Journal of Physcs: Conference Seres PAPER OPEN ACCESS Desgn and mplementaton of prorty and tmewndow based traffc schedulng and routngspectrum allocaton mechansm n elastc optcal networks To cte ths artcle: Honghuan Wang et al 016 J. Phys.: Conf. Ser. 679 0101 Related content - A hgh performance herarchcal storage management system for the Canadan ter- 1 centre at TRIUMF D C Deatrch, S X Lu and R Tafrout - Optmzaton of on-lne prncpal component analyss E Schlösser, D Saad and M Behl - Mössbauer spectroscopy n the energy doman usng synchrotron radaton M Seto, R Masuda, S Hgashtanguch et al. Vew the artcle onlne for updates and enhancements. Ths content was downloaded from IP address 37.44.06.44 on 11/01/018 at 10:34
Desgn and mplementaton of prorty and tme-wndow based traffc schedulng and routng-spectrum allocaton mechansm n elastc optcal networks Honghuan Wang 1, Fangyuan Xng 1, Hongx Yn 1 *, Nan Zhao 1 and Bzhan Lan 1 Lab of Optcal Communcatons and Photonc Technology, School of Informaton and Communcaton Engneerng, Dalan Unversty of Technology, Dalan, 116034, Chna HAEPC Informaton and Telecommuncaton Company, Zhengzhou, 450000, Chna E-mal: *hxyn@dlut.edu.cn Abstract. Wth the explosve growth of network servces, the reasonable traffc schedulng and effcent confguraton of network resources have an mportant sgnfcance to ncrease the effcency of the network. In ths paper, an adaptve traffc schedulng polcy based on the prorty and tme wndow s proposed and the performance of ths algorthm s evaluated n terms of schedulng rato. The routng and spectrum allocaton are acheved by usng the Floyd shortest path algorthm and establshng a node spectrum resource allocaton model based on greedy algorthm, whch s proposed by us. The farness ndex s ntroduced to mprove the capablty of spectrum confguraton. The results show that the desgned traffc schedulng strategy can be appled to networks wth multcast and broadcast functonaltes, and makes them get real-tme and effcent response. The scheme of node spectrum confguraton mproves the frequency resource utlzaton and gves play to the effcency of the network. 1. Introducton In recent years, wth the rapd development of broadband and hgh rate servces, such as bg data, cloud computng, hgh defnton vdeo on demand and Internet of Thngs, optcal networks need to be able to deal wth the enormous carrer pressure brought by these large capacty servces. Nowadays, the fxed-grd rgd-bandwdth WDM network s wdely used to allocate resources. Ths fxed-grd WDM optcal network allocates the same spectrum resources for spectrum requrements of dfferent servces at varous rate and dfferent bandwdth, whch wll lead to excessve resource waste when the servces need only low-rate and low-bandwdth requrements. Moreover, the waste of resources wll show deteroratng trend wth the expanson of networks. Therefore, the novel spectrum-slced elastc optcal path (SLICE) network [1, ] based on programmable devces has been proposed. However, the flexble grd network s also facng new ssues, such as traffc schedulng scheme [3] and the effectve allocaton of network resources, to be addressed. Therefore, an adaptve traffc schedulng polcy based on the prorty and tme wndow s proposed n ths paper. The performance of ths algorthm s evaluated n terms of schedulng rato. Moreover, the routng and spectrum allocaton are acheved by usng the Floyd shortest path algorthm and establshng a node spectrum resource allocaton model based on greedy algorthm. The farness ndex (FI) [4] s ntroduced to mprove the capablty of spectrum confguraton. Content from ths work may be used under the terms of the Creatve Commons Attrbuton 3.0 lcence. Any further dstrbuton of ths work must mantan attrbuton to the author(s) and the ttle of the work, journal ctaton and DOI. Publshed under lcence by Ltd 1
