Network Visualization Presented by Shahed. Introduction.

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Presentation transcript:

Network Visualization Presented by Shahed

Introduction

3 Basic building blocks –Node –Links (relationship between nodes) –Spatial information –Network data

4 Introduction

5 Paper List Visualizing Network Data –Richard A. Becker, Stephen G. Eick, Allan R. Wilks. 3D Geographic Network Displays –Kenneth C. Cox, Stephen G. Eick, Taosong He. CyberNet: A framework for managing networks using 3D metaphoric worlds –P. Abel and P. Gros and D. Loisel and C. Russo Dos Santos

6 Paper List Visualizing Network Data –Richard A. Becker, Stephen G. Eick, Allan R. Wilks. 3D Geographic Network Displays –Kenneth C. Cox, Stephen G. Eick, Taosong He. CyberNet: A framework for managing networks using 3D metaphoric worlds –P. Abel and P. Gros and D. Loisel and C. Russo Dos Santos

7 Goal Visualize the data associated with a network –Understand data, not network themselves Coping with large data volumes –Hundreds of nodes –Thousands of links –Data from time periods Overcome the map clutter problem

8 Traditional Approach To reduce cluttering of data (traditional) –Aggregation: for large numbers of links or nodes –Averaging: for large numbers of time periods –Thresholding: for detecting changes

9 Solution SeeNet –Static Displays Link Map Node Map Matrix –Interactive Controls Parameter focusing Data filtering –Animation Smooth zoom

10 Dataset Telecommunication traffic 110 switches in the AT&T network 12,000 links Oct. 17, 1989, (San Francisco earthquake) FOCUS: –Traffic flow between switches (nodes)

Static Displays

12 Static Displays (1/3) LINK MAP –Draw lines connecting nodes –Show values using colors or thickness of line

13 Static Displays (LinkMap) Focus on one Node (Oakland)

14 Static Displays (LinkMap) Include all nodes (10% of links shown)

15 Disadvantage Disadvantage of Link Map –Too many links cause map cluttering –Use Node Maps !!!

16 Static Displays (2/3) NODE MAP –Aggregation of information at each node –Use Glyphs Vary Size, shape, color for statistics

17 Static Displays (NodeMap) 1)Tall & Thin: Outbound overload (green) 2)Short & Fat: Inbound Overload (red) 3)Square: Equal load (white)

18 Disadvantage Disadvantage of Node Maps –Detailed Information about particular links lost –Solution: Do away with geography Try Matrix display

19

20 Matrix Display

21 Static Displays (3/3) MATRIX –Concentrates on links of a network (like Linkmap) –Color of square designates traffic –Does not have problems of geographic displays: Visual prominence of long lines Long lines (transcontinental) over plots others

22 Disadvantage Disadvantage of Matrix Display –Information about geography lost Tries to fix problem with nodes ordered from west coast to east coast along axis

Parameter Focusing

24 Parameter Focusing Parameters determine network display Parameter values (range) control what is displayed –Example: –Glyph size in node maps –Coloring of nodes & links Dynamic parameter adjustments helpful

25 Parameter Focusing Example (Shortened Links)

26 Parameter classes Statistics Levels Geography / topology Time Aggregation Size Color

27 Issues with parameter focusing Space of parameters large Combination of parameters to chose Displays sensitive to particular parameter values SOLUTION –Allow Direct manipulation of parameters

28 Direct Manipulation Automatic animation Manual animation Sound Conditioning (‘and’ operation on parameters) Identification (display tool tip of node) Zoom Birds-eye view

29 Example (zoom in Link Map) Left: All line segments intersecting the display Middle: any line segments with at least one endpoint in the display Right: only lines that both begin and end inside the display

30 Other applications (non geographic) CICNET Communication

31 Critique The Good –Clear graphs with interpretation –Presented motivation and challenge papers –Tested on different data sets –Provides implementation details (C++ & Vz) The Evil –Self evaluation (no user studies) –Redundant information (parameters and direct manipulation)

32 Paper List Visualizing Network Data –Richard A. Becker, Stephen G. Eick, Allan R. Wilks. 3D Geographic Network Displays –Kenneth C. Cox, Stephen G. Eick, Taosong He. CyberNet: A framework for managing networks using 3D metaphoric worlds –P. Abel and P. Gros and D. Loisel and C. Russo Dos Santos

33 Introduction Presents “ SeeNet 3D” –5 network views 2 views are geography related 3 views concentrate on portion of a large network SeeNet3D follow-up of –SeeNet –NicheWorks

34 Global Network 1/2 Global packet count in 2 hour period Tall red glyphs have more traffic

35 Disadvantage Only Front side of map viewable –Occludes arc ends Solution –Make globe partially translucent (does not work with too many arcs) –Allow user to route arcs (through globe if needed) –Filtering

36 Global Network (2/2) - Arc Maps Draw arcs on flat 2D map in 3D space –2D map can be oriented as desired –Eliminates line crossing to a certain extent (vary arc height)

37 Arc Map without parameterization of height

38 Arc Map with parameterization of arc height Add translucency of arc &, coloring and size glyphs of countries

39 Drill Down network views Three types of views: –Spokes on a wheel –Helix –Pin Cushion

40 Spokes on a wheel -Works for 50 to 100 nodes -Does not make efficient use of screen space : All spokes of equal length -Better approach (Helix) Traffic to/from US to other countries

41 Helix -When Viewed from above, Helix view becomes spoke view -Use rotation of helix to bring occluded nodes into view -Preferred approach by authors over others (more ordered)

42 Pin Cushion -Motivated by helix display -Position uniformly around sphere (anchor node) - Number of circles and number of nodes per circle chosen such that angle between circles and between nodes in a circle same

43 Critique The Good –Shows more in less space (5 vs 3) –Provides implementation details The Evil –No user studies (as usual) –Some displays have limited information –Does not give scalability constraints for most

44 Paper List Visualizing Network Data –Richard A. Becker, Stephen G. Eick, Allan R. Wilks. 3D Geographic Network Displays –Kenneth C. Cox, Stephen G. Eick, Taosong He. CyberNet: A framework for managing networks using 3D metaphoric worlds –P. Abel and P. Gros and D. Loisel and C. Russo Dos Santos

45 Introduction Network administration in 3D Provides 5 metaphors Dynamically builds & updates 3D world Captures information –Topology, Connectivity, Routing, Mailing, NFS Each 3D tool solves specific problems – chose metaphor that best suites a task

46 Geographic administration building metaphor -For physical link problem detection -Building ( a container for network devices) -Object location is relative to position in actual world -User allowed to chose destination (automated paths) -Filtering

47 Topology administration cone-tree metaphor Red: switches Blue: Hubs Leaves: Computers Size of cone depends on bandwidth flow in hub

48 Distributed system admin city metaphor - Maps Client/server (Mail, DBMS, NFS) -Separate Client & server view -Metaphors: Town : sub network District: Computer Building: Disk resource On server: -Each client a floor -Each window a File Handle

49 Computer admin tool solar system metaphor Metaphors: Stars Planets satellites To: Computers Users Processes

50 Network traffic characterization landscape metaphor

51 More on CyberNet Users can toggle between various 3D structures Technical Stages –Collecting Layer (subscribe/notify, agents) –Structuring Layer (build service model tree) –Visualization Layer (generate 3D form)

52 Critique The Good –design architecture explained –Implementation language for each stage (VRML, corba, Java, perl) –Screen Shots helpful The Evil –Some concepts unclear (city metaphor) –No user studies Mentions users found metaphors helpful –No scalability discussion –Dead Site !!

? QUESTIONS ?