Live media production: multicast optimization and visibility for clos fabric in media data centers

Media production data centers are undergoing a major architectural shift to introduce digitization concepts to media creation and media processing workflows. Content companies such as NBC Universal, CBS/Viacom and Disney are modernizing their workflows to take advantage of the flexibility of IP and virtualization. In these new environments, multicast is utilized to provide point-to-multi-point communications. In order to build point-to-multi-point trees, Multicast has an established set of control protocols such as IGMP and PIM. The existing multicast protocols do not optimize multicast tree formation for maximizing network throughput which lead to decreased fabric utilization and decreased total number of admitted flows. In addition, existing multicast protocols are not bandwidth-aware and could cause links to over-subscribe leading to packet loss and lower video quality. TV production traffic patterns are unique due to ultra high bandwidth requirements and high sensitivity to packet loss that leads to video impairments. In such environments, operators need monitoring tools that are able to proactively monitor video flows and provide actionable alerts. Existing network monitoring tools are inadequate because they are reactive by design and perform generic monitoring of flows with no insights into video domain. The first part of this dissertation includes a design and implementation of a novel Intelligent Rendezvous Point algorithm iRP for bandwidth-aware multicast routing in media DC fabrics. iRP utilizes a controller-based architecture to optimize multicast tree formation and to increase bandwidth availability in the fabric. The system offers up to 50\% increase in fabric capacity to handle multicast flows passing through the fabric. In the second part of this dissertation, DiRP algorithm is presented. DiRP is based on a distributed decision-making approach to achieve multicast tree capacity optimization while maintaining low multicast tree setup time. DiRP algorithm is tested using commercially available data center switches. DiRP algorithm offers substantially lower path setup time compared to centralized systems while maintaining bandwidth awareness when setting up the fabric. The third part of this dissertation studies the utilization of machine learning algorithms to improve on multicast efficiency in the fabric. The work includes implementation and testing of LiRP algorithm to increase iRP\u27s fabric efficiency by implementing k-fold cross validation method to predict future multicast group memberships for time-series analysis. Testing results confirm that LiRP system increases the efficiency of iRP by up to 40\% through prediction of multicast group memberships with online arrival. In the fourth part of this dissertation, The problem of live video monitoring is studied. Existing network monitoring tools are either reactive by design or perform generic monitoring of flows with no insights into video domain. MediaFlow is a robust system for active network monitoring and reporting of video quality for thousands of flows simultaneously using a fraction of the cost of traditional monitoring solutions. MediaFlow is able to detect and report on integrity of video flows at a granularity of 100 mSec at line rate for thousands of flows. The system increases video monitoring scale by a thousand-fold compared to edge monitoring solutions

On energy consumption of switch-centric data center networks

Data center network (DCN) is the core of cloud computing and accounts for 40% energy spend when compared to cooling system, power distribution and conversion of the whole data center (DC) facility. It is essential to reduce the energy consumption of DCN to esnure energy-efficient (green) data center can be achieved. An analysis of DC performance and efficiency emphasizing the effect of bandwidth provisioning and throughput on energy proportionality of two most common switch-centric DCN topologies: three-tier (3T) and fat tree (FT) based on the amount of actual energy that is turned into computing power are presented. Energy consumption of switch-centric DCNs by realistic simulations is analyzed using GreenCloud simulator. Power related metrics were derived and adapted for the information technology equipment (ITE) processes within the DCN. These metrics are acknowledged as subset of the major metrics of power usage effectiveness (PUE) and data center infrastructure efficiency (DCIE), known to DCs. This study suggests that despite in overall FT consumes more energy, it spends less energy for transmission of a single bit of information, outperforming 3T

Datacenter Traffic Control: Understanding Techniques and Trade-offs

Datacenters provide cost-effective and flexible access to scalable compute and storage resources necessary for today's cloud computing needs. A typical datacenter is made up of thousands of servers connected with a large network and usually managed by one operator. To provide quality access to the variety of applications and services hosted on datacenters and maximize performance, it deems necessary to use datacenter networks effectively and efficiently. Datacenter traffic is often a mix of several classes with different priorities and requirements. This includes user-generated interactive traffic, traffic with deadlines, and long-running traffic. To this end, custom transport protocols and traffic management techniques have been developed to improve datacenter network performance. In this tutorial paper, we review the general architecture of datacenter networks, various topologies proposed for them, their traffic properties, general traffic control challenges in datacenters and general traffic control objectives. The purpose of this paper is to bring out the important characteristics of traffic control in datacenters and not to survey all existing solutions (as it is virtually impossible due to massive body of existing research). We hope to provide readers with a wide range of options and factors while considering a variety of traffic control mechanisms. We discuss various characteristics of datacenter traffic control including management schemes, transmission control, traffic shaping, prioritization, load balancing, multipathing, and traffic scheduling. Next, we point to several open challenges as well as new and interesting networking paradigms. At the end of this paper, we briefly review inter-datacenter networks that connect geographically dispersed datacenters which have been receiving increasing attention recently and pose interesting and novel research problems.Comment: Accepted for Publication in IEEE Communications Surveys and Tutorial

Wireless Communication in Data Centers: A Survey

Data centers (DCs) is becoming increasingly an integral part of the computing infrastructures of most enterprises. Therefore, the concept of DC networks (DCNs) is receiving an increased attention in the network research community. Most DCNs deployed today can be classified as wired DCNs as copper and optical fiber cables are used for intra- and inter-rack connections in the network. Despite recent advances, wired DCNs face two inevitable problems; cabling complexity and hotspots. To address these problems, recent research works suggest the incorporation of wireless communication technology into DCNs. Wireless links can be used to either augment conventional wired DCNs, or to realize a pure wireless DCN. As the design spectrum of DCs broadens, so does the need for a clear classification to differentiate various design options. In this paper, we analyze the free space optical (FSO) communication and the 60 GHz radio frequency (RF), the two key candidate technologies for implementing wireless links in DCNs. We present a generic classification scheme that can be used to classify current and future DCNs based on the communication technology used in the network. The proposed classification is then used to review and summarize major research in this area. We also discuss open questions and future research directions in the area of wireless DCs

