A Survey of Computer Network Topology and Analysis Examples
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
Part 2: Packet Transmission
Mesh networks LAN technologies and network topology • Early local networks used dedicated links between each pair of computers LANs and shared media • Some useful properties Locality of reference – hardware and frame details can be tailored for Star, bus and ring topologies each link Medium access control protocols – easy to enforce security and privacy Disadvantages of meshes Links between rooms/buildings • Poor scalability • Many links would follow the same physical path Shared Communication Channels Locality of reference • Shared LANs invented in the 1960s • LANs now connect more computers than any other form of network • Rely on computers sharing a single medium • The reason LANs are so popular is due to • Computers coordinate their access the principle of locality of reference • Low cost – physical locality of reference - computers more • But not suitable for wide area - likely to communicate with those nearby communication delays inhibit coordination – temporal locality of reference - computer is more likely to communicate with the same computers repeatedly 1 LAN topologies • LANs may be categorised according to topology ring bus star Pros and cons Example bus network: Ethernet • Star is more robust but hub may be a • Single coaxial cable - the ether - to which bottleneck computers connect • Ring enables easy coordination but is • IEEE standard specifies details sensitive to a cable being cut – data rates • Bus requires less wiring but is also sensitive – maximum length and minimum separation to a cable being cut – frame formats -
Basic Properties of Filter Convergence Spaces
Basic Properties of Filter Convergence Spaces Barbel¨ M. R. Stadlery, Peter F. Stadlery;z;∗ yInstitut fur¨ Theoretische Chemie, Universit¨at Wien, W¨ahringerstraße 17, A-1090 Wien, Austria zThe Santa Fe Institute, 1399 Hyde Park Road, Santa Fe, NM 87501, USA ∗Address for corresponce Abstract. This technical report summarized facts from the basic theory of filter convergence spaces and gives detailed proofs for them. Many of the results collected here are well known for various types of spaces. We have made no attempt to find the original proofs. 1. Introduction Mathematical notions such as convergence, continuity, and separation are, at textbook level, usually associated with topological spaces. It is possible, however, to introduce them in a much more abstract way, based on axioms for convergence instead of neighborhood. This approach was explored in seminal work by Choquet [4], Hausdorff [12], Katˇetov [14], Kent [16], and others. Here we give a brief introduction to this line of reasoning. While the material is well known to specialists it does not seem to be easily accessible to non-topologists. In some cases we include proofs of elementary facts for two reasons: (i) The most basic facts are quoted without proofs in research papers, and (ii) the proofs may serve as examples to see the rather abstract formalism at work. 2. Sets and Filters Let X be a set, P(X) its power set, and H ⊆ P(X). The we define H∗ = fA ⊆ Xj(X n A) 2= Hg (1) H# = fA ⊆ Xj8Q 2 H : A \ Q =6 ;g The set systems H∗ and H# are called the conjugate and the grill of H, respectively. -
Network Topologies Topologies
Network Topologies Topologies Logical Topologies A logical topology describes how the hosts access the medium and communicate on the network. The two most common types of logical topologies are broadcast and token passing. In a broadcast topology, a host broadcasts a message to all hosts on the same network segment. There is no order that hosts must follow to transmit data. Messages are sent on a First In, First Out (FIFO) basis. Token passing controls network access by passing an electronic token sequentially to each host. If a host wants to transmit data, the host adds the data and a destination address to the token, which is a specially-formatted frame. The token then travels to another host with the destination address. The destination host takes the data out of the frame. If a host has no data to send, the token is passed to another host. Physical Topologies A physical topology defines the way in which computers, printers, and other devices are connected to a network. The figure provides six physical topologies. Bus In a bus topology, each computer connects to a common cable. The cable connects one computer to the next, like a bus line going through a city. The cable has a small cap installed at the end called a terminator. The terminator prevents signals from bouncing back and causing network errors. Ring In a ring topology, hosts are connected in a physical ring or circle. Because the ring topology has no beginning or end, the cable is not terminated. A token travels around the ring stopping at each host. -
Topology and Data
