Cloud Storage for Small Cell Networks

Transcription

1 Cloud Storage for Small Cell Network Ejder Baştuğ, Jean-Loui Guénégo, and Mérouane Debbah Alatel-Luent Chair - SUPÉLEC, Gif-ur-Yvette, Frane {ejder.batug, jean-loui.guenego, merouane.debbah}@upele.fr Abtrat The Maive dene deployment of Small Cell Network (SCN) i a promiing way of inreaing apaity. Interetingly, by having uh a huge amount of uer devie a well a mall ell deployed in indoor or outdoor area, one an take benefit of uh ditributed network for torage purpoe. Hene, Depending on the deployed enario, thee torage unit an alo be ued for ontent ahing to relieve the bakhaul ontraint and inreae the peak rate. In thi work, by extending onept of loud torage to SCN, we diu the theoretial hallenge in order to embed mall ell with torage apabilitie. We alo briefly introdue Open Cloud Protool (OCP) a a unified oftware torage framework. Index Term loud torage, private loud, ontent ahing, ditributed torage, Small Cell network, open loud protool. I. Introdution In the year of oial network, high demand of rih ontent treaming by the uer and/or mahine i puhing the apaity of the legay mobile wirele network up to the limit [1]. Beide advane in legay maro ell network (MCN), maively dene deployment of mall ell network (SCN) ha a partiular interet to overome thi iue [2]. Moreover, the market foreat expet almot fully SCN enario in the near future [3]. Although their attrativene, everal hallenge till exit. For intane, a the ell denity inreae, thee low-ot, energy-effiient, elf-onfigurable SCN beome more dependent to bakhaul ommuniation, due to their lower proeing ability ompared to MCN. Auming limited bakhaul apaity, even uing fiber-opti able, onneting all mall ell to the network i expenive. Therefore, by propoing SCN a a olution, one hould alo take into aount the apaity of the bakhaul. One novel approah for thi i to put high torage unit to mall ell and uing heap low-rate bakhaul, rather than highrate expenive alternative [4]. In thi work, we extend the idea of [4] by introduing onept of loud torage on SCN, and diu poible enario. We then give theoretial hallenge from the point of information theory, in the ontext of ditributed torage. We preent Open Cloud Protool (OCP) a a unified oftware framework, and we finally onlude. II. Senario Aording to National Intitute of Standard and Tehnology (NIST) definition of loud omputing [5], we an build up many enario depending on the deployment trategy (ee Fig. 1). A. Private loud It i a type of loud where a ingle organization erve multiple utomer in the network. In our ae, thi i typially a network operator that ue reoure of uer devie (i.e. mobile phone, laptop), mall ell, data enter or any ombination of them a a ditributed torage node. The operator an ue thi ditributed torage for ontent treaming or peritent torage purpoe. The work [4], [6] an be aumed a a private loud, where fixed number of mall ell are ued for the ontent treaming. B. Community loud Thi i the enario where peifi type of onumer in the ommunity make a loud for their miion. For intane, any uer in the mobile network an oially hare it mobile torage with other uer in order to join thi loud. C. Publi loud The loud i open to ue and it might be owned, managed, and operated by a buine, aademi or government organization or ombination of them. The loal information of a ity with augmented reality an be tored in the mall ell or in other type of node, and the publi uer an take benefit of thi ervie. D. Hybrid loud Any ombination of the loud above an alo be a loud. In ome ene, loud of loud might be alled a hybrid loud. III. Challenge By uing the notion of information theory, we an deribe poible hallenge into four ategorie: 1) ode deign, 2) erey, 3) ditributed torage alloation, and 4) proative heduling. Hereafter, we deribe them tep by tep. Note that the metri in the deign an hange depending on the mall ell and bakhaul deployment trategie. For example, we might have different metri with different variability for mall ell deployed in indoor, outdoor, hot-pot or rural area.