Source-Routed Multicast Schemes for Large-Scale Cloud Data Center Networks

Data centers (DCs) have been witnessing unprecedented growth in size, number and complexity in recent years. They consist of tens of thousands of servers interconnected by fast network switches, hosting and enabling numerous applications with various traffic characteristics and requirements. As a result, DC networks have been presented with several unique challenges, pertaining to the scaling and allocation of network resources during the forwarding and moving of data across the different DC servers. Traffic routing in general and multicast routing in particular are important functions in DC networks, especially that modern cloud DCs tend to exhibit one-to-many communication traffic patterns. Unfortunately, recent multicast routing approaches that adopt IP multicast suffer from scalability and load balancing issues, and do not scale well with the number of supported multicast groups when used for cloud DC networks. In this thesis, we propose a set of new, complementary schemes that overcome these challenges. More specifically, firstly, we study existing DC network topologies, and propose Circulant Fat-Tree topology, an improvement over the traditional Fat-Tree topology with better properties to suit nowadays DC networks. Then, we review and classify recent studies that investigate and measure the traffic behavior of operational DC networks. We focus on the way they collect the traffic as well as on the key findings made in these studies. Secondly, we propose Bert, a source-initiated multicast routing scheme for DCs. Bert scales well with both the number and the size of multicast groups, and does so through clustering, by dividing the members of the multicast group into a set of clusters with each cluster employing its own forwarding rules. In essence, Bert yields much lesser multicast traffic overhead than state-of-the-art schemes. Thirdly, we propose, Ernie, a scalable and load-balanced multicast source routing scheme. Ernie introduces a novel method for scaling out the number of supported mul- ticast groups. In particular, it appropriately constructs and organizes multicast header information inside packets in a manner that allows core/root switches to only forward down the needed information. Ernie also introduces an effective multicast traffic load balancing technique across downstream links. Specifically, it prudently assigns multicast groups to core switches to ensure the evenness of load distribution across the downstream links

RDNA: Arquitetura Definida por Resíduos para Redes de Data Centers

"Recentemente, temos observado o crescente uso das tecnologias de informação e da comunicação. Instituições e usuários simplesmente necessitam de alta qualidade na conectividade de seus dados, com expectativa de acesso instantâneo a qualquer hora e em qualquer lugar. Um elemento essencial para garantir qualidade na conectividade da nuvem é a arquitetura da rede de comunicação no Data Center (DCNs - Data Center Networks). Isso ocorre porque uma parte significativa do tráfego da Internet é baseada na comunicação de dados e no processamento que acontece dentro da infraestrutura do Data Center (DC). No entanto, os protocolos de roteamento, a forma de encaminhamento e gerenciamento que são executados atualmente, se revelam insuficientes para atender as demandas atuais por conectividade na nuvem. Isto ocorre principalmente pela dependência da operação de busca nas tabelas de encaminhamento, levando à um incremento de latência fim a fim, ademais, mecanismos de recuperação tradicionais utilizam estados adicionais nas tabelas, aumentando a complexidade nas rotinas de gerenciamento, além de reduzir drasticamente a escalabilidade de proteção nas rotas. Outra dificuldade é a comunicação multicast dentro do DC, as soluções existentes são complexas de implementar e não suportam a configuração dos grupos nas taxas atuais requeridas. Neste contexto, essa tese explora o sistema numérico de resíduos centrado no Teorema Chinês do Resto (TCR) como fundamento, aplicado no projeto de um novo sistema de roteamento para DCN. Mais especificamente, introduzimos a arquitetura RDNA que avança o estado da arte a partir de uma simplificação do modelo de encaminhamento para o núcleo, baseado em uma operação de resíduo (resto da divisão). Nesse sentido, a rota é definida como resíduo entre um identificador de rota e identificadores locais (números primos) atribuídos aos switches de núcleo. Os switches de borda, recebem entradas configurando os fluxos de acordo com a política de rede definida pelo controlador. Cada fluxo é mapeado na borda, através de um identificador de rota principal e um emergencial. Essas operações de resíduos permitem encaminhar os pacotes pela respectiva porta de saída. Em situações de falha, o identificador de rota emergencial viabiliza rápida recuperação enviando os pacotes por uma porta de saída alternativa. A RDNA é escalável assumindo uma topologia 2-tier Clos Network amplamente utilizada em DCNs. Com o objetivo de confrontar a RDNA com outros trabalhos da literatura, analisamos a escalabilidade em termos de número de bits necessário para comunicação unicast e multicast. Na análise, variou-se o número de nós na rede, o grau dos nós e o número de hosts físicos para cada topologia. Na comunicação unicast, a RDNA reduziu em 4.5 vezes o tamanho do cabeçalho, comparada à proposta COXCast. Na comunicação multicast, um modelo de programação linear foi concebido para minimizar uma função polinomial. A RDNA reduziu em até 50% o tamanho do cabeçalho comparando com a mesma quantidade de membros por grupo. Como prova de conceito, dois protótipos foram implementados, um no ambiente emulado Mininet e outro na plataforma NetFPGA SUME. Os resultados mostraram que a RDNA alcança latência determinística no encaminhamento dos pacotes, 600 nanosegundos no tempo de comutação por elemento de núcleo, recuperação de falha ultra-rápida na ordem de microssegundos e sem variação de latência (jitter) no núcleo da rede.