An effective hop-by-hop Inteest shaping mechanism fo CCN communications Natalya Rozhnova, Sege Fdida To cite this vesion: Natalya Rozhnova, Sege Fdida. An effective hop-by-hop Inteest shaping mechanism fo CCN communications. INFOCOM NOMEN wokshop, Ma 2012, Olando, Floida, United States. pp.322-327, 2012, <10.1109/INFCOMW.2012.6193514>. <hal-00997088> HAL Id: hal-00997088 http://hal.upmc.f/hal-00997088 Submitted on 28 May 2014 HAL is a multi-disciplinay open access achive fo the deposit and dissemination of scientific eseach documents, whethe they ae published o not. The documents may come fom teaching and eseach institutions in Fance o aboad, o fom public o pivate eseach centes. L achive ouvete pluidisciplinaie HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau echeche, publiés ou non, émanant des établissements d enseignement et de echeche fançais ou étanges, des laboatoies publics ou pivés.
An effective hop-by-hop Inteest shaping mechanism fo CCN communications Natalya Rozhnova Univesité Piee et Maie Cuie (UPMC) Sobonne Univesité - CNRS Laboatoie d Infomatique de Pais 6 (LIP6) Pais, Fance Email: natalya.ozhnova@lip6.f Sege Fdida Univesité Piee et Maie Cuie (UPMC) Sobonne Univesité - CNRS Laboatoie d Infomatique de Pais 6 (LIP6) Pais, Fance Email: sege.fdida@lip6.f Abstact We intoduce a ate-based congestion contol mechanism fo Content-Centic Netwoking (CCN). It builds on the fact that one Inteest etieves at most one Data packet. Congestion can occu when aggegate convesations aive in excess and fill up the tansmission queue of a CCN oute. We compute the available capacity of each CCN oute in a distibuted way in ode to shape thei convesations Inteest ate and theefoe, adjust dynamically thei Data ate and tansmission buffe occupancy. We demonstate the convegence popeties of this Hop-by-hop Inteest Shaping mechanism (HoBHIS) and povide a pefomance analysis based on vaious scenaios using ou ns 2 simulation envionment. I. INTRODUCTION The inceasing impotance of content has tiggeed a temendous inteest fom the netwoking eseach community, moving away fom packets and getting close to the sevice deliveed to the use. In paticula, the achitectue of Content- Centic Netwoking (CCN) poposed by Van Jacobson and al. in [1] appeas as the most popula one. At this stage, CCN defines design pinciples and has developed a CCNx Open Souce Platfom. Howeve, many functionalities ae still at an ealy stage, o have been consideed in vey simple contexts. CCN decouples the sende fom the eceive in a mode that is simila to the Publish and Subscibe sevice model. Content names ae used instead of netwok addesses to convey the infomation to the inteested paties. The content might be located anywhee in the netwok thanks to extensive caching capabilities. Theefoe, the data is not necessaily associated with the content publishe as the content can be deliveed by any cache in the netwok. In CCN, the equest fom the content consume is called Inteest and the pat of the associated content is called a Chunk o Data. We will name a steam of Inteest/Chunk pais a Convesation. Taffic engineeing has been lightly addessed in CCN. Congestion might aise in such netwoks as chunks can satuate the tansmission buffe of a netwok face. It is thus necessay to egulate the steam of chunks, and theefoe, the associated steam of inteest in ode to avoid congestion and pefomance degadation. This poblem has not yet been fomalized and studied in CCN. In this pape, we popose a congestion contol mechanism fo CCN, based on hop-by-hop Inteest shaping. It elies on the assumption that any CCN oute can contol the futue ate of data-chunks it will eceive by shaping the ate of the Inteest it is cuently sending towads content povides, as one Inteest etieves at most one Data packet. We monito the level of Chunks stoed in the oute tansmission buffe in ode to dynamically adjust the associated Inteests ate that have geneated the Chunks in that buffe. We povide a simple analytical model to demonstate the convegence of ou algoithm, complemented by simulation esults to evaluate the behaviou of ou solution in moe complex settings. The emainde of the pape is oganized as follows: Section III is devoted to a bief desciption of a CCN node. We discuss congestion in CCN and intoduce taffic contol issues in section IV. Ou congestion contol algoithm is pesented in Section V. A simple mathematical model is deived in Section VI and VII in ode to highlight the convegence popeties of ou algoithm. The pefomance