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.

Given a set of machines and a set of Web applications with dynamically changing demands, an online application placement controller decides how many instances to run for each application and where to put them, while observing all kinds of resource constraints. This NP hard problem has real usage in commercial middleware products. Existing approximation algorithms for this problem can scale to at most a few hundred machines, and may produce placement solutions that are far from optimal when system resources are tight. In this paper, we propose a new algorithm that can produce within 30seconds high-quality solutions for hard placement problems with thousands of machines and thousands of applications. This scalability is crucial for dynamic resource provisioning in large-scale enterprise data centers. Our algorithm allows multiple applications to share a single machine, and strivesto maximize the total satisfied application demand, to minimize the number of application starts and stops, and to balance the load across machines. Compared with existing state-of-the-art algorithms, for systems with 100 machines or less, our algorithm is up to 134 times faster, reduces application starts and stops by up to 97%, and produces placement solutions that satisfy up to 25% more application demands. Our algorithm has been implemented and adopted in a leading commercial middleware product for managing the performance of Web applications.

/pdf/a-scalable-application-placement-controller-for-enterprise-n4k65djcc4.pdf

A scalable application placement controller for enterprise data centers

A novel method for logically routing a packet between a source machine that is in a first logical domain and a destination machine that is in a second logical domain is described. The method configures a managed switching element as a second-level managed switching element. The method configures a router in a host that includes the second-level managed switching element. The method communicatively couples the second-level managed switching element with the router. The method causes the router to route a packet when the router receives a packet from the first logical domain that is addressed to the second logical domain.

Distributed logical l3 routing

A system and method for developing, deploying, managing and monitoring a web application in a single environment is disclosed herein. The single environment is preferably an integrated development environment (“IDE”). The system and method preferably allows for deployment to a cloud provider, and preferably allows for use of Web resources from multiple cloud providers. One preferred IDE is the APTANA® STUDIO IDE.

System and method for developing, deploying, managing and monitoring a web application in a single environment

A method, system and computer program product for dynamically building a set of compute nodes to host a user's workload. An administrative server receives workload definitions that include the types of workloads that are to be run in a cloud group as well as a number of instances of each workload the cloud group should support. These workload definitions are used to determine the virtual machine demands that the cloud group will place on the cloud environment. The administrative server further receives the demand constraints, placement constraints and license enforcement policies. The administrative server identifies a set of compute nodes to host the user's workload based on the virtual machines demands, the demand constraints, the placement constraints and the license enforcement policies. In this manner, a set of compute nodes is dynamically built for consideration in forming a cloud group without the user requiring knowledge of the cloud's composition.

Dynamically building a set of compute nodes to host the user's workload

CPU demand for web serving: Measurement analysis and dynamic estimation

Managing the resources in a large Web serving system requires knowledge of the resource needs for service request-s of various kinds, and these needs may change over time. Assessing resource needs is commonly performed using techniques such as offline profiling, application instrumentation, and kernel-based instrumentation. Little attention has been given to the dynamic estimation of dynamic resource needs, relying only on external and high-level measurements such as overall resource utilization and request rates. We consider the problem of dynamically estimating dynamic CPU demands of multiple kinds of requests using CPU utilization and throughput measurements. We formulate the problem as a linear regression problem and obtain its basic solution. However, in practice one is faced with issues such as insignificant flows, collinear flows, space and temporal variations, and background noise. In order to deal with such issues, we present several mechanisms such as data aging, flow rejection, flow combining, noise reduction, and smoothing. We implemented these techniques in a Work Profiler component that we delivered as part of a broader system management product. We present experimental results from using this component in scenarios inspired by real-world usage of that product; our technique produces estimates that are roughly within a factor of 2 of the right answer, for the request flows that draw significant CPU power.

Dynamic estimation of CPU demand of web traffic

This paper introduces several novel load-balancing algorithms for distributing Session Initiation Protocol (SIP) requests to a cluster of SIP servers. Our load balancer improves both throughput and response time versus a single node while exposing a single interface to external clients. We present the design, implementation, and evaluation of our system using a cluster of Intel ×86 machines running Linux. We compare our algorithms to several well-known approaches and present scalability results for up to 10 nodes. Our best algorithm, Transaction Least-Work-Left (TLWL), achieves its performance by integrating several features: knowledge of the SIP protocol, dynamic estimates of back-end server load, distinguishing transactions from calls, recognizing variability in call length, and exploiting differences in processing costs for different SIP transactions. By combining these features, our algorithm provides finer-grained load balancing than standard approaches, resulting in throughput improvements of up to 24% and response-time improvements of up to two orders of magnitude. We present a detailed analysis of occupancy to show how our algorithms significantly reduce response time.

https://researcher.watson.ibm.com/researcher/files/us-aruni/dispatcherToN-journal-v3.pdf

Design, implementation, and performance of a load balancer for SIP server clusters

A technique is provided for creating virtual units in a computing environment. A virtual system definition is received by a processor that is utilized to create the virtual units for a virtual system. Relationship constraints between the virtual units in the virtual system are received by the processor. The relationship constraints between the virtual units include a communication link requirement between the virtual units and/or a location requirement between the virtual units. The virtual units in the virtual system are deployed by the processor according to the relationship constraints between virtual units.

Wolfgang Segmuller

Papers

Dynamically building a set of compute nodes to host the user's workload

CPU demand for web serving: Measurement analysis and dynamic estimation

Dynamic estimation of CPU demand of web traffic

Design, implementation, and performance of a load balancer for SIP server clusters

Integrated virtual infrastructure system