Keywords Cloud Computing, Service level agreement, cloud provider, business level policies, performance objectives.

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1 Volum 3, Issu 6, Jun 2013 ISSN: X Intrnational Journal of Advancd Rsarch in Computr Scinc and Softwar Enginring Rsarch Papr Availabl onlin at: wwwijarcsscom Dynamic Ranking and Slction of Cloud Providrs Using Srvic Lvl Agrmnts Prti Gulia, Sumdha Sood Dpartmnt of Computr Scinc and Applications MD Univrsity, Rohtak, Haryana, India Abstract Cloud computing is gaining hug attntion ths days Srvic lvl agrmnts play a crucial rol in cloud computing A providr offring good SLA will always hav an dg ovr othr providrs in markt as consumrs would prfr th cloud that offrs good SLA as compard to othrs Srvic lvl agrmnts hlp a cloud consumr to choos th bst cloud by matching his rquirmnts with th srvics offrd by clouds as mntiond in thir srvic lvl agrmnt Howvr, this procss of matching bcoms quit complicatd whn prformd manually by a cloud customr Th rason for th sam can b attributd to incrasing numbr of providrs offring srvics with growing popularity of cloud computing As a rsult a consumr may mak a wrong dcision and thus risk his ntir businss on an unsuitabl cloud Hnc, kping th abov issu in mind w propos a framwork that rmovs th burdn of slction from th customr by automatically slcting th bst cloud for a usr Th givn approach slcts th most suitabl cloud by comparing diffrnt clouds on th basis of srvic thy offr and on th basis of usr rquirmnts and prioritis Kywords Cloud Computing, Srvic lvl agrmnt, cloud providr, businss lvl policis, prformanc objctivs I INTRODUCTION As th world is advancing, th rol of IT in our daily livs is incrasing rapidly As a rsult, th dmand of computing powr is also incrasing day by day Whil thr was always an incrasing dmand for high procssing powr and rsourcs at th industry lvl, computing nds at th prsonal lvl ar also incrasing at a vry high rat [1] All ths factors hav lad to succss of cloud computing This is so bcaus with cloud computing on dos not nd to purchas computing powr and rsourcs but can asily accss thm on th rntal basis (pay as you us basis) from various organizations (providrs) Cloud computing can b dfind as a novl computing paradigm in which various computing rsourcs such as hardwar and softwar that ar availabl in rmot locations can b accssd according to pay as you us modl by mans of intrnt [2]Sinc cloud computing rmovs th ovrhad of buying ntir computing powr and rsourcs, it provs to b much mor cost ffctiv than prvious traditional approachs Thr is also limination of maintnanc costs with cloud computing and various additional faturs such as scal up and scal down of rsourcs ar also availabl Srvic lvl agrmnt play an important rol in cloud computing Thy can b dfind as short documnts that contain various prformanc promiss mad by a providr Thy also contain pnaltis that a providr would hav to pay in cas h is not abl to dlivr promisd srvics [3] Whil a providr can us SLA to promot his srvics [4], a consumr can us th sam to slct th bst cloud by matching SLAs offrd by diffrnt clouds with his own rquirmnts Following ar th som important points that must b considrd whil valuating a cloud srvic lvl agrmnt [5]: 1 Undrstand Rols and Rsponsibilitis: Th cloud consumrs should b clar about thir rols and rsponsibilitis which ar containd in SLA For this thy should b abl to idntify ach and vry actor involvd in cloud computing nvironmnt Th cloud consumr should also b abl to idntify activitis of actors and clarly dfin thir rquirmnts and dsird srvic lvls 2 Evaluat businss lvl policis: Th businss stratgis and policis dvlopd for th businss purpos