BULLETIN (New Series) OF THE AMERICAN MATHEMATICAL SOCIETY Volume 46, Number 2, April 2009, Pages 255–308 S 0273-0979(09)01249-X Article electronically published on January 29, 2009 TOPOLOGY AND DATA GUNNAR CARLSSON 1. Introduction An important feature of modern science and engineering is that data of various kinds is being produced at an unprecedented rate. This is so in part because of new experimental methods, and in part because of the increase in the availability of high powered computing technology. It is also clear that the nature of the data we are obtaining is significantly different. For example, it is now often the case that we are given data in the form of very long vectors, where all but a few of the coordinates turn out to be irrelevant to the questions of interest, and further that we don’t necessarily know which coordinates are the interesting ones. A related fact is that the data is often very high-dimensional, which severely restricts our ability to visualize it. The data obtained is also often much noisier than in the past and has more missing information (missing data). This is particularly so in the case of biological data, particularly high throughput data from microarray or other sources. Our ability to analyze this data, both in terms of quantity and the nature of the data, is clearly not keeping pace with the data being produced. In this paper, we will discuss how geometry and topology can be applied to make useful contributions to the analysis of various kinds of data. -
The Design of PROFIBUS-DP HUB Based on FPGA
International Conference on Computer Science and Service System (CSSS 2014) The Design of PROFIBUS-DP HUB based on FPGA Jiao Ping Zhou Tong Lab. of Networked Control Systems Lab. of Networked Control Systems Shenyang Institute of Automation (SIA), Chinese Shenyang Institute of Automation (SIA), Chinese Academy of Sciences China, Shenyang Academy of Sciences China, Shenyang [email protected] [email protected] Abstract—This paper analyzes the PROFIBUS-DP and specified the standard EIA RS-485, and the traffic rate is physical layer signals states, DP time series and other from 9.6kbps to 12Mbps [2, 3, 6]. characteristics. In the past, PROFIBUS-DP HUB common IEC 1158-2 specified the station number of problems of poor universal apply, shape communication is PROFIBUS-DP is 126 (station address from 0 to 125 contain more time-consuming, required message analysis, Drop frame master and slave station) [4]. In the one segment of etc, this paper propose a new design of PROFIBUS-DP HUB PROFIBUS-DP, the maximum station is 32. DP HUB or DP which based on FPGA. The design contain a detector which Repeater device requires the use, if want to connect more used to monitor the physical layer signal state of the DP bus, stations or change the network topology. As figure shown, use of FPGA synthesis logic signal, could control the direction DP HUB or DP Repeater divided the DP network into many of data flow in the physical layer, and Unrelated with the subnet segments [7]. Each interface of DP HUB is a upper layer protocol, without message analysis, compliance the protocol which used the standard RS-485, and Repeater, which can independently drive a PROFIBUS baudrate-adaptive. -
Field Networking Solutions
Field Networking Solutions Courtesy of Steven Engineering, Inc. ! 230 Ryan Way, South San Francisco, CA 94080-6370 ! Main Office: (650) 588-9200 ! Outside Local Area: (800) 258-9200 ! www.stevenengineering.com TYPES OF FIELDBUS NETWORKS* Field Networking 101 Features and Benefits of Fieldbus Networks The combination of intelligent field devices, digital bus networks, and various open communications protocols Fieldbus networks provide an array of features and benefits that make them an excellent choice is producing extraordinary results at process plants in nearly all process control environments. around the world. Compared to conventional technology, fieldbus networks deliver the following benefits: Just as our ability to retrieve, share, and analyze data Reduced field wiring costs has increased tremendously by use of the Internet and - Two wires from the control room to many devices PC network technology in our homes and at our desk- Reduced commissioning costs tops, so has our ability to control and manage our - Less time and personnel needed to perform process plants improved. Digital connectivity in process I/O wiring checkouts - No time spent calibrating intermediate signals manufacturing plants provides an infrastructure for the (such as 4-20mA signals) - Digital values are delivered directly from field flow of real-time data from the process level, making it devices, increasing accuracy available throughout our enterprise networks. This data Reduced engineering/operating costs is being used at all levels of the enterprise to provide - Much smaller space required for panels, I/O racks, and connectivity boxes increased process monitoring and control, inventory and - Fewer I/O cards and termination panels for materials planning, advanced diagnostics, maintenance control system equipment - Lower power consumption by control system planning, and asset management. -