of ou solution is evaluated by ns 2 simulation and discussed in section VIII. Section IX concludes the pape and highlights futue wok. II. RELATED WORK Infomation Centic Netwoks (ICN) is widely studied [3] with solutions such as PSIRP [4] o DONA [5]. The CCN famewok was fist intoduced by Van Jacobson and the PARC eseach goup in [1], [2]. Vaious issues aising in CCN have been consideed such as content oute issues [6], data tansfe modelling [7] o chunk-level caching [8]. In [9] the authos have pesented the modelling and evaluation of caching policies based on Makov chains. CCN Congestion contol has not been studied yet, aguing that its hop-by-hop contol will enfoce a easonable level of pefomance. Some peliminay wok on a tanspot potocol fo CCN is pesented by S. Aianfa and al. in [13]. This potocol is based on the TCP congestion window pinciples but uses Data packets as acknowledgments to enfoce decisions to incease o decease the congestion window. Congestion can appea in CCN and theefoe, we pomote the utilization of an algoithm to contol the level of congestion of CCN outes filled by Data packets. We follow simila pinciples as in [14], whee the authos pesent ERAQLES, a ate contol mechanism fo Available Bit Rate (ABR) ATM communications, and define an analytical
Fig. 1. The CCN node model method to compute the advetised explicit ate to which the souces have to adapt. A simila wok is pesented in [15]. In [16], the authos descibe a ate-based hop-by-hop congestion contol mechanism in which a desied sevice ate is computed at each switch as a function of the taget queue occupancy. Feedback infomation is then exchanged between neighbo switches so that they can dynamically adjust the sevice ate fo each connection. III. CCN NODE MODEL In this section we descibe the CCN node model and discuss the most meaningful popeties of CCN fo ou wok. The geneal CCN node model was intoduced in [1]. A simple oute model is illustated in Figue 1. In this figue, we omit the fowading infomation base (FIB) and the pending inteest table (PIT). The fome is used to fowad Inteests towad the data souce while the late keeps tack of the fowaded Inteests so that the etuned Chunks can be sent to its equesto. We fist intoduce ou model of a CCN oute in ode to illustate whee congestion can appea. In [1] the authos advocate that CCN does not have FIFO queues between links but athe an LRU memoy (the cache). Howeve, in a CCN oute, it is impotant to diffeentiate the memoy allocated fo tansmiting packets fom the one used fo caching. If a single Content-Stoe was used to stoe both packets waiting fo tansmission and cached Data chunks, the whole cache will become congested by Data chunks waiting fo tansmission though the congested inteface and so it will penalize anothe convesation going though non-congested intefaces. Thus, it would be had to conceptualize the CCN node behaviou when thee is a congestion of a single output inteface. Anothe undesiable side is the huge delay induced by the filling of a vey lage cache used as a tansmission buffe, befoe congestion detection. Finally, it is cucial that at any given time, each output inteface schedules which packet is the next one to be tansmitted on the physical channel. This can be achieved with the use of pe-inteface queue athe than a single shaed cache. IV. TRAFFIC CONTROL IN CCN One key CCN popety is that one Inteest etieves at most one Data packet. This behaviou enfoces a flow balance that is maintained in the netwok and allows the communication between the diffeent machines and at diffeent speeds. The flow balance enables multiple Inteests to be issued at once. The CCN node behaviou is descibed theeafte; when a Data-chunk is eceived on one face o is etieved fom the cache by an incoming matching Inteest, it must be tansfeed to the output inteface(s). Depending on the esults of the PIT lookup, it is then queued on one o moe tansmission buffes. At the same time the Data chunk can also be stoed into the shaed cache to enable futhe etieving. Because some Data chunks will pesent vey few incentives fo being cached (shot-lived o non-popula Data chunk), the copy of data-chunks to the content stoe is not mandatoy. Caching decisions ae out-of-scope of this pape. Congestion in a CCN oute is defined as the oveflow of the buffe associated to an output inteface and manifests itself by the loss of data chunks. V. HOP-BY-HOP INTEREST SHAPING MECHANISM (HOBHIS) In this section, we pesent the hop-by-hop Inteest Shaping mechanism (HoBHIS). Evey CCN oute will contol the ate of individual Data chunks convesations by appopiately shaping the ate of the associated sending Inteests. The congestion contol scheme based on hop-by-hop inteest shaping was pefeed to an end-to-end mechanism such as TCP. Ou mechanism is poactive and the shae of the netwok capacity allocated to diffeent convesations is contolled by the algoithm implemented in each CCN node. Inteest shaping allows us to anticipate the dop of data packets due to buffe oveflow. This is anothe advantage ove TCP congestion contol scheme that stats to eact only afte the dop of one segment, unless a mechanism such as RED is used. In addition, using a hop-by-hop contol povides a feedback infomation moe quickly thanks to the smalle distances between hops. The system unde study consists of a set of CCN outes fowading Inteest packets issued by a consume. As a esponse, Data chunks ae fowaded back to the consume (namely, the souce of the Inteests). Once an Inteest has been issued by a given CCN oute, the coesponding Data chunk will be piggybacked to that oute afte a vaiable delay A(t) named Response Delay, assuming no loss. This paamete diffes fom the usual RTT fom TCP as the Data might be stoed in any cache on the path o at the publishe site (the souce of the Data). Thus, in such achitectue as CCN it is possible sometimes to obseve lage vaiations of A(t) that leads to the queue size oscillations. But thanks to the congestion contol mechanism, the queue size will be fast stabilized. We also infe that A(t) should not change dastically on shot time scales as it is likely that when the data is stoed in a given cache, it should stay thee fo some time, at least until the netwok and demand conditions have lagely evolved. The objective of HoBHIS is to avoid congestion in CCN tansmission queues by enfocing the queue size to convege to a given objective, defined as a pecentage of the capacity of that buffe. We achieve this objective by shaping the Inteest ate. In ode to avoid the losses of Inteests when shaping is enfoced we
TABLE I NOTATIONS C(t) C int (t) γ(t) A(t) e(t) B available bandwidth to send the chunks at time t available bandwidth to send the Inteests at time t shaping ate at time t delay fom Inteest to the elated content numbe of queued packets at time t buffe size queue theshold Fig. 2. Fig. 3. Repesentation of the system Repesentation of the model need some back-pessue mechanism which is out-of-scope of this pape and will be povided in futue wok. Upon aival of a Data chunk in the tansmission queue, the oute computes the Inteest ate based on the queue occupancy and the available esouces fo each convesation. It adjusts the Inteest ate accoding to this infomation. If the actual numbe of queued packets is less than some theshold value, then the oute can tempoaily incease the shaping ate. On the othe hand, if the numbe of queued packets is highe than, then the oute will decease its shaping ate. The system unde study is pesented in figue 2. The Shaping time component is esponsible fo the computation of the shaping delay that the Inteests packets will have to satisfy. Evey Inteest packet will be shaped accoding to the occupancy of the tansmission queue, as well as the paamete A(t). VI. SINGLE ROUTER MODEL Fo the pupose of the analysis, we conside the simplified model pesented in figue 3. It is chaacteized by a single convesation. In addition, all packets have the same size. The contol is applied to each chunk enteing the tansmission queue. We do not conside any caching policy o outing mechanism. The paametes and notations ae given in Table I. A. Computation of the shaping ate Let e(t) define the occupancy of a CCN oute tansmission queue expessed in numbe of chunks. We conside the following function that epesents the maximum shaping ate at time t, while still being able to contol the tansmission queue unde a feedback delay equal to A(t): γ(t) = C(t)+ B e(t),o (1) A(t) γ(t) = C(t)+h e(t), (2) A(t) whee h is a design paamete that aims to contol the dynamicity of ou scheme towads the objective. In the geneal case when thee ae F convesations flowing though a CCN node, we need to divide the available buffe capacity between all active convesations at time t. We allow each convesation to shae a pat equal to F of the total buffe capacity. If a convesation is using less than F, the emainde essouces may be used fo queue size oscillations caused by A(t) (cf. Section V). Let e i (t) be the numbe of packets fom