. Adaptve schedulng algorthm The prorty s defned consderng bandwdth and duraton of a servce request, assumng that bandwdths are proportonal to data-rates. The model that determnes the schedulng order s abstractly expressed as T( s, d, p, dt, w ), where s and d are the source node and the destnaton node, respectvely, and p s the traffc prorty. dt s the expected startng tme of schedulng and w represents tme wndow. Fgure 1 denotes the tme-wndow model of schedulng. If the actual scheduled startng moment S can move wthn tme wndow followng dt,.e., dt w S, the traffc s scheduled, whch stops at E. Otherwse, the schedulng fals. When dt s the same, the scheduled startng moment s movable wthn the ndvdual tme wndow. Table 1 represents prortes and tme-wndow settng. The traffc wth hgh-prorty should be scheduled earler, whle the tme effcency of schedulng should also be consdered at the same tme. The shorter tme wndow of traffc,.e., the earler deadlne dt w, can save more dle tme for schedulng more traffc. Therefore, schedulng effcency of each servce request conssts of prorty effcency and tme effcency. The prorty effcency s expressed as a p. The tme effcency s (-0.1( - )/( - expressed as dt b w S E S )) e, 1,,. The overall effcency of a scheduled traffc s G a b, whch s exploted to measure the performance of the schedulng algorthm. Obvously, ths algorthm reflects a better performance wth a greater schedulng effcency. The goal of ths algorthm s N 1 G =max s. t. S dt (1) w 0 () dt w S (3) where S dt represents that the actual startng moment s not earler than expected startng tme of schedulng, w 0 shows that the tme wndow s not less than 0, dt w S means that the actual startng moment s before the deadlne of request. The adaptve schedulng algorthm wth tme wndow wll have a range and sort crtera to adjust to the actual schedulng order when a large number of servce requests arrve synchronously. The method s depcted n Algorthm 1. The core of ths schedulng polcy s the sortng a large number of servce requests based on three dfferent crtera, whch are the prorty rule (PR), the deadlne rule (DR), and the prorty-deadlne rule (PDR). The performance of ths algorthm s evaluated n terms of schedulng rato. w dt S E Fgure 1. Tme-wndow model of schedulng. Table 1. Prortes and Tme-wndow Settng. Requests Prorty Tme Wndow(ms) Hgh-bandwdth, Short-duraton 4 50 Hgh-bandwdth, Long-duraton 3 30 Low-bandwdth, Short-duraton 0 Low-bandwdth, Long-duraton 1 10 t
Algorthm 1 Adaptve Schedulng Algorthm 1: Intalze dle tme : Read the requests belongng to a schedulng perod 3: Sort the requests by prorty or deadlne 4: Take the sorted requests n order 5: whle requests queue s not empty, do 6: for dle tme meet the dt and w do 7: (a) A request jon executve matrx. 8: (b) Watng for allocaton of spectrum resources. 9: (c) Update startng pont of dle tme. 10: end for 11: (a) Request added to delay matrx. 1: (b) Update requests to the next schedulng perod 13: end whle 14: Schedulng fnshed 3. Routng and node spectrum confguraton Schedulng and resource allocaton model n Fgure shows that the traffc successfully added to the executon queue wll wat for correspondng routng and spectrum allocaton accordng to the source node and destnaton node. The shortest path between any two nodes s calculated by usng Floyd algorthm [5] n ths paper. The spectrum resource dstrbuton of node output lnks s altered on a regular bass, takng nto account the network spectrum consstency and contnuty n the perspectve of network node spectrum resource reconfguraton. Assume that each node has the capablty of center frequency converson [6]. As shown n Fgure 3, the spectrum resource s allocated for the traffc to access the respectve lnks through node. An approprate spectrum allocaton polcy can groom traffc as much as possble, and save spectrum resources substantally, whle ensurng the qualty of servce. In order to make the output lnks of node get equtable dstrbuton of spectrum resources and reduce traffc blockng probablty, a node spectrum allocaton scheme based on greedy algorthm s proposed. The steps of ths algorthm are presented below. 