Measuring and Understanding Throughput of Network Topologies

High throughput is of particular interest in data center and HPC networks. Although myriad network topologies have been proposed, a broad head-to-head comparison across topologies and across traffic patterns is absent, and the right way to compare worst-case throughput performance is a subtle problem. In this paper, we develop a framework to benchmark the throughput of network topologies, using a two-pronged approach. First, we study performance on a variety of synthetic and experimentally-measured traffic matrices (TMs). Second, we show how to measure worst-case throughput by generating a near-worst-case TM for any given topology. We apply the framework to study the performance of these TMs in a wide range of network topologies, revealing insights into the performance of topologies with scaling, robustness of performance across TMs, and the effect of scattered workload placement. Our evaluation code is freely available

Control Plane Compression

We develop an algorithm capable of compressing large networks into a smaller ones with similar control plane behavior: For every stable routing solution in the large, original network, there exists a corresponding solution in the compressed network, and vice versa. Our compression algorithm preserves a wide variety of network properties including reachability, loop freedom, and path length. Consequently, operators may speed up network analysis, based on simulation, emulation, or verification, by analyzing only the compressed network. Our approach is based on a new theory of control plane equivalence. We implement these ideas in a tool called Bonsai and apply it to real and synthetic networks. Bonsai can shrink real networks by over a factor of 5 and speed up analysis by several orders of magnitude.Comment: Extended version of the paper appearing in ACM SIGCOMM 201

Experimenting with routing protocols in the data center : An ns-3 simulation approach

Massive scale data centers (MSDC) have become a key component of current content-centric Internet architecture. With scales of up to hundreds of thousands servers, conveying traffic inside these infrastructures requires much greater connectivity resources than traditional broadband Internet transit networks. MSDCs use Fat-Tree type topologies, which ensure multipath connectivity and constant bisection bandwidth between servers. To properly use the potential advantages of these topologies, specific routing protocols are needed, with multipath support and low control messaging load. These infrastructures are enormously expensive, and therefore it is not possible to use them to experiment with new protocols; that is why scalable and realistic emulation/simulation environments are needed. Based on previous experiences, in this paper we present extensions to the ns-3 network simulator that allow executing the Free Range Routing (FRR) protocol suite, which support some of the specific MSDC routing protocols. Focused on the Border Gateway Protocol (BGP), we run a comprehensive set of control plane experiments over Fat-Tree topologies, achieving competitive scalability running on a single-host environment, which demonstrates that the modified ns-3 simulator can be effectively used for experimenting in the MSDC. Moreover, the validation was complemented with a theoretical analysis of BGP behavior over selected scenarios. The whole project is available to the community and fully reproducible

Scalable topological forwarding and routing policies in RINA-enabled programmable data centers

This is the peer reviewed version of the following article: Leon Gaixas S, Perelló J, Careglio D, Grasa E, López DR, Aranda PA. Scalable topological forwarding and routing policies in RINA-enabled programmable data centers. Trans Emerging Tel Tech. 2017;28:e3256, DOI 10.1002/ett.3256, which has been published in final form at DOI: 10.1002/ett.3256. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-ArchivingGiven the current expansion of cloud computing, the expected advent of the Internet of Things, and the requirements of future fifth-generation network infrastructures, significantly larger pools of computational and storage resources will soon be required. This emphasizes the need for more scalable data centers that are capable of providing such an amount of resources in a cost-effective way. A quick look into today's commercial data centers shows that they tend to rely on variations of well-defined leaf-spine/Clos data center network (DCN) topologies, offering low latency, ultrahigh bisectional bandwidth, and enhanced reliability against concurrent failures. However, DCNs are typically restricted by the use of the Transmission Control Protocol/Internet Protocol (TCP/IP) suite, thus suffering limited routing scalability. In this work, we study the benefits that replacing TCP/IP with the recursive internetwork architecture (RINA) can bring into commercial DCNs, focusing on forwarding and routing scalability. We quantitatively evaluate the benefits that RINA solutions can yield against those based on TCP/IP and highlight how, by deploying RINA, topological routing solutions can improve even more the efficiency of the network. To this goal, we propose a rule-and-exception forwarding policy tailored to the characteristics of several DCN variants, enabling fast forwarding decisions with merely neighbors' information. Upon failures, few exceptions are necessary, whose computation can also profit from the known topology. Extensive numerical results show that the proposed policy requirements depend mainly on the number of neighbors and concurrent failures in the DCN rather than its size, dramatically reducing the amount of forwarding and routing information stored at DCN nodes.Peer ReviewedPostprint (author's final draft

