemes for efficiently delivering educational video contents for Learning Software as a Service (LSaaS)

A Novel Framework to Select Intelligent Video Streaming Scheme for Learning Software as a Service

Cloud computing offers many benefits for government, business and educational institutions as exemplified in many cases. Options to deliver video streaming contents for educational purposes over cloud computing infrastructures are highlighted in this study. In such case, parameters that affect video quality directly or indirectly must be taken into account such as bandwidth, jitter and loss of data. Currently, several intelligent schemes to improve video streaming services have been proposed by researchers through different approaches. This study aims to propose a novel framework to select appropriate intelligent video streaming schemes for efficiently delivering educational video contents for Learning Software as a Service (LSaaS)

Decision Making Analysis of Video Streaming Algorithm for Private Cloud Computing Infrastructure

The issue on how to effectively deliver video streaming contents over cloud computing infrastructures is tackled in this study. Basically, quality of service of video streaming is strongly influenced by bandwidth, jitter and data loss problems. A number of intelligent video streaming algorithms are proposed by using different techniques to deal with such issues. This study aims to propose and demonstrate a novel decision making analysis which combines ISO 9126 (international standard for software engineering) and Analytic Hierarchy Process to help experts selecting the best video streaming algorithm for the case of private cloud computing infrastructure. The given case study concluded that Scalable Streaming algorithm is the best algorithm to be implemented for delivering high quality of service of video streaming over  the private cloud computing infrastructure