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

Efficient Traffic Control of VoD System

It has been a challenging issue to provide digital quality multimedia data stream to the remote user through the distributed system. The main aspects to design the real distributed system, which reduce the cost of the network by means of reduce packet loss and enhanced over all system performance. Since the number of user increased rapidly in the network it posed heavy load to the video servers. The requested clients, servers are all distributed in nature and the data stream delivered to the user without error. In this work I have presented the performance of the video on demand server by efficient traffic control at real time with respect to incoming multirate traffic pattern . In this work, I present how the overall system performance gradually decreases when the client population sized in the clusters increase. This work indicated the load balancing required for the on demand video distributed system to provide efficient cost effective service to the local or remote clients.Comment: 12 pages, 12 figur

User behavior impact on IPTV platform performance

Tese de mestrado em Segurança Informática, apresentada à Universidade de Lisboa, através da Faculdade de Ciências, 2010As plataformas de IPTV têm sido introduzidas pelos prestadores de serviços de rede e de telecomunicações como forma de competir com os operadores de cabo e satélite, impulsionando a receita por utilizador e simultaneamente reduzindo, na medida do possível, os custos associados à exploração de infra-estrutura legada. Através da análise de métricas de desempenho relativas ao funcionamento interno de um sistema complexo procuramos revelar padrões e ocorrências isoladas que possam indicar a existência de problemas de desempenho. Usando esta informação, analisámos também as características da actividade dos utilizadores. A hipótese subjacente é que deve ser possível correlacionar o desempenho de um sistema ou sub-sistema tendo por base o comportamento dos utilizadores, mesmo que estes não interajam directamente com o referido sub-sistema. Adicionalmente, esta correlação deve seguir regras que possam ser usadas, por exemplo, para redefinir a arquitectura do sistema ou detectar anomalias proactivamente. Neste projecto analisámos métricas de desempenho dos Servidores de Distribuição e dos Servidores de VOD. De seguida estudámos os Registos de Actividade das STB de forma a caracterizar as acções dos utilizadores que têm maior influência no desempenho da plataforma de IPTV. Demonstrámos que estas análises em domínios distintos (utilizadores/STB e servidores internos) pode convergir e possibilitar a activação de alarmes quando a probabilidade de ocorrência de problemas de desempenho é elevada.IPTV platforms are being introduced by many network operators in order to compete with cable and satellite operators, increasing the average revenue per user, while taking advantage and reducing as much as possible the losses associated with legacy infra-structure. By analyzing performance metrics regarding the inner works of complex systems we aimed at unveiling patterns and identifying outlier occurrences that indicate actual or potential problems. Using such information we analyzed user activity information seeking to match the identified outlier patterns with characteristic user activity. The broader underlying hypothesis is that it is possible to correlate a system, or system’s performance problem based on the behavior of the end users even if they do not interact with it. Furthermore, we assume that this correlation follow rules which could thereafter be used for architecture redesign and proactive anomaly detection. In this project, we examined performance metrics of the Distribution Servers and VOD Servers. We then used STB activity logs to characterize the user actions with greater influence on the IPTV platform. We showed that these analyzes of multiple domains (user/STB and internal servers) can be merged enabling to raise alerts whenever there is high probability of occurring efficiency problems in the system

Self-Optimization of Internet Services with Dynamic Resource Provisioning

Self-optimization through dynamic resource provisioning is an appealing approach to tackle load variation in Internet services. It allows to assign or release resources to/from Internet services according to the varying load. However, dynamic resource provisioning raises several challenges among which: (i) How to plan a good capacity of an Internet service, i.e.~a necessary and sufficient amount of resource to handle the Internet service workload, (ii) How to manage both gradual load variation and load peaks in Internet services, (iii) How to prevent system oscillations in presence of potentially concurrent dynamic resource provisioning, and (iv) How to provide generic self-optimization that applies to different Internet services such as e-mail services, streaming servers or e-commerce web systems. This paper precisely answers these questions. It presents the design principles and implementation details of a self-optimization autonomic manager. It describes the results of an experimental evaluation of the self-optimization manager with a realistic e-commerce multi-tier web application running in a Linux cluster of computers. The experimental results show the usefulness of self-optimization in terms of end-user's perceived performance and system's operational costs, with a negligible overhead

CloudMedia: When cloud on demand meets video on demand

Internet-based cloud computing is a new computing paradigm aiming to provide agile and scalable resource access in a utility-like fashion. Other than being an ideal platform for computation-intensive tasks, clouds are believed to be also suitable to support large-scale applications with periods of flash crowds by providing elastic amounts of bandwidth and other resources on the fly. The fundamental question is how to configure the cloud utility to meet the highly dynamic demands of such applications at a modest cost. In this paper, we address this practical issue with solid theoretical analysis and efficient algorithm design using Video on Demand (VoD) as the example application. Having intensive bandwidth and storage demands in real time, VoD applications are purportedly ideal candidates to be supported on a cloud platform, where the on-demand resource supply of the cloud meets the dynamic demands of the VoD applications. We introduce a queueing network based model to characterize the viewing behaviors of users in a multichannel VoD application, and derive the server capacities needed to support smooth playback in the channels for two popular streaming models: client-server and P2P. We then propose a dynamic cloud resource provisioning algorithm which, using the derived capacities and instantaneous network statistics as inputs, can effectively support VoD streaming with low cloud utilization cost. Our analysis and algorithm design are verified and extensively evaluated using large-scale experiments under dynamic realistic settings on a home-built cloud platform. © 2011 IEEE.published_or_final_versionThe 31st International Conference on Distributed Computing Systems (ICDCS 2011), Minneapolis, MN., 20-24 June 2011. In Proceedings of 31st ICDCS, 2011, p. 268-27

Performance Analysis of IO Intensive Task Allocation Strategies for Heterogeneous Web Servers

The current rate of growth of the World Wide Web has led to an explosion in internet traffic for many popular websites. To overcome the problem of falling quality of service for its customers an efficient approach would be to use a heterogeneous cluster of nodes which replicate the entire site data. In a centralized system, a master node would load balance the user requests and allocate them to the appropriate node. A web application which mainly provides file sharing services to its users offers a system where the tasks are basically of retrieval based nature and hence more IO intensive. In order to address the allocation problem of these tasks, several IO aware policies have been designed and compared with respect to certain standard performance metrics. The study shows that considering the IO nature of tasks yields significantly better results than other existing algorithms