Experimental Evaluation of Memory Effects on TCP Traffic in Congested Networks

Transcription

1 IJCSI Inernaional Journal of Compuer Science Issues, Vol. 7, Issue 5, Sepember ISSN (Online): Experimenal Evaluaion of Memory Effecs on Traffic in Congesed Neworks Kulvinder Singh, Anil Kumar Assisan Professor, Deparmen of Comp. Sc. & Engg. Vaish College of Engineering, Rohak(Haryana), India Assisan Professor, Deparmen of Comp. Sc. & Engg. Vaish College of Engineering, Rohak(Haryana), India Absrac Today he Inerne is a worldwide-inerconneced compuer nework ha ransmis daa by packe swiching based on he /IP proocol suie. Inerne has as he main proocol of he ranspor layer. The performance of is sudied by many researchers. They are rying o analyically characerizing he hroughpu of s congesion conrol mechanism. Inerne rouers were widely believed o need big memory spaces. Commercial rouers oday have huge packe memory spaces, ofen soring millions of packes, under he assumpion ha big memory spaces lead o good saisical muliplexing and hence efficien use of expensive long-haul links. In his paper, we summarize he works and presen he experimenal sudy resul wih big memory space size and give a qualiaive analysis of he resul. Our conclusion is ha he, round-rip ime (RTT) is no increased by linear, bu by quadric when he memory space size of he boleneck is big enough. Our goal is o esimae he average queue lengh of he memory space size and develop a model based on RTT and he average queue lengh. Keywords: Traffic managemen, Congesion conrol, congesion mechanism, congesion model, memory size.. Inroducion The raffic across inerne is increasing so congesion is becoming an imporan issue in nework applicaions. When congesion is occurred he packe round rip ime is increased and probabiliy is los and decreased in he hroughpu. Transpor proocol mus deal wih his raffic congesion in order o make bes use of he capaciy of nework. adop a window based congesion conrol mechanism. Tradiionally experimenal sudy and measuremen have been he ools of choice for checking he performance of various aspecs of. Bu he amoun of non- raffic flows (such as mulimedia raffic) keep increasing in oday s Inerne, non- flows should share he bandwidh wih flows friendly, which means he hroughou of he non- flows ranspor proocol should be approximaely he same as he. In order o do ha, we mus analyically model he behavior and characerize he hroughpu of s congesion conrol mechanism. In his paper, we invesigae is he behaviour of a single flow when using memory spaces wih differen size. We summarize he congesion conrol mechanism and he mehod of analyically characerize he hroughpu of s congesion conrol mechanism. We presen he experimenal sudy resul wih big memory space size and give a qualiaive analysis of he resul.. An overview of Differen mechanisms of congesion conrol We can disinguish wo major kinds of congesion conrol window-based such as (Transmission Conrol Proocol), and rae-based ha for example regulaes ATM- ABR [] (Available Bi Rae service of an Asynchronous Transfer Mode nework) raffic. The window-based congesion conrol model in he Inerne aemps o solve an opimizaion problem by decoupling he nework problem o ha of individual source uiliy maximizaion by assigning bi-marks. We have a reliable proocol window-based acknowledgmen clocked flow conrol proocol. The sender conrol he sending rae by increasing or decreasing he size of is congesion window according o he acknowledgemen received. The sraegy used for congesion window size adjusmen is known as AIMD (Addiive Increase Muliplicaive Decrease).