and th policis containd in srvic lvl agrmnt ar intrdpndnt on ach othr Hnc, th cloud customr should carfully valuat all th data policis as wll as businss lvl policis of th cloud providr as all ths policis dirctly affct cloud consumr s cloud stratgis as wll as businss cass 3 Undrstand srvic and dploymnt diffrncs: Th cloud srvics offrd mostly fall in on of thr main catgoris namly IaaS, SaaS or PaaS Th SLAs for all ths catgoris ar diffrnt from ach othr This is so bcaus srvic lvl objctivs, ky prformanc indicators and lvl of cloud rsourc abstraction which constitut a SLA ar diffrnt for all th thr catgoris Hnc, ths should b carfully valuatd at th tim of dfining SLA Bsids srvic modls, information on dploymnt modls should also b includd SLAs should contain th typ of dploymnt modl and dploymnt tchnologis that hav bn adoptd by th providr 2013, IJARCSSE All Rights Rsrvd Pag 93

2 Gulia t al, Intrnational Journal of Advancd Rsarch in Computr Scinc and Softwar Enginring 3(6), Jun , pp Idntify Critical prformanc Objctivs: Thos prformanc attributs that ar ssntial as pr th cloud consumr must b includd in SLA Ths gnrally includ availability, rspons tim, tc Th prformanc statmnts should b masurabl and documntd proprly in SLA and should satisfy both th consumr as wll as th providr 5 Undrstand disastr rcovry plan: Thr could b any kind of disastr such as natural disastr or any man-mad vnt that could advrsly affct th cloud consumr s businss Thus, to prvnt any undu losss du to disastrs a cloud providr must mak appropriat disastr rcovry plans Th disastr rcovry plans dpnd to a larg xtnt on th cloud consumr, sinc th infrastructur or application dmands varis from on consumr to anothr Thrfor, th disastr rcovry plan of ach organization varis and businss lvl objctivs hav an important rol to play in disastr rcovry planning Many currnt cloud SLAs don t provid guarants in cas of SLA violation du to natural disastr Th cloud consumr mak clar following issus rgarding disastr rcovry with th providr as arly as possibl How srvic outag is dfind? What lvl of rdundancy is adoptd by cloud providr to minimiz violations What procdur would b followd to sttl down unplannd accidnts What masurs will b takn to prvnt unplannd incidnts from occurring What masurs will b takn in cas thr is a continuous disruption in providing guarantd srvics and thus causing srious impact to businss What contingncy plan will b adoptd during a disastr How th disastr rcovry tsts will b prformd and what will b thir frquncy Will th customr b informd about ths tsts 6 Undrstand th xit procss: Each srvic lvl agrmnt must contain an xit claus It should cit th rasons rsponsibl for arly trmination and rsponsibilitis of both th providr and consumr in cas such a situation is dvlopd Srvic lvl agrmnts hlp a cloud consumr to slct th bst cloud by matching his rquirmnts with a cloud srvic lvl agrmnt Howvr, as th numbrs of providr offring cloud srvic ar incrasing rapidly, this manual procss of cloud slction bcoms quit complicatd and tim consuming Th usr may hav to go through srvic lvl agrmnts of a numbr of clouds that do not vn fulfil thir singl rquirmnt, thus lading to wastag of thir crucial tim Sinc, SLA of on providr varis from othr providr to a grat xtnt, raching to a corrct dcision can bcom complicatd for a usr Wrong dcision can put th customr at a high risk sinc a customr has to risk his ntir businss on th providr Thus to mak th abov procss of slction simpl for a usr, this papr proposs an dynamic algorithm that would automatically slct th most suitabl cloud for th usr and thus rduc th burdn of slcting th bst cloud Th cloud is slctd as pr usr s rquirmnts and prioritis Th approach is