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

Network Coding Enabled Named Data Networking Architectures

The volume of data traffic in the Internet has increased drastically in the last years, mostly due to data intensive applications like video streaming, file sharing, etc.. This motivates the development of new communication methods that can deal with the growing volume of data traffic. To this aim, Named Data Networking (NDN) has been proposed as a future Internet architecture that changes how the Internet works, from the exchange of content between particular nodes of the network, to retrieval of particular content in the network. The NDN architecture enables ubiquitous in-network caching and naturally supports dynamic selection of content sources, characteristics that fit well with the communication needs of data intensive applications. However, the performance of data intensive applications is degraded by the limited throughput seen by applications, which can be caused by (i) limited bandwidth, (ii) network bottlenecks and (iii) packet losses. In this thesis, we argue that introducing network coding into the NDN architecture improves the performance of NDN-based data intensive applications by alleviating the three issues presented above. In particular, network coding (i) enables efficient multipath data retrieval in NDN, which allows nodes to aggregate all the bandwidth available through their multiple interfaces; (ii) allows information from multiple sources to be combined at the intermediate routers, which alleviates the impact of network bottlenecks; and (iii) enables clients to efficiently handle packet losses. This thesis first provides an architecture that enables network coding in NDN for data intensive applications. Then, a study demonstrates and quantifies the benefits that network coding brings to video streaming over NDN, a particular data intensive application. To study the benefits that network coding brings in a more realistic NDN scenario, this thesis finally provides a caching strategy that is used when the in-network caches have limited capacity. Overall, the evaluation results show that the use of network coding permits to exploit more efficiently available network resources, which leads to reduced data traffic load on the sources, increased cache-hit rate at the in-network caches and faster content retrieval at the clients. In particular, for video streaming applications, network coding enables clients to watch higher quality videos compared to using traditional NDN, while it also reduces the video servers' load. Moreover, the proposed caching strategy for network coding enabled NDN maintains the benefits that network coding brings to NDN even when the caches have limited storage space

Cooperative Interval Caching in Clustered Multimedia Servers

In this project, we design a cooperative interval caching (CIC) algorithm for clustered video servers, and evaluate its performance through simulation. The CIC algorithm describes how distributed caches in the cluster cooperate to serve a given request. With CIC, a clustered server can accommodate twice (95%) more number of cached streams than the clustered server without cache cooperation. There are two major processes of CIC to find available cache space for a given request in the cluster: to find the server containing the information about the preceding request of the given request; and to find another server which may have available cache space if the current server turns out not to have enough cache space. The performance study shows that it is better to direct the requests of the same movie to the same server so that a request can always find the information of its preceding request from the same server. The CIC algorithm uses scoreboard mechanism to achieve this goal. The performance results also show that when the current server fails to find cache space for a given request, randomly selecting a server works well to find the next server which may have available cache space. The combination of scoreboard and random selection to find the preceding request information and the next available server outperforms other combinations of different approaches by 86%. With CIC, the cooperative distributed caches can support as many cached streams as one integrated cache does. In some cases, the cooperative distributed caches accommodate more number of cached streams than one integrated cache would do. The CIC algorithm makes every server in the cluster perform identical tasks to eliminate any single point of failure, there by increasing availability of the server cluster. The CIC algorithm also specifies how to smoothly add or remove a server to or from the cluster to provide the server with scalability

Ontwerp en evaluatie van content distributie netwerken voor multimediale streaming diensten.

Traditionele Internetgebaseerde diensten voor het verspreiden van bestanden, zoals Web browsen en het versturen van e-mails, worden aangeboden via één centrale server. Meer recente netwerkdiensten zoals interactieve digitale televisie of video-op-aanvraag vereisen echter hoge kwaliteitsgaranties (QoS), zoals een lage en constante netwerkvertraging, en verbruiken een aanzienlijke hoeveelheid bandbreedte op het netwerk. Architecturen met één centrale server kunnen deze garanties moeilijk bieden en voldoen daarom niet meer aan de hoge eisen van de volgende generatie multimediatoepassingen. In dit onderzoek worden daarom nieuwe netwerkarchitecturen bestudeerd, die een dergelijke dienstkwaliteit kunnen ondersteunen. Zowel peer-to-peer mechanismes, zoals bij het uitwisselen van muziekbestanden tussen eindgebruikers, als servergebaseerde oplossingen, zoals gedistribueerde caches en content distributie netwerken (CDN's), komen aan bod. Afhankelijk van de bestudeerde dienst en de gebruikte netwerktechnologieën en -architectuur, worden gecentraliseerde algoritmen voor netwerkontwerp voorgesteld. Deze algoritmen optimaliseren de plaatsing van de servers of netwerkcaches en bepalen de nodige capaciteit van de servers en netwerklinks. De dynamische plaatsing van de aangeboden bestanden in de verschillende netwerkelementen wordt aangepast aan de heersende staat van het netwerk en aan de variërende aanvraagpatronen van de eindgebruikers. Serverselectie, herroutering van aanvragen en het verspreiden van de belasting over het hele netwerk komen hierbij ook aan bod

