Content Delivery System for Optimal VoD Streaming

The demand of video contents has rapidly increased in the past years as a result of the wide deployment of IPTV and the variety of services offered by the network operators. One of the services that has especially become attractive to the customers is real-time video on demand (VoD) because it offers an immediate streaming of a large variety of video contents. The price that the operators have to pay for this convenience is the increased traffic in the networks, which are becoming more congested due to the higher demand for VoD contents and the increased quality of the videos. As a solution, in this paper we propose a hierarchical network system for VoD content delivery in managed networks, which implements redistribution algorithm and a redirection strategy for optimal content distribution within the network core and optimal streaming to the clients. The system monitors the state of the network and the behavior of the users to estimate the demand for the content items and to take the right decision on the appropriate number of replicas and their best positions in the network. The system's objectives are to distribute replicas of the content items in the network in a way that the most demanded contents will have replicas closer to the clients so that it will optimize the network utilization and will improve the users' experience. It also balances the load between the servers concentrating the traffic to the edges of the network

Network overload avoidance by traffic engineering and content caching

The Internet traffic volume continues to grow at a great rate, now driven by video and TV distribution. For network operators it is important to avoid congestion in the network, and to meet service level agreements with their customers. This thesis presents work on two methods operators can use to reduce links loads in their networks: traffic engineering and content caching. This thesis studies access patterns for TV and video and the potential for caching. The investigation is done both using simulation and by analysis of logs from a large TV-on-Demand system over four months. The results show that there is a small set of programs that account for a large fraction of the requests and that a comparatively small local cache can be used to significantly reduce the peak link loads during prime time. The investigation also demonstrates how the popularity of programs changes over time and shows that the access pattern in a TV-on-Demand system very much depends on the content type. For traffic engineering the objective is to avoid congestion in the network and to make better use of available resources by adapting the routing to the current traffic situation. The main challenge for traffic engineering in IP networks is to cope with the dynamics of Internet traffic demands. This thesis proposes L-balanced routings that route the traffic on the shortest paths possible but make sure that no link is utilised to more than a given level L. L-balanced routing gives efficient routing of traffic and controlled spare capacity to handle unpredictable changes in traffic. We present an L-balanced routing algorithm and a heuristic search method for finding L-balanced weight settings for the legacy routing protocols OSPF and IS-IS. We show that the search and the resulting weight settings work well in real network scenarios

Research Article An Improved Particle Swarm Optimization Based on Deluge Approach for Enhanced Hierarchical Cache Optimization in IPTV Networks

Abstract: In recent years, IP network has been considered as a new delivery network for TV services. A majority of the telecommunication industries have used IP network to offer on-demand services and linear TV services as it can offer a two-way and high-speed communication. In order to effectively and economically utilize the IP network, caching is the technique which is usually preferred. In IPTV system, a managed network is utilized to bring out TV services, the requests of Video on Demand (VOD) objects are usually combined in a limited period intensively and user preferences are fluctuated dynamically. Furthermore, the VOD content updates often under the control of IPTV providers. In order to minimize this traffic and overall network cost, a segment of the video content is stored in caches closer to subscribers, for example, Digital Subscriber Line Access Multiplexer (DSLAM), a Central Office (CO) and Intermediate Office (IO). The major problem focused in this approach is to determine the optimal cache memory that should be assigned in order to attain maximum cost effectiveness. This approach uses an effective Grate Deluge algorithm based Particle Swarm Optimization (GDPSO) approach for attaining the optimal cache memory size which in turn minimizes the overall network cost. The analysis shows that hierarchical distributed caching can save significant network cost through the utilization of the GDPSO algorithm

