Context Aware Energy Efficient Optimization for Video On-demand Service over Wireless Networks

Transcription

1 Context Aware Energy Effcent Optmzaton for Vdeo On-demand Servce over Wrele Network Changyang She and Chenyang Yang School of Electronc and Informaton Engneerng, Behang Unverty, Bejng, Chna Emal: Abtract Vdeo on-demand VOD ervce wdely requeted, and becomng a domnant applcaton n wrele network, where energy effcency EE a major degn goal. Reducng e energy conumpton of VOD ervce w gven qualty of ervce QoS requrement can mprove e EE of wrele ytem. Recent fndng how at uer moblty hghly predctable, and hence future locaton nformaton poble to know. In paper, we tudy EE-optmal tranmt power and bandwd allocaton for VOD ervce n orogonal frequency dvon multplexng OFDM ytem by explotng context nformaton. We conder two knd of context nformaton,.e., e predctve average channel gan and e QoS of VOD ervce. The optmal reource allocaton polcy at mnmze e average energy conumpton for VOD ervce propoed. At e begnnng of e ervce, e average tranmt power and number of ued ubcarrer are allocated w future average channel gan. Durng e procedure of e ervce, e ntantaneou tranmt power allocated to dfferent ubcarrer after e ntantaneou channel gan become avalable. Smulaton reult how at e energy conumed for VOD ervce w e propoed polcy around half of at w an extng polcy. I. INTRODUCTION Global moble data traffc ha grown dramatcally over e pat year, where a large porton of e data generated by moble vdeo. A hown n [], 55 % of e overall data traffc moble vdeo n 24, and e percentage predcted to become 72 % by 29. Moreover, e vdeo on-demand VOD ervce wdely provded by content provder lke Netflx and YouTube. Th ndcate at VOD ervce ha a gnfcant contrbuton to e ncreang moble data traffc. On e oer hand, mprovng energy effcency EE an mportant degn goal for ff generaton 5G cellular network [2]. However, e requrement of e VOD ervce have not been well addreed n e EE degn. Inpred by e recent fndng n [3] at uer moblty hghly predctable, mprovng EE by explotng context nformaton ha drawn gnfcant attenton a e mart phone popularze. Context nformaton can be clafed nto applcaton e.g., qualty of ervce QoS, network e.g., congeton tatu, uer e.g., uer locaton, and devce level [4]. In pror work w e predcted uer locaton [5, 6], e data rate adjuted by adaptng e ervce tme. In orogonal frequency dvon multplexng OFDM ytem at are prevalent n extng and future cellular network, t poble to adjut e number of actve ubcarrer and tranmt power on dfferent ubcarrer to furer mprove e EE. In paper, we tudy EE-optmal reource allocaton for OFDM ytem by explotng uer- and applcaton-level context nformaton,.e., e future average channel gan and QoS requrement of VOD. Dfferent from [6] at w an mplct aumpton of perfectly known future ntantaneouly channel gan, we aume at only e future average channel gan are avalable. We optmze e reource allocaton for VOD ervce at maxmze e EE of a mult-cell OFDM network, whch nclude a pre-reource allocaton and a dynamc power allocaton. At e begnnng of e VOD ervce, e pre-reource allocaton fnd e average tranmt power and e number of ued ubcarrer w predctve average channel gan. Durng e tranmon procedure for e VoD ervce, e dynamc power allocaton allocate e tranmt power among ubcarrer baed on e ntantaneou channel gan. Smulaton reult how at w e optmal reource allocaton polcy e energy conumed by e VOD ervce around half of at when e polcy n [6] appled. II. SYSTEM MODEL We conder e cenaro at one moble uer w VOD ervce travel acro mult-cell, and e uer erved by e nearet BS. Suppoe at e vdeo fle encoded nto multple layer w calable vdeo