2 IJCSI Inernaional Journal of Compuer Science Issues, Vol. 7, Issue 5, Sepember ISSN (Online): Slow Sar and Congesion Avoidance The slow sar[8] and congesion avoidance algorihms mus be used by a sender o conrol he amoun of ousanding daa being injeced ino he nework. The congesion window (cwnd) is a sender-side limi on he amoun of daa he sender can ransmi ino he nework before receiving an acknowledgmen (ACK), while he receiver's adverised window (rwnd) is a receiver-side limi on he amoun of ousanding daa. The minimum of cwnd and rwnd governs daa ransmission. The variables hreshold (sshresh) is used o deermine wheher he slow sar or congesion avoidance algorihm is used o conrol daa ransmission. The slow sar algorihm is used a he beginning of a ransfer, or afer repairing loss deeced by he reransmission imer... Congesion Avoidance In congesion avoidance we deal wih los packes due o raffic congesion. I is described in [4]. The assumpion of he algorihm is ha packe loss caused by damage is very small; herefore he loss of a packe signals congesion somewhere in he nework beween he source and desinaion. There are wo indicaions of packe loss: a imeou occurring and he receip of duplicae ACKs. Congesion avoidance and slow sar are independen algorihms wih differen objecives. Bu when congesion occurs mus slow down is ransmission rae of packes ino he nework, and hen invoke slow sar o ge hings going again..3. Fas Reransmi A receiver should send an immediae duplicae ACK when an ou-of-order segmen arrives. The purpose of his ACK is o inform he sender ha a segmen was received ou-of-order and which sequence number is expeced. From he sender's perspecive, duplicae ACKs can be caused by a number of nework problems. Firs, hey can be caused by dropped segmens. In his case, all segmens afer he dropped segmen will rigger duplicae ACKs. Second, duplicae ACKs can be caused by he re-ordering of daa segmens by he nework. Finally, duplicae ACKs can be caused by replicaion of ACK or daa segmens by he nework. The sender should use he "fas reransmi" algorihm o deec and repair loss, based on incoming duplicae ACKs. The fas reransmi algorihm uses he arrival of 3 duplicae ACKs as an indicaion ha a segmen has been los. Afer receiving 3 duplicae ACKs, performs a reransmission of wha appears o be he missing segmen, wihou waiing for he reransmission imer o expire..4. Fas Recovery A receiver should send an immediae duplicae ACK when an ou-of-order segmen arrives. The purpose of his ACK is o inform he sender ha a segmen was received ou-of-order and which sequence number is expeced. From he sender's perspecive, duplicae ACKs can be caused by a number of nework problems. Firs, hey can be caused by dropped segmens. In his case, all segmens afer he dropped segmen will rigger duplicae ACKs. Second, duplicae ACKs can be caused by he re-ordering of daa segmens by he nework. Finally, duplicae ACKs can be caused by replicaion of ACK or daa segmens by he nework. In addiion, a receiver should send an immediae ACK when he incoming segmen fills in all or par of a gap in he sequence space. This will generae more imely informaion for a sender recovering from a loss hrough a reransmission imeou, a fas reransmi, or an experimenal loss recovery algorihm. 3. Congesion Conrol and Sizing Rouer Memory spaces The goal of his research is o invesigae he memory space size ha is required in order o provide full link uilizaion given a used congesion conrol algorihm. We sar by considering he case of a single connecion. We have seen ha he sandard congesion conrol algorihm is made of a probing phase ha increases he inpu rae up o fill he memory space and hi nework capaciy []. A ha poin packes sar o be los and he receiver sends duplicae acknowledgmens. Afer he recepion of hree duplicae acknowledgmens, he sender infers nework congesion and reduces he congesion window by half. does no modify behavior in environmens wih high o mild congesion (ypical of low speed neworks) [5]. In high bandwidh-delay neworks in which HighSpeed sends burss of large number of packes, he amoun of buffer available in he boleneck rouer is an imporan issue o keep he rouer highly uilized during congesion periods. A large buffer increases delay and delay variance which adversely affecs real-ime applicaions (e.g., video games, device conrol and video over IP applicaions.) I is herefore imporan o invesigae he effecs of buffering on performance such as hroughpu, convergence o fairness and ineracion. 4. The Model for Congesion Conrol Tradiionally, experimenal sudy and implemenaion or measuremens have been he ools of choice for examining