Topological Optimisation of Artificial Neural Networks for Financial Asset
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by LSE Theses Online The London School of Economics and Political Science Topological Optimisation of Artificial Neural Networks for Financial Asset Forecasting Shiye (Shane) He A thesis submitted to the Department of Management of the London School of Economics for the degree of Doctor of Philosophy. April 2015, London 1 Declaration I certify that the thesis I have presented for examination for the MPhil/PhD degree of the London School of Economics and Political Science is solely my own work other than where I have clearly indicated that it is the work of others (in which case the extent of any work carried out jointly by me and any other person is clearly identified in it). The copyright of this thesis rests with the author. Quotation from it is permitted, provided that full acknowledgement is made. This thesis may not be reproduced without the prior written consent of the author. I warrant that this authorization does not, to the best of my belief, infringe the rights of any third party. 2 Abstract The classical Artificial Neural Network (ANN) has a complete feed-forward topology, which is useful in some contexts but is not suited to applications where both the inputs and targets have very low signal-to-noise ratios, e.g. financial forecasting problems. This is because this topology implies a very large number of parameters (i.e. the model contains too many degrees of freedom) that leads to over fitting of both signals and noise. -
A TEXTBOOK of TOPOLOGY Lltld
SEIFERT AND THRELFALL: A TEXTBOOK OF TOPOLOGY lltld SEI FER T: 7'0PO 1.OG 1' 0 I.' 3- Dl M E N SI 0 N A I. FIRERED SPACES This is a volume in PURE AND APPLIED MATHEMATICS A Series of Monographs and Textbooks Editors: SAMUELEILENBERG AND HYMANBASS A list of recent titles in this series appears at the end of this volunie. SEIFERT AND THRELFALL: A TEXTBOOK OF TOPOLOGY H. SEIFERT and W. THRELFALL Translated by Michael A. Goldman und S E I FE R T: TOPOLOGY OF 3-DIMENSIONAL FIBERED SPACES H. SEIFERT Translated by Wolfgang Heil Edited by Joan S. Birman and Julian Eisner @ 1980 ACADEMIC PRESS A Subsidiary of Harcourr Brace Jovanovich, Publishers NEW YORK LONDON TORONTO SYDNEY SAN FRANCISCO COPYRIGHT@ 1980, BY ACADEMICPRESS, INC. ALL RIGHTS RESERVED. NO PART OF THIS PUBLICATION MAY BE REPRODUCED OR TRANSMITTED IN ANY FORM OR BY ANY MEANS, ELECTRONIC OR MECHANICAL, INCLUDING PHOTOCOPY, RECORDING, OR ANY INFORMATION STORAGE AND RETRIEVAL SYSTEM, WITHOUT PERMISSION IN WRITING FROM THE PUBLISHER. ACADEMIC PRESS, INC. 11 1 Fifth Avenue, New York. New York 10003 United Kingdom Edition published by ACADEMIC PRESS, INC. (LONDON) LTD. 24/28 Oval Road, London NWI 7DX Mit Genehmigung des Verlager B. G. Teubner, Stuttgart, veranstaltete, akin autorisierte englische Ubersetzung, der deutschen Originalausgdbe. Library of Congress Cataloging in Publication Data Seifert, Herbert, 1897- Seifert and Threlfall: A textbook of topology. Seifert: Topology of 3-dimensional fibered spaces. (Pure and applied mathematics, a series of mono- graphs and textbooks ; ) Translation of Lehrbuch der Topologic. Bibliography: p. Includes index. 1. -
General Topology
General Topology Tom Leinster 2014{15 Contents A Topological spaces2 A1 Review of metric spaces.......................2 A2 The definition of topological space.................8 A3 Metrics versus topologies....................... 13 A4 Continuous maps........................... 17 A5 When are two spaces homeomorphic?................ 22 A6 Topological properties........................ 26 A7 Bases................................. 28 A8 Closure and interior......................... 31 A9 Subspaces (new spaces from old, 1)................. 35 A10 Products (new spaces from old, 2)................. 39 A11 Quotients (new spaces from old, 3)................. 43 A12 Review of ChapterA......................... 48 B Compactness 51 B1 The definition of compactness.................... 51 B2 Closed bounded intervals are compact............... 55 B3 Compactness and subspaces..................... 56 B4 Compactness and products..................... 58 B5 The compact subsets of Rn ..................... 59 B6 Compactness and quotients (and images)............. 61 B7 Compact metric spaces........................ 64 C Connectedness 68 C1 The definition of connectedness................... 68 C2 Connected subsets of the real line.................. 72 C3 Path-connectedness.......................... 76 C4 Connected-components and path-components........... 80 1 Chapter A Topological spaces A1 Review of metric spaces For the lecture of Thursday, 18 September 2014 Almost everything in this section should have been covered in Honours Analysis, with the possible exception of some of the examples. For that reason, this lecture is longer than usual. Definition A1.1 Let X be a set. A metric on X is a function d: X × X ! [0; 1) with the following three properties: • d(x; y) = 0 () x = y, for x; y 2 X; • d(x; y) + d(y; z) ≥ d(x; z) for all x; y; z 2 X (triangle inequality); • d(x; y) = d(y; x) for all x; y 2 X (symmetry). -