codng SVC, and tranmtted va HTTP-baed protocol [7]. The SVC-encoded HTTP adaptve vdeo dvded nto everal egment, and each egment encoded nto one bae layer and everal enhance layer. If e data n e bae layer of each egment conveyed to e uer before deplayng, en no playback nterrupton wll occur. Data lo n enhance layer only lead to e vdeo qualty deteroraton. Snce e tranportaton n core network not a bottleneck, we aume at e requeted data avalable at each BS when e uer acceed to e BS. A. Tranmon and Channel Model Snce ere may ext ome real tme ervce e.g. voce n e network, e BS can only employ e remanng reource to erve e uer of VOD. Conder an OFDM ytem, where P max and K max denote e tranmt power and number of ubcarrer avalable for e VOD ervce, repectvely. Suppoe at e vdeo fle dvded nto N v egment w equal playback tme L v ΔT, where N v and L v are nteger. The overall vdeo playback tme can be dvded nto N L frame each w duraton ΔT, and each frame dvded nto N S tme lot each w duraton τ ΔT. Conder frequency-electve block Raylegh fadng channel. Aume

2 at e average channel gan contant wn duraton ΔT and change from one frame to anoer, and e ntantaneou channel gan contant wn duraton τ and ndependently and dentcally dtrbuted..d. among tme lot and among ubcarrer. Denote α gj k a e compote channel gan on e k ubcarrer n e j tme lot of e frame, where α and gj k are e average and ntantaneou channel gan, repectvely. For e condered Raylegh fadng channel, gj k exponentally dtrbuted w mean of one. W e predcted uer locaton [3] and rado map, e average channel gan α, =,..., N L are predctable. We aume at ey are perfectly known by e t BS e uer acceed to before e vdeo tranmon tart. The ntantaneou channel gan gj k aumed to be perfectly known at e uer and e BS t acceed to at e begnnng of e j tme lot of e frame. W e capacty achevng codng, e ntantaneou tranmon/ervce rate n e j tme lot of e frame can be expreed a, K j = B log 2 + α bt/, k= σ 2 p k jgj k where B e ubcarrer pacng, σ 2 e varance of Gauan noe, K e number of ued ubcarrer n e frame, and p k j e tranmt power on e k ubcarrer n e j tme lot of e frame. B. Queueng Model for VOD Servce Denote e amount of data tranmtted to e buffer at e uer and dplayed n e frame a S and R, repectvely. Then, S = τ NS j. When a certan qualty level of e j= vdeo choen by e uer, R, =,..., N L, are gven. Aume at e buffer ze larger an e ze of e vdeo, whch reaonable for mart phone nce torage devce are cheap nowaday. Hence, we do not need to conder e buffer overflow probablty. To guarantee e requeted vdeo qualty, e vdeo egment need to be tranmtted to e buffer at e uer before ey are dplayed. Then, e QoS requrement of e VoD ervce can be expreed a e followng contrant [6], l n+l v n+l l v Q + S R,l =,..., N v, n= =nl v+ n= =nl v+ where Q = Lv R e ntal queue leng, whch reflect = e fact at e vdeo playback tart after e uer ha receved e frt vdeo egment. For notatonal mplcty but wout lo of generalty, we et L v =n e followng. Then, N v = N L. In wrele channel, uch QoS contrant are hard to atfy w probablty one due to channel fadng. To overcome dffculty, alternatve contrant at are le trngent are condered n e equel. Denote e average ervce rate n e frame a, whch can be obtaned from a, K = B E [log 2 + α ] σ 2 p k jgj k bt/, 2 Snce S k= = τ NS N S, N S equvalent to l = j,wehave ΔT S = N S j= S j j= ΔT S j= j. When. en e QoS contrant are l+ R,l =,..., N L. 3 =2 In practce, e number of tme lot n each frame, N S, large but fnte. Then, ome data n each egment may not be conveyed by a tranmt polcy ubject to contrant 3 before dplayng. Noneele, w e SVC-baed HTTP adaptve vdeo, e lo of a mall amount of data n e