3 IJCSI Inernaional Journal of Compuer Science Issues, Vol. 7, Issue 5, Sepember ISSN (Online): he performance of various aspecs of. Recenly, here is a grea ineres in analyzing he performance of and -like algorihms o quanify he noion of "-friendliness", which means connecions ha use non- ranspor proocol, should ge a similar share of bandwidh as connecions ha share he same link under he same condiions of loss, RTT ec. In his model, he hroughpu of 's congesion conrol mechanism is characerized as a funcion of packe loss and round rip delay. [7]Consider a flow saring a ime =. For any given ime, define N o be he number of packes ransmied in he inerval [, ], and B = N/, he hroughpu on ha inerval. The seady sae hroughpu B should be: N B lim B lim A sample pah of he evoluion of congesion window size is given in figure. W W W W3 B ( p ) p b p 3 b b RTT 6 which can be expressed as: B ( p ) RTT 3 bp 8 ( p ) 3 bp b ( p ) 3 p o p b 6 b 3 b Exends his model o include he case where he sender imes-ou and he impac of window limiaion of receiver adverised window size, i can be derived ha: Wmin B( p) min RTT bp 3bp RTT T min o 3 p( 3p ) 3 8 where T o - inerval waiing for ime ou, W min - receiver adverised window size. 5. Experimenal Work TDP TDP TDP 3 A A A3 Figure Triple Duplicae Period. Beween wo riple duplicae ACKs loss indicaions, he sender is in congesion avoidance phase. Define a TD period (TDP) o be a period beween wo riple duplicae ACKs loss indicaions. For he i-h TDP, define Yi o be he number of packes sen in he period, Ai he duraion of he period, and Wi he window size a he end of he period. Considering {Wi}i o be a Markov regeneraive process wih rewards{yi}i, i can be shown ha E[ Y ] B E[ A] () I can be derived ha E[Y] = l/p + E[W] - =E[W]*(E[W]*3/ - )*b/4 + E[W]/ () E[A] =(b*e[w]/+)*rtt (3) Where: p - loss probabiliy, b window increases by l/b packes per ACK, RTT round rip ime. From (I) () (3), we can ge We are using here rae based congesion conrol proocols, one of which is ( Friendly Rae Conrol Proocol)[3]. The model assumes ha he congesion window size increase is linear during congesion avoidance, which is no always rue. When he memory space size of he bole-neck node is big enough, he increase is sub-linear, which lead o he analyical resul will be higher han he acual resul. We use QualNe nework simulaor [6] o verify he assumpion. Table : Parameers used in he simulaion. Queue Size beween R & R 4~9 Delay beween R & R 35 ms Bandwidh beween R & R 5 Mb window size Queue Algorihm Drop Tail Bandwidh of Branch 8 Mb Delay of Branch ms We perform 4 experimenal ess. Table lis he number of connecions in each simulaion. Table : Number of connecions in each simulaion.

4 IJCSI Inernaional Journal of Compuer Science Issues, Vol. 7, Issue 5, Sepember ISSN (Online): Experimen No. 3 4 Connecions Connecions In each simulaion, we increase he memory space size of RO and RI from 5 o 85 sep by and he resul is shown in figure - figure 5. In each bar diagram, X axis is memory space size and Y axis is he mean of bandwidh of connecions and connecions Figure 4 3 & Figure 6 & 6 Figure 5 64 & Analysis Figure 3 4 & 4 From he resul of he experimens, we can find ha when he memory space size is much less han he Bandwidh*Delay, he model resul is quie close o he acual resul. However, as he memory space size increases, he experimenal sudy resul show ha he connecions ge more bandwidh han he connecions, which means he analyical resul, is higher han he acual resul. We hink i is because when he memory space size is big enough, he congesion window size increase is by sub-linear, no by linear. Considering equaion (3), his implies ha he increase of RTT is by linear in a TDP. In fac he increase of RTT is no by linear. We can find ha he RTT will increase much more when he congesion window is big han ha when he congesion window is small. When he memory space size of he boleneck node is small, he congesion window can no be very big, so he RTT can be approximaely viewed as increases by linear. Bu when he memory space