1) Set a certan tme perod. Calculate the average value of maxmum and mnmum bandwdth among traffc requests through each lnk n the set tme nterval. Ths average bandwdth B s defned as the ntal soluton of bandwdth for lnk. ) Set an approprate frequency slot perod. Select several lnks randomly and make them share a same frequency-slot perod, and accumulate each B of these selected lnks. If the sum of B s less than the frequency slots perod, replace each B wth a larger bandwdth B n the traffc requests queue. If the sum s stll lower than the frequency slots perod, do the same operaton untl t s closest to the perod. 3) Move central frequences of traffc to the correspondng spectrum. 4) Use the frst-ft spectrum assgnment approach to allocate spectrum resources for traffc leadng to dfferent lnks through the node. Source nodes Request1 Optcal network Destnaton nodes Request Traffc Schedulng RSA Data Processng RequestN Optcal Network Fgure. Schedulng and resource allocaton model. 3
Queue (, 1) Queue (, )... Queue (, N-1) Queue (, N) Node L 1... L N-1 FSs1 FSs L N L 1 L L 3 L N Fgure 3. Spectrum allocaton model of node. The effectveness of the proposed algorthm n terms of better qualty of servce s modfed by assgnng broadband for each output lnks of the node. The farness ndex (FI) can be defned as below to measure the equty of spectrum allocaton scheme N ( ( B / A )) 1 FI, 1,, N N N ( B / A ) 1 where N s the total number of node output lnks. A and B are respectvely the request spectrum bandwdth and the actual assgned bandwdth for lnk. Vsbly, FI s a value between 0 and 1. The FI closer to 1 ndcates a better farness between the lnks and a lower blockng probablty. When FI s lower than the threshold, the node spectrum for lnks s reconfgured. 4. Results and dscussons 4.1. Performance of schedulng polcy To verfy the performance of the adaptve schedulng algorthm based on prorty and tme wndow, the number of prortes s ncreased by addng the number of bandwdth threshold of request. Sx prortes and 50ms schedulng nterval are set n the smulaton. The schedulng rato wth dfferent prortes s taken as a evaluaton ndex. The result shows schedulng performance comparson curve of three crtera, as shown n Fgure 4. (4) 1 Schedulng Rato 0.8 0.6 0.4 0. PR DR PDR 0 1 3 4 5 6 Prorty Fgure 4. Schedulng rato vs. prorty under three crtera 10 4 50 55 1 10 40 6 5 0 3 5 5 Fgure 5. 6-node test network. 4
Fgure 4 shows that schedulng rato of PR and PDR ncreases lnearly wth the growth of prorty. The schedulng rato of DR has the smlar trend wth the former two crtera when the prorty s low, whle presentng a downtrend wth hgher prortes. In ths case, schedulng rato of DR depends prmarly on the deadlne of traffc requrement. Therefore, dfferent schedulng rules exhbt ther own advantages n dfferent requrements. The PDR or DR should be selected to avod low-prorty traffc not to be treated for a long tme. The PR presents better schedulng rato when the prorty s hgh. Therefore, an approprate sort rule should be chosen to meet the user's mult-meda servce requests wth dfferent granulartes. Ths schedulng scheme s also applcable among multple networks. The approprate adjustments for prorty or tme wndow of servce request can mprove the probablty of a tmely response for the network wth real-tme requrements. 4.. Performance of routng and node spectrum allocaton The performance of routng algorthm s verfed through a 6-node test network presented n Fgure 5. As seen from the weghted graph, Floyd algorthm can accurately calculate the shortest path between any two nodes n the network. The objectve of spectrum allocaton s to meet servce requrements whle reducng the spectral fragmentaton. Assume that each node has the capablty of center frequency converson. The traffc passes node to dfferent destnatons through respectve output lnks. Seven output lnks are set to verfy the farness of node spectrum allocaton n the smulaton. 