Capacity of P2P on-demand streaming with simple, robust and decentralized control

The performance of large-scaled peer-to-peer (P2P) video-on-demand (VoD) streaming systems can be very challenging to analyze. In practical P2P VoD systems, each peer only interacts with a small number of other peers/neighbors. Further, its upload capacity may vary randomly, and both its downloading position and content availability change dynamically. In this paper, we rigorously study the achievable streaming capacity of large-scale P2P VoD systems with sparse connectivity among peers, and investigate simple and decentralized P2P control strategies that can provably achieve close-to-optimal streaming capacity. We first focus on a single streaming channel. We show that a close-to-optimal streaming rate can be asymptotically achieved for all peers with high probability as the number of peers N increases, by assigning each peer a random set of Θ(log N) neighbors and using a uniform rate-allocation algorithm. Further, the tracker does not need to obtain detailed knowledge of which chunks each peer caches, and hence incurs low overhead. We then study multiple streaming channels where peers watching one channel may help in another channel with insufficient upload bandwidth. We propose a simple random cache-placement strategy, and show that a close-to-optimal streaming capacity region for all channels can be attained with high probability, again with only Θ(logN) per-peer neighbors. These results provide important insights into the dynamics of large-scale P2P VoD systems, which will be useful for guiding the design of improved P2P control protocols. © 2013 IEEE.published_or_final_versio

User-Centric Quality of Service Provisioning in IP Networks

The Internet has become the preferred transport medium for almost every type of communication, continuing to grow, both in terms of the number of users and delivered services. Efforts have been made to ensure that time sensitive applications receive sufficient resources and subsequently receive an acceptable Quality of Service (QoS). However, typical Internet users no longer use a single service at a given point in time, as they are instead engaged in a multimedia-rich experience, comprising of many different concurrent services. Given the scalability problems raised by the diversity of the users and traffic, in conjunction with their increasing expectations, the task of QoS provisioning can no longer be approached from the perspective of providing priority to specific traffic types over coexisting services; either through explicit resource reservation, or traffic classification using static policies, as is the case with the current approach to QoS provisioning, Differentiated Services (Diffserv). This current use of static resource allocation and traffic shaping methods reveals a distinct lack of synergy between current QoS practices and user activities, thus highlighting a need for a QoS solution reflecting the user services. The aim of this thesis is to investigate and propose a novel QoS architecture, which considers the activities of the user and manages resources from a user-centric perspective. The research begins with a comprehensive examination of existing QoS technologies and mechanisms, arguing that current QoS practises are too static in their configuration and typically give priority to specific individual services rather than considering the user experience. The analysis also reveals the potential threat that unresponsive application traffic presents to coexisting Internet services and QoS efforts, and introduces the requirement for a balance between application QoS and fairness. This thesis proposes a novel architecture, the Congestion Aware Packet Scheduler (CAPS), which manages and controls traffic at the point of service aggregation, in order to optimise the overall QoS of the user experience. The CAPS architecture, in contrast to traditional QoS alternatives, places no predetermined precedence on a specific traffic; instead, it adapts QoS policies to each individual’s Internet traffic profile and dynamically controls the ratio of user services to maintain an optimised QoS experience. The rationale behind this approach was to enable a QoS optimised experience to each Internet user and not just those using preferred services. Furthermore, unresponsive bandwidth intensive applications, such as Peer-to-Peer, are managed fairly while minimising their impact on coexisting services. The CAPS architecture has been validated through extensive simulations with the topologies used replicating the complexity and scale of real-network ISP infrastructures. The results show that for a number of different user-traffic profiles, the proposed approach achieves an improved aggregate QoS for each user when compared with Best effort Internet, Traditional Diffserv and Weighted-RED configurations. Furthermore, the results demonstrate that the proposed architecture not only provides an optimised QoS to the user, irrespective of their traffic profile, but through the avoidance of static resource allocation, can adapt with the Internet user as their use of services change.France Teleco