convesation i waiting in the tansmission queue. The shaping ate fo convesation i is expessed as follows: γ i F (t) = C(t)+h e i(t), (3) A i (t) Note that the shaping ate is bounded by Cint(t) defined as the maximum capacity to send the Inteests at time t. The expession fo γ i (t) becomes: γ i F (t) = min[max[c(t)+h e i(t),0],c int (t)], (4) A i (t) It is possible fom equation (2) that the shaping ate becomes negative. In this situation, the Inteests ae blocked until eithe the tansmission queue size e(t) becomes less o equal to, o a Chunk aives at the queue and the Inteest shaping ate is e-evaluated. We use an exponential weighted moving aveage mechanism to estimate the value of A(t). B. Queue convegence In this section we demonstate that the tansmission queue length conveges to the objective. We assume a single convesation that can use the entie link capacity to send its Data. Let A j (espectively A j+1 ) be the Response Delay fo packet numbe j (espectively packet j +1). The queue evolution fo a single convesation is witten as follows: and e(t+1) = e(t)+γ(t).a j+1 C.A j+1 (5) γ(t) = C +h e(t 1) A, (6) j
TABLE II NOTATIONS Fig. 4. Based on above we can wite : e(t+1) = e(t) h. A j+1 A j This fomula can be simplified as with Repesentation of the model.e(t 1)+[h.. A j+1 A ] (7) j e i+1 = e i +α.e i 1 +β (8) α = h. A j+1 A, β = h.. A j+1 j A and e i 1 = e(t 1) (9) j We wite e i+1 as e i+1 = f i+1 β α (10) Then we obtain fi+1 = f i +α.f i 1, (11) which is the seies of Fibonacci. So, due to [12] we have whee z is the oot of equation Thus, we need that f i+1 = P.z i+1 (12) z = z 0 +α = 1+α (13) z < 1 (14) and if i tends to infinity then f i+1 conveges to 0. But the condition z < 1 will be tue only if : And finally, 0 < h < 2. A j A j+1 (15) lim e i = lim[ β i i α ] = (16) We found that the tansmission queue is conveging to as expected. We will obseve that we can face a bust of Data Chunks duing the initialization peiod. This is because ou algoithm stats only afte the eception of the fist data packet. Until then, the system sends the packets with the maximum available ate. This poblem is solved by limiting the initial sending ate accoding to the shaping ate fomula. We now conside F convesations. Ou shaping ate fomula is defined by: γ i F (t) = C(t)+h e i(t), (17) A i (t) It appeas that the queue size fo each convesation conveges to F. So, the total queue size will convege to as expected. λ c i aival Chunks ate to node i λ I x aival Inteests ate µ i sevice ate of node i γ i A i e i (t) B shaping ate of node i delay fom Inteest to the elated content fo node i numbe of queued packets at time t of node i buffe size queue theshold VII. NETWORK OF NODES We now extend ou simple initial scenaio to the case of a netwok of nodes. This model, descibed in Figue 4, consists of N nodes using HoBHIS. We have now a hop by hop congestion contol mechanisms using the shaping ate computed at each oute. The notations ae pesented in Table II. We stat with a single convesation flowing though the system. The Response Delay is defined by paamete A. The Chunks aive into the nodes with the ate λ c chunks/second. A. Response delay evaluation The Response Delay A of one node depends on downsteam nodes up to the oute caching the Data o the souce itself. Let s define A i and A i 1 the Response Delays fo nodes i and i 1 espectively. A i can be expessed as follows: A i = A i 1 + X 1 j=1 γ j i 1 + e i 1 µ i 1 (18) The Response Delay fo a given packet p in node i depends on the numbe of packets X queued fo tansmission ahead of p towads the downsteam node and also depends on the numbe of packets e i 1 queued befoe the esponse will be sent-back to node i. The quantity X j=1 1 γ j i 1 means that we ecompute the shaping ate γ i 1 fo each Chunk enteing the queue and hence the Inteests could be sent with diffeents ates. B. Convegence popety We have demonstated fo a single oute model that, if the minimal ate among all nodes is γ i, associated to node i, then the queue of node i conveges to. In addition, we know that lim t eγi i (t+1) = and lim t eγ k i (t+1) = (19) So, accoding to the limit inequality theoem we have: fo all othe outes shaing the same convesation s paths as oute i. VIII. PERFORMANCE EVALUATION The aim of this section is to analyze, though simulations, the pefomance of the CCN Inteest shaping mechanism. We have developed the CCN module in Netwok Simulato 2 (ns 2 ). Accoding to ou knowledge, thee is no vesion of CCN in ns 2 at the time of witing.
