Delay-Constrainted Optimal Traffic Allocation in Heterogeneous Wireless Networks for Smart Grid

Transcription

1 elay-consraned Opmal Traffc Allocaon n Heerogeneous Wreless eworks for Smar Grd Sya Xu, ngzhe Xng, 3, Shaoyong Guo, and Luomng Meng Sae Key Laboraory of eworkng and Swchng Technology, Beng Unversy of Poss and Telecommuncaons, 00876, Beng, Chna School of Elecronc and Informaon Engneerng, Beng Jaoong Unversy, 00044, Beng, Chna 3 Sae Grd Jbe Elecrc Power Company Lmed Informaon & Communcaon spach, 00053, Beng, Chna Emal: xusyaxsy@homal.com; xngnngzhe@63.com; {syguo, lmmeng}@bup.edu.cn Absrac In he smar dsrbuon grd, varous communcaon echnologes are adoped o form a seamless heerogeneous communcaon nework o delver conrol and proecon sgnals. However, mos schedulng sraeges desgned for smar grd am a opmzng sysem operaon performance whou consderng he ransmsson cos. To address hs problem, we consruc a delay-consraned cos opmzaon model o accomplsh he followng wo goals: o opmze he cos and o sasfy QoS requremens. Frsly, we esablsh a queung model accordng o he characerscs of heerogeneous servces and oupu neworks for smar grd. Then, a delay-consraned opmal raffc allocaon sraegy s desgned o dynamcally allocae heerogeneous servce daa o dfferen oupu neworks. The allocaon sraegy heren s based on he Lyapunov heory. Fnally, smulaon resuls show ha our proposed allocaon sraegy sgnfcanly reduces he cos and mees ransmsson delay consrans for all servce raffc. communcaon echnologes are appled o consue he exsng heerogeneous communcaon nework o provde ubquous low-cos connecons for Smar srbuon Grd Communcaon ework (SGC) only. As shown n Fg., he heerogeneous nework s manly deployed n access nework layer beween dsrbuon subsaon and ermnal layer. srbuon sub-saon CMA Zgbee Index Terms Smar dsrbuon grd, cos, raffc allocaon sraegy, queung model, Lyapunov heory, ransmsson delay I. T-LTE 30Mhz Access layer WIMAX ITROUCTIO Inellgen dsrbuon ermnal FTU/U /TTU Smar grd s recognzed as a promsng echnology ha wll mprove effcency, relably, and sably of he power grd by managng and conrollng grd resources effecvely [], [ ]. We can learn ha servces n smar grd communcaon nework have more heerogeneous characerscs compared wh he general communcaons nework s, and have greaer dfference n QoS requremens. For nsance, smar grd conrol and proecon applcaons have more demandng requremens for delay and relably (e.g., dsrbued feeder auomaon applcaons requre low-laency and hgh-daa-rae communcaons among subsaons and nellgen elecronc devces n order o mely deec and solae fauls). On he oher hand, smar meerng applcaons requre laency-oleran nformaon exchange beween he meers and uly managemen cener [3]. Snce heerogeneous servce raffc has dverse requremens of QoS, here s no sngle echnology ha can solve all he needs by self [4]. A varey of Mcro-grd Elecrcy consumpon nformaon acquson Load conrol and managemen Termnal layer Fg.. Heerogeneous nework model for SGC. Inegraon of hese communcaon echnologes s non-rval due o he dsnc dfferences n QoS and he cos. Traffc schedulng across SGC poses a novel research problem whch s consderably more challengng han n radonal grd for dsrbued producon and prced-based local consumpon [5]. Besdes, he lack of a consoldaed plan leads o neffecve usage of communcaon resources. In wreless neworks, a subopmal dsrbued conrol algorhm s presened o effcen suppor QoS hrough channel conrol, flow conrol, schedulng and roung decsons n [6]. I s appled n Cognve Rado ework (CR) over smar grd for daa delvery o maxmze he nework ules and suppor QoS. Smlarly, anoher hroughpu algorhm s proposed n [7] ha eravely ncreases he rae of each flow unl converges o he opmal rae of all of he flows. Auhors of [8] desgn a dynamc sraegy algorhm learnng algorhm deployed a each user ha explos he expeced delay and maxmze user uly. In Manuscrp receved May 0, 05; revsed Sepember, 05. Ths work s suppored by he aonal Scence and Technology Suppor Program of Chna (05BAG0B0). do:0.70/cm Journal of Communcaons srbued generaon 8

