Maintaining Balanced Trees for Structured Distributed Streaming Systems

International audienceIn this paper, we propose and analyze a simple local algorithm to balance a tree. The motivation comes from live distributed streaming systems in which a source diffuses a content to peers via a tree, a node forwarding the data to its children. Such systems are subject to a high churn, peers frequently joining and leaving the system. It is thus crucial to be able to repair the diffusion tree to allow an efficient data distribution. In particular, due to bandwidth limitations, an efficient diffusion tree must ensure that node degrees are bounded. Moreover, to minimize the delay of the streaming, the depth of the diffusion tree must also be controlled. We propose here a simple distributed repair algorithm in which each node carries out local operations based on its degree and on the subtree sizes of its children. In a synchronous setting, we first prove that starting from any n-node tree our process converges to a balanced binary tree in O(n 2) rounds. We then describe a more restrictive model, adding a small extra information to each node, under which we adapt our algorithm to converge in Θ(n log n) rounds

Multiple-Tree Push-based Overlay Streaming

Multiple-Tree Overlay Streaming has attracted a great amount of attention from researchers in the past years. Multiple-tree streaming is a promising alternative to single-tree streaming in terms of node dynamics and load balancing, among others, which in turn addresses the perceived video quality by the streaming user on node dynamics or when heterogeneous nodes join the network. This article presents a comprehensive survey of the different aproaches and techniques used in this research area. In this paper we identify node-disjointness as the property most approaches aim to achieve. We also present an alternative technique which does not try to achieve this but does local optimizations aiming global optimizations. Thus, we identify this property as not being absolute necessary for creating robust and heterogeneous multi-tree overlays. We identify two main design goals: robustness and support for heterogeneity, and classify existing approaches into these categories as their main focus

Optimizing Key Distribution in Peer to Peer Network Using B-Trees

Peer to peer network architecture introduces many desired features including self-scalability that led to achieving higher efficiency rate than the traditional server-client architecture. This was contributed to the highly distributed architecture of peer to peer network. Meanwhile, the lack of a centralized control unit in peer to peer network introduces some challenge. One of these challenges is key distribution and management in such an architecture. This research will explore the possibility of developing a novel scheme for distributing and managing keys in peer to peer network architecture efficiently

Study of Repair Protocols for Live Video Streaming Distributed Systems

International audience—We study distributed systems for live video streaming. These systems can be of two types: structured and un-structured. In an unstructured system, the diffusion is done opportunistically. The advantage is that it handles churn, that is the arrival and departure of users, which is very high in live streaming systems, in a smooth way. On the opposite, in a structured system, the diffusion of the video is done using explicit diffusion trees. The advantage is that the diffusion is very efficient, but the structure is broken by the churn. In this paper, we propose simple distributed repair protocols to maintain, under churn, the diffusion tree of a structured streaming system. We study these protocols using formal analysis and simulation. In particular, we provide an estimation of the system metrics, bandwidth usage, delay, or number of interruptions of the streaming. Our work shows that structured streaming systems can be efficient and resistant to churn

Recent Advances in Graph Partitioning

We survey recent trends in practical algorithms for balanced graph partitioning together with applications and future research directions

Optimizing on-demand resource deployment for peer-assisted content delivery (PhD thesis)

Increasingly, content delivery solutions leverage client resources in exchange for service in a peer-to-peer (P2P) fashion. Such peer-assisted service paradigms promise significant infrastructure cost reduction, but suffer from the unpredictability associated with client resources, which is often exhibited as an imbalance between the contribution and consumption of resources by clients. This imbalance hinders the ability to guarantee a minimum service fidelity of these services to the clients. In this thesis, we propose a novel architectural service model that enables the establishment of higher fidelity services through (1) coordinating the content delivery to optimally utilize the available resources, and (2) leasing the least additional cloud resources, available through special nodes (angels) that join the service on-demand, and only if needed, to complement the scarce resources available through clients. While the proposed service model can be deployed in many settings, this thesis focuses on peer-assisted content delivery applications, in which the scarce resource is typically the uplink capacity of clients. We target three applications that require the delivery of fresh as opposed to stale content. The first application is bulk-synchronous transfer, in which the goal of the system is to minimize the maximum distribution time -- the time it takes to deliver the content to all clients in a group. The second application is live streaming, in which the goal of the system is to maintain a given streaming quality. The third application is Tor, the anonymous onion routing network, in which the goal of the system is to boost performance (increase throughput and reduce latency) throughout the network, and especially for bandwidth-intensive applications. For each of the above applications, we develop mathematical models that optimally allocate the already available resources. They also optimally allocate additional on-demand resource to achieve a certain level of service. Our analytical models and efficient constructions depend on some simplifying, yet impractical, assumptions. Thus, inspired by our models and constructions, we develop practical techniques that we incorporate into prototypical peer-assisted angel-enabled cloud services. We evaluate those techniques through simulation and/or implementation. (Major Advisor: Azer Bestavros