Hybrd Uncast and Multcast Flow Control: A Lnear Optmzaton Approach Homayoun Youse zadeh Fatemeh Fazel Hamd Jaarhan Department o EECS Unversty o Calorna, Irvne
Flow Control Motvaton Content delvery over mutlcast networs s challengng Real-Tme Delay Constrants Recever Heterogenety Intra-Sesson Farness Qualty o Servce Inter-Sesson (Flow) Farness Networ Resource Sharng Flow arness or mxed UDP and TCP sessons s complcated. Unle TCP, UDP lacs bult-n low arness support. A generc soluton s requred.
Bacground Wor Farness Issues Ammar, Georga Tech Rubensten, Columba Kurose, UMass Feedbac Aggregaton Imploson Garca, UCSC DeLuca, USC Flow Control Srant, UIUC Kelly, Cambrdge Low, Caltech Jae, MIT Towsley, UMass Congeston Control Jacobson, UCB Floyd, UCB Vcsano, UC London
Flow Farness Utlty The utlty s dened as x U( x) = mn(, ) = where s the requested bandwdth o low wth... 2 x,, x x > Max-Mn Farness Denton: A bandwdth allocaton scheme among a number o competng lows s max-mn ar no low can be allocated a hgher bandwdth wthout reducng the allocaton o another low wth an equal or a lower rate.
Centralzed Flow Control: Global Topology Problem Formulaton x x, x, = max W ( ) Subject To : w x C j {...,, l} Further, = { W,..., W } { C,..., C l }... x {...,, } x x {...,, } } + 2 weghtng unctons ln capactes w j LP can be solved wth 2 complexty O(( l+ 2 )) j j, lowutlzesln j = 0, otherwse Theorem: The soluton s max-mn ar by W >... > W Multcast reward by settng W W η = = η where { η,..., η } are the number o low end nodes. j L w j
Decentralzed Flow Control: Local Ln Problem Formulaton x max x, x, = Subject To : x C = 2 C ln capacty... 2 Theorem: The LP can be solved wth lnear O( ) complexty utlzng the water-llng approach x x x Water-Fllng Soluton Case : C, then Case 2: C j, then nteger j = x =, < j =, h h x = C j= j, h+ h h C 0 h h = 0 h satses h+ 0 h = 0 j
Quas-Centralzed Flow Control: Zone Comparson o FC Schemes Global soluton may be overhead prohbtve Local Soluton s max-mn ar but sub-optmal or the overall topology Soluton Hybrd Flow Control Tradeo between accuracy and complexty Exchange state normaton wthn the local zones Mnmum ar share o a low spannng over multple zones s consdered Descrpton Dene local zones wth assocated Desgnated Nodes (DNs) Zone Dscovery Process DN sends broadcast plot pacets wth a gven TTL Eectve or sparse topologes wth ew populated areas Hybrd complexty o O l 2 (( z + 2 z)) wth l lns and z n the largest zone z lows
ECN Marng Utlze Bnary Marng Gven an ordered lst o per ln ar shares 2 n l l... l Identy bottlenec ln by conveyng λ λ Φ ++ = + ++ 2 n N n N N N N N = [( λ) ( λ ) ] ( λ)[ ( ) ( ) ] λ λ λ to end nodes, where l N Mar wth probablty exp( ( λ ) ) Measure the recevng rate o N unmared pacets Ξ = exp( Φ ) Estmate mnmum ar share as Requres numercal stablzaton λ = ( ln Ξ ) N
ECN-Based Implementaton: Uncast Intermedate Node Calculate mnmum ar share o the ln rom one o the decentralzed or quascentralzed FC algorthms Determne the values o C λ = /l = l Calculate lmax,, [ ] 2 ε b, and = l mn, l ε max, [ ] 2 ε l max, mn, ϕ C b λ = log ( ) End Node Calculate the rate o recevng unmared pacets or the prevous tme nterval as N Ξ = exp( Φ ) Approxmate mnmum ar share o the path rom the source as ( C / ( b ) ϑ ) where / ϑ [ ln )] N = Ξ Mar a pacet wth probablty N exp( ( ϕ ) ) or some large N
Multcastng Implcatons Consder one-to-many multcast trees Expand a multcast sesson as a set o vrtual uncast sessons wth the multcast source and an ndvdual recever. Address eedbac mploson n the dscovery process Feedbac aggregaton or detectng ndvdual ar shares n a group o nodes. Tmer-based eedbac supresson or detectng the overall mnmum ar share o a group o recevers.
Layered Meda Flow Control Treat each layer as an ndependent low. Snce, W... W and..., low-bandwdth hgh-prorty lows are accommodated rst under both global and local algorthms. Under partal ulllment due to bandwdth lmtaton, the bandwdth assgned to low-prorty groups s gven to hghprorty groups.
Topology (): Flow Control
Topology (2): Layered Meda
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