Interactivity And User-heterogeneity In On Demand Broadcast Video

Video-On-Demand (VOD) has appeared as an important technology for many multimedia applications such as news on demand, digital libraries, home entertainment, and distance learning. In its simplest form, delivery of a video stream requires a dedicated channel for each video session. This scheme is very expensive and non-scalable. To preserve server bandwidth, many users can share a channel using multicast. Two types of multicast have been considered. In a non-periodic multicast setting, users make video requests to the server; and it serves them according to some scheduling policy. In a periodic broadcast environment, the server does not wait for service requests. It broadcasts a video cyclically, e.g., a new stream of the same video is started every t seconds. Although, this type of approach does not guarantee true VOD, the worst service latency experienced by any client is less than t seconds. A distinct advantage of this approach is that it can serve a very large community of users using minimal server bandwidth. In VOD System it is desirable to provide the user with the video-cassette-recorder-like (VCR) capabilities such as fast-forwarding a video or jumping to a specific frame. This issue in the broadcast framework is addressed, where each video and its interactive version are broadcast repeatedly on the network. Existing techniques rely on data prefetching as the mechanism to provide this functionality. This approach provides limited usability since the prefetching rate cannot keep up with typical fast-forward speeds. In the same environment, end users might have access to different bandwidth capabilities at different times. Current periodic broadcast schemes, do not take advantage of high-bandwidth capabilities, nor do they adapt to the low-bandwidth limitation of the receivers. A heterogeneous technique is presented that can adapt to a range of receiving bandwidth capability. Given a server bandwidth and a range of different client bandwidths, users employing the proposed technique will choose either to use their full reception bandwidth capability and therefore accessing the video at a very short time, or using part or enough reception bandwidth at the expense of a longer access latency

Side-channel timing attack on content privacy of named data networking

Tese de Doutoramento em Engenharia Electrónica e de ComputadoresA diversity of current applications, such as Netflix, YouTube, and social media, have used the Internet mainly as a content distribution network. Named Data Networking (NDN) is a network paradigm that attempts to answer today’s applications need by naming the content. NDN promises an optimized content distribution through a named content-centric design. One of the NDN key features is the use of in-network caching to improve network efficiency in terms of content distribution. However, the cached contents may put the consumer privacy at risk. Since the time response of cached contents is different from un-cached contents, the adversary may distinguish the cached contents (targets) from un-cached ones, through the side-channel timing responses. The scope of attack can be towards the content, the name, or the signature. For instance, the adversary may obtain the call history, the callee or caller location on a trusted Voice over NDN (VoNDN) and the popularity of contents in streaming applications (e.g. NDNtube, NDNlive) through side-channel timing responses of the cache. The side-channel timing attack can be mitigated by manipulating the time of the router responses. The countermeasures proposed by other researches, such as additional delay, random/probabilistic caching, group signatures, and no-caching can effectively be used to mitigate the attack. However, the content distribution may be affected by pre-configured countermeasures which may go against the goal of the original NDN paradigm. In this work, the detection and defense (DaD) approach is proposed to mitigate the attack efficiently and effectively. With the DaD usage, an attack can be detected by a multi-level detection mechanism, in order to apply the countermeasures against the adversarial faces. Also, the detections can be used to determine the severity of the attack. In order to detect the behavior of an adversary, a brute-force timing attack was implemented and simulated with the following applications and testbeds: i. a trusted application that mimics the VoNDN and identifies the cached certificate on a worldwide NDN testbed, and ii. a streaming-like NDNtube application to identify the popularity of videos on the NDN testbed and AT&T company. In simulation primary results showed that the multi-level detection based on DaD mitigated the attack about 39.1% in best-route, and 36.6% in multicast communications. Additionally, the results showed that DaD preserves privacy without compromising the efficiency benefits of in-network caching in NDNtube and VoNDN applications.Várias aplicações atuais, como o Netflix e o YouTube, têm vindo a usar a Internet como uma rede de distribuição de conteúdos. O Named Data Networking (NDN) é um paradigma recente nas redes de comunicações que tenta responder às necessidades das aplicações modernas, através da nomeação dos conteúdos. O NDN promete uma otimização da distribuição dos conteúdos usando uma rede centrada nos conteúdos. Uma das características principais do NDN é o uso da cache disponivel nos nós da rede para melhorar a eficiência desta em termos de distribuição de conteúdos. No entanto, a colocação dos conteúdos em cache pode colocar em risco a privacidade dos consumidores. Uma vez que a resposta temporal de um conteúdo em cache é diferente do de um conteúdo que não está em cache, o adversário pode distinguir os conteúdos que estão em cache dos que não estão em cache, através das respostas de side-channel. O objectivo do ataque pode ser direcionado para o conteúdo, o nome ou a assinatura da mensagem. Por exemplo, o adversário pode obter o histórico de chamadas, a localização do callee ou do caller num serviço seguro de voz sobre NDN (VoNDN) e a popularidade do conteúdos em aplicações de streaming (e.g. NDNtube, NDNlive) através das respostas temporais de side-channel. O side-channel timing attack pode ser mitigado manipulando o tempo das respostas dos routers. As contramedidas propostas por outros pesquisadores, tais como o atraso adicional, o cache aleatório /probabilístico, as assinaturas de grupo e não fazer cache, podem ser efetivamente usadas para mitigar um ataque. No entanto, a distribuição de conteúdos pode ser afetada por contramedidas pré-configuradas que podem ir contra o propósito original do paradigma NDN. Neste trabalho, a abordagem de detecção e defesa (DaD) é proposta para mitigar o ataque de forma eficiente e eficaz. Com o uso do DaD, um ataque pode ser detectado por um mecanismo de detecção multi-nível, a fim de aplicar as contramedidas contra as interfaces dos adversários. Além disso, as detecções podem ser usadas para determinar a gravidade do ataque. A fim de detectar o comportamento de um adversário, um timing attack de força-bruta foi implementado e simulado com as seguintes aplicações e plataformas (testbeds): i. uma aplicação segura que implementa o VoNDN e identifica o certificado em cache numa plataforma NDN mundial; e ii. uma aplicação de streaming do tipo NDNtube para identificar a popularidade de vídeos na plataforma NDN da empresa AT&T. Os resultados da simulação mostraram que a detecção multi-nível oferecida pelo DaD atenuou o ataque cerca de 39,1% em best-route e 36,5% em comunicações multicast. Para avaliar o efeito nos pedidos legítimos, comparou-se o DaD com uma contramedida estática, tendo-se verificado que o DaD foi capaz de preservar todos os pedidos legítimos

