A Survey on Cloud Storage

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1 A Survey n Clud Strage Swathi.C, Vishnupriya. S, Rajeshkumar.R 1, 2, 3 Sri Eshwar cllege f Engineering, Kinathukadavu, Cimbatre, India ABSTRACT As technlgy in the clud increases, there has been a lt f imprvements in the maturity and firmness f clud strage technlgies. Many end-users and IT managers are getting very excited abut the ptential benefits f clud strage, such as being able t stre and retrieve data in the clud and capitalizing n the prmise f higher-perfrmance, mre scalable and cut-price strage. In this thesis, we present a typical Clud Strage system architecture, a referral Clud Strage mdel and Multi-Tenancy Clud Strage mdel, value the past and the state-fthe-art f Clud Strage, and examine the Edge and prblems that must be addressed t implement Clud Strage. Use cases in diverse Clud Strage fferings were als abridged. KEYWORDS Clud Strage, Clud Cmputing, referral mdel, Multi-Tenancy, survey I. INTRODUCTION One f IT s biggest expenses is disk strage. Cmputer Wrld estimates that in many enterprises strage is respnsible fr almst 30% f capital investment as the average grwth f data appraches clse t 50% annually in mst enterprise. Amng this backgrund, there s strng cncern that enterprise will drwn in the expense f string data, mainly in unstructured data. T address this need, Clud strage services have started t becme ppular. Ranging frm Clud strage fcused at the enterprise t that fcused n end users, Clud strage prviders ffer huge capacity reductin reductins, the eliminatin f labr required fr strage management and maintenance, and immediate prvisining f capacity at a very lw cst per terabyte. Clud strage, thugh, is nt a brand new cncept. The central ideas fr Clud strage are related t past service bureau cmputing paradigms and t thse f applicatin service prviders and strage service prviders f the late 90 s. This time, hwever, the ecnmic situatin and the advent f new technlgies have sparked strng interest in the Clud strage prvider mdel. With n-premises strage csts already high and rising in many IT departments, Clud strage prviders can lwer cst by ff-lading the burden f strage management and shielding enterprises frm ther csts as well, such as strage and netwrk hardware changes. Clud strage prviders deliver ecnmies f scale by using the same strage capacity t meet the needs f many rganizatins, passing the cst savings t their custmer base. Clud Strage is part f a wider definitin called Clud Cmputing which, accrding t the Natinal Institute f Standards and Technlgy, is a mdel fr ffering cnvenient, n demand netwrk access t a shared pl f cnfigurable cmputing resurces (e.g., netwrks, servers, strage, and ther services) that can be rapidly prvisined and released with minimal management effrt r service prvider interactin. The service mdels are splitted up in Clud Sftware as a Service (SaaS), Clud Platfrm as a Service (PaaS) and Clud Infrastructure as a Service (IaaS). Cmputing resurces like servers and netwrk can be replaced, but the cre f mst f the rganizatins is the infrmatin, generally stred in data centers. Fr this reasn security and availability are the first issues when cmpanies are deciding t migrate part f their data t the clud, generally by the internet. IJIRCCE 139