dynamic as it will produc diffrnt rsults dynamically dpnding upon usr rquirmnts This papr is organizd as follows Th sction II discusss rlatd work Sction III discusss th proposd work with th hlp of proposd algorithm Sction IV compriss of tabls usd in th givn approach Sction V xplains th rsults with th hlp of rsult tabl Th papr finally concluds in sction VI II RELATED WORK Prviously also an algorithm was dvlopd with by Tjas Chauhan t al with th motiv of slcting th bst cloud for a givn usr Thy dvlopd an algorithm with th aim of slcting th bst cloud providr automatically for usr It was implmntd using Jna API by matching usr s rquirmnt (rfrrd to as rquirmnt modl) with cloud s Srvic Lvl Agrmnt (rfrrd to as Cloud Capability Modl) Th abov procss of matching two modls was don on th basis of various srvic lvl agrmnt paramtrs Total nin paramtrs namly Virtual machin, Storag Capability, Mmory capability, Ethrnt, Availability, Procssor spd, rspons tim Srvr rboot, Srvic Crdit wr considrd [6] Thn a framwork, SMICloud was proposd by Saurabh Kumar Garg, Stv Vrstg and Rajkumar Buyya which also slctd th bst cloud for th usr Thy usd srvic masurmnt indx in ordr to masur srvics of providrs AHP approach was usd to rank providrs Thr IaaS cloud providrs namly Amazon EC2, Windows Azur, and Rackspac wr takn and thir prformanc was compard as pr srvic masurmnt indx using AHP ranking [7] Although it is vry important to automat srvic lvl agrmnts, howvr in th ral world, th agrmnts ar still offrd as onlin wb pags on th providr s wbsits For xampl Amazon EC2 SLA and GoGrid SLA ar two documnts that ar availabl onlin on Amazon wbsit [8] and GoGrid [16] wbsits rspctivly [6] III PROPOSED WORK Th main motiv of this work is to rduc th burdn of cloud slction from th usr This approach would slct th bst cloud for th usr by taking into account usr rquirmnts and prioritis This proposd algorithm is a modification of wightd product modl According to wightd product modl following quation is obtaind n P (C K /C L ) = (C Kj / C w Lj) j for K, L =1, 2, 3 m [9] Whr, 2013, IJARCSSE All Rights Rsrvd Pag 94

3 Gulia t al, Intrnational Journal of Advancd Rsarch in Computr Scinc and Softwar Enginring 3(6), Jun , pp C k and C L can b takn as two clouds Thr ar total m clouds and th ratio of all ths m clouds is calculatd Th ratio of two clouds is calculatd by taking th product of ratios of ach paramtr For xampl if thr ar 3 paramtrs, than (C K1 / C L1)* (C K2 / C L2)* (C K3 / C L3) will b calculatd in ordr to obtain final ratio C K /C L This would b don for ach of th m cloud Howvr, our approach will compar two clouds by taking th diffrnc of thir paramtrs instad of finding th ratios Than in contrast to prvious approach in which product of ratios was takn, w would add th diffrncs obtaind Th main motiv of taking diffrnc is to compar two clouds If P (Cloud A Cloud B) > 0, this mans points of cloud A ar gratr than cloud B and thus cloud A is bttr than cloud B n P (C K C L ) = (C Kj C Lj ) Pj for K, L =1, 2, 3 m J=1 This approach has bn dvlopd using JAVA (JDBC) as front nd and My SQL as back nd It maks us of thr tabls: 1 Cloud providr Tabl -- This tabl contains how much srvic a providr promiss to provid for ach of th considrd SLA paramtr 2 Rquirmnt Tabl -- It contains th minimum amount of srvic that a givn cloud consumr xpcts for ach of th considrd SLA paramtr from th providr Total 14 rquirmnts ar takn 3 Priority Tabl It contains th prioritis of usrs for ach of th rquirmnts Prioritis indicat usrs dgr of importanc for SLA paramtr as pr thr rquirmnts Th proposd algorithm works as follows: 1 Match th rquirmnt tabl and cloud providr tabl to slct thos clouds that mt all th usr