Proactive Mechanisms for Video-on-Demand Content Delivery

Video delivery over the Internet is the dominant source of network load all over the world. Especially VoD streaming services such as YouTube, Netflix, and Amazon Video have propelled the proliferation of VoD in many peoples' everyday life. VoD allows watching video from a large quantity of content at any time and on a multitude of devices, including smart TVs, laptops, and smartphones. Studies show that many people under the age of 32 grew up with VoD services and have never subscribed to a traditional cable TV service. This shift in video consumption behavior is continuing with an ever-growing number of users. satisfy this large demand, VoD service providers usually rely on CDN, which make VoD streaming scalable by operating a geographically distributed network of several hundreds of thousands of servers. Thereby, they deliver content from locations close to the users, which keeps traffic local and enables a fast playback start. CDN experience heavy utilization during the day and are usually reactive to the user demand, which is not optimal as it leads to expensive over-provisioning, to cope with traffic peaks, and overreacting content eviction that decreases the CDN's performance. However, to sustain future VoD streaming projections with hundreds of millions of users, new approaches are required to increase the content delivery efficiency. To this end, this thesis identifies three key research areas that have the potential to address the future demand for VoD content. Our first contribution is the design of vFetch, a privacy-preserving prefetching mechanism for mobile devices. It focuses explicitly on OTT VoD providers such as YouTube. vFetch learns the user interest towards different content channels and uses these insights to prefetch content on a user terminal. To do so, it continually monitors the user behavior and the device's mobile connectivity pattern, to allow for resource-efficient download scheduling. Thereby, vFetch illustrates how personalized prefetching can reduce the mobile data volume and alleviate mobile networks by offloading peak-hour traffic. Our second contribution focuses on proactive in-network caching. To this end, we present the design of the ProCache mechanism that divides the available cache storage concerning separate content categories. Thus, the available storage is allocated to these divisions based on their contribution to the overall cache efficiency. We propose a general work-flow that emphasizes multiple categories of a mixed content workload in addition to a work-flow tailored for music video content, the dominant traffic source on YouTube. Thereby, ProCache shows how content-awareness can contribute to efficient in-network caching. Our third contribution targets the application of multicast for VoD scenarios. Many users request popular VoD content with only small differences in their playback start time which offers a potential for multicast. Therefore, we present the design of the VoDCast mechanism that leverages this potential to multicast parts of popular VoD content. Thereby, VoDCast illustrates how ISP can collaborate with CDN to coordinate on content that should be delivered by ISP-internal multicast