50 spectrum slces are set to a frequency slot perod (FS) and allocated to partal lnks randomly. When the spectral occupancy of one FS reaches the upper lmt, another FS s assgned to remanng lnks. Fgure 6 (a) shows the status of node spectrum. The whte and blue hstograms, respectvely, represent dle spectrum and request spectrum of lnks, whle the red hstogram presents the occuped spectrum wthn FS. Fgure 6 (b) reports the spectrum allocaton of output lnks. Clearly, lnks 6, 4,, 1 share the same FS and lnks 5, 3 share the second FS, whle lnk 7 s confgured n another FS. Result of smulaton shows that the node spectrum confguraton scheme greatly reduces spectrum fragmentaton and mproves the utlzaton of spectrum resources. The throughput of the node s set to 110 Erlang n the node spectrum allocaton smulaton based on greedy algorthm. The bandwdth s assgned to each lnk to satsfy traffc transmsson. Farness Index (FI) vares wth varance between the lnks under node spectrum allocaton as shown n Fgure 7. When the bandwdth of each lnk request s smlar,the FI s closer to 1, namely, the farness of allocated spectrum between lnks s better. If FI s less than a set threshold, reset the combnaton of lnks sharng the same FS or shorten FS to reduce the lnk varance. In ths case, less allocated spectrum for one lnk that affects the qualty of servce and ncreases blockng probablty s avoded. (a) 50 Slces 40 30 0 10 0 Occuped Request Idle 1 3 4 5 6 7 Lnk (b) Frequency Slots 5 4 3 1 L7 L5 L3 L6 L4 L L1 1 10 0 30 40 50 Slces Fgure 6. (a) Status of node spectrum (b) Spectrum allocaton of output lnks 5
1 0.8 0.6 FI 0.4 0. 0 10 0 30 40 50 60 70 80 Varance between the Lnks Fgure 7. Farness vs. varance between the lnks under node spectrum allocaton. 5. Concluson In ths paper, an adaptve traffc schedulng algorthm based on prorty and tme wndow s presented. Routng and spectrum allocaton for scheduled traffc are acheved wth the flexble and reconfgurable network node. The desgned traffc schedulng strategy can be appled to the networks wth multcast and broadcast, and makes them get real-tme and effcent response, whch lays the foundaton for the schedulng nvestgaton of multmeda servces wth dfferent granularty n the future network. The scheme of node spectrum confguraton mproves the frequency resource utlzaton and gves play to the effcency of the network, whle the farness of spectrum assgnments for servces through lnks leadng to dfferent destnaton nodes, s ensured. Acknowledgment Ths work was supported n part by the Natonal Natural Scence Foundaton of Chna (NSFC) under Grants 6107113 and The Frst HAEPC Scence and Technology Project n 015 under Grant 517Q014006V. References [1] Jnno M, Takara H, Kozck B, Tsukshma Y, Sone Y and Matsuoka S 009 Spectrum-effcent and scalable elastc optcal path network: archtecture, benefts, and enablng technologes Communcatons Magazne 47 66-73 [] Jnno M, Ohara T, Sone Y, Hrano A, Ishda O and Tomzawa M 011 Elastc and adaptve optcal networks: possble adopton scenaros and future standardzaton aspects Communcatons Magazne 49 164-17 [3] Huang X and Ma M 005 An effcent schedulng algorthm for real-tme traffc on WDM optcal networks The 9th Int. Conf. on Communcatons Systems pp 366-370 [4] Thagarajan S and Soman A K 001 Capacty farness of WDM networks wth groomng capabltes Optcal Network Magazne 4-3 [5] Floyd R 196 Algorthm 97: shortest path Comm. ACM 5 345 [6] Paolucc F, Sambo N, Melon G, Berrettn G, Fres F, Pot L and Castold P 014 SDN control of all-optcal frequency converson and defragmentaton for super-channels OFC pp 1,3, 9-13 6