Topic
Network planning and design
About: Network planning and design is a research topic. Over the lifetime, 12393 publications have been published within this topic receiving 229776 citations. The topic is also known as: network design.
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Proceedings Article•
01 Jan 2007
TL;DR: The Survivable Network Design Library (SNDlib), a data library for fixed telecommunication network design, is described and a mathematical model for each design problem considered in the library is described.
Abstract: This article describes the Survivable Network Design Library (SNDlib), a data library for fixed telecommunication network design available at http://sndlib. zib.de. In the current version 1.0, the library contains data related to 22 networks which, combined with a set of selected planning parameters, leads to 830 network design problem instances. In this article, we discuss the data concepts of SNDlib and describe a mathematical model for each design problem considered in the library. We also provide information on characteristic features and the origin of the SNDIib problem instances.
535 citations
TL;DR: The impact of network architecture on control performance in a class of distributed control systems called networked control systems (NCSs) is discussed and design considerations related to control quality of performance as well as network quality of service are provided.
Abstract: This paper discusses the impact of network architecture on control performance in a class of distributed control systems called networked control systems (NCSs) and provides design considerations related to control quality of performance as well as network quality of service. The integrated network-control system changes the characteristics of time delays between application devices. This study first identifies several key components of the time delay through an analysis of network protocols and control dynamics. The analysis of network and control parameters is used to determine an acceptable working range of sampling periods in an NCS. A network-control simulator and an experimental networked a machine tool have been developed to help validate and demonstrate the performance analysis results and identify the special performance characteristics in an NCS. These performance characteristics are useful guidelines for choosing the network and control parameters when designing an NCS.
524 citations
TL;DR: In this paper, a new Benders decomposition approach is proposed to solve power transmission network expansion planning problems, which is characterized by using a linear disjointctive model which ensures the optimality of the solution found and by using additional constraints, iteratively evaluated, besides the traditional Benders cuts.
Abstract: In this paper we describe a new Benders decomposition approach to solve power transmission network expansion planning problems. This new approach is characterized by using a linear (0-1) disjuntctive model which ensures the optimality of the solution found and by using additional constraints, iteratively evaluated, besides the traditional Benders cuts. The results obtained, considering a real world power transmission network expansion planning study with the southeastern Brazilian system, show the efficiency of this approach.
504 citations
TL;DR: In this paper, the authors derived a related adjoint network representation and sensitivity coefficients for networks containing a very broad class of elements: those that admit a parametric representation, and a brief discussion is given as to how these results may be exploited in a general automated network design scheme.
Abstract: It has been established that the adjoint network and network sensitivities play important roles in automated network design algorithms. The present paper derives a related adjoint network representation and sensitivity coefficients for networks containing a very broad class of elements: those that admit a parametric representation. A brief discussion is given as to how these results may be exploited in a general automated network design scheme.
503 citations
18 Jun 2018
TL;DR: Pointwise convolution as discussed by the authors is a new convolution operator that can be applied at each point of a point cloud, which can yield competitive accuracy in both semantic segmentation and object recognition task.
Abstract: Deep learning with 3D data such as reconstructed point clouds and CAD models has received great research interests recently. However, the capability of using point clouds with convolutional neural network has been so far not fully explored. In this paper, we present a convolutional neural network for semantic segmentation and object recognition with 3D point clouds. At the core of our network is point-wise convolution, a new convolution operator that can be applied at each point of a point cloud. Our fully convolutional network design, while being surprisingly simple to implement, can yield competitive accuracy in both semantic segmentation and object recognition task.
496 citations