Videosisällön jakelu Internetin välityksellä

Popularity of multimedia streaming services has created great demand for reliable and effective content delivery over unreliable networks, such as the Internet. Currently, a significant part of the Internet data traffic is generated by video streaming applications. The multimedia streaming services are often bandwidth-heavy and are prone to delays or any other varying network conditions. In order to address high demands of real-time multimedia streaming applications, specialized solutions called content delivery networks, have emerged. A content delivery network consists of many geographically distributed replica servers, often deployed close to the end-users. This study consists of two parts and a set of interviews. First part explores development of video technologies and their relation to network bandwidth requirements. Second part proceeds to present the content delivery mechanisms related to video distribution over the Internet. Lastly, the interviews of selected experts was used to gain more relevant and realistic insights for two first parts. The results offer a wide overview of content delivery related findings ranging from streaming techniques to quality of experience. How the video related development progress would affect the future networks and what kind of content delivery models are mostly used in the modern Internet.Multimediapalveluiden suosio on noussut huomattavasti viime vuosina. Videoliikenteen osuus kaikesta tiedonsiirrosta Internetissä on kasvanut merkittävästi. Tämä on luonut suuren tarpeen luotettaville ja tehokkaille videosisällön siirtämisen keinoille epäluotettavien verkkojen yli. Videon suoratoistopalvelut ovat herkkiä verkossa tapahtuville häiriöille ja lisäksi ne vaativat usein verkolta paljon tiedonsiirtokapasiteettia. Ratkaistakseen multimedian reaaliaikaisen tiedonsiirron vaatimukset on kehitetty sisällönsiirtoon erikoistuneita verkkoja (eng. content deliver network - CDN). Nämä sisällönjakoon erikoistuneet verkot ovat fyysisesti hajautettuja kokonaisuuksia. Yleensä ne sijoitetaan mahdollisimman lähelle kohdekäyttäjäryhmää. Tämä työ koostuu kahdesta osasta ja asiantuntijahaastatteluista. Ensimmäinen osa keskittyy taustatietojen keräämiseen, videotekniikoiden kehitykseen ja sen siirtoon liittyviin haasteisiin. Toinen osa esittelee sisällönjaon toiminnot liittyen suoratoistopalveluiden toteutukseen. Haastatteluiden tarkoitus on tuoda esille asiantuntijoiden näkemyksiä kirjallisuuskatsauksen tueksi. Tulokset tarjoavat laajan katsauksen suoratoistopalveluiden sisällönjakotekniikoista, aina videon kehityksestä palvelun käyttökokemukseen saakka. Miten videon kuvanlaadun ja pakkaamisen kehitys voisi vaikuttaa tulevien verkkoteknologioiden kehitykseen Internet-pohjaisessa sisällönjakelussa

Design and evaluation of load balancing algorithms in P2P streaming.

Wang, Yongzhi.Thesis (M.Phil.)--Chinese University of Hong Kong, 2009.Includes bibliographical references (p.68-72).Abstract also in Chinese.Abstract --- p.iAcknowledgement --- p.iiChapter 1 --- Introduction --- p.1Chapter 2 --- Abstract Model --- p.7Chapter 2.1 --- Request allocation problem --- p.7Chapter 2.2 --- Neighbor selection problem --- p.11Chapter 3 --- Simulation Model --- p.14Chapter 4 --- Load Balancing Algorithms --- p.18Chapter 4.1 --- Request allocation --- p.18Chapter 4.2 --- Neighbor selection algorithms --- p.24Chapter 4.2.1 --- What to measure? --- p.24Chapter 4.2.2 --- Timeout-based neighbor selection algorithms --- p.25Chapter 4.2.3 --- Periodic neighbor selection algorithms --- p.33Chapter 4.2.4 --- Comparison: Timeout-based versus Periodical neighbor selection algorithms --- p.39Chapter 4.3 --- Further experiments --- p.41Chapter 4.3.1 --- Request window size --- p.41Chapter 4.3.2 --- Impact of K --- p.42Chapter 4.3.3 --- Adaptive adjustment of the neighbor selection period --- p.43Chapter 4.3.4 --- Performance with adequate bandwidth --- p.45Chapter 5 --- Minimizing Server´ةs Load --- p.49Chapter 6 --- Background Study --- p.56Chapter 6.1 --- P2P content distribution system --- p.56Chapter 6.1.1 --- P2P File sharing system --- p.56Chapter 6.1.2 --- P2P streaming system --- p.59Chapter 6.1.3 --- P2P Video on Demand system --- p.61Chapter 6.2 --- Congestion control --- p.62Chapter 7 --- Conclusion --- p.67Bibliography --- p.6