Session 5.3. Switching/Routing and Transmission planning

Transcription

1 ITU Regonal Semnar Belgrade Serba and Montenegro June 2005 Sesson 5.3 Swtchng/Routng and Transmsson plannng volvng nfrastructures to NGN and related Plannng Strateges and Tools I.S. Sesson Locaton problem : Swtchng plannng Optmal placement of exchanges RSU routers DSLAM etc. subscrbers/users n areas/zones Boundares problem : subscrbers/users n locatons/stes Optmal servce areas of exchanges RSU routers DSLAM etc. volvng nfrastructures to NGN and related Plannng Strateges and Tools I.S. Sesson

2 Swtchng plannng Locaton problem Subscrber zones / subscrber grd model => volvng nfrastructures to NGN and related Plannng Strateges and Tools I.S. Sesson Swtchng plannng Locaton problem Theoretcally for the set of optmal locaton Y the partal dervatves of the total network C = 0 for = 12 N cost functon C wth regard to C Y = 0 and Y are equal to zero : Dfferent methods for solvng ths 2* equaton system could be employed dependng upon the methods of measurng the dstances n the network In the most complcated case we get a system of 2*N non-lnear equatons If C and C Y are expanded nto Taylor-seres ths leads to a system of 2*N lnear equatons n F and YF whch can easly be solved by standard methods volvng nfrastructures to NGN and related Plannng Strateges and Tools I.S. Sesson

3 Swtchng plannng Locaton problem - dstance measurement methods Mean dstance from exchange to grd element : x y x2 y2 The mean dstance from to the rectangle can then be found from : Ly x 2 y2 1 D = d Y x y dx dy area x y Y D x1 y1 L x Y along the cathete : Y x y = x + Y 1 1 along the hypotenuse : D Y x y = x Lx + Y y Ly y volvng nfrastructures to NGN and related Plannng Strateges and Tools I.S. Sesson Swtchng plannng Smplfed method for locaton optmzaton Based on the access network cost S only : S = sub Cs D for For optmal locatons Y the partal dervatves of the cost functon C= S wth regard to and Y are equal to zero : C = 0 C Y = 0 for = 12 N For a case wth one locaton only for we get: C = [ sub Cc D D ] the partal dervatve depends only on the dstance volvng nfrastructures to NGN and related Plannng Strateges and Tools I.S. Sesson

4 4 volvng nfrastructures to NGN and related Plannng Strateges and Tools I.S. Sesson Swtchng plannng Swtchng plannng Smplfed method for locaton optmzaton Wth smplfed dstance method along the cathete : Y Y D + = = c f f D C sub C 1 1 We get : Thus : > < = + + c c D C sub D C sub Fnally f dsregard the tr. meda cost same everywhere we get: Or : > < = c c D C sub D C sub > < = sub sub volvng nfrastructures to NGN and related Plannng Strateges and Tools I.S. Sesson Swtchng plannng Swtchng plannng xample locatons Optmum locaton accordng to the smplfed method s the medan of the accumulated subscrbers sum 4033 s wthn row 5 Y=R5

5 Swtchng plannng Locaton problem Graph model subscrbers n nodes => volvng nfrastructures to NGN and related Plannng Strateges and Tools I.S. Sesson Swtchng plannng Locaton problem - graph model Graph model presents network nodes and lnks connectng these nodes - cost functon C s a dscrete functon over all node locatons.e. t s not possble to use partal dervatves of C Obvous soluton s to calculate the total network cost C for all combnatons solutons and fnd the smallest C = Cmn Dstances calculaton as dstances on graph shortest path problem and correspondng algorthms For n nodes and N equpment tems n! cost combnatons n-n! N! volvng nfrastructures to NGN and related Plannng Strateges and Tools I.S. Sesson

6 Swtchng plannng Locaton problem - graph model Check all combnatons - for very small networks - pontless to nvestgate many of the combnatons Heurstc methods - elmnate the obvous senseless combnatons and nvestgate only some of the combnatons Probablstc methods for locaton optmzaton - Smulated annealng / Smulated allocaton / Genetc algorthms volvng nfrastructures to NGN and related Plannng Strateges and Tools I.S. Sesson Boundares problem Swtchng plannng grd model graph model volvng nfrastructures to NGN and related Plannng Strateges and Tools I.S. Sesson