2 heerogeneous nework envronmen, an opmal conrol for general neworks wh boh wreless and wred componens and me varyng channels s developed n [9]. I s decoupled no separae algorhms for flow conrol, roung, and resource allocaon o make opmally far decsons abou whch daa o serve when npus exceed nework capacy. ue o he lae recognon of economc cos and exremely src QoS consrans (e.g. delay olerance), here exss no proper soluon ha provde a cos-opmal ye QoS-consraned allocaon mechansm for dvers se of applcaons n SGC. Wh growng need and cos n communcaon nework for SG, he ransmsson coss under QoS consrans can no be gnored anymore. To solve he cos opmzaon problem, we adop Lyapunov heores and propose a delay-consraned allocaon sraegy alored o unque characerscs of SGC. By makng oupu nework access conrol, mnmzes cos and mees he QoS requremens of smar grd applcaons. Techncally, usng Lyapunov drf-pluspenaly analyss, we show ha he sraegy realzes cos opmzaon wh a correspondng radeoff n average queue backlog. The remnder of hs paper s organzed as follows. Frsly, he nework model along wh dealed sysem model s consruced n Secon II. Then, Secon III defnes sysem delay as a performance merc and desgns a lyapunov-based cos opmzaon allocaon sraegy for our sysem. ex, Secon IV descrbes smulaon envronmens and llusraes performance evaluaon resuls. Fnally, Secon V draws conclusons. II. ETWORK MOEL Consder he sysem wh hree pars: npu queue se, oupu queue se and me-varyng fadng channels beween hese wo queue ses. Inpu queues are used o sore npu raffc daa. Assume ha heerogeneous servce raffc flows are properly dfferenaed no M classes and be allocaed prores for classfcaon. Each raffc prory corresponds o a dedcaed npu queue, whch means ha npu queue only adm arrval of raffc flow wh prory. So, he number of npu queues s M. The oupu neworks represen dfferen choces for delvery under dfferen communcaon echnologes ncludng LTE, WCMA, WIMAX, Zgbee and ec.. In each me slo, new daa randomly arrves o npu queues and was o be ransmed from npu queues o oupu queues, and hen be delvered no oupu neworks. The nework conroller adops allocaon sraeges o decde whch packe o be served, whch oupu nework o be conneced and how many packes o be ransmed a each schedulng me. A. Inpu Queues Assumed all queue buffers are descrbed n me slos, and he fxed duraon of me slo s equal o s. To hs end, our sysem can be regarded as a dscree-me sysem, n sloed me 0,,,. Traffc flows wh smlar QoS requremens nec no he same npu queue. When a nework conroller makes allocaon decsons, cares he servce prory raher han he acual sze of a packe. Le A,,, be he packe se of class arrves n me slo, and A be he packe number. If S,x s he acual sze of packe x n uns, hen he average packe sze of class s S,x = E S, x uns. The arrvals of he class on slo s a = A S. So he me average arrval rae of class can be compued as: T lm sup S A, for,, M () T T 0 Q s he backlog n npu queue a he begnnng of me slo, ha s, he amoun of daa need o be ransmed. Q = Q,Q, QM s he vecor of backlogs n all npu queues over neger me slo 0,,. The allocaon sraeges represened by U U U U,,,, M, are subeced by he curren channel capacy. Then, we have: CAP mn, U Q C () In me slo, nework conroller selecs U uns of daa o be removed from npu queue o