2 II. CLOUD STORAGE INFRASTRUCTURE REQUIREMENTS When yu cmbine the technlgy trends such as virtualizatin with the increased ecnmic pressures, explding grwth f unstructured data and regulatry envirnments that are requiring enterprises t keep data fr lnger span f time, it is easy t see the need fr a trustwrthy and apprpriate strage infrastructure. In case a clud is public r private, the key t success is creating a strage infrastructure in which all resurces can be efficiently utilized and shared. Because all data resides n the strage systems, data strage becmes even mre pivtal in a shared infrastructure mdel. There are ten key cmmn character that must be cnsidered t make clud strage valuable. These include: A. Elasticity Clud strage must be plaint t rapidly adjust the underlying infrastructure t changing subscriber demands and cmply with Service Level Agreements (SLAs). B. Autmatic Clud strage must have the aptness t be prgrammed s that plicies can be leveraged t make underlying infrastructure changes such as placing user and cntent management in different strage tiers and gegraphic lcatins quickly and withut human interventin. C. Scalability Clud strage needs t scale quickly and t huge capacities. This translates int scalability acrss bjects, perfrmance, clients, and capacity with a single name space acrss all strage capacity being critical fr lw Opex reasns. D. Data Security Fr private cluds, security is assumed t be highly cntrlled. Fr public cluds, data shuld either be stred n a partitin f a shared strage system, r clud strage prviders must establish multi-tenancy plicies t allw multiple business units r separate cmpanies t securely share the same strage hardware. E. Perfrmance A evince strage infrastructure prviding fast, rbust data recvery is an essential element f a clud service. F. Reliability Enterprise clients als want t make sure that their data is reliably backed up fr disaster recvery purpses and that it meets pertinent cmpliance guidelines. G. Ease f Management The need fr highly imprved manageability in the face f explring strage capability and csts is a majr benefit enterprises are expecting frm clud strage deplyment. H. Ease f Data Access Ease t access f data in the clud is critical in enabling seamless integratin f clud strage int existing enterprise wrkflws and t minimize the learning curve fr clud strage adptin. IJIRCCE 140

3 I. Energy Efficiency IT data centers are grwing bttlenecks and appraching ceilings n available pwer, cling and flring space. Green strage technlgy is the technlgy that enables energy efficiency and waste reductin in strage slutins leading t an verall lwer carbn ftprint. J. Latency Nt all applicatins are suitable fr a Clud strage mdel. It is imprtant t measure and test netwrk latency befre cmmitting t a migratin. Virtual machines can intrduce additinal latency thrugh the time-dividing nature f the underlying hardware and unanticipated sharing and reallcatin f machines can significantly affect run times. A. Typical clud strage system architecture III. MULTI-TENANCY CLOUD STORAGE REFERRAL MODEL A typical clud strage system architecture includes a master cntrl server and several strage servers, as shwn in Fig 1. Figure 1. A typical Clud Strage system architecture Fr sme cmputer wners, finding enugh strage space t hld all the data they've acquired is a real challenge. Sme users invest in huge hard drives. Others bring external strage devices like thumb drives r cmpact discs. Hpeless cmputer wners might delete entire flders wrth f ld files in rder t make space fr new infrmatin. But sme are chsing t lean n a grwing trend: clud strage. While clud strage sunds like it has smething t d with weather frnts and strm systems, it refers t saving data t an ff-site strage system maintained by a third party. Inspite f string infrmatin t user cmputer's hard drive r ther lcal strage device, user save it t a remte databases. The Internet prvides the cnnectin between user cmputer and the database. S clud strage is mre cnvenient and ffers mre flexibility. B. Clud Strage reference mdel IJIRCCE 141

4 The appeal f clud strage is due t sme f the same attributes that define ther clud services: pay as user g, the illusin f infinite capacity (elasticity), and the easy f management. It is therefre imprtant that any interface fr clud strage supprt these attributes, while allwing fr a multiple n f business cases and fferings, large int the future. The mdel created and published by the Strage Netwrking Industry Assciatin,shws multiple types f clud data strage interfaces able t supprt bth legacy and new applicatins. All f the interfaces give strage t be prvided n demand, btained frm a pl f resurces. The limit is drawn frm a pl f strage capacity prvided by strage services. The data services are appeal t individual data elements as determined by the data system metadata. Metadata mentin the data requirements n the basis f individual data elements r n grups f data elements (cntainers). As shwn in Fig 2, the SNIA Clud Data Management Interface (CDMI) is the functinal interface that applicatins will use t create, update, retrieve and delete data elements frm the clud. As a part f this interface the client will be able t discver the capabilities f the clud strage ffering and use this interface t manage cntainers and the data that is placed in them. In secndary, metadata can be set n cntainers and their cntained data elements thrugh this interface. Figure 2.Clud Strage reference mdel It is expected that the interface will be able t be implemented by the majrity f existing clud strage fferings tday. This culd dne with an adapter t their existing prprietary interface, r by implementing the interface directly. In secndary, existing client libraries such as XAM can be adapted t this interface as shw in Figure 2. Accrd clud fferings may ffer a subset f either interface as lng as they expse the limitatins in the capabilities part f the interface. IJIRCCE 142

