Doctor of Philosophy

dissertationNetwork emulation has become an indispensable tool for the conduct of research in networking and distributed systems. It offers more realism than simulation and more control and repeatability than experimentation on a live network. However, emulation testbeds face a number of challenges, most prominently realism and scale. Because emulation allows the creation of arbitrary networks exhibiting a wide range of conditions, there is no guarantee that emulated topologies reflect real networks; the burden of selecting parameters to create a realistic environment is on the experimenter. While there are a number of techniques for measuring the end-to-end properties of real networks, directly importing such properties into an emulation has been a challenge. Similarly, while there exist numerous models for creating realistic network topologies, the lack of addresses on these generated topologies has been a barrier to using them in emulators. Once an experimenter obtains a suitable topology, that topology must be mapped onto the physical resources of the testbed so that it can be instantiated. A number of restrictions make this an interesting problem: testbeds typically have heterogeneous hardware, scarce resources which must be conserved, and bottlenecks that must not be overused. User requests for particular types of nodes or links must also be met. In light of these constraints, the network testbed mapping problem is NP-hard. Though the complexity of the problem increases rapidly with the size of the experimenter's topology and the size of the physical network, the runtime of the mapper must not; long mapping times can hinder the usability of the testbed. This dissertation makes three contributions towards improving realism and scale in emulation testbeds. First, it meets the need for realistic network conditions by creating Flexlab, a hybrid environment that couples an emulation testbed with a live-network testbed, inheriting strengths from each. Second, it attends to the need for realistic topologies by presenting a set of algorithms for automatically annotating generated topologies with realistic IP addresses. Third, it presents a mapper, assign, that is capable of assigning experimenters' requested topologies to testbeds' physical resources in a manner that scales well enough to handle large environments

Hybrid IP/SDN networking: open implementation and experiment management tools

The introduction of SDN in large-scale IP provider networks is still an open issue and different solutions have been suggested so far. In this paper we propose a hybrid approach that allows the coexistence of traditional IP routing with SDN based forwarding within the same provider domain. The solution is called OSHI - Open Source Hybrid IP/SDN networking as we have fully implemented it combining and extending Open Source software. We discuss the OSHI system architecture and the design and implementation of advanced services like Pseudo Wires and Virtual Switches. In addition, we describe a set of Open Source management tools for the emulation of the proposed solution using either the Mininet emulator or distributed physical testbeds. We refer to this suite of tools as Mantoo (Management tools). Mantoo includes an extensible web-based graphical topology designer, which provides different layered network "views" (e.g. from physical links to service relationships among nodes). The suite can validate an input topology, automatically deploy it over a Mininet emulator or a distributed SDN testbed and allows access to emulated nodes by opening consoles in the web GUI. Mantoo provides also tools to evaluate the performance of the deployed nodes.Comment: Accepted for publication in IEEE Transaction of Network and Service Management - December 2015 http://dx.doi.org/10.1109/TNSM.2015.250762

How To Build a Better Testbed: Lessons From a Decade of Network Experiments on Emulab

International audienceThe Emulab network testbed provides an environment in which researchers and educators can evaluate networked systems. Available to the public since 2000, Emulab is used by thousands of experimenters at hundreds of institutions around the world, and the research conducted on it has lead to hundreds of publications. The original Emulab facility at the University of Utah has been replicated at dozens of other sites. The physical design of the Emulab facility, and many other testbeds like it, has been based on the facility operators' expectations regarding user needs and behavior. If operators' assumptions are incorrect, the resulting facility can exhibit inefficient use patterns and sub-optimal resource allocation. Our study, the first of its kind, gains insight into the needs and behaviors of networking researchers by analyzing more than 500,000 topologies from 13,000 experiments submitted to Emulab. Using this dataset, we re-visit the assumptions that went into the physical design of the Emulab facility and consider improvements to it. Through extensive simulations with real workloads, we evaluate alternative testbeds designs for their ability to improve testbed utilization and reduce hardware costs