2 b) Community a) Private ) Publi d) Hybrid Figure 1: Poible enario on SCN. A. Code deign When we want to tore the information to a ditributed medium, ome of the node may be in fail and/or they may not be available. In order to be able to overome thee failure event, and be able to obtain thi ditributed information later on in a reliable way, we might need to introdue ome redundany. The mot redundant but reliable ae would be to tore that information between all the node, but in thi ae, the amount of the traffi overhead a well a torage effiieny might be non-deirable. Taking into aount thee ontraint, we need to deign the ode to ditribute the information among the network, and we need to be able to repair and/or deode it under the given performane. For the tate of art, maximum ditane eparable (MDS) ode offer uh a reliability by enoding k paket of the information into the n paket, where n > k. Then, we an uffiiently reover the original data. In the ontext of the ditributed torage, n enoded paket an be tored in n node ditributed in the network. After that, when a node fail, urrent node or inoming node an tart a repair proe in order to keep the ontant reliability. The repair proe i ategorized a funtional repair, exat repair and exat repair for the ytemati part [7]. The funtional repair ha been tudied theoretially in [8], but it ha ome pratial impliation due to the ontinuou update of the repairing and deoding funtion. Indeed, uh an operation may not be deirable, ine an eavedropper an detet the funtionality that dereae the onfidentiality of the private data. On the other hand, the exat repair problem i muh harder and yet open in general. Signifiant amount of work ha done in [8] and [7] aording to the different performane metri. The mot important metri are repair bandwidth and torage effiieny. For the olution thee extreme ae, exat minimum torage regenerating (MSR) ode [9] and exat minimum torage regenerating (MBR) ode [10], [11] have been propoed. B. Serey In the ditributed enario, an eavedropper an atively read the data tored in a ubet of torage node, or it may paively ae the information generated during enoding, repairing and deoding proee. For uh ae, the ditributed torage ytem hould be able to atify deired erey rate to protet the information. Previouly, [12], [13] have tudied a paive eavedropper ae, where it read the data tored in a ubet of l < k torage node, and it get the information from l < l node during the funtional repair proe. The work [12] haraterized the upper bound on the number of meage ymbol that we an tore eretly, and howed that the MSR ode an ahieve the erey under an appropriate etting. On the other hand, [13] extended the idea and gave an expliit ontrution way for both MSR and MBR ode. The reult of thee work are built on undeired funtional repair. Although, they are the firt tep toward the haraterization of the erey apaity in the ditributed torage. In ompliated enario, like onidering an open ditributed torage ytem where the information of intended node mut be kept eret to other, exiting ode annot be applied. Any information leakage from the intended node may reult with detetion of the determiniti enoding funtion from other node. Hene, one may ugget a eret key ommuniation on top of the regenerating ode. C. Ditributed torage alloation Conider a network where the node are not fully onneted to eah other, and the link between the node are apaity-limited. One a node requet it ditributed data

3 Crypt Split Send Figure 2: Storing and retrieving data in OCP. from another node in the network, there might be a ingle or everal link from the oure to the detination. In uh a ae, the bet option may not be the diret link -or the hortet path- due to the apaity ontraint and the random failure probability, where ubet of indiret path with ome ahing node may ahieve optimal information flow. Therefore, the ditributed torage alloation problem arie on how to pik the bet path and how to alloate the information on the temporary node during the flow. In [4], [6], the problem ha been tudied auming that a entral maro bae tation i ending information to it onneted uer, where a fixed amount of mall-ell are in harge of ahing the information to help the maro bae tation. The information ahed inide the high torage apaity mall ell i made of file with a given popularity ditribution, and the link from the uer to eah mall ell ha a finite tranmiion rate. Under thi etting, the optimal alloation to minimize the delay with repet to uer and file ha been found both for the oded and unoded file. On the other hand, for the apture of the burty and random behavior of the mall ell availability, the work [14], [15] have modeled the link between the uer and mall ell a an eraure hannel, i.e. the link i either withed on or withed off with ome probability, and the tati i known to the alloation ontroller. More peifially, [14] uppoe that only a random et of the mall ell are aeible, while [15] model eah link a the Bernoulli proe with a given eraure probability. D. Proative heduling We have deribed above the ditributed torage alloation problem for a given time intane auming that the loation of the node i fixed. However, in pratie, ome node may have mobility and make requet dynamially in different loation aro time intane. If mobility and requet pattern an be learned by the ytem [16] in a relatively long time ale (eaon, week, day, hour) and/or in a peifi event, then, we an deign our ahing and tranmiion mehanim more effiiently. Suh a ahing and heduling would offer a great flexibility in the network. A reent framework [17], [18] ignifiantly redue the outage apaity by prediting node requet and antiipating the data tranmiion prior to the atual requet ompared to a non-proative ae. Neverthele, the model i a implified