Cloud-based Content Distribution on a Budget

To leverage the elastic nature of cloud computing, a solution provider must be able to accurately gauge demand for its offering. For applications that involve swarm-to-cloud interactions, gauging such demand is not straightforward. In this paper, we propose a general framework, analyze a mathematical model, and present a prototype implementation of a canonical swarm-to-cloud application, namely peer-assisted content delivery. Our system – called Cyclops – dynamically adjusts the off-cloud bandwidth consumed by content servers (which represents the bulk of the provider's cost) to feed a set of swarming clients, based on a feedback signal that gauges the real-time health of the swarm. Our extensive evaluation of Cyclops in a variety of settings – including controlled PlanetLab and live Internet experiments involving thousands of users – show significant reduction in content distribution costs (by as much as two orders of magnitude) when compared to non-feedback-based swarming solutions, with minor impact on content delivery times

Understanding collaboration in volunteer computing systems

Volunteer computing is a paradigm in which devices participating in a distributed environment share part of their resources to help others perform their activities. The effectiveness of this computing paradigm depends on the collaboration attitude adopted by the participating devices. Unfortunately for software designers it is not clear how to contribute with local resources to the shared environment without compromising resources that could then be required by the contributors. Therefore, many designers adopt a conservative position when defining the collaboration strategy to be embedded in volunteer computing applications. This position produces an underutilization of the devices’ local resources and reduces the effectiveness of these solutions. This article presents a study that helps designers understand the impact of adopting a particular collaboration attitude to contribute with local resources to the distributed shared environment. The study considers five collaboration strategies, which are analyzed in computing environments with both, abundance and scarcity of resources. The obtained results indicate that collaboration strategies based on effort-based incentives work better than those using contribution-based incentives. These results also show that the use of effort-based incentives does not jeopardize the availability of local resources for the local needs.Peer ReviewedPostprint (published version

Raptorqp2P: Maximize The Performance Of P2P File Distribution With Raptorq Coding

BitTorrent is the most popular Peer-to-Peer (P2P) file sharing system widely used for distributing large files over the Internet. It has attracted extensive attentions from both network operators and researchers for investigating its deployment and performance. For example, recent studies have shown that under steady state, its rarest first scheme with the tit-for-tat mechanism can work very effectively and make BitTorrent near optimal for the generic file downloading process. However, in practice, the highly dynamic network environment, especially the notorious user churns prevalently existing in most peer-to-peer systems, can severely degrade the downloading performance. In this thesis, we first study on the limitations of BitTorrent under dynamic network environments, focusing on two scenarios where with our preliminary modeling and analysis, we clearly identify how network dynamics and peer churns can significantly degrade the performance. With these findings, we further propose a novel protocol named RaptorQP2P, which is based on RaptorQ coding, to overcome the limitations of current BitTorrent design and maximize the performance of P2P file distribution. The new protocol features two levels of RaptorQ encoding. At the top layer, the entire file is RaptorQ encoded to yield a collection of source blocks and repair blocks, and then each source and repair block is RaptorQ encoded independently to yield a collection of source symbols and repair symbols for the block. The symbols are independently transferred among the peers and when a sufficient number of distinct symbols for a particular block have been received, whether source or repair, the block can be reconstructed. The file can be reconstructed using a sufficient arbitrary number of distinct blocks. Our results show that RaptorQP2P can well handle the network dynamics as well as peer churns and significantly shorten the downloading completion time by up to 41.4% with excellent scalability on both file size and user population

Design of Scalable On-Demand Video Streaming Systems Leveraging Video Viewing Patterns

The explosive growth in on-demand access of video across all forms of delivery (Internet, traditional cable, IPTV, wireless) has renewed the interest in scalable delivery methods. Approaches using Content Delivery Networks (CDNs), Peer-to-Peer (P2P) approaches, and their combinations have been proposed as viable options to ease the load on servers and network links. However, there has been little focus on how to take advantage of user viewing patterns to understand their impact on existing mechanisms and to design new solutions that improve the streaming service quality. In this dissertation, we leverage on the observation that users watch only a small portion of videos to understand the limits of existing designs and to optimize two scalable approaches -- the content placement and P2P Video-on-Demand (VoD) streaming. Then, we present our novel scalable system called Joint-Family which enables adaptive bitrate streaming (ABR) in P2P VoD, supporting user viewing patterns. We first provide evidence of such user viewing behavior from data collected from a nationally deployed VoD service. In contrast to using a simplistic popularity-based placement and traditionally proposed caching strategies (such as CDNs), we use a Mixed Integer Programming formulation to model the placement problem and employ an innovative approach that scales well. We have performed detailed simulations using actual traces of user viewing sessions (including stream control operations such as pause, fast-forward, and rewind). Our results show that the use of segment-based placement strategy yields substantial savings in both disk storage requirements at origin servers/VHOs as well as network bandwidth use. For example, compared to a simple caching scheme using full videos, our MIP-based placement using segments can achieve up to 71% reduction in peak link bandwidth usage. Secondly, we note that the policies adopted in existing P2P VoD systems have not taken user viewing behavior -- that users abandon videos -- into account. We show that abandonment can result in increased interruptions and wasted resources. As a result, we reconsider the set of policies to use in the presence of abandonment. Our goal is to balance the conflicting needs of delivering videos without interruptions while minimizing wastage. We find that an Earliest-First chunk selection policy in conjunction with the Earliest-Deadline peer selection policy allows us to achieve high download rates. We take advantage of abandonment by converting peers to "partial seeds"; this increases capacity. We minimize wastage by using a playback lookahead window. We use analysis and simulation experiments using real-world traces to show the effectiveness of our approach. Finally, we propose Joint-Family, a protocol that combines P2P and adaptive bitrate (ABR) streaming for VoD. While P2P for VoD and ABR have been proposed previously, they have not been studied together because they attempt to tackle problems with seemingly orthogonal goals. We motivate our approach through analysis that overcomes a misconception resulting from prior analytical work, and show that the popularity of a P2P swarm and seed staying time has a significant bearing on the achievable per-receiver download rate. Specifically, our analysis shows that popularity affects swarm efficiency when seeds stay "long enough". We also show that ABR in a P2P setting helps viewers achieve higher playback rates and/or fewer interruptions. We develop the Joint-Family protocol based on the observations from our analysis. Peers in Joint-Family simultaneously participate in multiple swarms to exchange chunks of different bitrates. We adopt chunk, bitrate, and peer selection policies that minimize occurrence of interruptions while delivering high quality video and improving the efficiency of the system. Using traces from a large-scale commercial VoD service, we compare Joint-Family with existing approaches for P2P VoD and show that viewers in Joint-Family enjoy higher playback rates with minimal interruption, irrespective of video popularity