5 C. Multi-Tenancy Clud Strage The terms multi-tenant and multi-tenancy are nt new; bth have been used t describe applicatin architectures designed t supprt multiple users r tenants fr lng years. With the advent f clud cmputing, this has simply been extended t include any clud architecture r infrastructure element within that architecture (applicatin, netwrk, server, strage) that supprts multiple users. Users culd be separate cmpanies, r departments within a cmpany, r even just different applicatins. T prvide secure multi-tenancy and address the cncerns f clud skeptics, a mechanism t enfrce separatin at ne r mre layers within the infrastructure is required: Applicatin layer. A specially written, multi-tenant applicatin r multiple, divided instances f the same applicatin can prvide multi-tenancy at this level. Server layer. Server virtualizatin and perating systems prvide a means f separating tenants and applicatin instances n servers and cntrlling utilizatin f and access t server resurces. Netwrk Layer. Varius mechanisms, including zning and VLANs, can be used t enfrce netwrk separatin. IP security (IPsec) als prvides netwrk encryptin at the IP layer (applicatin independent) fr additinal security. Strage Layer. Mechanisms such as LUN masking and SAN zning can be used t cntrl strage access. Physical strage partitins segregate and assign resurces (CPU, memry, disks, interfaces, etc.) int fixed cntainers. Clud cmputing services can be brken dwn int a variety f types, ranging frm Sftware as a Service (SaaS) in which the prvider delivers specific applicatin services t each tenant t Data strage as a Service (DaaS) which is virtualized strage n demand ver a netwrk. Tenant requirements are typically defined in terms f service level agreements (SLAs), which cver a variety f capabilities including: Security Perfrmance Data prtectin and availability Data management Frm the prvider s perspective, multi-tenant strage shuld prvide cnvenient mechanisms fr satisfying these and ther tenant SLAs as well as supprting additinal capabilities such as: Accunting: The ability t mnitr usage by each tenant fr billing r ther purpses. Self service: The ability t allw a tenant t perfrm a defined set f management tasks n their data and the strage they use, thereby fflading these functins frm the prvider. Nn-disruptive upgrades and repairs: Dwntime in multi-tenant envirnments may be difficult r impssible t schedule, s maintenance activities must be pssible withut incurring dwntime frm the pint f view f the tenant. Perfrmance management: The ability t balance cst and perfrmance as the lifecycle requirements f data changes ver time. Designed t enable multi-tenant strage fferings, the SNIA s Clud Data Management Interface (CDMI) fr clud strage and data management integrates and is interperable with varius types f client applicatins. IJIRCCE 143

6 IV. CLOUD STORAGE USE CASES In this part we will summarizes the use cases in varius Clud Strage fferings. A. Web Facing Applicatins Web facing applicatins will typically use a Clud Strage ffering that prvides the data directly t the user s brwser using a URL. The data is typed (MIME) and the brwser invkes the apprpriate applicatin t view the data. Media (audi, vide) files are served as a stream f data, allwing use f parts f the data within the file withut requiring all data in the file t have been received by the client. Figure 3. Data Strage as a Service Scial media sites include Myspace, Facebk, Twitter, Blgs, etc. Clud Strage is used as a auxiliary strage space augmenting the web facing scial applicatin. Pictures and cntent are stred in Clud Strage (URL based typically). A cntent management system is used t keep track f additinal metadata assciated with the data. Smugmug is an example f this. B. Unstructured Data Strage This is a pre-allcated strage space (LUN, Filesystem) that is exprted via standard client prtcls (ex: WebDAV, NFS, CIFS), and munted n a lcal machine. Nrmal POSIX semantics are available at that pint fr creating/reading/writing/deleting the files. A number f vendrs have fferings in this space. A sub case is clud desktp. Examples include iclud, ThinkGrid etc. This is the ability t synchrnize lcal client data, frm multiple clients, with a Clud Strage versin. Changes are detected and then synchrnizatin is dne asynchrnusly and pprtunistically. Access may r may nt be thrugh standard file prtcls and URIs. Clients and servers have a way f sharing state describing what has/needs t be synced. Figure 4. Backup t the Clud IJIRCCE 144

