Recursive SDN for Carrier Networks

Control planes for global carrier networks should be programmable (so that new functionality can be easily introduced) and scalable (so they can handle the numerical scale and geographic scope of these networks). Neither traditional control planes nor new SDN-based control planes meet both of these goals. In this paper, we propose a framework for recursive routing computations that combines the best of SDN (programmability) and traditional networks (scalability through hierarchy) to achieve these two desired properties. Through simulation on graphs of up to 10,000 nodes, we evaluate our design's ability to support a variety of routing and traffic engineering solutions, while incorporating a fast failure recovery mechanism

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

Understanding the characteristics of Internet traffic and designing an efficient RaptorQ-based data transport protocol for modern data centres

This thesis is the amalgamation of research on efficient data transport protocols for data centres and a comprehensive and systematic study of Internet traffic, which came as a result of the need to understand traffic patterns and workloads in modern computer networks. The first part of the thesis is on the development of efficient data transport pro- tocols for data centres. We study modern data transport protocols for data centres through large scale simulations using the OMNeT++ simulator. We developed and experimented with an OMNeT++ model of NDP. This has led to the identification of limitations of the state of the art and the formulation of research questions with respect to data transport protocols for modern data centres. The developed model includes an implementation of a Fat-tree topology and per-packet ECMP load bal- ancing. We discuss how we integrated the model with the INET Framework and validated it by running various experiments that test different model parameters and components. This work revealed limitations of NDP with respect to efficient one-to-many and many-to-one communication in data centres, which led to the de- velopment of SCDP, a novel and general-purpose data transport protocol for data centres that, in contrast to all other protocols proposed to date, natively supports one-to-many and many-to-one data communication, which is extremely common in modern data centres. SCDP does so without compromising on efficiency for short and long unicast flows. SCDP achieves this by integrating RaptorQ codes with receiver-driven data transport, in-network packet trimming and Multi-Level Feed- back Queuing (MLFQ); (1) RaptorQ codes enable efficient one-to-many and many- to-one data transport; (2) on top of RaptorQ codes, receiver- driven flow control, in combination with in-network packet trimming, enable efficient usage of network re- sources as well as multi-path transport and packet spraying for all transport modes. Incast and Outcast are eliminated; (3) the systematic nature of RaptorQ codes, in combination with MLFQ, enable fast, decoding-free completion of short flows. We extensively evaluated SCDP in a wide range of simulated scenarios with realistic data centre workloads. For one-to-many and many-to-one transport sessions, SCDP performs significantly better than NDP. For short and long unicast flows, SCDP performs equally well or better compared to NDP. In the second part of the thesis, we extensively study Internet traffic. Getting good statistical models of traffic on network links is a well-known, often-studied problem. A lot of attention has been given to correlation patterns and flow duration. The distribution of the amount of traffic per unit time is an equally important but less studied problem. We study a large number of traffic traces from many different networks including academic, commercial and residential networks using state-of-the-art statistical techniques. We show that the log-normal distribution is a better fit than the Gaussian distribution. We also investigate a second, heavy- tailed distribution and show that its performance is better than Gaussian but worse than log-normal. We examine anomalous traces which are a poor fit for all tested distributions and show that this is often due to traffic outages or links that hit maximum capacity. Stationarity tests showed that the traffic is stationary at some range of aggregation times. We demonstrate the utility of the log-normal distribution in two contexts: predicting the proportion of time traffic will exceed a given level (for link capacity estimation) and predicting 95th percentile pricing. We also show the log-normal distribution is a better predictor than Gaussian orWeibull distributions

Scalability and Resilience Analysis of Software-Defined Networking

Software-defined Networking (SDN) ist eine moderne Architektur für Kommunikationsnetze, welche entwickelt wurde, um die Einführung von neuen Diensten und Funktionen in Netzwerke zu erleichtern. Durch eine Trennung der Weiterleitungs- und Kontrollfunktionen sind nur wenige Kontrollelemente mit Software-Updates zu versehen, um Veränderungen am Netz vornehmen zu können. Allerdings wirft die Netzstrukturierung von SDN neue Fragen bezüglich Skalierbarkeit und Ausfallsicherheit auf, welche in dezentralen Netzstrukturen nicht auftreten. In dieser Arbeit befassen wir uns mit Fragestellungen zu Skalierbarkeit und Ausfallsicherheit in Bezug auf Unicast- und Multicast-Verkehr in SDN-basierten Netzen. Wir führen eine Komprimierungstechnik für Routingtabellen ein, welche die Skalierungsproblematik aktueller SDN Weiterleitungsgeräte verbessern soll und ermitteln ihre Effizienz in einer Leistungsbewertung. Außerdem diskutieren wir unterschiedliche Methoden, um die Ausfallsicherheit in SDN zu verbessern. Wir analysieren sie auf öffentlich zugänglichen Netzwerken und benennen Vor- und Nachteile der Ansätze. Abschließend schlagen wir eine skalierbare und ausfallsichere Architektur für Multicast-basiertes SDN vor. Wir untersuchen ihre Effizienz in einer Leistungsbewertung und zeigen ihre Umsetzbarkeit mithilfe eines Prototypen.Software-Defined Networking (SDN) is a novel architecture for communication networks that has been developed to ease the introduction of new network services and functions. It leverages the separation of the data plane and the control plane to allow network services to be deployed solely in software. Although SDN provides great flexibility, the applicability of SDN in communication networks raises several questions with regard to scalability and resilience against network failures. These concerns are not prevalent in current decentralized network architectures. In this thesis, we address scalability and resilience issues with regard to unicast and multicast traffic for SDN-based networks. We propose a new compression method for inter-domain routing tables to address hardware limitations of current SDN switches and analyze its effectiveness. We propose various resilience methods for SDN and identify their key performance indicators in the context of carrier-grade and datacenter networks. We discuss the advantages and disadvantages of these proposals and their appropriate use cases. Finally, we propose a scalable and resilient software-defined multicast architecture. We study the effectiveness of our approach and show its feasibility using a prototype implementation