Multimedia delivery in the future internet

The term “Networked Media” implies that all kinds of media including text, image, 3D graphics, audio and video are produced, distributed, shared, managed and consumed on-line through various networks, like the Internet, Fiber, WiFi, WiMAX, GPRS, 3G and so on, in a convergent manner [1]. This white paper is the contribution of the Media Delivery Platform (MDP) cluster and aims to cover the Networked challenges of the Networked Media in the transition to the Future of the Internet. Internet has evolved and changed the way we work and live. End users of the Internet have been confronted with a bewildering range of media, services and applications and of technological innovations concerning media formats, wireless networks, terminal types and capabilities. And there is little evidence that the pace of this innovation is slowing. Today, over one billion of users access the Internet on regular basis, more than 100 million users have downloaded at least one (multi)media file and over 47 millions of them do so regularly, searching in more than 160 Exabytes1 of content. In the near future these numbers are expected to exponentially rise. It is expected that the Internet content will be increased by at least a factor of 6, rising to more than 990 Exabytes before 2012, fuelled mainly by the users themselves. Moreover, it is envisaged that in a near- to mid-term future, the Internet will provide the means to share and distribute (new) multimedia content and services with superior quality and striking flexibility, in a trusted and personalized way, improving citizens’ quality of life, working conditions, edutainment and safety. In this evolving environment, new transport protocols, new multimedia encoding schemes, cross-layer inthe network adaptation, machine-to-machine communication (including RFIDs), rich 3D content as well as community networks and the use of peer-to-peer (P2P) overlays are expected to generate new models of interaction and cooperation, and be able to support enhanced perceived quality-of-experience (PQoE) and innovative applications “on the move”, like virtual collaboration environments, personalised services/ media, virtual sport groups, on-line gaming, edutainment. In this context, the interaction with content combined with interactive/multimedia search capabilities across distributed repositories, opportunistic P2P networks and the dynamic adaptation to the characteristics of diverse mobile terminals are expected to contribute towards such a vision. Based on work that has taken place in a number of EC co-funded projects, in Framework Program 6 (FP6) and Framework Program 7 (FP7), a group of experts and technology visionaries have voluntarily contributed in this white paper aiming to describe the status, the state-of-the art, the challenges and the way ahead in the area of Content Aware media delivery platforms

An Efficient Holistic Data Distribution and Storage Solution for Online Social Networks