7 C. Backup t the Clud 1) Backup Sftware running n, sme, lcal machines destinatin Clud Strage. This is lcal backup sftware r backup server using Clud Strage as the destinatin f backup data. Backup Sftware n each machine (i.e.timefinder) Backup Server based fr multiple lcal machines File Server Appliance lcally with embeddedbackup t Clud A cmmn technique used by sme lcal servers is t have the client cmputers turn n data sharing (i.e. becming a CIFS server). Then having the lcal backup server becme a CIFS client f the backup client and then backing up the data in that manner. This is an elegant way t circumvent having t install 3rd party backup sftware n the backup clients. 2) Backup f Clud Cmputing Data Backup f the data used in Clud Cmputing (IaaS). Example(s): vsphere (includes de-dup as well) 3) Backup frm ne clud prvider t the ther This is the case f using a secnd clud prvider as the target f backup data frm the first clud prvider. 4) Restre (i.e. Give me back all my laptp data) D. Archive/Retentin t the Clud This is the use case f using the Clud Strage fr archiving f data. Theretically XAM shuld be an ideal interface fr this. Irn Muntain - VFS (nt XAM based) is an example f this. Cnsideratins fr the use case: Figure 5. Archive as a Service Des the user maintain a lcal cpy? IJIRCCE 145

8 Retentin Perid: Keep my files fr X amunt f time Secure Deletin: When it s gne, it s REALLY gne ediscvery : Satisfy my subpenas E. Preservatin in the Clud Preservatin is distinguished frm Archive/Retentin in that the gal f preservatin is t actively maintain the upkeep f infrmatin, mst likely fr lng perids f time. F. Databases in the Clud Clud Table Strage falls int the fllwing categries: 1) Hrizntally Scalable, Object-Relatinal:Examples include Micrsft Azure Tables, Ggle BigTable, (hypertable), SimpleDB. 2) Vertically Scalable, Traditinal Relatinal: SQL services is an example. 3) Dcument Mdel: Example(s): CuchDB is an example. G. Strage fr Clud Cmputing 1) Strage fr IaaS Traditinal data strage which is accessible as part f the cmputing infrastructure. EC2 leverages S3 as if it were a private clud. Image Strage Guest Auxiliary Strage Applicatin Image Strage Figure 6. Strage fr Clud Cmputing IJIRCCE 146

9 2) Strage fr PaaS This type f strage is nt usually surfaced r manageable. 3) Strage fr SaaS (Sftware as a Service) This type f strage is nt usually surfaced r manageable. A typical examples is Salesfrce.cm uses strage service frm Aamzn S3. H. Cntent Distributin Distributing data glbally fr the purpses f decreasing latency and increasing scalability. Here list the fllwing examples: Ht media serving mve t pint f presence, replicate ut t caches, then recver the resurces when unused. Data transfrmatin in rute (i.e. lcalizatin, NTSC->PAL) This use case as a layering n tp f the standard interfaces. I. Clud Strage Peering (i.e. Interclud Strage) This is the cncept f having the Strage Cluds f different Clud Strage Prviders being able t interperate between each ther (in ther wrds ding fr Strage Cluds what the Internet did fr separate, prprietary netwrks). Pssible Characteristics: Shared strage and replicatin between clud strage fferings. Distribute the data acrss clud strage prviders (pssibly via a strage brker that prvides a blended rate). Data may be erasure encded as well as replicated. Caching and distributin between the client and dumb strage prvider, gegraphic staging and replicatin. Activatin and de-activatin relative t sme trust mdel activatin requires assembly frm the erasure cded blcks, decding and decryptin, de-activatin invlve encryptin, encding and distributin. Tplgy f the netwrk is mre nuanced than the typical tw tier prcessing mdel and mre dynamic as well. Examples include Federated Clud Strage, Clud Exchange,Clud Bursting, fflading, Hybrid Internal/External Cluds. A. Advantage f clud strage V. ADVANTAGES AND CHALLENGES Ease f management IJIRCCE 147

