Live Streaming in P2P and Hybrid P2P-Cloud Environments for the Open Internet

Peer-to-Peer (P2P) live media streaming is an emerging technology that reduces the barrier to stream live events over the Internet. However, providing a high quality media stream using P2P overlay networks is challenging and gives raise to a number of issues: (i) how to guarantee quality of the service (QoS) in the presence of dynamism, (ii) how to incentivize nodes to participate in media distribution, (iii) how to avoid bottlenecks in the overlay, and (iv) how to deal with nodes that reside behind Network Address Translators gateways (NATs). In this thesis, we answer the above research questions in form of new algorithms and systems. First of all, we address problems (i) and (ii) by presenting our P2P live media streaming solutions: Sepidar, which is a multiple-tree overlay, and GLive, which is a mesh overlay. In both models, nodes with higher upload bandwidth are positioned closer to the media source. This structure reduces the playback latency and increases the playback continuity at nodes, and also incentivizes the nodes to provide more upload bandwidth. We use a reputation model to improve participating nodes in media distribution in Sepidar and GLive. In both systems, nodes audit the behaviour of their directly connected nodes by getting feedback from other nodes. Nodes who upload more of the stream get a relatively higher reputation, and proportionally higher quality streams. To construct our streaming overlay, we present a distributed market model inspired by Bertsekas auction algorithm, although our model does not rely on a central server with global knowledge. In our model, each node has only partial information about the system. Nodes acquire knowledge of the system by sampling nodes using the Gradient overlay, where it facilitates the discovery of nodes with similar upload bandwidth. We address the bottlenecks problem, problem (iii), by presenting CLive that satisfies real-time constraints on delay between the generation of the stream and its actual delivery to users. We resolve this problem by borrowing some resources (helpers) from the cloud, upon need. In our approach, helpers are added on demand to the overlay, to increase the amount of total available bandwidth, thus increasing the probability of receiving the video on time. As the use of cloud resources costs money, we model the problem as the minimization of the economical cost, provided that a set of constraints on QoS is satisfied. Finally, we solve the NAT problem, problem (iv), by presenting two NAT-aware peer sampling services (PSS): Gozar and Croupier. Traditional gossip-based PSS breaks down, where a high percentage of nodes are behind NATs. We overcome this problem in Gozar using one-hop relaying to communicate with the nodes behind NATs. Croupier similarly implements a gossip-based PSS, but without the use of relaying

ElfStore: A Resilient Data Storage Service for Federated Edge and Fog Resources

Edge and fog computing have grown popular as IoT deployments become wide-spread. While application composition and scheduling on such resources are being explored, there exists a gap in a distributed data storage service on the edge and fog layer, instead depending solely on the cloud for data persistence. Such a service should reliably store and manage data on fog and edge devices, even in the presence of failures, and offer transparent discovery and access to data for use by edge computing applications. Here, we present Elfstore, a first-of-its-kind edge-local federated store for streams of data blocks. It uses reliable fog devices as a super-peer overlay to monitor the edge resources, offers federated metadata indexing using Bloom filters, locates data within 2-hops, and maintains approximate global statistics about the reliability and storage capacity of edges. Edges host the actual data blocks, and we use a unique differential replication scheme to select edges on which to replicate blocks, to guarantee a minimum reliability and to balance storage utilization. Our experiments on two IoT virtual deployments with 20 and 272 devices show that ElfStore has low overheads, is bound only by the network bandwidth, has scalable performance, and offers tunable resilience.Comment: 24 pages, 14 figures, To appear in IEEE International Conference on Web Services (ICWS), Milan, Italy, 201

SCOPE: Synergistic Content Distribution and Peer-to-Peer Networks

Distributing content on the Internet is an important economic, educational, social, and cultural endeavor. To this end, several existing efforts use traditional server-based content distribution networks (CDNs) to replicate and distribute Web and multimedia content of big content producers, such as news Web sites, or big businesses, such as online shopping websites, etc., to millions of Internet users. This approach places a large number of content servers at strategic locations on the Internet, incurring a very large deployment and operating cost. Therefore, it is available only to some wealthy companies/organizations. Individual users and small content publishers may rely on a more economical content dissemination approach based on recent peer-to-peer technology to distribute their own content. Nevertheless, it is the ephemeral and the limited resources nature of peer-to-peer networks that hinder a wide spread adoption of peer-to-peer technology as a reliable content distribution solution. It is, therefore, important that a new generation of cost-effective and reliable content distribution framework be proposed and investigated. Building on the successes and failures of previous content distribution approaches, the proposed research goal is to find and evaluate a Synergistic Content Distribution and Peer-to-Peer Networks (SCOPE). SCOPE leverages the reliability and the resourcefulness of traditional server-based CDNs while tapping on the economical and dynamic resources of peers

Video-on-Demand over Internet: a survey of existing systems and solutions

Video-on-Demand is a service where movies are delivered to distributed users with low delay and free interactivity. The traditional client/server architecture experiences scalability issues to provide video streaming services, so there have been many proposals of systems, mostly based on a peer-to-peer or on a hybrid server/peer-to-peer solution, to solve this issue. This work presents a survey of the currently existing or proposed systems and solutions, based upon a subset of representative systems, and defines selection criteria allowing to classify these systems. These criteria are based on common questions such as, for example, is it video-on-demand or live streaming, is the architecture based on content delivery network, peer-to-peer or both, is the delivery overlay tree-based or mesh-based, is the system push-based or pull-based, single-stream or multi-streams, does it use data coding, and how do the clients choose their peers. Representative systems are briefly described to give a summarized overview of the proposed solutions, and four ones are analyzed in details. Finally, it is attempted to evaluate the most promising solutions for future experiments. Résumé La vidéo à la demande est un service où des films sont fournis à distance aux utilisateurs avec u

A Taxonomy of Data Grids for Distributed Data Sharing, Management and Processing

Data Grids have been adopted as the platform for scientific communities that need to share, access, transport, process and manage large data collections distributed worldwide. They combine high-end computing technologies with high-performance networking and wide-area storage management techniques. In this paper, we discuss the key concepts behind Data Grids and compare them with other data sharing and distribution paradigms such as content delivery networks, peer-to-peer networks and distributed databases. We then provide comprehensive taxonomies that cover various aspects of architecture, data transportation, data replication and resource allocation and scheduling. Finally, we map the proposed taxonomy to various Data Grid systems not only to validate the taxonomy but also to identify areas for future exploration. Through this taxonomy, we aim to categorise existing systems to better understand their goals and their methodology. This would help evaluate their applicability for solving similar problems. This taxonomy also provides a "gap analysis" of this area through which researchers can potentially identify new issues for investigation. Finally, we hope that the proposed taxonomy and mapping also helps to provide an easy way for new practitioners to understand this complex area of research.Comment: 46 pages, 16 figures, Technical Repor