Module de Placement pour une émulation distribuée de réseaux SDN/NFV

With the increased complexity of today’s networks, emulation has become an essential tool to test and validate a new proposed networking solution. As these solutions also become more and more complex with the introduction of softwarization, network function virtualization, andartificial intelligence, there is a need of scalable tools to carry out resource intensive emulations. To this end, distributed emulation has been proposed. However, distributing a network emulation over a physical platform requires to choose carefully how the experiment is run over the equipment at disposal. In this work, we evaluate the placement algorithms which were proposed for, and implemented in, existing distributed emulation tools. We show that they may lead to bad placements in which several hardware resources such as link bandwidth, CPU, and memory are overloaded. Through extensive experiments, we exhibit the impact of such placements on important network metrics such as real network bandwidth usage and emulation execution time, and show that they may lead to unreliable results and to a waste of platform resources.To deal with this issue, we propose and implement a new placement module for distributed emulation. Our algorithms take into account both link and node resources and minimize the number of physical hosts needed to carry out the emulation. Through extensive numerical evaluations, simulations, and experiments, we show that our placement methods outperform existing ones leading to reliable experiments using a minimum number of resources.Avec la complexité croissante des réseaux actuels, l’émulation est devenue un outil essentiel pour tester et valider une nouvelle solution réseau.Comme ces solutions deviennent également de plus en plus complexes avec l’introduction des réseaux logiciels, de la virtualisation des fonctions réseau et de l’intelligence artificielle, il est nécessaire de disposer d’outils qui passent à l’échelle pour réaliser des émulations intensives en ressources. A cette fin, il a été proposé de distribuer les émulations. Cependant, la distribution d’une émulation de réseau sur une plate-forme physique nécessite de choisir avec soin la manière dont l’expérience est menée sur l’équipement à disposition. Dans ce travail, nous évaluons les algorithmes de placement qui ont été proposés et implémentés dans les outils d’émulation distribuée existants. Nous montrons qu’ils peuvent conduire à de mauvais placements dans lesquels plusieurs ressources matérielles telles que la bande passante de liens, le processeur et la mémoire peuvent être surchargés. Grâce à des expériences approfondies, nous montrons l’impact de ces placements sur des paramètres importants du réseau tels que l’utilisation réelle de la bande passante et le temps d’exécution de l’émulation, et nous montrons qu’ils peuvent conduire à des résultats peu fiables et `a un gaspillage des ressources de la plate-forme. Pour traiter cette question, nous proposons et implémentons un nouveau module de placement pour l’émulation distribuée. Nos algorithmes prennent en compte les ressources des liens et des nœuds et minimisent le nombre d’hôtes physiques nécessaires pour réaliser l’émulation. Grâce à des évaluations numériques, des simulations et des expériences poussées, nous montrons que nos méthodes de placement sont plus performantes que les méthodes existantes, ce qui permetde réaliser des expériences fiables en utilisant un nombre minimal de ressources

Resolving data center power bill disputes: the energy-performance trade-offs of consolidation

This is the author accepted manuscript. The final version is available from ACM via http://dx.doi.org/10.1145/2768510.2770933In this paper we challenge the common evaluation practices used for Virtual Machine (VM) consolidation, such as simulation and small testbeds, which fail to capture the fundamental trade-off between energy consumption and performance. We identify a number of over-simplifying assumptions which are typically made about the energy consumption and performance characteristics of modern networked systems. In response, we describe how more accurate models for data-center systems can be designed and used in order to create an evaluation framework that allows the more reliable exploration of the energy-performance trade-off for VM consolidation strategies.This work was jointly supported by by MINECO (grant TEC2014- 55713-R), the EPSRC INTERNET Project EP / H040536/1, and the Defense Advanced Research Projects Agency (DARPA) and the Air Force Research Laboratory (AFRL), under contract FA8750-11-C-0249. The views, opinions, and/or findings contained in this article/presentation are those of the author/presenter and should not be interpreted as representing the official views or policies, either expressed or implied, of the Defense Advanced Research Projects Agency or the Department of Defense