oupu queue. Fuure saes of npu queue are drven by sochasc arrval and allocaon process accordng o he followng dynamc equaon: where,for 0,, Q Q a u (3) a s raffc arrval rae n npu queue over u s he oal ransmsson rae for all slo and oupu neworks, ha s B. Oupu Queues u U (4) The hybrd access nework consss of ndvdual oupu neworks. Le P represens he backlog of oupu nework queue on slo, and P, P, Q P be vecor of he curren backlogs n all oupu nework queues for 0,,. u s he quany of daa necng no oupu nework queue. Therefore, we have: M u U (5) 05 Journal of Communcaons 8

3 So, he updae rule for oupu nework queue can be descrbed as: where b max,0 P P b u P u b (6) s he servce rae of oupu nework over s he acual servce rae due o lack of packes sorng n oupu queues. meslo and b mn b, P III. OPTIMIZATIO MOEL A TRAFFIC ALLOCATIO STRATEGY A. Sysem elay The sysem delay, denoed by, consss of hree pars. They are npu queung delay, oupu queung delay, and delvery delay n he oupu nework. Inpu queung delay n represens he wang me of a packe before ransmng o oupu queues. By Lle s law, he average wang me n npu queue expressed n me slos s n T lm sup T T E Q (7) 0 Oupu queung delay ou s he wang me n oupu queues before beng served. Once a packe necs no oupu nework, ou s deermned by he oal ransmsson rae b. The average assgnmen rao and oupu queue s where U u and servce rae T beween npu queue T U T lm sup E T 0 a (8) s he daa ransmsson quany from npu queue o oupu queue ; a s he amoun of raffc arrves n npu queue. For P s he backlog of oupu queue a me, he wang me ou before beng served s ou P b (9) From (), (9), (0), he me average wang me n oupu queues can be descrbed as ou P T U lm sup E (0) T T 0 b Once ransferred o an oupu nework, he oupu nework s n charge of forwardng he packe o s fnal desnaon. Transmng hrough dfferen oupu neworks wll resul n dfferen delvery delays. For nsance, he delvery delay n Zgbee s less han n LTE. Assumed ha delvery delay n oupu nework s d, we can calculae he mean delvery delay among all oupu neworks by d E U T r lm sup T T 0 () The overall sysem delay s he sum of all delays boh n npu queues and oupu queues, as well as n oupu neworks. Hence () n ou r From he expressons, we can fnd ha he mean oupu queung delay r and he mean delvery delay are ou all funcons of allocaon sraeges U. B. Lyapunov-Based Opmzaon Problem Model As dscussed n prevous secons, he performance of our sysem s deermned by allocaon polces. Unlke mos pror works ha only care abou operaon performance of hroughpu, sysem ulzaon, as well as daa blockng and droppng [0-], he sraegy presened heren especally focus on cos. For hs purpose, we desgn a delay-consraned opmal raffc allocaon sraegy (OTAS) o pursu a hgher economc effcency whle meeng delay requremens. To opmze he cos, we formulae allocaon sraeges by applyng Lyapunov heores o our queung sysem []. For average cos by compung y s cos funcon, we can oban he Y lmsup y (3) 0 The opmzaon problem can be formulaed as Subec o All Q and Mn: Y (4) lm d,,, M (5) P queues are mean rae sable (6) To solve problems gven n (4), we ransform all nequaly and equaly consrans no queue sably problems. efne vrual queues H () o monor, n each raffc prory class, he amoun of pas observed delay volang delay consrans. Assumed ha H (0) s non-negave and fne and H () s fne for {,, M}, he updae equaons of H () are compued accordng o * H max H W, x d,,0 x A (6) where A () s he packe se of class removed from npu queue o oupu queue. efne * lm d, d d x A as he oal queung delay 05 Journal of Communcaons 83

