Group Study MAE 298
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This 15 page Class Notes was uploaded by Consuelo Herman DDS on Tuesday September 8, 2015. The Class Notes belongs to MAE 298 at University of California - Davis taught by David Horsley in Fall. Since its upload, it has received 43 views. For similar materials see /class/187470/mae-298-university-of-california-davis in Engineering Mechanical & Aero at University of California - Davis.
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Date Created: 09/08/15
MAE 298 Lecture 11 Feb 20 2008 K J wr m k J quot 1 Flow on realworld networks Topics o Optimal allocation of facilities and transport networks Michael Gastner SFI and Mark Newman U Mich 0 Network flows on road networks User vs System Optimal ll Braess Paradox Michael Zhang UC Davis Scale invariance in road networks Kalapala Sanwalani Clauset Moore UNMSFI o Layered interacting networks Kurant and Thiran EPFL Interacting complex networks Multiple Length and Time Scales Transportation Networks Power grid distribution collection networks Computer networks ath i K Social networks Immunology Information drug design 1 39 Commerce 22 January 2007 CSE Advance Biological networks protein interaction genetic regulation lt IOU IOITITITI Our modern infrastructure Layered interacting networks EOOmr m I Optimal design of spatial distribution systems Download Gastnerpdf Flow on transportation networks Download Zhangppt Layered complex networks M Kurant and P Thiran Layered Complex Networks Phys Rev Lett 89 2006 o Offer a simple formalism to think about two coexisting network topologies The physical topology 0 And the virtual application topology Example 1 WWW and IP layer views of the Internet a Each WWW link virtually connects two IP addresses a Those two IP nodes are typically far apart in the underlying IP topology so the virtual connection is realized as a multihop path along IP routers o Of course the IP network is then mapped onto the physical layer of optical cables and routers The Internet hourglass Applications Video Audio 39 ping As Transport protocols Boproute TCP SCTP UDP CMP TraceRoutequot Routerevegt Ethernei 8021 Powerline 39 Bluetooth Link technologies picture from David Alderson Example 2 Transportation networks Up until now separate studies of 1 Physical topology of roads 2 Reallife traffic patterns Want a comprehensive view analyzing them both together The formalism Consider two different networks 0 G W5 E the physical graph 0 GA VA EA the logicaIapplicationIayer graph Assume both sets of nodes identical V VA The load on a node a Load on node z39 lz is the sum of the weights of all logical edges whose paths traverse 239 o Eg in a transportation network lz is the total amount of traffic that flows through node 239 Application Study three transportation systems 1 Mass transit system of Warsaw Poland 2 Rail network of Switzerland 3 Rail network of major trains in the EU Load They can estimate the real load from the timetables some assumptions decompose into units one train one bus etc independent of number of people Two load estimators 1 The node degree of the physical network 2 Betweenness of the physical network Note these estimators are the ones currently in use in almost all cases 1 Resilience of networks to edge removal 2 Modeling cascading failures etc Findings M Kurant and P Thiran Layered Complex Networks Phys Rev Lett 89 2006 o All three estimators 1 real load 2 degree 3 betweenness differ from oneanother o Using the twolayer view can see the logical graphs may have radically different properties than the physical graphs a May lead to reexamination of network robustness previous studies on Internet power grid etc based on physical layer
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