Design and Management of DOT: A Distributed OpenFlow Testbed

Abstract-With the growing adoption of Software Defined Networking (SDN), there is a compelling need for SDN emulators that facilitate experimenting with new SDN-based technologies. Unfortunately, Mininet [1], the de facto standard emulator for software defined networks, fails to scale with network size and traffic volume. The aim of this paper is to fill the void in this space by presenting a low cost and scalable network emulator called Distributed OpenFlow Testbed (DOT). It can emulate large SDN deployments by distributing the workload over a cluster of compute nodes. Through extensive experiments, we show that DOT can overcome the limitations of Mininet and emulate larger networks. We also demonstrate the effectiveness of DOT on four Rocketfuel topologies. DOT is available for public use and community-driven development at dothub.org

Hybrid SDN Evolution: A Comprehensive Survey of the State-of-the-Art

Software-Defined Networking (SDN) is an evolutionary networking paradigm which has been adopted by large network and cloud providers, among which are Tech Giants. However, embracing a new and futuristic paradigm as an alternative to well-established and mature legacy networking paradigm requires a lot of time along with considerable financial resources and technical expertise. Consequently, many enterprises can not afford it. A compromise solution then is a hybrid networking environment (a.k.a. Hybrid SDN (hSDN)) in which SDN functionalities are leveraged while existing traditional network infrastructures are acknowledged. Recently, hSDN has been seen as a viable networking solution for a diverse range of businesses and organizations. Accordingly, the body of literature on hSDN research has improved remarkably. On this account, we present this paper as a comprehensive state-of-the-art survey which expands upon hSDN from many different perspectives

Scalable Emulator for Software Defined Networks

Since its inception, Software Defined Network (SDN) has made itself a very appealing architecture for both Data Center and Wide Area networks by offering more automated control through programmability and simplified network operations and management with its centralized control plane. However, extensive rollout of SDN in the production environment requires thorough validation. Thus, there is a compelling need for SDN emulators that facilitate experimenting with new SDN-based technologies (e.g., SDN-based routing and traffic engineering schemes). Valuable insights on these technologies can be gained from real trace-driven experiments on an emulator platform. Accordingly, network operators can gain confidence in these technologies without jeopardizing their infrastructures and businesses. Mininet, the de facto standard SDN emulator, allows users to emulate an OpenFlow-based SDN on a single server. Due to the physical resource limitations of a single machine, Mininet fails to scale with large network size and high traffic volume. To address these limitations, we developed Distributed OpenFlow Testbed (DOT), a highly scalable emulator for SDN. DOT distributes the emulated network across multiple physical machines to scale with large network sizes and high traffic volumes. It also provides guaranteed compute and network resources for the emulated components (i.e., switches, hosts and links). Moreover, DOT can emulate a wider range of network services compared to other publicly available SDN emulators and simulators

Abstractions and Algorithms for Control of Extensible and Heterogeneous Virtualized Network Infrastructures

Virtualized network infrastructures are currently deployed in both research and commercial contexts. The complexity of the virtualization layer varies greatly in different deployments, ranging from cloud computing environments, to carrier Ethernet applications using stacked VLANs, to networking testbeds. In all of these cases, many users are sharing the resources of one provider and each user expects their resources to be isolated from all other users. There are many challenges associated with the control and management of these systems, including resource allocation and sharing, resource isolation, system security, and usability. Among the different types of virtualized infrastructures, network testbeds are of particular interest due to their widespread use in education and in the networking research community. Networking researchers rely extensively on testbeds when evaluating new protocols and ideas. Indeed, a substantial percentage of top research papers include results gathered from testbeds. Network emulation testbeds in particular are often used to conduct innovative research because they allow users to emulate diverse network topologies in a controlled environment. That is, researchers run experiments with a collection of resources that can be reconfigured to represent many different network scenarios. The user typically has control over most of the resources in their experiment which results in a high level of reproducibility. As such, these types of testbeds provide an excellent bridge between simulation and deployment of new ideas. Unfortunately, most testbeds suffer from a general lack of resource extensibility and diversity. This dissertation extends the current state of the art by designing a new, more general testbed infrastructure that expands and enhances the capabilities of modern testbeds. This includes pertinent abstractions, software design, and related algorithms. The design has also been prototyped in the form of the Open Network Laboratory network testbed, which has been successfully used in educational and research pursuits. While the focus is on network testbeds, the results of this research will also be applicable to the broader class of virtualized system infrastructures