rquirmnts Th clouds that provid srvic ithr qual to or abov th valus spcifid in rquirmnt tabl will b ligibl and rmaining will b non ligibl 2 Calculat th points for ach cloud using following formula: a Points (cloud 1 ) = (cloud 1 cloud 1 ) = (C 11 C 11 ) *p1 + (C 12 C 12 ) *p2+ + (C 1C C 1C ) *pc + (C 1m C 1m ) Points (cloud 2 ) = (cloud 2 cloud 1 ) = (C 21 C 11 ) *p1 + (C 22 C 12 ) *p2+ + (C 1C C 2C ) * *pc + (C 2m C 1m ) Points (cloud 3 ) = (cloud 3 cloud 1 ) = (C 31 C 11 ) *p1 + (C 32 C 12 ) *p2+ + (C 1C C 3C ) *pc + (C 3m C 1m ) Points (cloud n ) = (cloud n cloud 1 ) = (C n1 C 11 ) *p1 + (C n2 C 12 ) *p2 + + (C 1c C nc ) *pc + (C nm C 1m ) Th points obtaind ar arrangd in dscnding ordr and ranks ar found Th points can also b obtaind by quations in (b) and (c) Th diffrnc btwn th quations in (a), (b) and (c) is that in (a) all th points ar calculatd with rspct to cloud 1 (i by comparing vry cloud with cloud 1 ), in (b), quations points ar calculatd with rspct to cloud 2 (i by comparing vry cloud with cloud 2 ) and in (c) points ar calculatd with rspct to cloud n (i by comparing vry cloud with cloud n ) b Points (cloud 1 ) = (cloud 1 cloud 2 ) = (C 11 C 21 ) *p1 + (C 12 C 22 ) *p2+ + (C 2C C 1C ) *pc + (C 1m C 2m ) Points (cloud 2 ) = (cloud 2 cloud 2 ) = (C 21 C 21 ) *p1 + (C 22 C 22 ) *p2+ + (C 2C C 2C ) *pc + (C 2m C 2m ) Points (cloud 3 ) = (cloud 3 cloud 2 ) = (C 31 C 21 ) *p1 + (C 32 C 22 ) *p2+ + (C 2C C 3C ) *pc + (C 3m C 2m ) Points (cloud n ) = (cloud n cloud 2 ) = (C n1 C 21 ) *p1 + (C n2 C 22 ) *p2 + + (C 2c C nc ) *p3 + (C nm C 2m ) Th points obtaind ar arrangd in dscnding ordr and ranks ar found Th ranks ar sam as that obtaind in (a) Thr ar total n ligibl clouds and m paramtrs c Points (cloud 1 ) = (cloud 1 cloud n ) = (C 11 C n1 ) *p1 + (C 12 C n2 ) *p2+ + (C nc C 1C ) *pc + (C 1m C nm ) Points (cloud 2 ) = (cloud 2 cloud n ) = (C 21 C n1 ) *p1 + (C 22 C n2 ) *p2+ +(C nc C 2C ) *pc + (C 2m C nm ) Points (cloud 2 ) = (cloud 3 cloud n ) = (C 31 C n1 ) *p1 + (C 32 C n2 ) *p2+ +(C nc C 3C ) *pc + (C 3m C nm ) 2013, IJARCSSE All Rights Rsrvd Pag 95

4 Gulia t al, Intrnational Journal of Advancd Rsarch in Computr Scinc and Softwar Enginring 3(6), Jun , pp Points (cloud n ) = (cloud n cloud n ) = (C n1 C n1 ) *p1 + (C n2 C n2 ) *p2 + + (C nc C nc ) *pc + (C nm C nm ) Th points obtaind ar arrangd in dscnding ordr and ranks ar found Th ranks ar sam as that obtaind in (a) and (b) Stp 2 would b rpatd for all th rquirmnts Sinc ranks obtaind by (a), (b), and (c) ar sam hnc, any on of thm can b don to calculat ranks It is not ncssary that all 3 of thm hav to b don Whr, Cloud 1 1 st ligibl cloud Cloud nd ligibl cloud Cloud n n th ligibl cloud (Total thr ar n ligibl clouds) C 11 valu of 1 st paramtr of 1 st ligibl cloud C 12 valu of 2 nd paramtr of 1 st ligibl cloud C 1C valu of cost paramtr of 1 st ligibl cloud C 1m -- valu of m th paramtr of 1 st ligibl cloud (Total thr ar m paramtrs) C 21 valu of 1 st paramtr of 2 nd ligibl cloud C 22 valu of 2 nd paramtr of 2 nd ligibl cloud C 2C valu of cost paramtr of 2 nd ligibl cloud C 2m -- valu of m th paramtr of 2 nd ligibl cloud C n1 valu of 1 st paramtr of nth ligibl cloud C n2 valu of 2 nd paramtr of nth ligibl cloud C nc valu of cost paramtr of n th ligibl cloud C nm -- valu of m th paramtr of n th ligibl cloud p 1 = priority of 1 st paramtr, p 2= priority of 2 nd paramtr p m= priority of m th paramtr 3 Rpat abov stps for all rquirmnts Tabl I Cloud Rackspac HP GoGrid Nphoscal Providr Rackspac HP GoGrid Nphoscal Th abov tabl (Tabl I) shows th dtaild points obtaind by ach ligibl cloud for rquirmnt1 Rquirmnt 1 is shown in rquirmnt tabl (Tabl III) in sction IV