UGC Video Sharing: Measurement and Analysis

User-generated content (UGC) site has become a new killer Internet application in the recent four years. Among those popular sites, YouTube is the most representative and successful one providing a new generation of short video sharing service. Today, YouTube is a dominant provider of online video in the Internet, and is still growing fast. Understanding the features of YouTube and similar video sharing sites is thus crucial to their sustainable development and to network traffic engineering.We investigate the YouTube site from two perspectives, internal and external. Using traces crawled in a 1.5-year span, we systematic measure the characteristics of YouTube videos. We find that YouTube videos have noticeably different statistics compared to traditional streaming videos, ranging from length, access pattern, to their active life span. The series of datasets also allows us to identify the growth trend of this fast evolving Internet site in various aspects, which has seldom been explored before. We also look closely at the social networking aspect of YouTube, as this is a key driving force toward its success. In particular, we find that the links to related videos generated by uploaders’ choices form a small-world network. This suggests that the videos have strong correlations with each other, and creates opportunities for developing novel caching or peer-to-peer distribution schemes to efficiently deliver videos to end users.We also provide an in-depth study into the effects of the external links of YouTube. We collected nearly one million videos’ external link information, and traced different types of videos for more than two months. Our study shows interesting characteristics of external links of YouTube. In particular, we find that views from external links are independent from total views in each category. Also, videos benefit more from external links in the early stage. Our work can serve as a initial step for the study of the external environment.Department of Computin

Distribuição de conteúdos over-the-top multimédia em redes sem fios

mestrado em Engenharia Eletrónica e TelecomunicaçõesHoje em dia a Internet é considerada um bem essencial devido ao facto de haver uma constante necessidade de comunicar, mas também de aceder e partilhar conteúdos. Com a crescente utilização da Internet, aliada ao aumento da largura de banda fornecida pelos operadores de telecomunicações, criaram-se assim excelentes condições para o aumento dos serviços multimédia Over-The-Top (OTT), demonstrado pelo o sucesso apresentado pelos os serviços Netflix e Youtube. O serviço OTT engloba a entrega de vídeo e áudio através da Internet sem um controlo direto dos operadores de telecomunicações, apresentando uma proposta atractiva de baixo custo e lucrativa. Embora a entrega OTT seja cativante, esta padece de algumas limitações. Para que a proposta se mantenha em crescimento e com elevados padrões de Qualidade-de-Experiência (QoE) para os consumidores, é necessário investir na arquitetura da rede de distribuição de conteúdos, para que esta seja capaz de se adaptar aos diversos tipos de conteúdo e obter um modelo otimizado com um uso cauteloso dos recursos, tendo como objectivo fornecer serviços OTT com uma boa qualidade para o utilizador, de uma forma eficiente e escalável indo de encontro aos requisitos impostos pelas redes móveis atuais e futuras. Esta dissertação foca-se na distribuição de conteúdos em redes sem fios, através de um modelo de cache distribuída entre os diferentes pontos de acesso, aumentando assim o tamanho da cache e diminuindo o tráfego necessário para os servidores ou caches da camada de agregação acima. Assim, permite-se uma maior escalabilidade e aumento da largura de banda disponível para os servidores de camada de agregação acima. Testou-se o modelo de cache distribuída em três cenários: o consumidor está em casa em que se considera que tem um acesso fixo, o consumidor tem um comportamento móvel entre vários pontos de acesso na rua, e o consumidor está dentro de um comboio em alta velocidade. Testaram-se várias soluções como Redis2, Cachelot e Memcached para servir de cache, bem como se avaliaram vários proxies para ir de encontro ás características necessárias. Mais ainda, na distribuição de conteúdos testaram-se dois algoritmos, nomeadamente o Consistent e o Rendezvouz Hashing. Ainda nesta dissertação utilizou-se uma proposta já existente baseada na previsão de conteúdos (prefetching ), que consiste em colocar o conteúdo nas caches antes de este ser requerido pelos consumidores. No final, verificou-se que o modelo distribuído com a integração com prefecthing melhorou a qualidade de experiência dos consumidores, bem como reduziu a carga nos servidores de camada de agregação acima.Nowadays, the Internet is considered an essential good, due to the fact that there is a need to communicate, but also to access and share information. With the increasing use of the Internet, allied with the increased bandwidth provided by telecommunication operators, it has created conditions for the increase of Over-the-Top (OTT) Multimedia Services, demonstrated by the huge success of Net ix and Youtube. The OTT service encompasses the delivery of video and audio through the Internet without direct control of telecommunication operators, presenting an attractive low-cost and pro table proposal. Although the OTT delivery is captivating, it has some limitations. In order to increase the number of clients and keep the high Quality of Experience (QoE) standards, an enhanced architecture for content distribution network is needed. Thus, the enhanced architecture needs to provide a good quality for the user, in an e cient and scalable way, supporting the requirements imposed by future mobile networks. This dissertation aims to approach the content distribution in wireless networks, through a distributed cache model among the several access points, thus increasing the cache size and decreasing the load on the upstream servers. The proposed architecture was tested in three di erent scenarios: the consumer is at home and it is considered that it has a xed access, the consumer is mobile between several access points in the street, the consumer is in a high speed train. Several solutions were evaluated, such as Redis2, Cachelot and Memcached to serve as caches, along with the evaluation of several proxies server in order to ful ll the required features. Also, it was tested two distributed algorithms, namely the Consistent and Rendezvous Hashing. Moreover, in this dissertation it was integrated a prefetching mechanism, which consists of inserting the content in caches before being requested by the consumers. At the end, it was veri ed that the distributed model with prefetching improved the consumers QoE as well as it reduced the load on the upstream servers