enhance layer doe not lead to evere deteroraton of uer experence. C. Power Model and EE defnton The total energy conumed by e BS durng e frame can be modeled a [8] E = N S K τp k j +ΔTP c K +ΔTP rt, 4 j= k= where, ] e power amplfer effcency, P c e crcut power conumed for baeband proceng on each ubcarrer, P rt e power conumpton for ervng oer real tme ervce. W e average channel gan avalable, e EE of e network can be defned a e rato of e average data tranmtted to e average total energy conumed at e BS durng e overall vdeo playback duraton,.e., EE L E g = L E g S K j= k= = τ NS j + S rt j= τp k j +ΔTP c L = K + TP rt, where S rt and P rt are e amount of data tranmtted and e tranmt power for e real tme ervce, repectvely. For VOD ervce, e amount of tranmtted data equal to e amount of data at requred to tranmt. Thu, L E g τ NS j = NL ΔT = NL R, whch gven = j= = when e vdeo choen by e uer at a certan qualty level. Snce we are only ntereted n reource allocaton for e VOD ervce, maxmzng e EE equvalent to mnmzng e average energy conumed for e VOD ervce,.e., E g L = N S K j= k= =2 L τp k j +ΔTP c = K 5

3 III. ENERGY EFFICIENT RESOURCE ALLOCATION POLICY A. Problem Formulaton Snce gj k not predctable, we cannot fnd pk j to mnmze 5 at e begnnng of e VOD ervce. However, f e dtrbuton of gj k known e.g., Raylegh fadng a we aumed, en 5 can be mnmzed by optmzng e average tranmt power and bandwd allocated to e VOD K ervce n e N L frame,.e., P E g p k j and K, k= =,..., N L. W e aumpton at gj k..d. among lot, we have E g τ NS K p k j =ΔT P. Then, 5 can be j= k= rewrtten a ΔT NL P + P c K. = W α, =,..., N L, at e begnnng of e VOD ervce, e frt BS acceed by e uer can fnd P and K to mnmze e average energy conumpton. Then, e BS end e polcy to e ubequent BS. We refer to { P,K, =,..., N L } a e pre-reource allocaton polcy. After gj k, k =,..., K are avalable at a BS acceed by e uer n e j tme lot of e frame, e BS allocate p k j w gven P and K to atfy e QoS contrant. We refer to p k j = p P,K,gj k,k =,...K,j =,..., N S a e dynamc power allocaton polcy n e frame. The optmal average tranmt power and number of ued ubcarrer n dfferent frame at mnmze e average energy conumpton under e QoS contrant n 3 can be found from e followng problem, L mn E ave ΔT K, P P + P c K 6.t. l = ΔT = l+ R, =2 P P max and K K max, 6a 6b where l, =,..., N L. For Raylegh fadng channel we condered, e average ervce rate n 2 can be expreed a = K Blog 2 [+ α p P,K σ 2,g ] g e g dg, whch depend on e form of e functon p P,K,g, where g e value of e ntantaneou channel gan on a ubcarrer n a lot. Th ndcate at dynamc power allocaton polcy affect e contrant n 6a, and hence affect e optmal oluton of problem 6. Therefore, e optmal value of e objectve functon [ n 6 a functon of p P,K,g. We denote t a Eave p P,K,g ]. Then, e optmal dynamc power [ allocaton polcy can be obtaned by mnmzng Eave p P,K,g ], denoted a p P,K,g, w whch we can fnd e optmal pre-reource allocaton polcy, { P,K,=,..., N L }. B. Optmal Dynamc Power Allocaton Polcy It very hard to fnd e optmal [ dynamc power allocaton polcy at mnmze Eave p P,K,g ], becaue e [ expreon of Eave p P,K,g ] can not be obtaned. In what follow, we ue an alternatve approach to fnd p P,K,g. Inpred by e fact at a polcy at maxmze w gven P and K can mnmze e P w gven and K, we frt fnd e power allocaton polcy at maxmze w gven P and K. A hown n [9], uch a polcy waterfllng, P p w,g = K { σ 2 α g g,g g,, g < g. 7 In Raylegh fadng channel, e water level g obtaned from g can be σ 2 α g e g dg = P. 8 g K Then, when gj k, k =,...K, are known at e BS n e j tme lot of e frame, p k j = pw P K,gj k. Now we how at p P,K,g=p w P K,g,.e., 7 e optmal dynamc power allocaton polcy. Propoton. Conder an arbtrary dynamc power allocaton polcy p P,K,g at dfferent from p w P K,g. The optmal oluton of problem 6 w polce p w P K,g and p P,K,g are denoted a { P w,kw,=,..., N L } and { P,K,=,..., N L }, repectvely. Then, Eave [ p w P,K w,g ] Eave [ p P,K,g ]. 