The Role of Inter-Controller Traffic for Placement of Distributed SDN Controllers

We consider a distributed Software Defined Networking (SDN) architecture adopting a cluster of multiple controllers to improve network performance and reliability. Besides the Openflow control traffic exchanged between controllers and switches, we focus on the control traffic exchanged among the controllers in the cluster, needed to run coordination and consensus algorithms to keep the controllers synchronized. We estimate the effect of the inter-controller communications on the reaction time perceived by the switches depending on the data-ownership model adopted in the cluster. The model is accurately validated in an operational Software Defined WAN (SDWAN). We advocate a careful placement of the controllers, that should take into account both the above kinds of control traffic. We evaluate, for some real ISP network topologies, the delay tradeoffs for the controllers placement problem and we propose a novel evolutionary algorithm to find the corresponding Pareto frontier. Our work provides novel quantitative tools to optimize the planning and the design of the network supporting the control plane of SDN networks, especially when the network is very large and in-band control plane is adopted. We also show that for operational distributed controllers (e.g. OpenDaylight and ONOS), the location of the controller which acts as a leader in the consensus algorithm has a strong impact on the reactivity perceived by switches.Comment: 14 page

Statistical modelling of software reliability

During the six-month period from 1 April 1991 to 30 September 1991 the following research papers in statistical modeling of software reliability appeared: (1) A Nonparametric Software Reliability Growth Model; (2) On the Use and the Performance of Software Reliability Growth Models; (3) Research and Development Issues in Software Reliability Engineering; (4) Special Issues on Software; and (5) Software Reliability and Safety

Expander selection for an on board ORC energy recovery system

This paper deals with the comparison between volumetric expanders (screw, scroll and rotary vane) and an Inlet Forward Radial (IFR) micro turbine for the exploitation of an on board Organic Rankine Cycle (ORC) energy recovery system. The sensible heat recovered from a common bus engine (typically 8000cc) feeds the energy recovery system that can generate sufficient extra power to sustain the air-conditioning system and part of the auxiliaries. The concept is suitable for all kind of thermally propelled vehicles, but the application considered here is specific for an urban bus. The ORC cycle performance is calculated by a Process Simulator (CAMEL Pro) and the results are discussed. A preliminary design of the considered expanders is proposed using ad-hoc made models implemented in MATLAB; the technical constraints inherent to each machine are listed in order to perform the optimal choice of the expander based on efficiency, reliability and power density. Last step will be the selection of the expander that suites the specific technical and design requests. The final choice relapsed on the screw motor, for it is the best compromise in terms of efficiency, lubrication and reliability

Evaluating strategies for implementing industry 4.0: a hybrid expert oriented approach of B.W.M. and interval valued intuitionistic fuzzy T.O.D.I.M.

open access articleDeveloping and accepting industry 4.0 influences the industry structure and customer willingness. To a successful transition to industry 4.0, implementation strategies should be selected with a systematic and comprehensive view to responding to the changes flexibly. This research aims to identify and prioritise the strategies for implementing industry 4.0. For this purpose, at first, evaluation attributes of strategies and also strategies to put industry 4.0 in practice are recognised. Then, the attributes are weighted to the experts’ opinion by using the Best Worst Method (BWM). Subsequently, the strategies for implementing industry 4.0 in Fara-Sanat Company, as a case study, have been ranked based on the Interval Valued Intuitionistic Fuzzy (IVIF) of the TODIM method. The results indicated that the attributes of ‘Technology’, ‘Quality’, and ‘Operation’ have respectively the highest importance. Furthermore, the strategies for “new business models development’, ‘Improving information systems’ and ‘Human resource management’ received a higher rank. Eventually, some research and executive recommendations are provided. Having strategies for implementing industry 4.0 is a very important solution. Accordingly, multi-criteria decision-making (MCDM) methods are a useful tool for adopting and selecting appropriate strategies. In this research, a novel and hybrid combination of BWM-TODIM is presented under IVIF information

AI and OR in management of operations: history and trends

The last decade has seen a considerable growth in the use of Artificial Intelligence (AI) for operations management with the aim of finding solutions to problems that are increasing in complexity and scale. This paper begins by setting the context for the survey through a historical perspective of OR and AI. An extensive survey of applications of AI techniques for operations management, covering a total of over 1200 papers published from 1995 to 2004 is then presented. The survey utilizes Elsevier's ScienceDirect database as a source. Hence, the survey may not cover all the relevant journals but includes a sufficiently wide range of publications to make it representative of the research in the field. The papers are categorized into four areas of operations management: (a) design, (b) scheduling, (c) process planning and control and (d) quality, maintenance and fault diagnosis. Each of the four areas is categorized in terms of the AI techniques used: genetic algorithms, case-based reasoning, knowledge-based systems, fuzzy logic and hybrid techniques. The trends over the last decade are identified, discussed with respect to expected trends and directions for future work suggested

Vibration based damage detection in a wind turbine blade based on autoregressive coefficients

Peer reviewedPreprin

The WiggleZ Dark Energy Survey: Survey Design and First Data Release

The WiggleZ Dark Energy Survey is a survey of 240,000 emission line galaxies in the distant universe, measured with the AAOmega spectrograph on the 3.9-m Anglo-Australian Telescope (AAT). The target galaxies are selected using ultraviolet photometry from the GALEX satellite, with a flux limit of NUV<22.8 mag. The redshift range containing 90% of the galaxies is 0.2<z<1.0. The primary aim of the survey is to precisely measure the scale of baryon acoustic oscillations (BAO) imprinted on the spatial distribution of these galaxies at look-back times of 4-8 Gyrs. Detailed forecasts indicate the survey will measure the BAO scale to better than 2% and the tangential and radial acoustic wave scales to approximately 3% and 5%, respectively. This paper provides a detailed description of the survey and its design, as well as the spectroscopic observations, data reduction, and redshift measurement techniques employed. It also presents an analysis of the properties of the target galaxies, including emission line diagnostics which show that they are mostly extreme starburst galaxies, and Hubble Space Telescope images, which show they contain a high fraction of interacting or distorted systems. In conjunction with this paper, we make a public data release of data for the first 100,000 galaxies measured for the project.Comment: Accepted by MNRAS; this has some figures in low resolution format. Full resolution PDF version (7MB) available at http://www.physics.uq.edu.au/people/mjd/pub/wigglez1.pdf The WiggleZ home page is at http://wigglez.swin.edu.au

Psychometrics in Practice at RCEC

A broad range of topics is dealt with in this volume: from combining the psychometric generalizability and item response theories to the ideas for an integrated formative use of data-driven decision making, assessment for learning and diagnostic testing. A number of chapters pay attention to computerized (adaptive) and classification testing. Other chapters treat the quality of testing in a general sense, but for topics like maintaining standards or the testing of writing ability, the quality of testing is dealt with more specifically.\ud All authors are connected to RCEC as researchers. They present one of their current research topics and provide some insight into the focus of RCEC. The selection of the topics and the editing intends that the book should be of special interest to educational researchers, psychometricians and practitioners in educational assessment