A cooperative and incentive-based proxy-and-client caching system for on-demand media streaming.

Ip Tak Shun.Thesis (M.Phil.)--Chinese University of Hong Kong, 2005.Includes bibliographical references (leaves 95-101).Abstracts in English and Chinese.Abstract --- p.iAcknowledgement --- p.ivChapter 1 --- Introduction --- p.1Chapter 1.1 --- Background --- p.1Chapter 1.1.1 --- Media Streaming --- p.1Chapter 1.1.2 --- Incentive Mechanism --- p.2Chapter 1.2 --- Cooperative and Incentive-based Proxy-and-Client Caching --- p.4Chapter 1.2.1 --- Cooperative Proxy-and-Client Caching --- p.4Chapter 1.2.2 --- Revenue-Rewarding Mechanism --- p.5Chapter 1.3 --- Thesis Contribution --- p.6Chapter 1.4 --- Thesis Organization --- p.7Chapter 2 --- Related Work --- p.9Chapter 2.1 --- Media Streaming --- p.9Chapter 2.2 --- Incentive Mechanism --- p.11Chapter 2.3 --- Resource Pricing --- p.14Chapter 3 --- Cooperative Proxy-and-Client Caching --- p.16Chapter 3.1 --- Overview of the COPACC System --- p.16Chapter 3.2 --- Optimal Cache Allocation (CAP) --- p.21Chapter 3.2.1 --- Single Proxy with Client Caching --- p.21Chapter 3.2.2 --- Multiple Proxies with Client Caching --- p.24Chapter 3.2.3 --- Cost Function with Suffix Multicast --- p.26Chapter 3.3 --- Cooperative Proxy-Client Caching Protocol --- p.28Chapter 3.3.1 --- Cache Allocation and Organization --- p.29Chapter 3.3.2 --- Cache Lookup and Retrieval --- p.30Chapter 3.3.3 --- Client Access and Integrity Verification --- p.30Chapter 3.4 --- Performance Evaluation --- p.33Chapter 3.4.1 --- Effectiveness of Cooperative Proxy and Client Caching --- p.34Chapter 3.4.2 --- Robustness --- p.37Chapter 3.4.3 --- Scalability and Control Overhead --- p.38Chapter 3.4.4 --- Sensitivity to Network Topologies --- p.40Chapter 4 --- Revenue-Rewarding Mechanism --- p.43Chapter 4.1 --- System Model --- p.44Chapter 4.1.1 --- System Overview --- p.44Chapter 4.1.2 --- System Formulation --- p.47Chapter 4.2 --- Resource Allocation Game --- p.50Chapter 4.2.1 --- Non-Cooperative Game --- p.50Chapter 4.2.2 --- Profit Maximizing Game --- p.52Chapter 4.2.3 --- Utility Maximizing Game --- p.61Chapter 4.3 --- Performance Evaluation --- p.74Chapter 4.3.1 --- Convergence --- p.76Chapter 4.3.2 --- Participation Incentive --- p.77Chapter 4.3.3 --- Cost effectiveness --- p.85Chapter 5 --- Conclusion --- p.87Chapter A --- NP-Hardness of the CAP problem --- p.90Chapter B --- Optimality of the Greedy Algorithm --- p.92Bibliography --- p.9