9 Proof: See Appendx A. C. Optmal Pre-reource Allocaton Polcy In e equel, we propoe a two-tep meod to fnd e optmal oluton of problem 6. In e frt tep, we derve e mnmum average power conumpton to upport e average ervce rate, and denote t a P vod, whch referred to a optmal power-rate relaton. The optmal power-rate relaton n each frame, ay e frame, can be obtaned from e followng of problem, mn P vod = P,K P + P c K [.t. K Blog 2 + α σ 2 P P max and K K max. p w P K,g ] g e g dg =, a b opt The optmal oluton denoted a { P, K opt }. Then, P vod = opt P +P c K opt In e econd tep, we fnd e optmal average ervce rate n all frame by olvng e followng problem, N L mn,=,...,n L =.t. l = P vod ΔT l+ R,l =,..., N L, a =2

4 = max, b where max e maxmum average ervce rate e ytem can upport n e frame, whch can be expreed a { [ max = K max E g Blog 2 + α ]} P σ 2 p w max,g g. Kmax 2 Denote {, =,..., N L } a e optmal oluton of problem. The followng propoton ndcate at opt { P,Kopt,=,..., N L } e optmal oluton of problem 6. Propoton 2. Denote { P,K,=,..., N L } a an arbtrary feable oluton of problem 6, where, =,..., N L are e related average ervce rate n dfferent frame. Then, L L [ ] P vod P +P c K. = Proof: The proof of propoton mlar to at of Propoton, and omtted due to e lack of pace. In what follow, we repectvely fnd e oluton of problem and. Optmal Power-Rate Relaton: Under contrant a, mnmzng e objectve functon n equvalent to maxmzng e rato of a to,.e., [ ] Blog 2 + α p w P σ 2 K,g g e g dg F P P K + P P c + P, c 3 whch e rato of average ervce rate per ubcarrer to e average power conumpton per ubcarrer, where P P K e average tranmt power per ubcarrer. Propoton 3. F P trctly concave n P. Proof: See Appendx B. Propoton 3 ndcate at 3 trctly quaconcave []. Therefore, e maxmum of 3 unque. We denote e optmal average tranmt power per ubcarrer a P. Furer conderng e maxmal reource contrant n b, e optmal power-rate relaton P vod ha followng two properte. The proof are omtted due to e lack of pace. Property. If e requred value of low uch at { < F P P max mn P,K max }, 4 en P vod lnear. Property 2. If [,max ], en P vod trctly convex. If <, en e average ervce rate can be acheved when e maxmal reource contrant n b are nactve,.e., P <P max and K <K max.if [ ], en,max at leat one of e maxmal reource contrant n b actve to acheve e requred average ervce rate. The properte ugget at P vod frt lnearly ncreae w, and en become trctly convex n. Therefore, P vod convex n, [, max ]. 2 Optmal Average Servce Rate Allocaton: Snce P vod convex n, e objectve functon n convex n, =,..., N L. W lnear contrant, problem a convex programmng, whch can be olved numercally by technque uch a e nteror-pont meod. IV. NUMERICAL AND SIMULATION RESULTS In ecton, we evaluate e propoed polcy by comparng w an extng polcy propoed n [6], whch alo conder VOD and explot e context nformaton. A. The Polcy for Comparon The polcy n [6] doe not nclude dynamc power allocaton, nce e channel wa aumed a flat fadng and contant wn e overall vdeo playback tme,.e., gj k =,, j, k. Moreover, e maxmal bandwd and tranmt power were appled to erve e uer of VOD, and e ervce rate adjuted by adaptng e ervce tme n each frame. After regular manpulaton, we can how at e power-rate relaton acheved by polcy alway lnear,.e., P ln = P max / + P c K max max, [, max ], 5 where max = K max max αp Blog 2 +. σ 2 In e cenaro where real-tme ervce Kmax ext n e network and hence e BS cannot turn nto dle mode, e rate allocaton polcy n [6] n fact mnmze NL P ln under = contrant a and max. To compare w our polcy farly over e frequencyelectve block fadng channel, we extend e polcy n [6] by ncorporatng e water-fllng power allocaton w e rate allocaton n [6]. To be pecfc, f e uer erved n a certan tme lot, e BS wll allocate tranmt power accordng to 7 over K max ubcarrer gven e maxmal tranmt power. Then, e acheved power-rate relaton become P max T P ln = P max / + P c K max max, [, max ], 6 where max hown n 2. Then, e extended polcy n fact mnmze NL P ln under contrant a and b, = whch denoted a Extng polcy n e legend. B. Performance Evaluaton We ue e frt two mnute of a x-layer vdeo n [] to evaluate e performance of dfferent polce. The ze of vdeo egment of dfferent layer can be obtaned from Sony G6B5 CIF DQP6 5EL / n [2]. The condered cenaro hown n Fg.. The uer travel from e tart pont of, m to e end pont of 24, m

5 Fg.. Scenaro for numercal and mulaton reult. Average ervce rate Mbp max extng polcy optmal polcy w velocty 72 km/h.e., 2 m/. Aume at e vdeo playback tart when e uer located at, m, where e frt vdeo egment ha been conveyed to e buffer of e uer. Durng e overall vdeo playback tme of 2, e uer repectvely erved by each of e ree BS, and e uer alway accee to e nearet BS. The pa lo model log D db, where D e BS-uer dtance n e frame. We take D 5 = 2 m and D 5 = 4 m a example to how e power-rate relaton w dfferent dtance. Oer parameter are lted n Table II, where e tranmt power and number of ubcarrer avalable for e VOD ervce are et a 8 of oe for a macro BS [3]. TABLE I LIST OF PARAMETERS [8, 3] Avalable tranmt power P max 5. W Avalable number of ubcarrer K max 28 Subcarrer pace B 5 khz Power amplfer effcency 38.8 % Crcut power conumpton for one ubcarrer P c Channel gan-to-noe rato when D = 5 m Duraton of each frame ΔT Duraton of each tme lot τ.2 W 2 db 5 m 2 Fg Tme Average ervce rate allocated by dfferent polce. Fgure 3 how e mpact of power-rate relaton on e rate allocaton polcy. The average ervce rate of Extng polcy and our polcy w legend Optmal polcy are repectvely obtaned w e lnear power-rate relaton n 6 and e optmal power-rate relaton P vod. W Extng polcy, e BS erve e uer when t cloe to one of e BS.e., when e maxmal ervce rate max n 2 hgh. Bede, e ervce rate equal to max n mot of e actve frame w >. By contrat, w Optmal polcy, e BS do not erve e uer w e maxmal ervce rate max. Rato Average power conumpton W D 5 =4m D 5 =2m 2 Lnear power rate relaton Optmal power rate relaton Average ervce rate Mbp Fg. 2. Power-rate relaton w dfferent uer-bs dtance. Fgure 2 llutrate e optmal power-rate relaton P vod and e lnear power-rate relaton n 6. The reult how at e mnmal average power conumpton requred by our polcy to upport a gven average ervce rate lower an at requred by e extended polcy n [6] Number of requred enhance layer Fg. 4. Rato of energy conumpton of e propoed polcy to at of e extended polcy n [6]. Fgure 4 how e energy avng rato of e propoed polcy w repectve to e extended extng polcy w dfferent vdeo qualte. The reult how at e energy conumed by e propoed polcy nearly halved compared to e energy conumed by e extng polcy. V. CONCLUSION In paper, we optmzed reource allocaton to mprove e EE of an OFDM ytem ervng VOD uer by explotng uer-level and applcaton-level context nformaton. The optmal reource allocaton polcy at jontly allocate tranmt power and e number of ubcarrer wa propoed, whch cont of a pre-reource allocaton and a dynamc power allocaton. At e begnnng of e ervce, e predctve

