Analysis and implementation of the Large Scale Video-on-Demand System

Next Generation Network (NGN) provides multimedia services over broadband based networks, which supports high definition TV (HDTV), and DVD quality video-on-demand content. The video services are thus seen as merging mainly three areas such as computing, communication, and broadcasting. It has numerous advantages and more exploration for the large-scale deployment of video-on-demand system is still needed. This is due to its economic and design constraints. It's need significant initial investments for full service provision. This paper presents different estimation for the different topologies and it require efficient planning for a VOD system network. The methodology investigates the network bandwidth requirements of a VOD system based on centralized servers, and distributed local proxies. Network traffic models are developed to evaluate the VOD system's operational bandwidth requirements for these two network architectures. This paper present an efficient estimation of the of the bandwidth requirement for the different architectures.Comment: 9 pages, 8 figure

Energy-Efficient VoD content delivery and replication in integrated metro/access networks

Today's growth in the demand for access bandwidth is driven by the success of the Video-on-Demand (VoD) bandwidth-consuming service. At the current pace at which network operators increase the end users' access bandwidth, and with the current network infrastructure, a large amount of video traffic is expected to flood the core/metro segments of the network in the near future, with the consequent risk of congestion and network disruption. There is a growing body of research studying the migration of content towards the users. Further, the current trend towards the integration of metro and access segments of the network makes it possible to deploy Metro Servers (MSes) that may serve video content directly from the novel integrated metro/access segment to keep the VoD traffic as local as possible. This paper investigates a potential risk of this solution, which is the increase in the overall network energy consumption. First, we identify a detailed power model for network equipment and MSes, accounting for fixed and load-proportional contributions. Then, we define a novel strategy for controlling whether to switch MSes and network interfaces on and off so as to strike a balance between the energy consumption for content transport through the network and the energy consumption for processing and storage in the MSes. By means of simulations and taking into account real values for the equipment power consumption, we show that our strategy is effective in providing the least energy consumption for any given traffic load

Class Based Admission Control by Complete Partitioning -Video on Demand Server

In the next generation network (NGN) environment specific consideration is on bandwidth minimization, because this reduces the cost of network. In response to the growing market demand for multimedia traffic transmission, NGN concept has been produced. The next generation network provides multimedia services over high speed networks, which supports DVD quality video on demand. Although it has numerous advantages, more exploration of the large-scale deployment video on demand is still needed. The focus of the research presented in this paper is a class based admission control by the complete partitioning of the video on demand server. In this paper we present analytically and by simulation how the blockage probability of the server significantly affects the on demand video request and the service. We also present how the blockage probability affects the performance of the video on demand server.Comment: 12 Pages, IJCN

Cost optimized multipath scheduling in 5G for Video-on-Demand traffic

This paper evaluates the limitations of existing scheduling algorithms when video-on-demand traffic is transported in multipath scenarios, and proposes a new scheduling algorithm called cost-optimized multipath (COM). The new algorithm is designed to decrease the mobile network operators' cost of the delivery of bursty video-on-demand traffic over multipath networks access. Local and Internet connected testbeds, as well as trials with real cellular customers have been deployed to analyse the video performance over MPTCP-based multipath. The results clearly demonstrate the impact the bursty nature of video-on-demand traffic has on the scheduling decisions in multipath scenarios, when traditional latency-based or cheapest-path-first schedulers are deployed. Based on the testbed and trial results, this paper presents the design of a new simple and scalable scheduling algorithm. The paper describes the typical use cases and shows preliminary testbed results, clearly demonstrating the cost benefits of the new algorithm, and indicating that the right balance between the user QoE and the operator cost can be achieved for the video traffic

Cost-efficient multipath scheduling of video-on-demand traffic for the 5G ATSSS splitting function

In modern multiservice networks, with terminals equipped with multiple network interfaces, there is a clear trend to move from the dominating single path transport towards multipath. There are obvious benefits of the multipath service delivery – these include better resilience and improved throughput – and the standardization of multipath transport protocols MP-TCP, MP-DCCP, MP-QUIC and their usage in the 3GPP rel. 16 5G ATSSS (Access Traffic Splitting, Steering and Switching) multipath framework pave the way for broad implementation. While the field of traffic distribution algorithms for multipath transport is subject of extensive research, this paper addresses the challenge of cost-based optimization of scheduling in the multipath 3GPP ATSSS context. The paper demonstrates that there is a major conflict for the Video-on-Demand (VoD) traffic between the achievable QoE and the consumed multipath resources when a simple path prioritization algorithm – e.g. the Cheapest-Path-First (CPF) – is used to direct traffic. Using real network and testbed trials, this paper shows that for VoD in multipath up to 90% of the expensive path resources are consumed while QoE does not take any advantage from this, primarily because of the natural burstiness of the VoD traffic. The paper then proposes a novel service transparent and lightweight Cost-Optimized-Multipath (COM) traffic scheduling algorithm. Using extensive measurement of YouTube video streams and a MP-TCP implementation of the COM scheduler, this work demonstrates that – by finding the right balance between the QoE and the incurred costs – the new scheduler can provide better QoE compared to the single path transport, while eliminating the spurious resource consumption on the expensive path