In the past few years, Online Social Networks (OSNs) have dramatically spread over the world. Facebook [4], one of the largest worldwide OSNs, has 1.35 billion users, 82.2% of whom are outside the US [36]. The browsing and posting interactions (text content) between OSN users lead to user data reads (visits) and writes (updates) in OSN datacenters, and Facebook now serves a billion reads and tens of millions of writes per second [37]. Besides that, Facebook has become one of the top Internet traffic sources [36] by sharing tremendous number of large multimedia files including photos and videos. The servers in datacenters have limited resources (e.g. bandwidth) to supply latency efficient service for multimedia file sharing among the rapid growing users worldwide. Most online applications operate under soft real-time constraints (e.g., ≤ 300 ms latency) for good user experience, and its service latency is negatively proportional to its income. Thus, the service latency is a very important requirement for Quality of Service (QoS) to the OSN as a web service, since it is relevant to the OSN’s revenue and user experience. Also, to increase OSN revenue, OSN service providers need to constrain capital investment, operation costs, and the resource (bandwidth) usage costs. Therefore, it is critical for the OSN to supply a guaranteed QoS for both text and multimedia contents to users while minimizing its costs. To achieve this goal, in this dissertation, we address three problems. i) Data distribution among datacenters: how to allocate data (text contents) among data servers with low service latency and minimized inter-datacenter network load; ii) Efficient multimedia file sharing: how to facilitate the servers in datacenters to efficiently share multimedia files among users; iii) Cost minimized data allocation among cloud storages: how to save the infrastructure (datacenters) capital investment and operation costs by leveraging commercial cloud storage services. Data distribution among datacenters. To serve the text content, the new OSN model, which deploys datacenters globally, helps reduce service latency to worldwide distributed users and release the load of the existing datacenters. However, it causes higher inter-datacenter communica-tion load. In the OSN, each datacenter has a full copy of all data, and the master datacenter updates all other datacenters, generating tremendous load in this new model. The distributed data storage, which only stores a user’s data to his/her geographically closest datacenters, simply mitigates the problem. However, frequent interactions between distant users lead to frequent inter-datacenter com-munication and hence long service latencies. Therefore, the OSNs need a data allocation algorithm among datacenters with minimized network load and low service latency. Efficient multimedia file sharing. To serve multimedia file sharing with rapid growing user population, the file distribution method should be scalable and cost efficient, e.g. minimiza-tion of bandwidth usage of the centralized servers. The P2P networks have been widely used for file sharing among a large amount of users [58, 131], and meet both scalable and cost efficient re-quirements. However, without fully utilizing the altruism and trust among friends in the OSNs, current P2P assisted file sharing systems depend on strangers or anonymous users to distribute files that degrades their performance due to user selfish and malicious behaviors. Therefore, the OSNs need a cost efficient and trustworthy P2P-assisted file sharing system to serve multimedia content distribution. Cost minimized data allocation among cloud storages. The new trend of OSNs needs to build worldwide datacenters, which introduce a large amount of capital investment and maintenance costs. In order to save the capital expenditures to build and maintain the hardware infrastructures, the OSNs can leverage the storage services from multiple Cloud Service Providers (CSPs) with existing worldwide distributed datacenters [30, 125, 126]. These datacenters provide different Get/Put latencies and unit prices for resource utilization and reservation. Thus, when se-lecting different CSPs’ datacenters, an OSN as a cloud customer of a globally distributed application faces two challenges: i) how to allocate data to worldwide datacenters to satisfy application SLA (service level agreement) requirements including both data retrieval latency and availability, and ii) how to allocate data and reserve resources in datacenters belonging to different CSPs to minimize the payment cost. Therefore, the OSNs need a data allocation system distributing data among CSPs’ datacenters with cost minimization and SLA guarantee. In all, the OSN needs an efficient holistic data distribution and storage solution to minimize its network load and cost to supply a guaranteed QoS for both text and multimedia contents. In this dissertation, we propose methods to solve each of the aforementioned challenges in OSNs. Firstly, we verify the benefits of the new trend of OSNs and present OSN typical properties that lay the basis of our design. We then propose Selective Data replication mechanism in Distributed Datacenters (SD3) to allocate user data among geographical distributed datacenters. In SD3,a datacenter jointly considers update rate and visit rate to select user data for replication, and further atomizes a user’s different types of data (e.g., status update, friend post) for replication, making sure that a replica always reduces inter-datacenter communication. Secondly, we analyze a BitTorrent file sharing trace, which proves the necessity of proximity-and interest-aware clustering. Based on the trace study and OSN properties, to address the second problem, we propose a SoCial Network integrated P2P file sharing system for enhanced Efficiency and Trustworthiness (SOCNET) to fully and cooperatively leverage the common-interest, geographically-close and trust properties of OSN friends. SOCNET uses a hierarchical distributed hash table (DHT) to cluster common-interest nodes, and then further clusters geographically close nodes into a subcluster, and connects the nodes in a subcluster with social links. Thus, when queries travel along trustable social links, they also gain higher probability of being successfully resolved by proximity-close nodes, simultaneously enhancing efficiency and trustworthiness. Thirdly, to handle the third problem, we model the cost minimization problem under the SLA constraints using integer programming. According to the system model, we propose an Eco-nomical and SLA-guaranteed cloud Storage Service (ES3), which finds a data allocation and resource reservation schedule with cost minimization and SLA guarantee. ES3 incorporates (1) a data al-location and reservation algorithm, which allocates each data item to a datacenter and determines the reservation amount on datacenters by leveraging all the pricing policies; (2) a genetic algorithm based data allocation adjustment approach, which makes data Get/Put rates stable in each data-center to maximize the reservation benefit; and (3) a dynamic request redirection algorithm, which dynamically redirects a data request from an over-utilized datacenter to an under-utilized datacenter with sufficient reserved resource when the request rate varies greatly to further reduce the payment. Finally, we conducted trace driven experiments on a distributed testbed, PlanetLab, and real commercial cloud storage (Amazon S3, Windows Azure Storage and Google Cloud Storage) to demonstrate the efficiency and effectiveness of our proposed systems in comparison with other systems. The results show that our systems outperform others in the network savings and data distribution efficiency

Development of a system compliant with the Application-Layer Traffic Optimization Protocol