Efficiently Triggering, Debugging and Decoding Low-Speed Serial Buses
Efficiently Triggering, Debugging and Decoding Low-Speed Serial Buses Hello, my name is Jerry Mark, I am a Product Marketing Engineer at Tektronix. The following presentation discusses aspects of embedded design techniques for “Efficiently Triggering, Debugging, and Decoding Low-Speed Serial Buses”. 1 Agenda Introduction – Parallel Interconnects – Transition from Parallel to Serial Buses – High-Speed versus Low-Speed Serial Data Buses Low-Speed Serial Data Buses – Challenges – Technology Reviews – Measurement Solutions Summary 2 In this presentation we will begin by taking a glance at the transition from parallel-to-serial data and the challenges this presents to engineers. Then we will briefly review some of the most widely used low-speed serial buses in industry today and some of their key characteristics. We will turn our attention to the key measurements on these buses. Subsequently, we will present by example how the low-speed serial solution from Tektronix addresses these challenges. 2 Parallel Interconnects Traditional way to connect digital devices used parallel buses Advantages – Simple point-to-point connections – All signals are transmitted in parallel, simultaneously – Easy to capture state of bus (if you have enough channels!) – Decoding the bus is relatively easy Disadvantages – Occupies a lot of circuit board space – All high-speed connections must be the same length – Many connections limit reliability – Connectors may be very large 3 Parallel buses present all of the bits in parallel, as shown in the logic analyzer display. A parallel connection between two ICs can be as simple as point-to-point circuit board traces for each of the data lines. If you can physically probe these lines, it is easy to display the bus state on a logic analyzer or mixed signal oscilloscope. -
DEFINITIONS and THEOREMS in GENERAL TOPOLOGY 1. Basic
DEFINITIONS AND THEOREMS IN GENERAL TOPOLOGY 1. Basic definitions. A topology on a set X is defined by a family O of subsets of X, the open sets of the topology, satisfying the axioms: (i) ; and X are in O; (ii) the intersection of finitely many sets in O is in O; (iii) arbitrary unions of sets in O are in O. Alternatively, a topology may be defined by the neighborhoods U(p) of an arbitrary point p 2 X, where p 2 U(p) and, in addition: (i) If U1;U2 are neighborhoods of p, there exists U3 neighborhood of p, such that U3 ⊂ U1 \ U2; (ii) If U is a neighborhood of p and q 2 U, there exists a neighborhood V of q so that V ⊂ U. A topology is Hausdorff if any distinct points p 6= q admit disjoint neigh- borhoods. This is almost always assumed. A set C ⊂ X is closed if its complement is open. The closure A¯ of a set A ⊂ X is the intersection of all closed sets containing X. A subset A ⊂ X is dense in X if A¯ = X. A point x 2 X is a cluster point of a subset A ⊂ X if any neighborhood of x contains a point of A distinct from x. If A0 denotes the set of cluster points, then A¯ = A [ A0: A map f : X ! Y of topological spaces is continuous at p 2 X if for any open neighborhood V ⊂ Y of f(p), there exists an open neighborhood U ⊂ X of p so that f(U) ⊂ V . -
Combinatorial Topology
Chapter 6 Basics of Combinatorial Topology 6.1 Simplicial and Polyhedral Complexes In order to study and manipulate complex shapes it is convenient to discretize these shapes and to view them as the union of simple building blocks glued together in a “clean fashion”. The building blocks should be simple geometric objects, for example, points, lines segments, triangles, tehrahedra and more generally simplices, or even convex polytopes. We will begin by using simplices as building blocks. The material presented in this chapter consists of the most basic notions of combinatorial topology, going back roughly to the 1900-1930 period and it is covered in nearly every algebraic topology book (certainly the “classics”). A classic text (slightly old fashion especially for the notation and terminology) is Alexandrov [1], Volume 1 and another more “modern” source is Munkres [30]. An excellent treatment from the point of view of computational geometry can be found is Boissonnat and Yvinec [8], especially Chapters 7 and 10. Another fascinating book covering a lot of the basics but devoted mostly to three-dimensional topology and geometry is Thurston [41]. Recall that a simplex is just the convex hull of a finite number of affinely independent points. We also need to define faces, the boundary, and the interior of a simplex. Definition 6.1 Let be any normed affine space, say = Em with its usual Euclidean norm. Given any n+1E affinely independentpoints a ,...,aE in , the n-simplex (or simplex) 0 n E σ defined by a0,...,an is the convex hull of the points a0,...,an,thatis,thesetofallconvex combinations λ a + + λ a ,whereλ + + λ =1andλ 0foralli,0 i n.