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

Virtual Machine (VM) environments (e.g., VMware and Xen) are experiencing a resurgence of interest for diverse uses including server consolidation and shared hosting. An application's performance in a virtual machine environment can differ markedly from its performance in a non-virtualized environment because of interactions with the underlying virtual machine monitor and other virtual machines. However, few tools are currently available to help debug performance problems in virtual machine environments.In this paper, we present Xenoprof, a system-wide statistical profiling toolkit implemented for the Xen virtual machine environment. The toolkit enables coordinated profiling of multiple VMs in a system to obtain the distribution of hardware events such as clock cycles and cache and TLB misses. The toolkit will facilitate a better understanding of performance characteristics of Xen's mechanisms allowing the community to optimize the Xen implementation.We use our toolkit to analyze performance overheads incurred by networking applications running in Xen VMs. We focus on networking applications since virtualizing network I/O devices is relatively expensive. Our experimental results quantify Xen's performance overheads for network I/O device virtualization in uni- and multi-processor systems. With certain Xen configurations, networking workloads in the Xen environment can suffer significant performance degradation. Our results identify the main sources of this overhead which should be the focus of Xen optimization efforts. We also show how our profiling toolkit was used to uncover and resolve performance bugs that we encountered in our experiments which caused unexpected application behavior.

/pdf/diagnosing-performance-overheads-in-the-xen-virtual-machine-zuymytqtxe.pdf

Diagnosing performance overheads in the xen virtual machine environment

The paravirtualized I/O driver domain model, used in Xen, provides severl advantages including device driver isolation in a safe execution environment, support for guest VM transparent services including live migration, and hardware independence for guests. However, these advantages currently come at the cost of high CPU overhead which can lead to low throughput for high bandwidth links such as 10 gigabit Ethernet. Direct I/O has been proposed as the solution to this performance problem but at the cost of removing the benefits of the driver domain model. In this paper we show how to significantly narrow the performance gap by improving the performance of the driver domain model. In particular, we reduce execution costs for conventional NICs by 56% on the receive path, and we achieve close to direct I/O performance for network devices supporting multiple hardware receive queues. These results make the Xen driver domain model an attractive solution for I/O virtualization for a wider range of scenarios.

/pdf/bridging-the-gap-between-software-and-hardware-techniques-w7urprkryz.pdf

Bridging the gap between software and hardware techniques for I/O virtualization

Cloud environments should provide network performance isolation for co-located untrusted tenants in a virtualized datacenter. We present key properties that a performance isolation solution should satisfy, and present our progress on Gatekeeper, a system designed to meet these requirements. Experiments on our Xen-based implementation of Gatekeeper in a datacenter cluster demonstrate effective and flexible control of ingress/egress link bandwidth for tenant virtual machines under both TCP and greedy unresponsive UDP traffic.

/pdf/gatekeeper-supporting-bandwidth-guarantees-for-multi-tenant-o59s78wrww.pdf

Gatekeeper: supporting bandwidth guarantees for multi-tenant datacenter networks

While cloud computing providers offer guaranteed allocations for resources such as CPU and memory, they do not offer any guarantees for network resources. The lack of network guarantees prevents tenants from predicting lower bounds on the performance of their applications. The research community has recognized this limitation but, unfortunately, prior solutions have significant limitations: either they are inefficient, because they are not work-conserving, or they are impractical, because they require expensive switch support or congestion-free network cores.In this paper, we propose ElasticSwitch, an efficient and practical approach for providing bandwidth guarantees. ElasticSwitch is efficient because it utilizes the spare bandwidth from unreserved capacity or underutilized reservations. ElasticSwitch is practical because it can be fully implemented in hypervisors, without requiring a specific topology or any support from switches. Because hypervisors operate mostly independently, there is no need for complex coordination between them or with a central controller. Our experiments, with a prototype implementation on a 100-server testbed, demonstrate that ElasticSwitch provides bandwidth guarantees and is work-conserving, even in challenging situations.

/pdf/elasticswitch-practical-work-conserving-bandwidth-guarantees-4bz2zh49fd.pdf

ElasticSwitch: practical work-conserving bandwidth guarantees for cloud computing

Recent research on memory disaggregation introduces a new architectural building block — the memory blade — as a cost-effective approach for memory capacity expansion and sharing for an ensemble of blade servers. Memory blades augment blade servers' local memory capacity with a second-level (remote) memory that can be dynamically apportioned among blades in response to changing capacity demand, albeit at a higher access latency. In this paper, we build on the prior research to explore the software and systems implications of disaggregated memory. We develop a software-based prototype by extending the Xen hypervisor to emulate a disaggregated memory design wherein remote pages are swapped into local memory on-demand upon access. Our prototyping effort reveals that low-latency remote memory calls for a different regime of replacement policies than conventional disk paging, favoring minimal hypervisor overhead even at the cost of using less sophisticated replacement policies. Second, we demonstrate the synergy between disaggregated memory and content-based page sharing. By allowing content to be shared both within and across blades (in local and remote memory, respectively), we find that their combination provides greater workload consolidation opportunity and performance-per-dollar than either technique alone. Finally, we explore a realistic deployment scenario in which disaggregated memory is used to reduce the scaling cost of a memcached system. We show that disaggregated memory can provide a 50% improvement in performance-per-dollar relative to conventional scale-out.

/pdf/system-level-implications-of-disaggregated-memory-9sn4kctjhs.pdf

Jose Renato Santos

Papers

Diagnosing performance overheads in the xen virtual machine environment

Bridging the gap between software and hardware techniques for I/O virtualization

Gatekeeper: supporting bandwidth guarantees for multi-tenant datacenter networks

ElasticSwitch: practical work-conserving bandwidth guarantees for cloud computing

System-level implications of disaggregated memory