queue ytem with aggregate apaity and doe not onider the torage problem. IV. Open Cloud Protool In thi etion, we introdue OCP a a unified oftware framework to eurely and reliably tore data in the network [19]. More preiely, eah OCP intalled devie in the network i alled a an OCP agent. The idea i to enable any eletroni devie with a memory and broadband internet ae to be a node of a ditributed ytem. Deired uer experiene ha to be ahieved through the following benefit: low ot torage, periteny, eurity, and performane of toring and retrieving data. OCP i deigned to allow an online torage market with many ator: onumer, provider and trader, it inlude billing funtionality. On the other hand, it target to have a flexible working arhiteture tarting from phyial layer to the top, inluding ability of working for different deployment enario a deribed above. A rough viualization of toring and retrieving data in OCP i hown in Fig. 2. A. Addre topology Every torage ytem ha the onept of addre, that allow it to know where an et an be tored inide it ontainer. Any ditributed torage ytem ha an addre topology, whih i a triplet(f, U, R) with F repreenting the addre format, U the et of all poible addree, alled the addre univere, and R being the repartition rule that peify for eah addre whih node i reponible for it and when. Any ditributed hah table (DHT) ha an addre topology. For intane CHORD [20], Kademlia [21] and Tapetry [22] have a ingle ring addre topology. The DHT ontent addreable network (CAN) ha a multidimenional box addre topology [23]. The partiularity of OCP i to have a multi-ring addre topology. B. Multiple Ring addre topology The multi-ring addre topology i a triplet(f, U, R) with F defined a a one field addre, U a a finite et,

4 n8 n7 n1 n2 n6 n10 n5 n3 n9 a a a Figure 3: Multiple Ring addre topology. and R a follow. Let u onider N ring, eah ring being a U repreentation a a ounter-lokwie direted ring. To eah node, i aigned a ring r and an element e of the ring whih ha an addre format. The ouple(r, e) i alled node id. Thi give to eah node a poition on one ring. A node B i ueor of a node A if and only if they are on the ame ring, and there i no node between them on thi ring, and node B i after A in the peified ring diretion. A node i reponible for all et with an addre between it and it ueor. The et of addree under the reponibility of a node i alled node reponibility area. Thi kind of topology allow to eaily manage redundany, and the ation to perform on node diappearing event. An example of thi topology i hown in Fig. 3. In the figure, we an ee a three ring addre topology with 10 node. The blak quare repreent an et loated at the addre a. Aording to the repartition rule R, a i under the reponibility of node n6, n5 and n9. The reponibility area of thee node are indiated with the arrow on the figure. C. Immutable et Client Cahe Storage Figure 4: Cahe on the road. n4 Owner agent OCP partiularity i to extenively ue immutable et and direted ayli graph (DAG) like GIT verioning ytem. An immutable et i an et that annot be modified. Thi i done by linking it ontent to it addre with a relation uh a addre = hah(ontent). An immutable et annot be updated while keeping it addre. So it beome diffiult for a node to modify an et. Another advantage of uing immutable et i that they an be ahed on any node. Thi allow a mehanim that we all a ahing on the road: when retrieving an et, the et an be ahed on all devie between the lient and the reponible node (ee Fig. 4). When a node reeive an et, it tore in it ahe if it i not reponible of it, ele it tore in it peritent torage area. Cahe poliie remove the et from the ahe when needed. Moreover, if the uer lient ha mobility, the ahing on the road mehanim will have an effet to keep data geographially loe to the lient. D. Mutable et OCP, however, ue mutable et for onnetion et. A onnetion et i an et tored at a peifi addre that an be retrieved by a uer without peifi information. For intane, OCP ue publi uer et. For a given uer with a login, the publi uer et i loated at addre = hah(login). OCP ue a well private uer et. For a given uer with a login and a paword, the private uer et i loated at addre = hah(f(login, paword)). The private uer et i a paword rypted et ontaining a pointer to the root of the uer ontainer, repreented and tored under a DAG. OCP mutable et annot be ahed. E. Uer et In OCP, all et belong to a peified uer. Thi allow the agent to publih billing report. All immutable et are enrypted with a uer eret key loated in the private uer et. When a uer tore a file, the file i plitted in many relatively mall blok that will be pread around the agent. F. Storing data To tore data on an OCP network, the uer tart an OCP agent ating a a lient. It reate an aount or ue it exiting one. The uer an login with an authentiation hallenge. The login tep onit to determine the addre of it publi and private uer et. Storing a data (file, tream, et.) onit of enrypting the data then plitting the enrypted data into blok and adding redundany through an eraure ode, and finally ending the blok on the OCP multiple ring addre topology DHT a immutable et organized in DAG (ee Fig. 2). Cahing on the road mehanim i ued. G. Retrieving data To retrieve data, the onneted uer retrieve all the addree of immutable et via the DAG root addre tored in the private uer et. Data i rebuilt from different blok uing eraure ode, and then derypted in order to be manipulated by the uer. H. Cahe and peritent torage OCP agent ha two kind of ontainer: one for toring data the agent i reponible for and another one for ahed immutable et. A a onequene, an OCP network an be ompoed of ahe oriented agent and peritent torage data agent. Thi help to have a torage network with independent peritene and performane apet.