4 bound for packes wh prory before beng served by oupu nework server. mnmze a bound on he followng drf-plus-penaly expecaon: (9) where E y s he average cos n our sysem over me slo, and V 0 s a conrol parameer chosen o represen how much we emphasze he cos mnmzaon and o radeoff beween he coss and QoS consrans. We need o develop sraeges U o acheve he mnmum bound of Lyapunov drf-plus-penaly greedly, whle keepng sysem sable. Le y * be he opmal, and assume E L 0, we have Y y* O / V (0) As (0) shows, any feasble allocaon sraeges can help us o ge a value O / V away from he opmal cos y *. We can approach he opmal value y * by amplfyng V, whch may cause he enlargemen of queue backlog n reurn. Sar subeced o dlm. Sep 6: The server of oupu nework servces packes a servce rae b VE y C. elay-consraned Opmal Traffc Allocaon Sraegy (OTAS) We desgn a elay-consraned Opmal Traffc Allocaon Sraegy (OTAS) o opmze cos whle sasfyng delay consrans by makng schedulng decsons. I can be decomposed no 7 seps: Sep : A he begnnng of each me slo, raffc daa s classfed no M classes and be sen no npu queue buffers accordng o prores. Sep : ework conroller checks he sysem o fnd ou f here are packes need o be sen by npu queue prory order and observe npu queues o ge he curren backlog Q. Sep 3: Check he sysem o oban he curren CAP capacy C of ransmsson channels. Sep 4: Check all oupu queues o oban he curren backlog P. Sep 5: By akng oupu nework access conrol, U uns of daa seleced o be ransferred o oupu queue based on delay and cos consrans, where U s he soluon o mnmze Y and be For =:M mn b, P, Check npu queue whch s nfluenced by allocaon sraegy U. Sep 7: A he boundary of every schedulng process, all queues updae accordng o sysem dynamc evoluon models. The flow-char depced n Fg. shows he workng process of OTAS proposed n hs paper. Check ransmsson channel o oban channel capacy Check all oupu queues. Lyapunov rf-plus-pleny Analyss Selec U() daa o be ransferred o oupu queue Le Θ Q, P, H be a concaenaed Q ( ) CCAP ( ) ework conroller deermnes allocaon sraegy U() P ( ) U ( ) vecor of all acual and vrual queues, and defne he Lyapunov funcon: L Be servced n oupu queues a servce rae b() M M Q P H (7) where weghng coeffcens, and are assgned o nensfy and balance each of consrans. Influences servce rae Updae all queues by evoluon models efne as he condonal Lyapunov drf n End slo : E L L Fg.. Flow-char of OTAS (8) where he expecaon relys on conrol polces U. I s wh respec o channel saes and he conrol acons made n response o hese channel saes. Insead of akng a conrol acon by formulang allocaon sraeges o mnmze a bound on, we 05 Journal of Communcaons IV. SIMULATIOS In hs secon, we presen he performance resuls of he proposed allocaon sraegy smulaed usng MATLAB. We run each smulaon scenaro 00 mes and acqure an average value of for comparson. In our 84

5 expermens, we defne a heerogeneous nework model wh hree knds of npu raffc and hree dfferen oupu neworks. A. ework Seng The prores of npu queues are se accordng o servce daa sorng n her buffers. The communcaon s characerzed by he fac ha mos of neracons mus ake place n real me wh hard me bound, whle ohers are nsensve o laency. To cope wh he dverse delay requremens [3], we se hree npu queues descrbed n Table I. Inpu queue TABLE I: S YSTEM PARAMETERS FOR IPUT QUEUES Applcaons Packe sze (un) Prory Arrval rae (packe/slo) elay Consran (slo) Tele-proecon 5 40/30/0 Hgh Auomaed demand response 3 30/0/0 Medum whch represen low-load condon, medum-load condon and hgh-load condon respecvely. Frsly, he me average cos under he OTAS s compared wh he elay-feasble Allocaon Sraegy (FEAS) and delay-farness allocaon sraegy (FAIR) [7], owng o he lack of cos-opmal allocaon mechansms. These allocaon sraeges are operaed under hgh-load condon a fx arrval raes: 40, 30, 3 4. Ths s because ha, he arrval rae se n he frs scenaro can make he sysem sable whle keepng he sysem offerng connuous servce n mos of me. Fg. 3 shows he me average delay measured n hree dfferen allocaon modes. I can be seen ha, he cos s obvously reduced wh he obecve of cos opmzaon. Furhermore, he average cos n me dmenson s changng more smoohly. Ths s because of he neglec of cos n FEAS and FAIR, whch manly concern delay consrans for servce. 