7 Boundares problem Swtchng plannng Boundary optmzaton s fndng servce/exchange area boundares n such a way that total network costs s mnmzed The cost of connectng one subscrber at locaton xy belongng to traffc zone K to an exchange/node at Y can thus be expressed as: C = C K + C + D C D + C b s f It depends of the cost of connectng the subscrber the average exchange cost per subscrber the backbone network cost of any subscrber The decson for the boundary can be made smply by comparson for every grd/node element the value C s calculated for every exchange /node and the lowest C then determnes volvng nfrastructures to NGN and related Plannng Strateges and Tools I.S. Sesson xample boundares Swtchng plannng Grd element wth 271 subscrbers on a dstance of 10 steps to upper exch. and 11 lo lower exch. attach to servce area of upper exch. Grd element wth 86 subscrbers on a dstance of 11 steps to upper exch. and 10 lo lower exch. attach to servce area of lower exch. Boundary between grd elements 271 and 86 volvng nfrastructures to NGN and related Plannng Strateges and Tools I.S. Sesson

8 Routng plannng transtng of traffc Drect routng 5 herarchcal network Hgh-usage route part of the traffc s carred on the drect route and the rest of the traffc overflows through a tandem 3 4 hgh-usage routes fnal routes Optmum 1 2 Dual homng load sharng CN alternatve routes Prmary routes wth Posson-type offered traffc N Crcuts N OPT N D volvng nfrastructures to NGN and related Plannng Strateges and Tools I.S. Sesson Routng plannng Dual homng load sharng - overflowng traffc s dvded wth predefned coeffcent α SF-A VT VN Combnatoral optmzaton Dsont Routng Problem of Vrtual Prvate Networks VPN demands must be routed through a network so that ther paths do not share common nodes or lnks SZ methods for non-herarchcal routng optmze routng and smultaneously optmally dmenson lnk capactes dsont routng volvng nfrastructures to NGN and related Plannng Strateges and Tools I.S. Sesson

9 Routng plannng IP networks typcally use OSPF to fnd shortest routes between ponts result could be that lnks on shortest routes are congested whle other lnks reman dle Traffc engneerng n MPLS means that traffc flows can be controlled n order to balance lnk loads. Qualty of servce control n MPLS means that bandwdth can be reserved for traffc flows. LSP desgn problem all packets of a flow may follow the same path the so-called label swtched path LSP Packet flow n the forward and reverse drectons volvng nfrastructures to NGN and related Plannng Strateges and Tools I.S. Sesson OPT1 A possble optmzaton crteron when computng LSP desgns s the mnmzaton of the maxmum arc load Routng plannng LSP desgn problem OPT2 A second optmzaton prncple s to set up the LSP desgn for the traffc demands along the shortest possble paths lke n standard IP routng As a result arcs wth hgh utlzaton are avoded whenever possble so that the traffc s more unformly dstrbuted heurstc optmzaton algorthms The paths contaned n a soluton P are shortest paths n terms of number of arcs used volvng nfrastructures to NGN and related Plannng Strateges and Tools I.S. Sesson

10 Transmsson plannng Based on crcut/bandwdth matrx and transmsson node/lnk data volvng nfrastructures to NGN and related Plannng Strateges and Tools I.S. Sesson Transmsson plannng Servce layer defnes the pont-to-pont traffc demands Transport layer characterzes one or more network layers that transport the servce layer demands; the transport layer can be any layer startng from the duct layer and gong all the way to the smallest sgnal level that s modelled n the transmsson herarchy e.g. 64 kbps Optcal channel layer provdng separaton of the electrcal and optcal domans creatng lambda traffc matrces end-to-end connectvty wholly n terms of optcal channels optcal aggregaton layer for other servce layers volvng nfrastructures to NGN and related Plannng Strateges and Tools I.S. Sesson

11 Transmsson plannng Typcal network archtectures and technologes that are modeled : optcal rng networks regonal SONT/SDH rngs nterconnected va an optcal mesh backbone wavelength routng and assgnment ultra long haul optcal transport systems WDM rngs thernet connectvty volvng nfrastructures to NGN and related Plannng Strateges and Tools I.S. Sesson Transmsson plannng optcal rng networks model ntegrated passve optcal rng swtchng support end-to-end rng network desgn functons ncludng: + creaton of canddate rngs + selecton of the most costeffectve rngs + rng routng + rng modularzaton and + costng support explct modelng of WDM systems together wth the assocated span engneerng rules and costs volvng nfrastructures to NGN and related Plannng Strateges and Tools I.S. Sesson