5 V. Conluion By inreaing the apaity of wirele network with SCN, we have hown that we an take benefit of uh a huge network for ditributed torage. We have alled thi onept a loud torage on SCN. Giving thee poible enario and exiting tehnial hallenge, we believe that there will be extenive reearh and engineering work in thi diretion, in the near future. VI. Aknowledgment Thi reearh ha been upported by the ERC Starting Grant MORE (Advaned Mathematial Tool for Complex Network Engineering), and Alatel-Luent, within the Alatel-Luent Chair in Flexible Radio, Supéle. Referene [1] Cio, Cio viual networking index: Global mobile data traffi foreat update, , White Paper, [Online] [2] J. Hoydi, M. Kobayahi, and M. Debbah, Green mall-ell network, IEEE Vehiular Tehnology Magazine, vol. 6(1), pp , [3] Small Cell Forum, Small ell to make up almot 90% of all bae tation by 2016, [Online] [4] N. Golrezaei, K. Shanmugam, A. G. Dimaki, A. F. Molih, and G. Caire, Femtoahing: Wirele video ontent delivery through ditributed ahing helper, arxiv preprint: , [5] P. Mell and T. Grane, The nit definition of loud omputing, National Intitute of Standard and Tehnology, [6] N. Golrezaei, A. F. Molih, A. G. Dimaki, and G. Caire, Femtoahing and devie-to-devie ollaboration: A new arhiteture for wirele video ditribution, arxiv preprint: , [7] A. G. Dimaki, K. Ramhandran, Y. Wu, and C. Suh, A urvey on network ode for ditributed torage, Proeeding of the IEEE, vol. 99, [8] A. G. Dimaki, B. Godfrey, Y. Wu, M. J. Wainwright, and K. Ramhandran, Network oding for ditributed torage ytem, Information Theory, IEEE Tranation on, vol. 56, no. 9, pp , [9] K. V. Rahmi, N. B. Shah, P. V. Kumar, and K. Ramhandran, Exat regenerating ode for ditributed torage, in Communiation, Control, and Computing (Allerton 2009). 47th Annual Allerton Conferene on, pp , [10] C. Suh and K. Ramhandran, Exat regeneration ode for ditributed torage repair uing interferene alignment, arxiv preprint: , [11] Y. Wu and A. Dimaki, Reduing repair traffi for eraure oding-baed torage via interferene alignment, in Information Theory, (ISIT 2009). IEEE International Sympoium on, vol. 4, pp , [12] S. Pawar, S. Y. E. Rouayheb, and K. Ramhandran, On eure ditributed data torage under repair dynami, in Information Theory Proeeding (ISIT), 2010 IEEE International Sympoium on, p , [13] N. B. Shah, K. V. Rahmi, and P. V. Kumar, Informationtheoretially eure regenerating ode for ditributed torage, in GLOBECOM, Auiting, Texa, pp. 1 5, [14] D. Leong, A. G. Dimaki, and T. Ho, Ditributed torage alloation for high reliability, in Communiation (ICC), 2010 IEEE International Conferene on, pp. 1 6, [15] V. Ntrano, G. Caire, and A. G. Dimaki, Alloation for heterogenou ditributed torage, in Information Theory Proeeding (ISIT), 2012 IEEE International Sympoium on, pp , [16] V. Etter, M. Kafi, and E. Kazemi, Been There, Done That: What Your Mobility Trae Reveal about Your Behavior, in Mobile Data Challenge by Nokia Workhop, in onjuntion with Int. Conf. on Pervaive Computing, [17] H. E. Gamal, J. Tadrou, and A. Eryilmaz, Proative reoure alloation: Turning preditable behavior into petral gain, in Communiation, Control, and Computing (Allerton), th Annual Allerton Conferene on, pp , [18] J. Tadrou, A. Eryilmaz, and H. E. Gamal, Proative reoure alloation: Harneing the diverity and multiat gain, arxiv preprint: , [19] Open Cloud Protool, [Online] [20] I. Stoia, R. Morri, D. Karger, M. F. Kaahoek, and H. Balakrihnan, Chord: A alable peer-to-peer lookup ervie for internet appliation, SIGCOMM Comput. Commun. Rev., vol. 31, pp , Aug [21] P. Maymounkov and D. Mazière, Kademlia: A peer-to-peer information ytem baed on the xor metri, in Revied Paper from the Firt International Workhop on Peer-to-Peer Sytem, IPTPS 01, (London, UK, UK), pp , Springer- Verlag, [22] B. Zhao, L. Huang, J. Stribling, S. Rhea, A. Joeph, and J. Kubiatowiz, Tapetry: a reilient global-ale overlay for ervie deployment, vol. 22, pp , [23] S. Ratnaamy, P. Frani, M. Handley, R. Karp, and S. Shenker, A alable ontent-addreable network, SIGCOMM Comput. Commun. Rev., vol. 31, pp , Aug