The Internet has led to the creation of a digital society, where (almost) everything is connected and is accessible from anywhere. However, despite their widespread adoption, traditional IP networks are complex and very hard to manage. It is both difficult to configure the network according to predefined policies, and to reconfigure it to respond to faults, load, and changes. To make matters even more difficult, current networks are also vertically integrated: the control and data planes are bundled together. Software-defined networking (SDN) is an emerging paradigm that promises to change this state of affairs, by breaking vertical integration, separating the network's control logic from the underlying routers and switches, promoting (logical) centralization of network control, and introducing the ability to program the network. The separation of concerns, introduced between the definition of network policies, their implementation in switching hardware, and the forwarding of traffic, is key to the desired flexibility: by breaking the network control problem into tractable pieces, SDN makes it easier to create and introduce new abstractions in networking, simplifying network management and facilitating network evolution. In this paper, we present a comprehensive survey on SDN. We start by introducing the motivation for SDN, explain its main concepts and how it differs from traditional networking, its roots, and the standardization activities regarding this novel paradigm. Next, we present the key building blocks of an SDN infrastructure using a bottom-up, layered approach. We provide an in-depth analysis of the hardware infrastructure, southbound and northbound application programming interfaces (APIs), network virtualization layers, network operating systems (SDN controllers), network programming languages, and network applications. We also look at cross-layer problems such as debugging and troubleshooting. In an effort to anticipate the future evolution of this new paradigm, we discuss the main ongoing research efforts and challenges of SDN. In particular, we address the design of switches and control platforms—with a focus on aspects such as resiliency, scalability, performance, security, and dependability—as well as new opportunities for carrier transport networks and cloud providers. Last but not least, we analyze the position of SDN as a key enabler of a software-defined environment.

https://publications.uni.lu/bitstream/10993/20596/1/survey_on_SDN.pdf

Software-Defined Networking: A Comprehensive Survey

Software-Defined Networking (SDN) is an emerging paradigm that promises to change this state of affairs, by breaking vertical integration, separating the network's control logic from the underlying routers and switches, promoting (logical) centralization of network control, and introducing the ability to program the network. The separation of concerns introduced between the definition of network policies, their implementation in switching hardware, and the forwarding of traffic, is key to the desired flexibility: by breaking the network control problem into tractable pieces, SDN makes it easier to create and introduce new abstractions in networking, simplifying network management and facilitating network evolution. In this paper we present a comprehensive survey on SDN. We start by introducing the motivation for SDN, explain its main concepts and how it differs from traditional networking, its roots, and the standardization activities regarding this novel paradigm. Next, we present the key building blocks of an SDN infrastructure using a bottom-up, layered approach. We provide an in-depth analysis of the hardware infrastructure, southbound and northbound APIs, network virtualization layers, network operating systems (SDN controllers), network programming languages, and network applications. We also look at cross-layer problems such as debugging and troubleshooting. In an effort to anticipate the future evolution of this new paradigm, we discuss the main ongoing research efforts and challenges of SDN. In particular, we address the design of switches and control platforms -- with a focus on aspects such as resiliency, scalability, performance, security and dependability -- as well as new opportunities for carrier transport networks and cloud providers. Last but not least, we analyze the position of SDN as a key enabler of a software-defined environment.

The computing world today is in the middle of a revolution: mobile clients and cloud computing have emerged as the dominant paradigms driving programming and hardware innovation today. The Fifth Edition of Computer Architecture focuses on this dramatic shift, exploring the ways in which software and technology in the "cloud" are accessed by cell phones, tablets, laptops, and other mobile computing devices. Each chapter includes two real-world examples, one mobile and one datacenter, to illustrate this revolutionary change. Updated to cover the mobile computing revolutionEmphasizes the two most important topics in architecture today: memory hierarchy and parallelism in all its forms.Develops common themes throughout each chapter: power, performance, cost, dependability, protection, programming models, and emerging trends ("What's Next")Includes three review appendices in the printed text. Additional reference appendices are available online.Includes updated Case Studies and completely new exercises.

Computer Architecture, Fifth Edition: A Quantitative Approach

Cloud computing is an emerging commercial infrastructure paradigm that promises to eliminate the need for maintaining expensive computing facilities by companies and institutes alike. Through the use of virtualization and resource time sharing, clouds serve with a single set of physical resources a large user base with different needs. Thus, clouds have the potential to provide to their owners the benefits of an economy of scale and, at the same time, become an alternative for scientists to clusters, grids, and parallel production environments. However, the current commercial clouds have been built to support web and small database workloads, which are very different from typical scientific computing workloads. Moreover, the use of virtualization and resource time sharing may introduce significant performance penalties for the demanding scientific computing workloads. In this work, we analyze the performance of cloud computing services for scientific computing workloads. We quantify the presence in real scientific computing workloads of Many-Task Computing (MTC) users, that is, of users who employ loosely coupled applications comprising many tasks to achieve their scientific goals. Then, we perform an empirical evaluation of the performance of four commercial cloud computing services including Amazon EC2, which is currently the largest commercial cloud. Last, we compare through trace-based simulation the performance characteristics and cost models of clouds and other scientific computing platforms, for general and MTC-based scientific computing workloads. Our results indicate that the current clouds need an order of magnitude in performance improvement to be useful to the scientific community, and show which improvements should be considered first to address this discrepancy between offer and demand.