Dissertação de mestrado integrado em Engenharia InformáticaWith the ever-increasing Internet usage that is following the start of the new decade, the need to optimize this world-scale network of computers becomes a big priority in the technological sphere that has the number of users rising, as are the Quality of Service (QoS) demands by applications in domains such as media streaming or virtual reality. In the face of rising traffic and stricter application demands, a better understand ing of how Internet Service Providers (ISPs) should manage their assets is needed. An important concern regards to how applications utilize the underlying network infras tructure over which they reside. Most of these applications act with little regard for ISP preferences, as exemplified by their lack of care in achieving traffic locality during their operation, which would be a preferable feature for network administrators, and that could also improve application performance. However, even a best-effort attempt by applications to cooperate will hardly succeed if ISP policies aren’t clearly commu nicated to them. Therefore, a system to bridge layer interests has much potential in helping achieve a mutually beneficial scenario. The main focus of this thesis is the Application-Layer Traffic Optimization (ALTO) work ing group, which was formed by the Internet Engineering Task Force (IETF) to explore standardizations for network information retrieval. This group specified a request response protocol where authoritative entities provide resources containing network status information and administrative preferences. Sharing of infrastructural insight is done with the intent of enabling a cooperative environment, between the network overlay and underlay, during application operations, to obtain better infrastructural re sourcefulness and the consequential minimization of the associated operational costs. This work gives an overview of the historical network tussle between applications and service providers, presents the ALTO working group’s project as a solution, im plements an extended system built upon their ideas, and finally verifies the developed system’s efficiency, in a simulation, when compared to classical alternatives.Com o acrescido uso da Internet que acompanha o início da nova década, a necessidade de otimizar esta rede global de computadores passa a ser uma grande prioridade na esfera tecnológica que vê o seu número de utilizadores a aumentar, assim como a exigência, por parte das aplicações, de novos padrões de Qualidade de Serviço (QoS), como visto em domínios de transmissão de conteúdo multimédia em tempo real e em experiências de realidade virtual. Face ao aumento de tráfego e aos padrões de exigência aplicacional mais restritos, é necessário melhor compreender como os fornecedores de serviços Internet (ISPs) devem gerir os seus recursos. Um ponto fulcral é como aplicações utilizam os seus recursos da rede, onde muitas destas não têm consideração pelas preferências dos ISPs, como exemplificado pela sua falta de esforço em localizar tráfego, onde o contrário seria preferível por administradores de rede e teria potencial para melhorar o desempenho aplicacional. Uma tentativa de melhor esforço, por parte das aplicações, em resolver este problema, não será bem-sucedida se as preferências administrativas não forem claramente comunicadas. Portanto, um sistema que sirva de ponte de comunicação entre camadas pode potenciar um cenário mutuamente benéfico. O foco principal desta tese é o grupo de trabalho Application-Layer Traffic Optimization (ALTO), que foi formado pelo Internet Engineering Task Force (IETF) para explorar estandardizações para recolha de informação da rede. Este grupo especificou um protocolo onde entidades autoritárias disponibilizam recursos com informação de estado de rede, e preferências administrativas. A partilha de conhecimento infraestrutural é feita para possibilitar um ambiente cooperativo entre redes overlay e underlay, para uma mais eficiente utilização de recursos e a consequente minimização de custos operacionais. É pretendido dar uma visão da histórica disputa entre aplicações e ISPs, assim como apresentar o projeto do grupo de trabalho ALTO como solução, implementar e melhorar sobre as suas ideias, e finalmente verificar a eficiência do sistema numa simulação, quando comparado com alternativas clássicas

Thirty Years of Machine Learning: The Road to Pareto-Optimal Wireless Networks

Future wireless networks have a substantial potential in terms of supporting a broad range of complex compelling applications both in military and civilian fields, where the users are able to enjoy high-rate, low-latency, low-cost and reliable information services. Achieving this ambitious goal requires new radio techniques for adaptive learning and intelligent decision making because of the complex heterogeneous nature of the network structures and wireless services. Machine learning (ML) algorithms have great success in supporting big data analytics, efficient parameter estimation and interactive decision making. Hence, in this article, we review the thirty-year history of ML by elaborating on supervised learning, unsupervised learning, reinforcement learning and deep learning. Furthermore, we investigate their employment in the compelling applications of wireless networks, including heterogeneous networks (HetNets), cognitive radios (CR), Internet of things (IoT), machine to machine networks (M2M), and so on. This article aims for assisting the readers in clarifying the motivation and methodology of the various ML algorithms, so as to invoke them for hitherto unexplored services as well as scenarios of future wireless networks.Comment: 46 pages, 22 fig