5 IJCSI Inernaional Journal of Compuer Science Issues, Vol. 7, Issue 5, Sepember ISSN (Online): size is big enough, he error beween linear and quadric curve can no be negleced. The acual ime of TDP is longer han he ime esimaed in he model when he memory space size is big, so he acual hroughpu is lower han he hroughpu esimaed in he model. 7. Relaed Work A survey on performance in a heerogeneous nework is given in []. I considers he differen characerisics of a pah crossed by raffic, focusing on bandwidh delay produc, round rip ime (RTT), on congesion losses, and bandwidh asymmery. I presens he problems and he differen proposed soluions. The model used in his paper was proposed in [7]. [3] use i o calculae he sending rae of he sender. Bu only he experimenal sudy resul wih small memory size was given. 8. Conclusion and Fuure Work In his paper, we summarize he congesion conrol mechanism and he analyical model. The model proposed in [7] capures no only he behavior of s fas reransmi mechanism, bu also he effec of s imeou mechanism on hroughpu. Bu wih he big memory space size, he model resul does no fi he acual resul well. We suppose ha i is because he increase of RTT is no by linear when he congesion window is big. We presen he experimenal sudy resul and give a qualiaive analysis. There are a lo of work remain o do. Firs, a quaniaive analysis will help us o make he model more precise. Second, he loss probabiliy of he packe plays an imporan role in he model. However, in pracice, i is hard o measure he loss probabiliy accuraely. So, if we ge he relaion of memory space size and he RTT, we can infer he queue lengh of he memory space a he boleneck node from RTT. In our fuure work, we would also like o invesigae he effecs of buffer size on he performance of oher recenly proposed high-speed varians, e.g. FAST [9] which changes is window according o buffer delay. In his way, we can model he congesion conrol mechanism mainly based on he queue lengh of he memory space and he RTT, which can be measured more accuraely han packe loss probabiliy. [] D. M. Chiu and R. Jain, Analysis of he increase and decrease algorihms for congesion avoidance in compuer neworks, Compuer Neworks and ISDN Sysems, Vol 7, pp. - 4, June 989. [3] S.Floyd, M.Handley, J.Padhye, and J.Widmer. Equaion- Based Congesion Conrol for Unicas Applicaions: he Exended Version, ICSI Technical Repor TR--3, March. [4] V. Jacobson, Congesion Avoidance and Conrol, Compuer Communicaion Review, vol. 8, no. 4, pp , Aug [5] S. Floyd, HighSpeed for Large Congesion Windows, in RFC 3649, Experimenal, December 3. [6] The Nework Simulaor QualNe, Tech. rep., WebPage: hp:// Version 5., July. [7] J.Padhye, V.Firoiu, D.Towsley, and J.Kurose, Modeling hroughpu: A simple model and is empirical validaion, Proceedings of SIGCOMM 98, 998. [8] W. Sevens. Slow Sar, Congesion Avoidance, Fas Reransmi, and Fas Recovery Algorihms. RFC, Jan 997. [9] C. Jin, D. X. Wei, and S. H. Low, FAST : Moivaion, Archiecure, Algorihms, Performance, in Proceedings of IEEE INFOCOM 4, March 4. [] Saverio Mascolo and Francesco Vacirca, Congesion Conrol & Memory Space Requiremens in Proceedings of he 44h IEEE Conference on Decision and Conrol, and he European Conrol Conference 5 Seville, Spain, December - 5, 5. Kulvinder Singh received he M.Tech.(CSE) degree in 6 and he M.Phil.(CS) degree in 8 from Ch. Devi Lal Universiy Sirsa(Haryana), India. A presen he is working as a Assisan Professor in Vaish College of Engineering, Rohak, India. He is a member of IEC. He presens many research papers in naional and inernaional conferences. His ineres areas are Neworking, Web Securiy, Inerne Congesion and Fuzzy Daabase. Anil Kumar received his bachelor degree from Delhi Universiy, Delhi, India and Maser degree from IGNOU, India and M.Tech in Compuer Science & Eng. From Kurukshera Universiy, Kurukshera, India in year and 6. Currenly he is pursuing Ph.D in Compuer Science from he Deparmen of Compuer Science & Applicaion Kurukshera Universiy, Kurukshera, India. Currenly is Ass. Professor in Compuer Science & Engineering Deparmen in Vaish Engineering College, Rohak, Haryana, India since Sepember, 6. He had also worked in sofware indusries more han hree years & being a lecure in oher engineering college more han wo years. His research areas include Sofware engineering, Reengineering, Sofware Merics, Objec Oriened analysis and design, Reusabiliy, Reliabiliy. References [l] Chadi Baraka, Eian Alman, and Walid Dabbous, On Performance in a Heerogeneous Nework: A Survey, IEEE Communicaions Magazine, January.