and cloud providr tabl is shown in tabl IIs in sction IV Th points ar as follows: (a) Points (Rackspac) = Rackspac Rackspac = 00 Points (HP) = HP Rackspac = 2255 Points(GoGrid) = GoGrid Rackspac = 7455 Points (Nphoscal) = Nphoscal Rackspac = Ths points (Cloud Providr -- Rackspac) ar sortd in dscnding ordr and ranks ar obtaind (b) Points (Rackspac) = Rackspac HP = 2255 Points (HP) = HP HP = 00 Points (GoGrid) = GoGrid HP = 9714 Points (Nphoscal) = Nphoscal HP = Ths points (Cloud Providr HP) ar sortd in dscnding ordr and ranks ar obtaind (Ranks ar sam as obtaind in (a)) (c) Points (Rackspac) = Rackspac GoGrid = 749 Points (HP) = HP GoGrid = 9714 Points (GoGrid) = GoGrid GoGrid =00 Points (Nphoscal) = Nphoscal GoGrid = Ths points (Cloud Providr GoGrid) ar sortd in dscnding ordr and ranks ar obtaind (Ranks ar sam as obtaind in stp (a) and (b)) 2013, IJARCSSE All Rights Rsrvd Pag 96

5 Gulia t al, Intrnational Journal of Advancd Rsarch in Computr Scinc and Softwar Enginring 3(6), Jun , pp (d) points (Rackspac) = Rackspac Nphoscal = points (HP) = HP Nphoscal = points (GoGrid) = GoGrid Nphoscal = points (Nphoscal) = Nphoscal- Nphoscal =00 Ths points (Cloud Providr Nphoscal) ar arrangd in dscnding sortd ordr and ranks ar obtaind (Ranks ar sam as obtaind in stp (a), (b) and (c)) For all th paramtrs such as availability, scurity, tc largr valu is bttr than smallr valu For xampl 100% availability is bttr than 99% availability, 24 hours of scurity is bttr than 20 hours of scurity Howvr, for cost smallr valu is bttr than gratr valu For xampl, if a cloud offrs srvics at $81760 it is bttr than a cloud that offrs srvics at $87060 Thus, for th cost paramtr whnvr diffrnc is takn btwn cloud A cloud B, it is cost of cloud B cloud A and not cost of cloud A cost of cloud B This would bcom clar by th following xampl: For xampl, considr th cas in which w hav to calculat th points obtaind by 2 nd cloud Thy can b obtaind by subtracting th paramtrs of cloud 1from paramtrs of cloud 2 and thn adding th diffrncs Now, 1 st cloud offrs srvics at $8766 and 2 nd cloud offrs srvics at $8176 Thus, 2 nd cloud is bttr than 1 st in cost and hnc cost paramtr should incras th ovrall points of 2 nd cloud Howvr, lik othr paramtrs, if w subtract cost of cloud 1 from cloud 2 i ( ), it will rsult in ngativ answr and would dcras th points of 2 nd cloud Thus, in cas of cost paramtr, 2 nd cloud is subtractd from 1 st cloud in ordr to gt corrct answr Similarly, whn calculating points of 1 st cloud, w will subtract 2 nd cloud from 1 st cloud for all paramtrs Now, 1 st cloud offrs srvics at 8766 and 2 nd cloud offrs srvics at 8176 If w subtract 2 nd cloud from 1 st cloud i ( ), it will rsult incras th points of cloud 1 Thus this again justifis prvious xampl Thrfor in cas of cost paramtr whil calculating diffrnc btwn any 2 clouds cloud x and cloud y w would calculat cloud y -- cloud x as compard to othr paramtrs in which cloud x --- cloud y will b calculatd to gt corrct answr Following srvic lvl agrmnt paramtrs ar considrd: 1) Scurity 2) Availability 3) Procssor cors 4) Procssor spd 5) Cost (Pr hour basis/monthly basis) 6) RAM 7) Storag IV TABLES USED IN ALGORITHM Th abov approach maks us of thr tabls namly cloud providr tabl; rquirmnt tabl and priority tabl Ths tabls ar stord in a My SQL databas 1) Cloud providr tabl contains th valus of ach of th considrd SLA paramtr that a providr aims to provid Only thos clouds that fulfil all th rquirmnts ar considrd ligibl and th rmaining clouds ar not ligibl Th ligibl clouds will b compard with ach othr and th comparisons will b multiplid with priority in ordr to find th bst cloud Data has bn collctd from wbsits