3 Smar meerng 5 3 4/3/ Low In order o model he heerogeneous access neworks, we consder hree possble deploymen opons for SGC whch are publc access neworks, prvae access neworks, and hybrd access neworks. Prvae nework and publc nework each have advanages and dsadvanages n many aspecs such as cos, safey, avalable ransmsson ably, ec. [3]-[5]. So, he hrd opon urns ou o be he bes by akng advanages of boh publc and prvae neworks. A presen, wreless echnologes are appled beween dsrbuon saons and dsrbuon ermnals [6]. We choose hree ypcal knds of access neworks o form our hybrd oupu neworks, whch are lsed n able II. In fac, low-cos wll always be along wh low servce raes. In oher words, packes roued hrough oupu nework 3 ncur a larger buffer laency, whle hose assgned o oupu nework and ncur larger coss. Oupu nework TABLE II: SYSTEM PARAMETERS FOR OUTPUT ETWORKS Mode eworkng Technology elvery elay (slo) Transmsson rae (bps) Cos (dollar /slo) Fg. 3. Tme average cos. By observng T a varous arrval raes ploed n Fg. 4(a-c), we can see he changng rends n access nework selecon more clearly. Under a low-load condon, packes n all npu queues are allocaed o low-cos oupu nework. In reacon o he ncreasng congeson, he algorhm forces more delay-sensve packes o be delvered n hgh-servce-rae oupu neworks. To hs end, more hgh-prory raffc ends o be redreced o he oupu nework. Meanwhle, he cos Y wll be rased for delay consrans. Publc LTE Hgh 0M 4 Prvae CMA Medum M 3 Mcropower Zgbee Low 50k B. Resuls Analyss We desgn a seres of smulaons a alernave raffc arrval raes and under specfc delay consrans o assess he performance of he OTAS wh packe-level smulaons. Three ypcal scenaros are consdered Fg. 4(a). Average assgnmen rao for npu queue 05 Journal of Communcaons 85

6 REFERECES [] [] [3] [4] Fg. 4(b). Average assgnmen rao for npu queue [5] [6] [7] [8] [9] Fg. 4(c). Average assgnmen rao for npu queue 3 [0] On he oher hand, Fg. 4(a-c) reveal ha he lowservce-rae and low-cos oupu nework s crcal o guaranee QoS and opmze ransmsson cos. I can be explaned ha mos of servce raffc whou src delay requremens ends o be assgned o hs oupu nework for cos savng. [] [] V. COCLUSIOS [3] To address he cos-savng problem, we esablsh a queung based nework sysem o model he characerscs of smar grd communcaon neworks. A elay-consraned Opmal Traffc Allocaon Sraegy (OTAS) s formulaed as an on-lne soluon o realze effcen and economc communcaon. In our sysem, smar grd ermnals can choose he mos approprae oupu neworks for heerogeneous raffc accordng o he curren real-me performance of access neworks and he acual needs of smar grd applcaons hemselves. Performance resuls reveal ha he cos s reduced by akng he proposed OTAS. Moreover, he delay consrans are sasfed n all servce prory classes, whch means ha OTAS can balance he cos and operaon performance well. [4] [5] [6] [7] Sya Xu (M 5), receved he B.E. degree from Unversy Of Scence and Technology Beng, Chna, n 00. She s currenly workng owards he Ph.. degree n Beng Unversy of Poss and Telecommuncaon. Her research neress nclude communcaon nework managemen and QoS for Smar Grd Communcaon eworks. ACKOWLEGMET Ths work s suppored by he aonal Key Technology R& Program (05BAG0B0) and he Sae Grd Technology Proec of Chna (SGIT0000KJJS500008). 