A Client-Server System for Ubiquitous Video Service

In this work we introduce a simple client-server system architecture and algorithms for ubiquitous live video and VOD service support. The main features of the system are: efficient usage of network resources, emphasis on user personalization, and ease of implementation. The system supports many continuous service requirements such as QoS provision, user mobility between networks and between different communication devices, and simultaneous usage of a device by a number of users

A Naïve Visual Cryptographic Algorithm for the Transfer of Compressed Medical Images

The transmission of a suitably compressed image over a bandwidth, over long distances, gives rise towards a new era in the field of information technology. A gradual increase in this appending scenic application, involving the transfer of the images securely over the Ethernet has become an increasingly important aspect to be addressed during thou phenomenon, especially in the transfer of the digital medical images vividly, encapsulated with abundant information related to these images. The compressed medical images of the DICOM format contain certain amount of confidential data, pertaining to a clinical research or to an individual, and the confidentiality of the same has to be preserved from various security threats and eves-dropping. With a widespread applications among various multimedia applicative systems, telemedicine, medical imaging, military and certain safety-critical applications, inter-net and intra-net communicative applications, etc, a reliable transfer of suitable information, efficiently & securely is considered as one of the revolutionary aims in today’s communication technology and visual cryptographic methodologies. Real-time applications as such detailed above majorly is concerned with the security measures and many algorithms have been developed as a proof for various visual cryptographic methodologies. In this paper we propose an efficient and a reliable visual cryptographic methodology which focuses on the encryption and decryption of the two-dimensional DICOM standard compressed medical image, effectively.  This paper discusses an efficient design of 192 bit encoder using AES Rijndael Algorithm with the decomposition of an image into square image size blocks and the image blocks are shuffled using 2D CAT map. The shuffling of the image blocks/pixels employs a Logistic map of these image pixels coupled with 2D mapping of the pixels of the DICOM standard medical image, generated randomly, being the control parameter thereby creating a confusion between the cipher and the plain image, gradually increasing the resistive factor against the significant attacks. This paper proposes various analytical metrics such as correlation analysis, entropy analysis, homogeneity analysis, energy analysis, contrast and mean of absolute deviation analysis, to evaluate the proposed algorithm, and their suitability in image encryption applications

QoE over-the-top multimédia em redes sem fios

One of the goals of an operator is to improve the Quality of Experience (QoE) of a client in networks where Over-the-top (OTT) content is being delivered. The appearance of services like YouTube, Netflix or Twitch, where in the first case it contains more than 300 hours of video per minute in the platform, brings issues to the managed data networks that already exist, as well as challenges to fix them. Video traffic corresponds to 75% of the whole transmitted data on the Internet. This way, not only the Internet did become the ’de facto’ video transmission path, but also the general data traffic continues to exponentially increase, due to the desire to consume more content. This thesis presents two model proposals and architecture that aim to improve the users’ quality of experience, by predicting the amount of video in advance liable of being prefetched, as a way to optimize the delivery efficiency where the quality of service cannot be guaranteed. The prefetch is done in the clients’ closest cache server. For that, an Analytic Hierarchy Process (AHP) is used, where through a subjective method of attribute comparison, and from the application of a weighted function on the measured quality of service metrics, the amount of prefetch is achieved. Besides this method, artificial intelligence techniques are also taken into account. With neural networks, there is an attempt of selflearning with the behavior of OTT networks with more than 14.000 hours of video consumption under different quality conditions, to try to estimate the experience felt and maximize it, without the normal service delivery degradation. At last, both methods are evaluated and a proof of concept is made with users in a high speed train.Um dos objetivos de um operador é melhorar a qualidade de experiência do cliente em redes onde existem conteúdos Over-the-top (OTT) a serem entregues. O aparecimento de serviços como o YouTube, Netflix ou Twitch, onde no primeiro caso são carregadas mais de 300 horas de vídeo por minuto na plataforma, vem trazer problemas às redes de dados geridas que já existiam, assim como desafios para os resolver. O tráfego de vídeo corresponde a 75% de todos os dados transmitidos na Internet. Assim, não só a Internet se tornou o meio de transmissão de vídeo ’de facto’, como o tráfego de dados em geral continua a crescer exponencialmente, proveniente do desejo de consumir mais conteúdos. Esta tese apresenta duas propostas de modelos e arquitetura que pretendem melhorar a qualidade de experiência do utilizador, ao prever a quantidade de vídeo em avanço passível de ser précarregado, de forma a optimizar a eficiência de entrega das redes onde a qualidade de serviço não é possível de ser garantida. O pré-carregamento dos conteúdos é feito no servidor de cache mais próximo do cliente. Para tal, é utilizado um processo analítico hierárquico (AHP), onde através de um método subjetivo de comparação de atributos, e da aplicação de uma função de valores ponderados nas medições das métricas de qualidade de serviço, é obtida a quantidade a pré-carregar. Além deste método, é também proposta uma abordagem com técnicas de inteligência artificial. Através de redes neurais, há uma tentativa de auto-aprendizagem do comportamento das redes OTT com mais de 14.000 horas de consumo de vídeo sobre diferentes condições de qualidade, para se tentar estimar a experiência sentida e maximizar a mesma, sem degradação da entrega de serviço normal. No final, ambos os métodos propostos são avaliados num cenário de utilizadores num comboio a alta velocidade.Mestrado em Engenharia de Computadores e Telemátic