10 Cst effectiveness Lwer impact utages and upgrades Disaster preparedness B. Challenges in the implementatin Hwever, with every type f clud strage, there are challenges in the implementatin (i.e. the devil is in the details). 1) Physical Security 2) Data encryptin 3) Access Cntrls 4) Service Level Agreements (SLA) 5) Trusted Service Prvider Figure 7. Survey n cncerns with clud strge services As shw in Fig 7, the prblem include security,cntrl, perfrmance,supprt,vendr lck-in, are cncerned by users with clud strge services. These challenges include: Security (always an issue and nt necessarily a clud strage specific issue) Data integrity (making sure the stred data is crrect ) Pwer (since yu have cpies yu will have extra strage which adds pwer) Replicatin time and csts (hw fast can yu replicate data since this can be imprtant t data resiliency) Cst (hw much extra mney d yu have t pay t buy the extra strage fr cpies) Reliability IJIRCCE 148

11 VI. CONCLUSIONS AND FUTURE WORK Clud Strage with a great deal f prmise, aren t designed t be high perfrming file systems but rather extremely scalable, easy t manage strage systems. They use a different apprach t data resiliency, Redundant array f inexpensive ndes, cupled with bject based r bject-like file systems and data replicatin (multiple cpies f the data), t create a very scalable strage system. This article gives a quick intrductin t clud strage. It cvers the key technlgies in Clud Cmputing and Clud Strage, several different types f cluds services, and describes the advantages and challenges f Clud Strage after the intrductin f the Clud Strage reference mdel. REFERENCES [1] Luis M.Vaquer,Luis Rder-Merin, Juan Caceres,Maik Lindner. A Break in the Cluds: Tward a Clud Definitin. ACM SIGCOMM Cmputer Cmmunicatin Review,2009,39(1): [2] Wu Jiyi,Ping Lingdi,Pan Xuezeng.Clud Cmputing: Cncept and Platfrm, Telecmmunicatins Science, 12:23-30, [3] Jnathan Strickland.Hw Clud Strage Wrks[OL], [4] Strage Netwrking Industry Assciatin.Clud Strage Reference Mdel,Jun [5] Strage Netwrking Industry Assciatin.Clud Strage fr Clud Cmputing,Jun [6] Luiz Andre Barrs,Jeffrey Dean,Urs Hlzle.Web search fr a planet: The Ggle cluster architecture. IEEE Micr, 2003,23(2): [7] Sanjay Ghemawat, Hward Gbiff, and Shun-Tak Leung. The Ggle file system. In: Prc. f the 19th ACM SOSP. New Yrk: ACM Press, [8] Rbert L.Grssman, Yunhng Gu, Michael Sabala,Wanzhi Zhang. Cmpute and strage cluds using wide area high perfrmance netwrks. Future Generatin Cmputer Systems, 2009,25(2): [9] Yunhng Gu and Rbert L.Grssman. Sectr and Sphere: the design and implementatin f a high-perfrmance data clud. Philsphical Transactins f the Ryal Sciety. A(2009)367: [10] Rbert L Grssman,Yunhng Gu. Data Mining Using High Perfrmance Data Cluds: Experimental Studies Using Sectr and Sphere. In Prc. f the 14th ACM SIGKDD internatinal cnference n Knwledge discvery and data mining,2008, [11] Daniel J. Abadi. Data Management in the Clud: Limitatins and Opprtunities. Bulletin f the IEEE Cmputer Sciety Technical Cmmittee n Data Engineering, 2009,32(1):3-12. [12] Peter Mell and Tim Grande. NIST. Retrieved frm [13] S Lesem. Clud Strage Strategy Retrieved frm IJIRCCE 149

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