05 Journal of Communcaons R. Yu, e al., Hybrd specrum access n cognve-rado-based smar-grd communcaons sysems, IEEE Sys. J, vol. 8, no., pp , 03. O. Al-Khab, W. Hardawana, and B. Vucec, Traffc modelng and opmzaon n publc and prvae wreless access neworks for smar grds, IEEE Trans. Smar Grd, 04, vol. 5, no. 4, pp G. A. Shah, V. C. Gungor, and O. B. Akan, A cross-layer desgn for QoS suppor n cognve rado sensor neworks for smar grd applcaons, n Proc. IEEE ICC, Oawa, Canada, 0. Y. Yan, Y. Qan, H. Sharf, and. Tpper, A survey on smar grd communcaon nfrasrucures: movaons, requremens and challenges, IEEE Commun. Surv. Tu., vol. 5, no., pp. 5-0, 0. G. Heyd, The nex generaon of power dsrbuon sysems, IEEE Trans. Smar Grd, vol., no. 3, pp. 5-35, ec. 00. G. A. Shah, V. C. Gungor, and O. B. Akan, A cross-layer qosaware communcaon framework n cognve rado sensor neworks for smar grd applcaons, IEEE Trans. Ind. Informa., vol. 9, no. 3, pp , 03. Y. Sh, e al., A dsrbued opmzaon algorhm for mul-hop cognve rado neworks, n Proc. IEEE IFOCOM, 008, pp S. Hsen-Po and M. V.. Schaar, Queung-based dynamc channel selecon for heerogeneous mulmeda applcaons over cognve rado neworks, IEEE Trans. Mulmeda, vol. 0, no. 5, pp , 008. M. eely, E. Modano, and C. L, Farness and opmal sochasc conrol for heerogeneous neworks, IEEE/ACM Trans. ew., vol. 6, no., pp , 008. L. Georgads, M. J. eely, and L. Tassulas, Resource allocaon and cross-layer conrol n wreless neworks, Foundaons and Trends n eworkng, vol., no., pp. -44, 006. H. L, W. Huang, C. Wu, Z. L, and F. C. M. Lau, Ulymaxmzng daa dssemnaon n socally selfsh cognve rado neworks, n Proc. IEEE MASS, 0, pp. -. M. J. eely, Sochasc nework opmzaon wh applcaon o communcaon and queueng sysems, M & Claypool, pp. 5-80, 00. J.. Mconald, The role of communcaons n smar grd, Whe Paper, Rado Resource Msson-Crcal Communcaons, Apr. 03. V. C. Gungor, e al., Smar grd echnologes: Communcaon echnologes and sandards, IEEE Trans. Ind. Informa., vol. 7, no. 4, pp , 0. T. Sauer and M. Lobashov, End-o-End Communcaon Archecure for Smar Grds, IEEE Trans. Ind. Elecron., vol. 58, no. 4, pp. 8-8, 0. K. C. Budka, e al., Communcaon nework archecure and desgn prncples for smar grds, Bell Labs Techncal Journal, vol. 5, no., pp. 05-7, 00. L. Chh-Png and M. J. eely, elay and rae-opmal conrol n a mul-class prory queue wh adusable servce raes, n Proc. IFOCOM, 0, pp

7 ngzhe Xng was born n Hebe, Chna n 978. He s a Ph. d suden n Beng Jaoong Unversy. He s workng for he IT secon n Sae Grd Corporaon of Chna. Hs research neress nclude Smar Grd communcaon ework, IT and nformaon Secury. ShaoYong Guo (M 5), receved he Ph.. degree from Beng Unversy of Poss and Telecommuncaon n 03 and B.E. degree from HeBe Unversy n 008 respecvely. He s currenly a pos-docoral n Beng Jaoong Unversy. Hs research neress nclude devce managemen, Inerne of Thngs, Ubquous ework and Smar Grds. Luomng Meng, receved he M.S. degree from Tsnghua Unversy, Beng, Chna, n 987. He s currenly a professor and Ph.. supervsor. He s he drecor of Communcaons Sofware Techncal Commee of Chna Insue of Communcaons and he charman of he aonal ework Managemen Sandards Sudy Group. He has publshed abou 0 SCI ndex papers. He has been responsble for several key research proecs ncludng he proecs suppored by aonal aural Scence Foundaon and aonal Hgh- Tech Research and evelopmen Program of Chna. Professor Meng s he proec chef scens of Chna 973 Program, he wnner of Yangse Rver Scholar, and he Ousandng Youh Scence Fund Recever. 05 Journal of Communcaons 87