Control de tráfico en el data center : Un enfoque experimental

Los centros de datos de escala masiva (MSDC, por sus siglas en ingles) se han convertido en un componente clave de la arquitectura de Internet. Con escalas de hasta cientos de miles de servidores, transportar tráfico dentro de estas infraestructuras requiere recursos de conectividad mucho mayores que en las redes de tránsito tradicionales de Internet. Usualmente, los MSCD utilizan topologías de tipo fat-tree, que brindan diversidad de caminos (o rutas múltiples) y un ancho de banda de bisección constante entre servidores. Para explotar las potenciales ventajas de estas topologías, se necesitan protocolos de enrutamiento específicos, con soporte para rutas múltiples y con baja carga de mensajería del plano de control. Estas infraestructuras tienen un alto costo, y por tanto, no es posible utilizarlas para experimentar con nuevos protocolos. Por esta razón, se necesitan entornos de emulación/simulación escalables y realistas que permitan experimentar emulando o simulando el comportamiento de estas grandes infraestructuras. En este trabajo, se revisaron y desarrollaron distintos ambientes de experimentación, tanto de un único host como distribuidos, que permiten analizar las ventajas y desventajas de las diferentes soluciones. Además, centrados en el Border Gateway Protocol (BGP), se ejecutó un conjunto de experimentos del plano de control sobre topologías fat-tree en entornos simulados y emulados. La validación de los resultados experimentales se complementó con un análisis teórico del comportamiento de BGP sobre un conjunto de escenarios seleccionados. Estos resultados experimentales y teóricos, así como la evaluación y desarrollo de los ambientes de experimentación, fueron oportunamente difundidos a la comunidad científica por medio de publicaciones científicas referadas. Todas los desarrollos de los entornos de experimentación realizados en el marco de este trabajo están disponibles y son reproducibles.Massive Scale Data Centers (MSDC) have become a key component of nowadays content-centric Internet architecture. With scales up to hundred thousands servers, conveying traffic inside these infrastructures requires much larger connectivity resources than traditional broadband Internet transit networks. MSCD uses fat-tree type topologies, which ensure multipath connectivity and constant bisection bandwidth between servers. To properly use the potential advantages of these topologies, specific routing protocols are needed, with multipath support and low control messaging load. These infrastructures are hugely expensive, and therefore, it is not possible to use them to experiment with new protocols. This rises the need for scalable and realistic emulation/simulation environments. In this work, we reviewed and developed several experimental environments, both single-host and distributed, analyzing the benefits and drawbacks of the different solutions. Also, focused on the Border Gateway Protocol (BGP), we ran a comprehensive set of control plane experiments over fat-tree topologies in both simulated and emulated environments. The validation of the experimental results was complemented with a theoretical analysis of BGP behavior over selected scenarios. These experimental and theoretical results, as well as the evaluation and development of the experimental environments, were opportunely disseminated to the scientic community through peer-reviewed scientic publications. All the development of the experimentation environments are available and can be reproduced.Beca de maestría nacional ANII

Squeezing the most benefit from network parallelism in datacenters

One big non-blocking switch is one of the most powerful and pervasive abstractions in datacenter networking. As Moore's law begins to wane, using parallelism to scale out processing units, vs. scale them up, is becoming exceedingly popular. The one-big-switch abstraction, for example, is typically implemented via leveraging massive degrees of parallelism behind the scene. In particular, in today's datacenters that exhibit a high degree of multi-pathing, each logical path between a communicating pair in the one-big-switch abstraction is mapped to a set of paths that can carry traffic in parallel. Similarly, each one-big-switch abstraction function, such as the firewall functionality, is mapped to a set of distributed hardware and software switches. Efficiently deploying this pool of networking connectivity and preserving the functional correctness of network functions, in spite of the parallelism, are challenging. Efficiently balancing the load among multiple paths is challenging because microbursts, responsible for the majority of packet loss in datacenters today, usually last for only a few microseconds. Even the fastest traffic engineering schemes today have control loops that are several orders of magnitude slower (a few milliseconds to a few seconds), and are therefore ineffective in controlling microbursts. Correctly implementing network functions in the face of parallelism is hard because the distributed set of elements that in parallel implement a one-big-switch abstraction can inevitably have inconsistent states that may cause them to behave differently than one physical switch. The first part of this thesis presents DRILL, a datacenter fabric for Clos networks which performs micro load balancing to distribute load as evenly as possible on microsecond timescales. To achieve this, DRILL employs packet-level decisions at each switch based on local queue occupancies and randomized algorithms to distribute load. Despite making per-packet forwarding decisions, by enforcing a tight control on queue occupancies, DRILL manages to keep the degree of packet reordering low. DRILL adapts to topological asymmetry (e.g. failures) in Clos networks by decomposing the network into symmetric components. Using a detailed switch hardware model, we simulate DRILL and show it outperforms recent edge-based load balancers particularly in the tail latency under heavy load, e.g., under 80% load, it reduces the 99.99th percentile of flow completion times of Presto and CONGA by 32% and 35%, respectively. Finally, we analyze DRILL's stability and throughput-efficiency. In the second part, we focus on the correctness of one-big-switch abstraction's implementation. We first show that naively using parallelism to scale networking elements can cause incorrect behavior. For example, we show that an IDS system which operates correctly as a single network element can erroneously and permanently block hosts when it is replicated. We then provide a system, COCONUT, for seamless scale-out of network forwarding elements; that is, an SDN application programmer can program to what functionally appears to be a single forwarding element, but which may be replicated behind the scenes. To do this, we identify the key property for seamless scale out, weak causality, and guarantee it through a practical and scalable implementation of vector clocks in the data plane. We build a prototype of COCONUT and experimentally demonstrate its correct behavior. We also show that its abstraction enables a more efficient implementation of seamless scale-out compared to a naive baseline. Finally, reasoning about network behavior requires a new model that enables us to distinguish between observable and unobservable events. So in the last part, we present the Input/Output Automaton (IOA) model and formalize networks' behaviors. Using this framework, we prove that COCONUT enables seamless scale out of networking elements, i.e., the user-perceived behavior of any COCONUT element implemented with a distributed set of concurrent replicas is provably indistinguishable from its singleton implementation

Virtual Data Center Networks Embedding Through Software Defined Networking

Software Defined Networking (SDN) has opened new ways to design, deploy, and operate networks with new abstractions and programmability at network control and data planes. In this paper, we approach SDN to embed virtual data center networks employing the Network-as-a-Service model. The proposed architecture is built upon abstractions to create a virtual topology using BGP configurations that allow an efficient mapping to a physical network of OpenFlow 1.3 switches. In the control plane, an algorithm is designed to perform efficient allocation of network resources to virtual paths based on the data plane state, such as allocated virtual networks and resource utilization metrics. Requirements such as bandwidth and resilience are used to define the tenants policies and construct the virtual topology graph mappings. 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