12 Transmsson plannng model a hybrd rng mesh network allow selecton and groupng of nodes and lnks to defne subnetworks support dentfcaton of gateway nodes and automatc demand parttonng nto regonal and backbone segments optmze through optcal mesh backbone network regonal SONT/SDH rngs nterconnected va an optcal mesh backbone modelng ULH and tradtonal WDM systems along wth Wavelength Routng and Assgnment volvng nfrastructures to NGN and related Plannng Strateges and Tools I.S. Sesson Transmsson plannng determne optmal routng and wavelength assgnment to maxmze utlzaton whle mnmzng system capacty wastage due to wavelength blockng support dfferent wavelength converson optons support 1+1 path protecton and shared capacty mesh restoraton wavelength routng and assgnment support a dstrbuted or provsonng mode and a centralzed or plannng mode volvng nfrastructures to NGN and related Plannng Strateges and Tools I.S. Sesson

13 Transmsson plannng WDM rngs model a hghly dversfed set of WDM rng technology optons specfy bandwdth management optons as maxmum rng-system capacty bandwdth band add/drop and λ add/drop granularty supports protecton optons as dedcated protecton shared protecton support span engneerng rules to allow to specfy WDM system constrants volvng nfrastructures to NGN and related Plannng Strateges and Tools I.S. Sesson Transmsson plannng thernet connectvty thernet connectons can be transported va SONT/SDH or optcal networks by multplexng them on to the approprate layer n the SONT/SDH/optcal herarchy. explctly model standard thernet connectons at 10Mbps 100Mbps 1Gbps and 10Gbps model the statstcal multplexng gan allowed by thernet by specfyng the desred gan factor for each thernet layer volvng nfrastructures to NGN and related Plannng Strateges and Tools I.S. Sesson

14 Transmsson plannng Modelng of Varous Protecton Schemes dverse routng traffc sharng based on multple-path routng multplex secton protecton path protecton rng-based protecton schemes In 1+1 optcal path protecton a dedcated protectng route protects the workng path and carres the sum of all traffc t needs to protect - the most expensve scheme to mplement. A shared mesh protecton ncludes more than one workng path for the same demand par and the workng paths themselves are usually utlzed to protect each other volvng nfrastructures to NGN and related Plannng Strateges and Tools I.S. Sesson Transmsson plannng MDLD MDLD SUM DI Mob SUM Optmzaton of transmsson nodes and lnk SUM sum Tsum Based on crcut/bandwdth matrx volvng nfrastructures to NGN and related Plannng Strateges and Tools I.S. Sesson

15 Transmsson plannng Optmzaton of rng/mesh protected transport networks Two types of nodes could be dstngushed n the network : traffc access nodes represent the abstract traffc entry ponts e.g. local exchange transmsson nodes represent the actual network nodes e.g. ADMs or DCs Requrements to the topology for protecton - rng or mesh topologes mult-rng structures hybrd rng-mesh topologes dfferent protecton schemes: path protecton lnk protecton path dversty In the optmzaton methods are solved combnatoral problems usually wth heurstc algorthms and based on the shortest path approach volvng nfrastructures to NGN and related Plannng Strateges and Tools I.S. Sesson Transmsson plannng Shortest path problem B 5 D 6 G to determne the shortest path between any two nodes as mnmum dstance A H 5 J to determne the mnmum cost path between two nodes C F I volvng nfrastructures to NGN and related Plannng Strateges and Tools I.S. Sesson

16 Transmsson plannng examne the adacent nodes and label each one wth ts dstance from the source node examne nodes adacent to those already labeled; when a node has lnks to two or more labeled nodes ts dstance from each node s added to the label of that node; the smallest sum s chosen and used as the label for the new node repeat above untl ether the destnaton node s reached f the shortest route to only one node s requred or untl all nodes have been labeled f the shortest routes to all nodes are requred Shortest path problem algorthm of Dantzg volvng nfrastructures to NGN and related Plannng Strateges and Tools I.S. Sesson Transmsson plannng Shortest path problem shortest path from A to J all partal paths contaned n the path from A to J-ABHJ: AB AB ABH B BH BHJ H HJ HJ are optmal paths e.g. from B to J the optmal path s BHJ every optmal path conssts of partally optmal paths volvng nfrastructures to NGN and related Plannng Strateges and Tools I.S. Sesson