/pdf/performance-analysis-of-cloud-computing-services-for-many-3e3awq09a7.pdf

Performance Analysis of Cloud Computing Services for Many-Tasks Scientific Computing

Emerging mega-trends (e.g., mobile, social, cloud, and big data) in information and communication technologies (ICT) are commanding new challenges to future Internet, for which ubiquitous accessibility, high bandwidth, and dynamic management are crucial. However, traditional approaches based on manual configuration of proprietary devices are cumbersome and error-prone, and they cannot fully utilize the capability of physical network infrastructure. Recently, software-defined networking (SDN) has been touted as one of the most promising solutions for future Internet. SDN is characterized by its two distinguished features, including decoupling the control plane from the data plane and providing programmability for network application development. As a result, SDN is positioned to provide more efficient configuration, better performance, and higher flexibility to accommodate innovative network designs. This paper surveys latest developments in this active research area of SDN. We first present a generally accepted definition for SDN with the aforementioned two characteristic features and potential benefits of SDN. We then dwell on its three-layer architecture, including an infrastructure layer, a control layer, and an application layer, and substantiate each layer with existing research efforts and its related research areas. We follow that with an overview of the de facto SDN implementation (i.e., OpenFlow). Finally, we conclude this survey paper with some suggested open research challenges.

A Survey on Software-Defined Networking

This paper presents mechanisms and optimizations to reduce the overhead of network interface virtualization when using the driver domain I/O virtualization model. The driver domain model provides benefits such as support for legacy device drivers and fault isolation. However, the processing overheads incurred in the driver domain to achieve these benefits limit overall I/O performance. This paper demonstrates the effectiveness of two approaches to reduce driver domain overheads. First, Xen is modified to support multi-queue network interfaces to eliminate the software overheads of packet demultiplexing and copying. Second, a grant reuse mechanism is developed to reduce memory protection overheads. These mechanisms shift the bottleneck from the driver domain to the guest domains, improving scalability and enabling significantly higher data rates. This paper also presents and evaluates a series of optimizations that substantially reduce the I/O virtualization overheads in the guest domain. In combination, these mechanisms and optimizations increase the maximum throughput achieved by guest domains from 2.9Gb/s to full 10 Gigabit Ethernet link rates.

/pdf/achieving-10-gb-s-using-safe-and-transparent-network-3x56kon3up.pdf

Achieving 10 Gb/s using safe and transparent network interface virtualization

Software Defined Networking, or SDN, based networks are being deployed not only in testbed networks, but also in production networks. Although fault-tolerance is one of the most desirable properties in production networks, there are not much study in providing fault-tolerance to SDN-based networks. The goal of this work is to develop a fault tolerant SDN architecture that can rapidly recover from faults and scale to large network sizes. This paper presents CORONET, a SDN fault-tolerant system that recovers from multiple link failures in the data plane. We describe a prototype implementation based on NOX that demonstrates fault recovery for emulated topologies using Mininet. We also discuss possible extensions to handle control plane and controller faults.

/pdf/coronet-fault-tolerance-for-software-defined-networks-mc1h3bmzsy.pdf

CORONET: Fault tolerance for Software Defined Networks

Managing data centers is a challenging endeavor. State-of-the-art management systems often rely on analytical modeling to assess the performance, availability, and/or energy implications of potential management decisions or system configurations. In this paper, we argue that actual experiments are cheaper, simpler, and more accurate than models for many management tasks. To support this claim, we built an infrastructure for experimentbased management of virtualized data centers, called JustRunIt. The infrastructure creates a sandboxed environment in which experiments can be run--on a very small number of machines--using real workloads and real system state, but without affecting the on-line system. Automated management systems or the system administrator herself can leverage our infrastructure to perform management tasks on the on-line system. To evaluate the infrastructure, we apply it to two common tasks: server consolidation/expansion and evaluating hardware upgrades. Our evaluation demonstrates that JustRunIt can produce results realistically and transparently, and be nicely combined with automated management systems.

/pdf/justrunit-experiment-based-management-of-virtualized-data-17ufkbm0vx.pdf

JustRunIt: experiment-based management of virtualized data centers

Packet processing for packets from a virtual machine includes receiving a packet from an external switch at a computer system hosting a plurality of virtual machines. If the received packet is a learning packet, storing a packet signature determined from the learning packet. For a packet to be transmitted from a virtual machine in the computer system, determining if the packet's signature matches the stored packet signature. If the packet's signature matches the stored packet signature, performing an action associated with the packet signature.

Virtual machine packet processing

This paper develops a series of performance models for predicting performance of applications on virtualized systems It introduces the main ideas of performance modeling and presents a complete case study of an application running on Linux that is migrated to a virtualized environment consisting of Linux and Xen The paper describes the models, the process of obtaining measurements for the models and calculates performance metrics for the two environments A validation of the results is also discussed in the paper

/pdf/performance-models-for-virtualized-applications-29i1ihoc6f.pdf

Jose Renato Santos

Papers

Achieving 10 Gb/s using safe and transparent network interface virtualization

CORONET: Fault tolerance for Software Defined Networks

JustRunIt: experiment-based management of virtualized data centers

Virtual machine packet processing

Performance models for virtualized applications