6 average channel gan are employed to fnd e average tranmt power and e number of ubcarrer n each frame. Durng e vdeo tranmon, e tranmt power allocated to dfferent ubcarrer after e ntantaneou channel gan become avalable. Smulaton reult howed at about half of e energy conumed for e VOD ervce can be aved by e propoed polcy compared to e extng polcy. APPENDIX A PROOF OF PROPOSITION Proof: Denote e average ervce rate acheved by e dynamc power allocaton polcy p P,K,g w prereource allocaton polcy { P,K, =,..., N L } a, =,..., N L. To prove e propoton, we need e followng property: e water-fllng polcy can mnmze P w gven K and average ervce rate [9]. Accordng to e property, gven K and, =,..., N L, e average tranmt power mnmzed w p w P. Denote e related mnmal K,g average tranmt power n e frame a P mn P, =,..., N L. Hence L N L mn P + P c K = = P + P c K mn P. Then,. A. Moreover, w p w P K,g, e optmal pre-reource allocaton { P w,kw,=,..., N L}. Thu, L N P L w + P c K w mn P + P c K. A.2 = = From A. and A.2, we have 9. The proof complete. APPENDIX B PROOF OF PROPOSITION 3 Proof: Subttutng 7 nto F P defned n 3, we can obtan F P a follow, F P = B ln 2 [ g ln g e g dg ln g e g ], B. where e relaton between g and P can be obtaned [ from ] 8. Then, F P a compoton functon, F g P, whoe econd order dervatve [ ] d 2 F g P d P = d2 F 2 d g dg 2 d P 2 + df dg d 2 g d P 2. B.2 [ ] To prove at F g P concave n P, we only need to prove at B.2 negatve. From B. we can derve at df dg = B ln 2 g d 2 F d g 2 = B ln 2 g e g, B.3 2 e g + B ln 2 g e g. B.4 From 8, we can fnd e relatonhp between P and g a P = σ2 α e g g g g e g dg. Then, we can derve d 2e at P = σ2 dg g α g. Accordng to e property of nvere functon,.e., d P dg dg d P =at any pont g, P,we have dg d P Furer conderng at d 2 g [ d P = 2 2g = α σ 2 d 2 g d P = d 2 g 2 e g. B.5 dg d P dg 3 +g 4] α σ 2 dg d P,wehave 2 e 2g. B.6 Subttutng B.3, B.4, B.5 and B.6 nto B.2, we can fnally derve at [ ] d 2 F g P d P = B 2 α 2 ln 2 σ 2 g 2 e g <. Th complete e proof. REFERENCES [] Cco, Cco vual networkng ndex: Global moble data traffc forecat update, 24-29, Cco whte paper, 25. [2] G. Wu, C. Yang, S. L, and G. L, Recent advance n energy-effcent network and t applcaton n 5G ytem, IEEE Wrele Commun. Mag., vol. 22, no. 2, pp. 45 5, Apr. 25. [3] C. Song, Z. Qu, N. Blumm, and A.-L. Baraba, Lmt of predctablty n human moblty, Scence, vol. 327, no. 5968, pp. 8 2, Feb. 2. [4] C. Park, Y. Seo, K. Park, and Y. Lee, The concept and realzaton of context-baed content delvery of NGSON, IEEE Commun. Mag., vol. 5, no., pp. 74 8, Jan. 22. [5] M. Draxler, P. Dremann, and H. Karl, Antcpatory power cyclng of moble network equpment for hgh demand multmeda traffc, n Proc. IEEE Onlne GreenComm, Nov. 24. [6] H. Abou-zed, H. S. Haanen, and S. Valentn, Energy-effcent adaptve vdeo tranmon: Explotng rate predcton n wrele network, IEEE Tran. Veh. Technol., vol. 63, no. 5, pp , Jun. 24. [7] Mchael Seufert, et al., A urvey on qualty of experence of HTTP adaptve treamng, IEEE Commun. Survey Tut., vol. 7, no., pp , 25. [8] Claude Deet, et al., Flexble power modelng of LTE bae taton, n Proc. IEEE WCNC, Apr. 22. [9] A. Goldm, Wrele Communcaton. Cambrdge Unverty Pre, 25. [] S. Boyd and L. Vandanberghe, Convex Optmzaton. Cambrdge Unv. Pre, 24. [] P. Seelng and M. Relen, Vdeo tranport evaluaton w H.264 vdeo trace, IEEE Commun. Survey Tut., vol. 4, no. 4, pp , 22. [2] Vdeo Trace Lbrary. [Onlne]. Avalable: [3] G. Auer, O. Blume, V. Gannn, I. Gódor, et al., D 2.3: Energy effcency analy of e reference ytem, area of mprovement and target breakdown, EARTH, Jan. 22. [Onlne]. Avalable: