On the Energy Efficiency of Content Delivery Architectures

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1 On the Energy Efficiency of Delivery Architectures Kyle Guan, Gary Atkinson, an Daniel C. Kilper Bell Las, Acatel-Lucent, 79 Holmel Roa, Holmel, NJ Ece Gulsen MIT, 77 Mass. Ave., Camrige, MA 039 Astract We examine the energy consumption of content elivery architectures, with a focus on the enefit of content centric networking (CCN an ynamic optical ypass. For each case, we uil energy moels ase on the energy consumption of current network equipment an evices. We further analyze the energy traeoff among key networking resources. By optimizing the placement of content accoring to its popularity, CCNs achieve goo scalaility in energy consumption, i.e., the per-it energy ecreases as the ownloa rate increases. The relative energy enefit from CCNs epens on numerous factors such as content popularity, equipment energy efficiency, an network topology. As such, we provie initial assessments of the operational regimes in which CCNs are avantageous. The comparison etween CCN an ynamic optical ypass suggests that CCN is more energy efficient in elivering popular content while ynamic optical ypass is more energy efficient in serving less popular content. Inex Terms content istriution network (CDN, content centric networking (CCN, optical ypass, energy efficiency I. INTRODUCTION istriution accounts for a significant portion of toay s internet usage as a result of the increasing popularity of sharing user generate ata (e.g., YouTue an elivering multi-meia content (e.g., Netflix []. The content an service proviers are rapily expaning ata centers as user eman grows. Concerns over the energy requirements for these ata centers an associate network equipment have rawn attention recently []. In the coming ecae, the improvement in networking energy efficiency is anticipate to increasingly lag traffic growth [3] [4]. As such, the energy consumption is preicte to increase sustantially unless the efficiency of the network, oth in terms of equipment an the associate architectures, improves proportionately. Motivate y uiling greener networks, in this paper we evaluate an compare the potential energy saving of ifferent approaches to content istriution an issemination. Legacy content istriution network (CDN architectures are host-oriente: content is elivere to en users through host servers that are centrally manage in a few ata centers. With the growing eman of large multimeia content, the energy consumption of a host-oriente architecture ecomes prolematic ue to factors such as over-provisioning (to satisfy the peak traffic an heat issipation requirements []. Moreover, as all content is store in a few fixe locations inepenent of the relative popularity, elivering especially popular content from a centralize location to the en users Storage Data Center server Ege Networks (a Storage Data Center server Ege/ Access Networks Ege Ege server Least popular Networks (c Most popular Networks ( Ege/ Access Networks Optical Bypass Ege/ Access Networks Fig.. elivery architectures: (a conventional an ecentralize server-ase CDN, ( CCN, an (c centralize server-ase CDN using ynamic optical ypass. increases anwith-mileage an often incurs unnecessary yet significant transport energy cost [5]. Decentralize CDNs [] [5], originally conceive to improve throughput an elay performance, ease the transport energy consumption. To reuce transit traffic an consequently the associate energy consumption, numerous micro or nano ata centers are eploye at multiple locations of core networks (Fig. (a. As such, a ecentralize CDN pushes the content closer to the network ege an en users. Recently content centric networking (CCN [] was propose to increase content elivery efficiency y using name ase routing, which enales popular content to e tracke an store at intermeiate noes. From the energy perspective, CCNs rely on content routers, which are roughly an orer of magnitue more energy efficient than content servers use in a conventional CDN []. In aition, CCNs further save energy through proportional computing an networking. As content caching is etermine y the frequency of which content is requeste, the more popular content is store close to the en users (as shown in Fig. (. Therefore, transport energy can e greatly reuce. Optical ypass is a physical layer approach in managing transport energy [5] [6]. Static optical ypass is commonly use in reconfigurale optical a-rop multiplexer (ROADM ase networks to transparently patch signals through a noe. With ynamic optical ypass, a connection is provisione on request to eliver content on eman across the network mostly via transparent optical connections, thus circumventing intermeiate core routers, as shown in Fig. (c. The ynamic capaility is necessary ecause eicate transparent path //$ IEEE

2 woul e impractical to eploy toay. At the same time, ynamic optical ypass faces the technical challenges in setting up an en-to-en wavelength route rapily on eman over long-haul istances. Since optical transmission harware is an orer of magnitue more energy efficient than core routers, using ynamic optical ypass can yiel a significant energy savings especially for elivering content over a large numer of network hops. Our ojective in this work is to aress the very question of how to achieve energy efficiency y traing off the consumption of various networking resources. In particular, we evaluate the energy cost of a CCN an optical ypass approach use in CDN architectures. For these techniques, we set up transaction-ase energy consumption moels [6], which take into consieration of important factors such as network topology, content popularity, equipment capacity, an power consumption. As energy consumption of conventional CDNs an optical ypass has een stuie efore [5][6], here we focus on evaluating the potential energy saving of CCNs, consiering oth conventional CDNs an ynamic optical ypass-ase networks. In particular, we examine how key networking, content, an equipment parameters impact the traeoff etween the transport an caching energy. Our results inicate that, y strategically placing popular content close to the network ege, CCNs are scalale in energy consumption, i.e, the per-it energy ecreases as the rate of requests (ownloas for the content increases. In other wors, CCNs are extremely efficient in elivering highly popular contents. However, in comparison to CCNs, ynamic optical ypass is more energy efficient in elivering infrequently accesse content, ue to the reuction (via ypass of power consuming routers. The comparison etween CCNs an conventional server-ase CDNs inicates that their relative energy performances epens on the content catalog size as well as the popularity istriution. Our initial results suggest that CCNs consume less energy in elivering a small size catalog; while conventional server ase CDNs consumes less energy in elivering a large size catalog. In this work, we also explicitly moel an evaluate the impact of the unerlying logical/physical topology on the energy consumption. The topological aspect has een mostly overlooke in previous work []-[6]. Specifically, we set up a power law moel that relates the numer of replicas (caching/storage energy to the average hop istance (transport energy. The en result provies insights into the topological structure that can lea to improve energy efficiency of content elivery. The rest of the paper is organize as follows. In Section II, we provie the network an content istriution moels. In Section III, we set up energy moels for ifferent content elivery architectures. Optimization formulations an analyses that evaluate energy efficiency of ifferent architectures are presente in Section IV. In Section V, we present the results of case stuies an iscuss their implications. (a Fig.. The placement of copies on a 5 5 gri topology. (a The optimal placement of copy; ( the optimal placement of 4 copies Fig. 3. Deploye networks: (a the prototype IP ackone network, with N =4an Δ =3.6; ( the European optical network (EON, with N = 9 an Δ =3.9. The mean noe egree of the network, Δ, isgiveny Δ =L/N. II. NETWORK AND CONTENT DISTRIBUTION MODELS In this section, we escrie the network an traffic moels to provie the necessary ackgroun an notation for the moeling an analyses in Sections III an IV, respectively. A. Network Moel We focus on core networks, which in this paper are assume to consist of oth long-haul an metropolitan networks. We follow the convention of representing the core network as a graph G(N,L, with N an L enoting the numer of noes (representing core routers or s an the numer of iirectional eges (representing links, respectively. In the context of CCN, a total of n replicas of the same content are cache in n content routers. That is, N n noes in the core network have to traverse through one or more hops to access a copy. As such, the average hop istance to a replica, H r, is an important measure of the placement efficiency. More importantly, H r rives the traeoff etween the caching an the transport energy, as will e seen in Sections III an IV. The exact form of H r epens on oth the network topology an the replica placement algorithm. In this paper, we stuy H r for oth symmetric an eploye networks. Among topologies with symmetric structures, we consier oth ring an gri topologies. For a ring topology of N noes, the optimal placement is achieve y maximizing the hop istance among the replicas. Base on this, an analytical expression ( of H r can e erive an approximate as H r (n N 4 n. For an M M gri topology, Hr can e 9 We use interchangealy with ROADM. We use the terms replica, copy, an cache content interchangealy herein. (

3 estimate as follows. When n =, the optimal placement of the copy is at the center of the gri, as shown in Fig. (a. An expression for H r ( can e erive an approximate as H r ( N.Forn>, them M gri is ivie into n su-gris with (almost equal size. It can e shown 3 that the optimal placement is to put each of the n copies at the center of each su-gri, as shown in Fig. (. H r for n> can ( thus e estimate as H r (n N n. As representations of the topological characteristics of eploye networks, we use a prototype IP ackone network an the European optical network (EON [7], as shown in Fig. 3 (a an (, respectively. For these two networks, we take a semi-analytical approach in eriving H r as a power law function of n. We first numerically compute the average hop istance to a replica 4. We next fit the compute ata to the function H r (n A ( N α, n with α>0. For the prototypical IP ackone network, H r can e estimate as 0.35(N/n 0.57 ; while for EON, H r has the form of 0.3(N/n Note that a smaller α inicates a etter efficiency in caching placement: fewer copies are require to achieve a given H r. B. Popularity Distriution Moel We assume that a content provier has a content catalog of size F, ranke from to F ase on popularity ( represents the most popular. Letting the total numer of requests in a given time uration t e R, the numer of requests for the content of popularity k, R k, follows a Zipf istriution as k β R k = R = R F k β. ( k= k β a 0 A large β inicates a relatively small set of very popular content. Typical values of β range etween 0.5 an.0 (e.g., for IPTV channels, β [8]. III. ENERGY CONSUMPTION MODELS In preparation for the analysis an optimization in Section IV, we set up energy consumption moels for a CCN, a conventional CDN, an a centralize CDN using ynamic optical ypass. We use a transaction ase moel in which the total energy is calculate y aing up the consumption incurre y all the equipment use to eliver a given service on a mean transaction asis [5]. For clarity of iscussion, we summarize the notation of the key parameters in Tale I. A. Energy Moel for a CCN For a CCN, we consier an iealize case in which content routers carry out the tasks of the content servers []. As content servers are infrequently accesse, their energy consumption is not consiere. As such, the total consume energy Etot CCN consists of two parts: the transport energy E tr an the caching energy E ca. The transport energy, in turn, inclues the energy consumption in the core, ege, an access networks, enote as Etr, c Etr, e an Etr, a respectively. We assume that in a 3 The proof is omitte in the paper ue to the limitation of the space. 4 A genetic algorithm approach is use to fin optimal or near-optimal placement of replicas. Due to space limitation, the etail is omitte here. TABLE I NOTATIONS AND VALUES OF THE KEY PARAMETERS Symols Notations Values N No. of noes Multiple values t Time uration 3600 secons R k No. of requests of the Multiple values kth-most popular content B k Size of the kth-most popular content Multiple values p r Power ensity of a core router. 0 8 J/it p wm Power ensity of a link J/it p oxc Power ensity of an J/it p ca Power of caching in router uffer 0 9 W/it p e Power ensity of an Ethernet switch J/it p g Power ensity of a gateway router J/it p pe Power ensity of a provier ege router J/it p st Power of storage (har isk W/it p s Power ensity of a server J/it n No. of caching replicas Multiple values H r Average numer of hops to a replica Multiple values uration t, the kth-most popular content (of size B k is ownloae R k times. Similar to the moels use in [5], E c tr an E e tr are expresse as an Etr(H c r =4B k R k [(p r + p oxc (H r ++p wm H r ] ( Etr e =4B k R k [3p e + p g +ppe ], (3 respectively. Note that a factor of four is use to account for reunancy an overhea [5]. Similar to the moeling in [5], we assume that the access networks are passive optical networks (PON whose energy consumption is inepenent of traffic loa an therefore only as an ientical constant to each case. As such, Etr a is not inclue in the analysis. If n copies of a particular content are cache in router uffers [], the energy consume y caching nb k its is given y E ca (n =B k tp ca n =(Btp ca A /α N/H α r, (4 since the network topologies use in our analysis all follow the power law scaling as H r (n =A(N/n α. Comining oth the transport an caching energy, we have E CCN tot = E c tr(h r +E e tr + E ca (H r. (5 B. Energy Moel for a Conventional CDN In a conventional CDN architecture, the total energy consumption Etot CDN consists of that consume y ata storage E st, transport E tr, an servers E sr. We assume that there are n micro or nano ata centers. Each content, inepenent of its relative popularity, is replicate n times in n storage evices. For a time of uration t, the storage energy is given y E st (n =B k tp st n, (6 where p st enotes the power of storage evices. The moeling of transport energy is similar to that for CCN. Since H r (n =A( N n α, the transport energy can e expresse

4 as E tr = 4B k R k [(p r + p oxc (A( N n α ++p wm A( N n α ] + 4B k R k (3p e + p g +ppe. (7 In aition, the server energy E sr nees to e consiere: E sr = B k R k p s. (8 By comining the transport, storage, an server energy, we have E CDN tot = E c tr + E e tr + E st + E sr. (9 C. Energy Moel for a Centralize CDN Using Dynamic Optical Bypass In ynamic optical ypass, the content is elivere y a server that is attache to a core router an transporte across the core network mostly via transparent optical connections. We assume that on average a noe is Hr s hops away from the server. The total energy Etot, p which consists of the transport, server, an storage energy, can e expresse as: E p tot = Etr(H c r s +Etr e + E sr + E st = 4B k R k [(p oxc (Hr s ++p wm Hr s +p r ] + Etr e + B k R k p s + B k tp st. (0 In the aove equation, H s r can e estimate as H s r = H r ( = AN α. Note that the implementation of ynamic optical ypass requires overhea of oth signaling an physical reconfiguration of the network elements. This overhea increases the wavelength switching time an thus reuces the utilization of wavelength capacity. This, in turn, will increase the effective energy consumption per ownloa. For simplicity, we o not inclue an uner-utilization factor in our moel y assuming that the wavelength is fully utilize. IV. PROBLEM FORMULATIONS AND SOLUTIONS In this section, we first fin the minimal energy consumption of content elivery using a CCN via the optimization of content placement. Next we analyze how the energy efficiency of a CCN, a conventional CDN, an a centralize CDN with optical ypass are affecte y network topology, content popularity, an equipment energy efficiency. A. Energy Optimization for CCN For a CCN, a close examination of equations ( an (4 shows that H r generally rives the transport energy in an increasing irection an the caching energy in a ecreasing irection. This is epicte in Fig. 4. To fin the optimal traeoff etween transport an caching energy, we formulate the following optimization prolem: minimize : H r Etot CCN (H r suject to 0 H r H max. ( Energy per it, E it (J/it.4 x , Transport, Caching, Total Avg. Hop Distance to a Replica, H r Fig. 4. The traeoff etween caching an transport energy for CCN. A ring topology with 64 noes (N =64isuse. Here H max enotes the maximal hop istance. Oserve that Etot CCN is a convex function of H r. As such, optimal solutions exist. The optimal values Hr an n can e solve as 5 [ ] Hr A α α+ α Ntp ca = 4R k (p r + poxc + p wm ( an n = [ 4ARk (p r + poxc tp ca + p wm ] α+ N α α+. (3 The expressions for Hr an n show how the relative power consumption of transport an caching affects the placement of content. As the ratio (p r + poxc + p wm /p ca increases, more copies of the content are cache across the network. This results in a ecreasing hop istance to access a copy. The expressions also show that the more popular content (with large R k is replicate more often an is therefore closer to the en user (smaller Hr. We also erive the expression of Hr in terms of the popularity inex k. By sustituting equation ( into (, we have [ ] Hr A α α a 0 Ntp cach k β α+ = 4R(p r + poxc + p wm. (4 That is, Hr scales with k in the form of Hr k αβ α+. Therefore the popular (low k content is place close to the en users. The optimal energy consumption is foun to e: Etot = E CCN tot + c 0 B k Rk (H r =E e tr +4B k R k p r +α (tp can α+ α (p r + poxc + p wm α+ (5, where c 0 = ( α+3 A α+. The energy per it E CCN can e otaine y iviing Etot CCN y the total numer of its ownloae R k B K. Thus, the per-it energy consumption for accessing content k is given y E = E tot =4[p r R k B +3pe + pg +ppe ] K + c 0 R +α α k (tp can α+ α [(p r + poxc + p wm ] 5 We only consier the cases for which H r <H max. α+. (6

5 We note that as R k, lim R k B ECCN =4[p r +3p e + p g +ppe ]. (7 K This can e explaine as follows. When the request rate is low for a particular content, only a few copies are cache across the core network. Thus, the energy consumption is ominate y transport energy. When a particular content is accesse more frequently, more copies are cache. As a result, the transport energy is reuce. As R k increases aove a certain value, copies are cache on every noe of the network (n = N, i.e, caching energy is maximize. In this case, the transport energy is reuce to the minimum, i.e., only the core router that connects to the ege networks contriutes to the transport energy consumption. Hence, though the caching energy is maximize, it is amortize y the ever increasing R k. B. Per-Bit Energy Benefit of a CDN with Dynamic Optical Bypass The per-it energy consumption of a centralize CDN using ynamic optical ypass E p can e expresse as E p = E p tot =4[(p oxc (Hr s ++p wm Hr s ] B k R k + 4[p r +3p e + p g +ppe ]+ps. (8 Note that E p is inepenent of R k. By comparison, the optimal per-it energy for a CCN is a ecreasing function of R k. By comparing the expression of lim Rk B K E (equation (7 with that of E p, we oserve that lim R k B ECCN <E p. (9 K That is, at sufficiently high access rates, CCN is more energy efficient than a centralize CDN using ynamic optical ypass. At a low access rates, the use of ynamic optical ypass is more energy efficient than CCN. The request rate at which CCN an optical ypass consume the same amount of energy, enote as Rk, can e otaine y numerically solving E (R k =E p. (0 C. Average Per Bit-Energy Performance of a CCN an CDN For F availale content items, we assume that the relative request frequency of the kth-most popular content is f(k. The numer of requests R k is Rf(k. The average per-it energy (over F ifferent content items for a CCN (enote as E CCN is F E CCN = E CCN (R k f(k. ( k= The energy per it for a CDN, E CDN, can e otaine y iviing E tot (equation (9 with B k R k : E CDN = ECDN tot B k R k + ntpst R k =4[(p r + poxc (A( N n α ++p wm A( N n α ] +3p e + pg +ppe + ps. ( The average per it energy (over F ifferent content items for CDN (enote as E CDN is F E CDN = E CDN (R k f(k. (3 k= In general, it is ifficult to carry out an analytical comparison of the average per-it energy of a CCN an a conventional CDN. As such, we mostly resort to a numerical approach, as illustrate in Section V. V. RESULTS AND DISCUSSIONS In this section, we evaluate the energy traeoff of ifferent content istriution architectures using various case stuies. We use the same values of the key parameters as those in [] [6], as shown in Tale I. To unerstan the placement strategy for content with ifferent popularity, we consier the case of elivering a catalog of size 00 (F = 00. The popularity of the content follows a Zipf istriution (equation ( with β =0.6. InFig. 5we plot the optimal hop istance to a copy H r as a function of popularity inex k for four ifferently topologies: a 64-noe ring, a 8 8 gri, the representative IP ackone, an EON. As shown in the plot, the more popular content is cache closer to the en users (smaller value of Hr. We oserve that the placements for topologies with higher average noe egree (gri, IP ackone, an EON show a clear cut off at a certain popularity inex. Only the top 5 0% most popular content is cache close to the en users; the rest of the content is place in the center of the topology. We next compare the energy efficiency of a CCN an a centralize CDN with ynamic optical ypass. In Fig. 6, we plot the optimal energy per it as a function of the request rate for oth a CCN an the ynamic optical ypass case. The same four ifferent topologies as efore are use for the comparison. The plot shows that ynamic optical ypass is more energy efficient in elivering infrequently accesse content, while a CCN is more energy efficient in elivering frequently accesse content. With a low R k, the energy for a CCN is ominate y transport energy. Optical ypass saves energy y avoiing the use of intermeiate routers, which accounts for the majority of the transport energy consumption. The enefit of optical ypass iminishes as the content is accesse more frequently ue to the high power consumption of the content server. In comparison, placing the popular content across the network for a CCN not only reuces the transport energy, ut also allows for efficient utilization of the caching energy. We note that the request rate at which a CCN an optical ypass consume the same amount of energy, Rk, is affecte y the topology. The plot shows a tren that Rk ecreases with the increasing average network connectivity. We also compare the energy efficiency of a CCN with that of a conventional CDN. In particular, we evaluate the influence of content popularity an catalog size on the energy consumption. In Fig. 7 we plot the ratio etween the per-it energy of a CCN an a conventional CDN as a function of

6 Fig. 5. Avg Hop Dist. to a Replica, H r X8 Gri, N=64 IP Backone, N=4 EON, N= Popularity Inex, k Hr for the kth-most popular content for ifferent network topologies. The Per Bit Energy Ratio Between CCN an CDN X8 Gri, N=64 IP Backone, N=4 EON, N= β in Zipf like Distriution F=50 The Per Bit Energy Ratio Between CCN an CDN X8 Gri, N=64 IP Backone, N=4 EON, N=9 CCN β in Zipf like Distriution, F=500 The Per Bit Energy Ratio Between CCN an CDN X8 Gri, N=64 IP Backone, N=4 EON, N= β in Zipf like Distriution F=000 Fig. 7. The ratio of optimal energy per it (J/it as a function of β an F, etween CCN an conventional CDN. Optimal Energy per it, E it (J/it.4 x , CCN, Bypass 8X8 Gri, N=64, CCN 8X8 Gri, N=64, Bypass IP Backone, N=4, CCN IP Backone, N=4, Bypass EON, N=9, CCN EON, N=9, Bypass No. of Requests, R k Fig. 6. Comparison of optimal energy per it (J/it as a function of R k, etween CCN an optical ypass. oth the content catalog size (the value of F an the content popularity istriution (the value of β in Zipf istriution. The total numer of requests R is set at 0,000. An immeiate oservation from the plot shows that with the same R, a CCN is more energy efficient serving a small size catalog while a conventional CDN is more efficient if serving a large size catalog. We also note that the ratio etween the per-it energy of CCN an conventional CDN ecreases with the increasing value of β, aleit the ifference etween low an high β values is insignificant except for the ring topology with F = 500 an F = 000. The impact of topology, manifeste through oth N an α, is evient. CCNs implemente on topologies with smaller N an higher α (e.g., IP ackone an EON have etter energy efficiency for all the values of F an β use in the evaluation. As our main focus in this work is to illustrate the tren an scaling of energy efficiency of ifferent content elivery approaches, we have ase the moels an analyses on iealize scenarios an have employe simplifying assumptions. Some practical issues, such as wavelength switching time for ynamic optical ypass, are not inclue in the moeling. We also note that except for the ring topology, the network topologies use in this work have relatively small average hop istance etween noes (3-6 hops. In comparison, ata flows in toay s Internet may go through 5 or more router hops [3][5]. As such, we expect that the energy enefit of CCNs on eploye networks will e more pronounce. To generate more accurate results, we plan to aress these issues in our future work y proviing more refine an realistic energy consumption moels. VI. CONCLUSIONS We have analyze the energy consumption of several content elivery approaches a CCN, a conventional server ase CDN, an a centralize server ase CDN with ynamic optical ypass. Given the energy consumption level of current network equipment an evices, our results show that CCNs are more energy efficient in elivering popular content; while the approach with optical ypass is more energy efficient in elivering infrequently accesse content. The relative energy enefit of CCNs an conventional CDNs is more complicate, since the energy performance also epens on factors such as content popularity an catalog size. Our results suggest that a hyri architecture a synergy of CCN, server-ase CDN, an ynamic optical ypass architectures may further improve the energy efficiency especially in serving content with heterogeneous popularity. REFERENCES [] U. Lee, I. Rimac, an V. Hilt, Greening the Internet with Centric Networking, ACM First International Conference on Energyefficient Computing an Networking (e-energy 0, Passau, Germany, Apr. 3-5, 00. [] V. Valancius, et al., Greening the Internet with Nano Data Centers, CoNext 009, Rome, Italy, Dec [3] D. Kilper, G. Atkinson, S. K. Korotky, S. Goyal, P. Vetter, D.Suvakovic, an O. Blume, Power Trens in Communication Networks, accepte for pulication in IEEE Journal on Selecte Topics in Quantum Electronics 0 Green Communication Issue. [4] O. Tamm, C. Hermsmeyer, an A. M. Rush, Eco-sustainale System an Network Architectures for Future Transport Networks, Bell Las Technical Journal, vol. 4, pp. 3-37, 00. [5] J. Baliga, R. Ayre, K. Hinton, an R. Tucker, Architectures for Energy- Efficient IPTV Networks, Optical Fier Communication Conference (OFC, San Diego, CA, Mar [6] J. Baliga, R. Ayre, K. Hinton, W. V. Sorin, an R. S. Tucker, Energy Consumption in Optical IP Networks, Journal of Lightwave Technology, vol. 7, pp , 009. [7] Network Topology Lists, last accesse Sept. 00. [8] M. Cha et al., Watching Television over an IP network, Proc. ACM Internet Measurement Conference, Vouliagmeni, Greece, Oct. 008.