Session 4.2. Switching planning. Switching/Routing planning

Transcription

1 ITU Semnar Warsaw Poland 6-0 Otober 2003 Sesson 4.2 Swthng/Routng plannng Network Plannng Strategy for evolvng Network Arhtetures Sesson 4.2- Swthng plannng Loaton problem : Optmal plaement of exhanges RSU routers SLAM et. srbers/users n areas/zones srbers/users n loatons/stes Boundares problem : Optmal serve areas of exhanges RSU routers SLAM et. Network Plannng Strategy for evolvng Network Arhtetures Sesson 4.2-2

2 Loaton problem Swthng plannng Subsrber zones / srber grd model > Network Plannng Strategy for evolvng Network Arhtetures Sesson Loaton problem Swthng plannng Theoretally for the set of optmal loaton Y the partal dervatves of the total network 0 ost funton wth regard to for 2 K N Y 0 and Y are equal to zero : fferent methods for solvng ths 2* equaton system ould be employed dependng upon the methods of measurng the dstanes n the network In the most omplated ase we get a system of 2*N non-lnear equatons If and Y are expanded nto Taylor-seres ths leads to a system of 2*N lnear equatons n F and Y F whh an easly be solved by standard methods Network Plannng Strategy for evolvng Network Arhtetures Sesson

3 Swthng plannng Loaton problem - dstane measurement methods Mean dstane from exhange to grd element : x y x 2 y2 The mean dstane from to the retangle an then be found from: Y Ly x y L x along the athete : Y x y x + Y y Y x2 y2 d Y x y dx dy area x y along the hypotenuse : Y x y x Lx + Y y Ly Network Plannng Strategy for evolvng Network Arhtetures Sesson Swthng plannng Smplfed method for loaton optmzaton Based on the aess network ost S only : S s for For optmal loatons Y the partal dervatves of the ost funton S wth regard to and Y are equal to zero : Y 0 0 for 2 KN For a ase wth one loaton only for we get: [ ] the partal dervatve depends only on the dstane Network Plannng Strategy for evolvng Network Arhtetures Sesson

4 4 Network Plannng Strategy for evolvng Network Arhtetures Sesson Swthng plannng Swthng plannng Smplfed method for loaton optmzaton Wth smplfed dstane method along the athete : Y Y + f f We get : Thus : > < Fnally f dsregard the tr. meda ost same everywhere we get: Or : > < > < Network Plannng Strategy for evolvng Network Arhtetures Sesson Swthng plannng Swthng plannng xample loatons Optmum loaton aordng to the smplfed method s the medan of the aumulated srbers sum 4033 s wthn row 5 YR5

5 Loaton problem Swthng plannng Graph modelsrbers n nodes > Network Plannng Strategy for evolvng Network Arhtetures Sesson Swthng plannng Loaton problem - graph model Graph model presents network nodes and lnks onnetng these nodes - ost funton s a dsrete funton over all node loatons.e. t s not possble to use partal dervatves of Obvous soluton s to alulate the total network ost for all ombnatons solutons and fnd the smallest mn stanes alulaton as dstanes on graph shortest path problem and orrespondng algorthms For n nodes and N equpment tems n! ost ombnatons n-n! N! Network Plannng Strategy for evolvng Network Arhtetures Sesson

6 Swthng plannng Loaton problem - graph model hek all ombnatons - for very small networks - pontless to nvestgate many of the ombnatons Heurst methods - elmnate the obvous senseless ombnatons and nvestgate only some of the ombnatons Probablst methods for loaton optmzaton - Smulated annealng / Smulated alloaton / Genet algorthms Network Plannng Strategy for evolvng Network Arhtetures Sesson 4.2- Boundares problem Swthng plannng grd model graph model Network Plannng Strategy for evolvng Network Arhtetures Sesson

7 Boundares problem Swthng plannng Boundary optmzaton s fndng serve/exhange area boundares n suh a way that total network osts s mnmzed The ost of onnetng one srber at loaton xy belongng to traff zone K to an exhange/node at Y an thus be expressed as : K b s f It depends of the ost of onnetng the srber the average exhange ost per srber the bakbone network ost of any srber The deson for the boundary an be made smply by omparson for every grd/node element the value s alulated for every exhange /node and the lowest then determnes Network Plannng Strategy for evolvng Network Arhtetures Sesson xample boundares Swthng plannng Grd element wth 27 srbers on a dstane of 0 steps to upper exh. and lo lower exh. attah to serve area of upper exh. Grd element wth 86 srbers on a dstane of steps to upper exh. and 0 lo lower exh. attah to serve area of lower exh. Boundary between grd elements 27 and 86 Network Plannng Strategy for evolvng Network Arhtetures Sesson

8 Routng plannng transtng of traff ret routng 5 herarhal network Hgh-usage route part of the traff s arred on the dret route and the rest of the traff overflows through a tandem 3 4 hgh-usage routes fnal routes Optmum 2 ual homng load sharng N alternatve routes Prmary routes wth Posson-type offered traff N ruts N OPT N Network Plannng Strategy for evolvng Network Arhtetures Sesson Routng plannng ual homng load sharng - overflowng traff s dvded wth predefned oeffent a SF-A VT VN ombnatoral optmzaton sont Routng Problem of Vrtual Prvate Networks VPN demands must be routed through a network so that ther paths do not share ommon nodes or lnks SZ methods for non-herarhal routng optmze routng and smultaneously optmally dmenson lnk apates dsont routng Network Plannng Strategy for evolvng Network Arhtetures Sesson

9 Routng plannng IP networks typally use OSPF to fnd shortest routes between ponts result ould be that lnks on shortest routes are ongested whle other lnks reman dle Traff engneerng n MPLS means that traff flows an be ontrolled n order to balane lnk loads. Qualty of serve ontrol n MPLS means that bandwdth an be reserved for traff flows. LSP desgn problem all pakets of a flow may follow the same path the so-alled label swthed path LSP Paket flow n the forward and reverse dretons Network Plannng Strategy for evolvng Network Arhtetures Sesson OPT A possble optmzaton rteron when omputng LSP desgns s the mnmzaton of the maxmum ar load Routng plannng LSP desgn problem OPT2 A seond optmzaton prnple s to set up the LSP desgn for the traff demands along the shortest possble paths lke n standard IP routng As a result ars wth hgh utlzaton are avoded whenever possble so that the traff s more unformly dstrbuted heurst optmzatonalgorthms The paths ontaned n a soluton P are shortest paths n terms of number of ars used Network Plannng Strategy for evolvng Network Arhtetures Sesson