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

Understand the Similarity of Internet Service Providers via Peer-to-Peer User Interest Analysis

University of Minnesota M.S. thesis. June 2019. Major: Computer Science. Advisor: Haiyang Wang. 1 computer file (PDF); 63 pages.Internet traffic continues to exhibit exponential growth in the past few years. This forces Internet service providers(ISPs) to continuously invest in infrastructure upgrades and deploy traffic management techniques, such as caching and locality, to fulfill the increasing user demand. To help ISPs better manage their infrastructures, it is important to compare and understand the similarity of their user interests. However, such a comparison is challenging because the ISP data is hard to obtain, not to mention the related modeling and analysis issues. In this thesis, we aim to understand the ISP similarity through an extensive analysis of Peer-to-Peer(P2P) user interest. To collect the P2P dataset, we develop a tool to automatically download BitTorrent's meta-info(torrent) files on the Internet. This tool also helps us to collect important peer and content information in these BitTorrent swarms without uploading any copyrighted files. As a result, we successfully obtained 16,697 active peers from 1,721 torrents in 1,097 unique Autonomous Systems(ASes). After that, we adopt the classic statistical and clustering approaches to compare their different user interests. Our research for the first time shows the existence of cloud users in such real-world content distribution systems as BitTorrent. The model analysis further indicates that we can adopt similar traffic management approaches (e.g., caching similar contents) across geographically closer ASes

A Holistic Approach for Collaborative Workload Execution in Volunteer Clouds

The demand for provisioning, using, and maintaining distributed computational resources is growing hand in hand with the quest for ubiquitous services. Centralized infrastructures such as cloud computing systems provide suitable solutions for many applications, but their scalability could be limited in some scenarios, such as in the case of latency-dependent applications. The volunteer cloud paradigm aims at overcoming this limitation by encouraging clients to offer their own spare, perhaps unused, computational resources. Volunteer clouds are thus complex, large-scale, dynamic systems that demand for self-adaptive capabilities to offer effective services, as well as modeling and analysis techniques to predict their behavior. In this article, we propose a novel holistic approach for volunteer clouds supporting collaborative task execution services able to improve the quality of service of compute-intensive workloads. We instantiate our approach by extending a recently proposed ant colony optimization algorithm for distributed task execution with a workload-based partitioning of the overlay network of the volunteer cloud. Finally, we evaluate our approach using simulation-based statistical analysis techniques on a workload benchmark provided by Google. Our results show that the proposed approach outperforms some traditional distributed task scheduling algorithms in the presence of compute-intensive workloads

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

Cloudy Weather for P2P, with a Chance of Gossip

Abstract—Peer-to-peer (P2P) and cloud computing, two of the Internet trends of the last decade, hold similar promises: the (virtually) infinite availability of computing and storage resources. But there are important differences: the cloud provides highlyavailable resources, but at a cost; P2P resources are for free, but their availability is affected by churn. This paper proposes a novel approach for the construction of dependable applications, using the cloud to provide highly-available and durable services, while exploiting “free ” P2P resources when available. The novelty of our idea stems from the clever combination of the gossip paradigm with a storage cloud, that allows to keep the monetary cost of the cloud always under control, in the presence of just one peer or with a million of them. We show the feasibility of our approach by designing a news feed service based on it. I