Fig. 5. Single convesation scenaio Fig. 7. Netwok topology Fig. 6. Multi convesation scenaio A. Simulation scenaio We stat with the single oute model. We conside both the single convesation and the multi-convesation scenaios pesented in Figue 5 and 6 espectively. As depicted in figue 5 and 6, ou netwok consists of the client, oute and seve components. The client sends the Inteests to the oute that takes the next decision accoding to the shaping mechanism. The seve ole is vey simple, as fo each eceived Inteest it esponds with the coesponding Chunk and sends it back to the oute. The shaping ate is computed accoding to the algoithm pesented in pevious sections. e(t) is the instantaneous measued value fo the numbe of Chunks at time t. The Inteest and Chunk packet sizes ae fixed on 500 and 1500 bytes espectively. The buffe paametes ae B=500 Chunks, = 100 Chunks, h = 0.1, 0.4 and 0.7. The clients geneate Inteests with ate 833.3 Chunks/s. The links ates ae given in figue 5 and 6. The bottleneck is the 1Mb link between the client and the oute. Paamete A(t) is a andom value unifomly distibuted in [0,1] and it is geneated in the seve fo evey packet to take into account the vaiability of the path between the oute and the seve. The Netwok topology used fo the evaluation is pesented in figue 7. We conside two convesations fom clients 1 and 2 espectively. Data fo convesation 1 is in the cache of node 3. Convesation 2 flows fom Client 2 to the Seve. The inteest ate is 2500 Chunks/s fo each client. The paametes fo the buffes ae B=500 Chunks, =250 Chunks and h=0.7. The capacity of each link is 2500 Chunks. The convesation 2 stats befoe convesation 1 and afte some time it stops. We ae inteested in the buffe state fo node 3, as well as the ate fo each convesation ove time. B. Simulation esults The simulation esults fo the single convesation scenaio ae pesented in Figue 8. We have tested ou algoithm fo diffeent values of h. In Figue 8 we can see that the queue conveges to the objective as expected (cf. in Section VII). Fig. 8. Queue convegence fo single convesation scenaio The busts in these cuves ae due to the initialization peiod when the algoithm is not yet in opeation. The diffeent values of h illustates its influence fo the contol mode and convegence ate. The highehthe slowe the convegence ate towads the objective and the hade the contol. The situation epeats fo the multi convesation scenaio in Figue 9. The aveage queue size conveges to as expected (cf. Section VII). Figues 10 and 11 illustate the netwok scenaio. As we use the same capacities fo each link, the queue of evey node is empty until convesation 1 stats. Then, the queue fo node 3 stats to fill up and conveges to the objective. Figue 11 illustates the Chunks aival ates fo each convesation in Chunks/s. At time 20, convesation 1 becomes active. At time 60, convesation 2 becomes inactive. Between time 20 and 60, when the two convesations ae active, each of them eceives a faie shae of the oute esouces. The Chunks aival ate, shaed between the two convesations ae contolled by the minimal shaping ate. In figues 10 and 11 we see that ou congestion contol mechanism is able to adapt the ate and to maintain the queue length at the expected level as it was designed. IX. CONCLUSION We pesented (HoBHIS), the fist hop-by-hop Inteest shaping congestion contol mechanism designed to avoid the congestion that can occu in the output inteface of a CCN node. HoBHIS monitos the tansmission buffes of a CCN
Fig. 9. Queue convegence fo multi convesation scenaio Fig. 11. Chunks ates fo netwok scenaio Fig. 10. Queue state fo netwok scenaio oute to compute the Inteests ate that have poduced the associated Chunks filling these intefaces. We demonstated analytically the convegence popety of ou algoithm. In addition, we have developed a CCN implementation in ns 2. We pefomed vaious expeiments with diffeent settings and pogessive complexity. We analyzed the single and multiple convesation scenaios in a single oute model. Finally, a netwok case was studied to demonstate the behaviou of ou algoithm in moe complex conditions. We have seen that the shaping mechanism pefoms as designed. Futue wok will extend the analysis as well as the design of HoBHIS. We will conside the case whee the shaing of the esouces among competing convesations will be diffeent fom a fai shae in ode to favo impotant content. We will also exploe the complexity of ou algoithm and its scalability. Monitoing all convesations is fa too expensive but we will concentate on the active convesations only, those fo which packets ae queued in the buffe, to educe the numbe of states stoed in the oute. In addition, the inteaction with TCP will be consideed. Finally, we will study moe complex scenaios to bette assess the behaviou of ou solution. ACKNOWLEDGMENTS This wok is patly funded by the Fench national eseach agency (ANR), CONNECT poject. The authos would also like to thank Naceu Malouch fo many useful discussions and fo valuable comments. REFERENCES [1] Van Jacobson, Diana K. Smettes, James D. Thonton, Michael F. Plass, Nicholas H. Biggs, and Rebecca L. Baynad. 2009. Netwoking named content. In Poceedings of the 5th intenational confeence on Emeging netwoking expeiments and technologies (CoNEXT 09). ACM, New Yok, NY, USA, 1-12. [2] D. Smettes, V. Jacobson, Secuing Netwok Content, PARC Tech Repot, Octobe 2009. [3] Sege Fdida and Mohamed Diallo. 2008. The netwok is a database. In Poceedings of the 4th Asian Confeence on Intenet Engineeing (AINTEC 08). ACM, New Yok, NY, USA, 1-6. [4] Publish-Subscibe Intenet Routing Paadigm (PSIRP) poject : http://www.psip.og [5] T. Koponen, M. Chawla, B. Chun, et al., A dataoiented (and beyond) netwok achitectue, ACM SIGCOMM Compute Communication Review, Volume 37, Issue 4, pp 181-192, Octobe 2007. [6] S. Aianfa, P. Nikande, and J. Ott. On content-centic oute design and implications. In Poc. of ACM ReAch 10. [7] G. Caofiglio, M. Gallo, L. Muscaiello, and D. Peino. Modeling data tansfe in content centic netwoking. In Poc. of 23d Intenational Teletafic Congess 2011 (ITC23). [8] G. Caofiglio, V. Gehlen, and D. Peino. Expeimental evaluation of stoage management in content-centic netwoking. In Poc. of IEEE ICC, 2011. [9] Ioannis Psaas, Richad G. Clegg, Raul Landa, Wei Koong Chai, and Geoge Pavlou. 2011. Modelling and evaluation of CCN-caching tees. In Poceedings of the 10th intenational IFIP TC 6 confeence on Netwoking - Volume Pat I (NETWORKING 11), Jodi Domingo-Pascual, Pieto Manzoni, Ana Pont, Segio Palazzo, and Cateina Scoglio (Eds.), Vol. Pat I. Spinge-Velag, Belin, Heidelbeg, 78-91. [10] J.-Y.Boudec. Rate adaptation, congestion contol and fainess: A tutoial. [11] C. Roche, S. Fdida, A Dynamic Resouce Management Mechanism fo LAN Inteconnection acoss High-Speed Netwoks, Infocom 94, Toonto, June 1994. [12] Fibonacci numbes and thei applications. Poceeding of the fist Intenational Confeence Numbes and thei Applications, Univesity of Patas, 1984. [13] S. Aianfa, J. Ott, L. Egget, P. Nikande, W. Wong. A Tanspot Potocol fo Content-centic Netwoks. Extended Abstact. 18th IEEE Intenational Confeence on Netwok Potocols (ICNP 10), Kyoto, Japan, 2010. [14] Moet, Y.; Fdida, S.; ERAQLES an efficient explicit ate algoithm fo ABR, Global Telecommunications Confeence, 1997. GLOBECOM 97., IEEE, vol.2, no., pp.801-805 vol.2, 38 Nov 1997 [15] Popotional Diffeentiated Sevices: Delay Diffeentiation and Packet Scheduling. With Dimitios Stiliadis and Pamesh Ramanathan. In Poceedings of the 1999 ACM SIGCOMM confeence, Cambidge MA, Septembe 1999. [16] Patho P. Misha and Hemant Kanakia. 1992. A hop by hop ate-based congestion contol scheme. In Confeence poceedings on Communications achitectues and potocols (SIGCOMM 92), David Oan (Ed.). ACM, New Yok, NY, USA, 112-123 [17] CCNx poject www.ccnx.og