Scalable high-capacity high-fan-out optical networks for constrained environments

The investigations carried out as part of the dissertation address the architecture and application of optical access networks pertaining to high-capacity and high fan-out applications such as in-flight entertainment (IFE) and video-gaming environment. High-capacity and high-fan-out optical networks have a multitude of applications such as expo-centers, train area networks (TAN), video gaming competitions and other applications that require large number of connected users. For the purpose of keeping the scope of the dissertation within limit however, we have concentrated this work on IFE systems. IFE systems present unique challenges at physical and application layers alike. In-flight entertainment (IFE) systems have been a part of passengers' experience for a while now. Currently available systems can be considered a bare-bone at best due to lack of adequate performance and support infrastructure. According to electronic arts (EA), one of the largest developers of video games in the world, an increase in demand for electronically distributed video games will exceed boxed games in just a matter of few years. This also shows a shifting trend towards the electronic distribution of video game content as opposed to physical distribution. Against the same backdrop, the dissertation project involved defining a novel system architecture and capacity based on the requirements for development of novel physical layer architecture utilizing optical networks for high-speed and high-fan-out distribution of content. At the physical layer of the stacked communication model a novel high-fan-out optical network was proposed and simulated for high data-rates. Having defined the physical layer, protocol stack was identified through rigorous observations and data traffic analysis from a large set of traffic traces obtained from various sources in order to understand the distribution and behavior of video game related traffic compared with regular internet traffic. Data requirements were laid down based on analysis keeping in mind that bandwidth requirements are increasing at a tremendous pace and that the network should be able to support future high-definition and 3D gaming as well. Based on the data analysis, analytical models and latency analysis models were also developed for bandwidth allocation in the high-fan-out network architectures. Analytical modeling gives an insight into the performance of the technique as a function of incoming traffic whereas latency analysis exposes the delay factors involved in running the technique over time. "State-full bandwidth allocation" (SBA) was proposed as part of the network layer design for upstream transmission. The novel technique involves keeping state information from previous states for future allocation. The results show that the proposed high-fan-out high-capacity physical layer architecture can be used to distribute video-gaming related content. Also, latency analysis and design and development of a novel SBA algorithm were carried out. Results were quiet promising, in that; a large number of users can be supported on the same single channel network. SBA criteria can be applied to multi-channel networks such as the physical architecture proposed / simulated and investigated in this project. In summary, the project involved design of a novel physical layer; network layer and protocol stack of the communication model and verification by simulations and mathematical modeling while adhering to application layer requirements

Efficient memory management in VOD disk array servers usingPer-Storage-Device buffering

We present a buffering technique that reduces video-on-demand server memory requirements in more than one order of magnitude. This technique, Per-Storage-Device Buffering (PSDB), is based on the allocation of a fixed number of buffers per storage device, as opposed to existing solutions based on per-stream buffering allocation. The combination of this technique with disk array servers is studied in detail, as well as the influence of Variable Bit Streams. We also present an interleaved data placement strategy, Constant Time Length Declustering, that results in optimal performance in the service of VBR streams. PSDB is evaluated by extensive simulation of a disk array server model that incorporates a simulation based admission test.This research was supported in part by the National R&D Program of Spain, Project Number TIC97-0438.Publicad

Architecture for Cooperative Prefetching in P2P Video-on- Demand System

Most P2P VoD schemes focused on service architectures and overlays optimization without considering segments rarity and the performance of prefetching strategies. As a result, they cannot better support VCRoriented service in heterogeneous environment having clients using free VCR controls. Despite the remarkable popularity in VoD systems, there exist no prior work that studies the performance gap between different prefetching strategies. In this paper, we analyze and understand the performance of different prefetching strategies. Our analytical characterization brings us not only a better understanding of several fundamental tradeoffs in prefetching strategies, but also important insights on the design of P2P VoD system. On the basis of this analysis, we finally proposed a cooperative prefetching strategy called "cooching". In this strategy, the requested segments in VCR interactivities are prefetched into session beforehand using the information collected through gossips. We evaluate our strategy through extensive simulations. The results indicate that the proposed strategy outperforms the existing prefetching mechanisms.Comment: 13 Pages, IJCN

Cooperative announcement-based caching for video-on-demand streaming

Recently, video-on-demand (VoD) streaming services like Netflix and Hulu have gained a lot of popularity. This has led to a strong increase in bandwidth capacity requirements in the network. To reduce this network load, the design of appropriate caching strategies is of utmost importance. Based on the fact that, typically, a video stream is temporally segmented into smaller chunks that can be accessed and decoded independently, cache replacement strategies have been developed that take advantage of this temporal structure in the video. In this paper, two caching strategies are proposed that additionally take advantage of the phenomenon of binge watching, where users stream multiple consecutive episodes of the same series, reported by recent user behavior studies to become the everyday behavior. Taking into account this information allows us to predict future segment requests, even before the video playout has started. Two strategies are proposed, both with a different level of coordination between the caches in the network. Using a VoD request trace based on binge watching user characteristics, the presented algorithms have been thoroughly evaluated in multiple network topologies with different characteristics, showing their general applicability. It was shown that in a realistic scenario, the proposed election-based caching strategy can outperform the state-of-the-art by 20% in terms of cache hit ratio while using 4% less network bandwidth