Are We Ready for SDN? Implementation Challenges for Software-Defined Networks

Cloud services are exploding, and organizations are converging their data centers in order to take advantage of the predictability, continuity, and quality of service delivered by virtualization technologies. In parallel, energy-efficient and high-security networking is of increasing importance. Network operators, and service and product providers require a new network solution to efficiently tackle the increasing demands of this changing network landscape. Software-defined networking has emerged as an efficient network technology capable of supporting the dynamic nature of future network functions and intelligent applications while lowering operating costs through simplified hardware, software, and management. In this article, the question of how to achieve a successful carrier grade network with software-defined networking is raised. Specific focus is placed on the challenges of network performance, scalability, security, and interoperability with the proposal of potential solution directions.

Exploring Technology Related Design-Space Limitations of High Performance Network Processing

This paper summarizes numerous research activities in high-performance networks and network security processing, and explores technology related performance constraints such as critical performance limitations of circuit architectures, which are set by the semiconductor technologies.

Neural network forecasts of input-output technology

A significant part of the literature on input-output (IO) analysis is dedicated to the development and application of methodologies forecasting and updating technology coefficients and multipliers. Prominent among such techniques is the RAS method, while more information demanding econometric methods, as well as other less promising ones, have been proposed. However, there has been little interest expressed in the use of more modern and often more innovative methods, such as neural networks in IO analysis in general. This study constructs, proposes and applies a Backpropagation Neural Network (BPN) with the purpose of forecasting IO technology coefficients and subsequently multipliers. The RAS method is also applied on the same set of UK IO tables, and the discussion of results of both methods is accompanied by a comparative analysis. The results show that the BPN offers a valid alternative way of IO technology forecasting and many forecasts were more accurate using this method. Overall, however, the RAS method outperformed the BPN but the difference is rather small to be systematic and there are further ways to improve the performance of the BPN.

Implementation of a novel credit based SCFQ scheduler for Broadband Wireless Access

A novel tag computation circuit for a credit based Self-Clocked Fair Queuing (SCFQ) Scheduler is presented. The scheduler combines Weighted Fair Queuing (WFQ) with a credit based bandwidth reallocation scheme. The proposed architecture is able to reallocate bandwidth on the fly if particular links suffer from channel quality degradation .The hardware architecture is parallel and pipelined enabling an aggregated throughput rate of 180 million tag computations per second. The throughput performance is ideal for Broadband Wireless Access applications, allowing room for relatively complex computations in QoS aware adaptive scheduling. The high-level system break-down is described and synthesis results for Altera Stratix II FPGA technology are presented.

A Novel Packet Marking Function for Real-Time Interactive MPEG-4 Video Applications in a Differentiated Services Network

The future convergence of voice, video and data applications on the Internet requires that next generation technology provides bandwidth and delay guarantees. Current technology trends are moving towards scalable aggregate-based systems where applications are grouped together and guarantees are provided at the aggregate level only. This solution alone is not enough for interactive video applications with sub-second delay bounds. This paper introduces a novel packet marking scheme that controls the end-to-end delay of an individual flow as it traverses a network enabled to supply aggregate- granularity Quality of Service (QoS). IPv6 Hop-by-Hop extension header fields are used to track the packet delay encountered at each network node and autonomous decisions are made on the best queuing strategy to employ. The results of network simulations are presented and it is shown that when the proposed mechanism is employed the requested delay bound is met with a 20% reduction in resource reservation and no packet loss in the network.

Neural network based control for synchronous generators

In this paper, a Radial Basis Function neural network based AVR is proposed. A control strategy which generates local linear models from a global neural model on-line is used to derive controller feedback gains based on the Generalised Minimum Variance technique. Testing is carried out on a micromachine system which enables evaluation of practical implementation of the scheme. Constraints imposed by gathering training data, computational load, and memory requirements for the training algorithm are addressed.

Metamaterial made of paired planar conductors: Particle resonances, phenomena and properties

The properties and characteristics of a recently proposed anisotropic metamaterial based upon layered arrays of tightly coupled pairs of "dogbone" shaped stripe conductors have been explored in detail. It has been found that a metamaterial composed of such stacked layers exhibits artificial magnetism and may support backward wave propagation. The equivalent network models of the constitutive conductor pairs arranged in the periodic array have been devised and applied to the identification of the specific types of resonances, and to the analysis of their contribution into the effective dielectric and magnetic properties of the artificial medium. The proposed "dogbone" configuration of conductor pairs has the advantage of being entirely realizable and assemblable in planar technology. It also appears more prospective than simple cut-wire or metal-plate pairs because the additional geometrical parameters provide an efficient control of separation between the electric and magnetic resonances that, in turn, makes it possible to obtain a fairly broadband left-handed behaviour of the structure at low frequencies.

Graphical determination of network limits for wind power integration

A graphical method is presented for determining the capability of individual system nodes to accommodate wind power generation. The method is based upon constructing a capability chart for each node at which a wind farm is to be connected. The capability chart defines the domain of allowable power injections at the candidate node, subject to constraints imposed by voltage limits, voltage stability and equipment capability limits being satisfied. The chart is first derived for a two-bus model, before being extended to a multi-node power system. The graphical method is employed to derive the chart for a two-node system, as well as its application to a multi-node power system, considering the IEEE 30-bus test system as a case study. Although the proposed method is derived with the intention of determining the wind farm capacity to be connected at a specific node, it can be used for the analysis of a PQ bus loading as well as generation.