of diffrnt providrs 10 providrs ar takn namly Googl comput ngin [10][11], Rackspac[12][13], HP[14][15], GoGrid[16][17], Opsourc[18][19], Nphoscal[20][21], Bitrfinry[22][23], Windows azur[24][25], saavisdirct[26][27], Joynt[28][29] Sinc no information about scurity was givn, hnc it has bn assumd Cloud Providr Googl comput ngin Scurity Availabili ty TABLE II CLOUD PROVIDER TABLE Procssor Cors Procssor spd(pr cor)* (appr ox) 22 hours 9995% Mntiond Cost (pr hour basis) Cost ( monthly basis) 8 $106 Mntiond RAM Storag 30 GB 3540GB Rackspac 23 hours 100% 23 GHz 8 $120 $ GB 1228GB Hp 22 hours 9995% 27 GHz 8 $112 $ GB 960 GB GoGrid 24 hours 100% 29 GHz 24 $192 $ GB 1228 GB OpSourc 22 hours 100% 21 GHz 8 $217 $ GB 2500GB Nphoscal 22 hours 9995% 24 GHz 8 Mntiond $ GB 1000 GB 2013, IJARCSSE All Rights Rsrvd Pag 97

6 Gulia t al, Intrnational Journal of Advancd Rsarch in Computr Scinc and Softwar Enginring 3(6), Jun , pp Bitrfinry 23 hours 100% 21 GHz 4 $ GB 150 GB Mntiond Windows 22 hours 9995% 16 GHz 8 $180 $ GB 2040 GB azur Savvisdir 22 hours 999% 267GHz 8 $ GB 500 GB ct Mntiond Joynt 22 hours 100% 16 $280 $ GB 2048GB Mntiond 2) Usr Rquirmnt Tabl -- Th 2 nd tabl is usr rquirmnt tabl It consists of how much a usr xpcts for diffrnt paramtrs from providrs Th valu of ach paramtr (xcpt cost) is th minimum valu that a givn usr xpcts from providrs Howvr, in cas of cost, th valu shown in tabl is maximum budgt of th usr For xampl 20 hours scurity mans minimum scurity usr xpcts is 20 hours and vry cloud that provids scurity ithr qual or abov that valu will b slctd Howvr, $2000 mans maximum cost that a usr is willing to pay is $2000 and vry cloud that offrs srvic blow th givn cost will b slctd This tabl is matchd with th cloud providr tabl in ordr to find th ligibl clouds If a cloud fails to provid srvic abov that mntiond in th rquirmnt tabl vn for a singl paramtr, it is considrd as non ligibl Th ligibl clouds ar rankd using th abov algorithm TABLE III USER REQUIREMENT TABLE Rquirm nts Rquirmn t1 Rquirmn t 2 Rquirmn t 3 Rquirmn t 4 Rquirmn t 5 Rquirmn t 6 Rquirmn t 7 Rquirmn t 8 Rquirmn t 9 Rquirmn t 10 Rquirmn t 11 Rquirmn t 12 Rquirmn t 13 Scurity Availability Procssor cors Procssor spd(pr cor)* (approx ) Cost RAM Storag 20 hours 975% 8 22 GHz $ GB 600 GB 19 hours 985% 8 23 GHz $ GB 500 GB Rquird 945% 4 2 GHz $2500 Rquird 100 GB 905% 4 18GHz $ GB 400 GB Rquird 20 hours 100% 4 21GHz $2(Pr 8GB 800GB Hour) 22 hours 90% 8 15 GHz $2200 (Pr 16 GB 400 GB month 940% $3(Pr hour Rquird Rquird Rquird Rquird Rquird 20 hours 90% 4 21 GHz $2100 (Pr 8 GB 100 GB month) 17 hours 100% 8 17GHz $2000 (Pr 8 GB 400 GB month) 20 hours 8 $1500 (Pr 16 GB 900 GB Rquird Rquird month) 22 hours $2900(Pr 32 GB Rquird Rquird Rquird month) Rquird Rquird Rquird Rquird Rquird Rquird Rquird 4 Rquird $28(Pr hour) $3 (Pr month) Rquird Rquird 100 GB 1000 GB Rquirmn t 14 Rquird 100% 8 Rquird $2500 (Pr month) 16 GB 100GB 3) Priority Tabl -- Priority tabl dpicts importanc of diffrnt Srvic lvl agrmnt paramtrs for usrs If two or mor paramtrs hav sam importanc, thy will b assignd sam priority Ths prioritis can b thought of as wights that a usr assigns to diffrnt paramtrs Th main motiv of prioritizing diffrnt paramtrs is to mak sur that th cloud assignd to a usr provids good srvic for thos paramtrs that ar important for a usr Th prioritis ar givn in dscnding ordr i th most important paramtr is givn highst in numbr priority For xampl in rquirmnt 1, most important paramtr is availability, thus it is assignd priority 7 th This is so bcaus ths prioritis will b multiplid with diffrnc to find points and th cloud gtting highst points is bst Hnc, 2013, IJARCSSE All Rights Rsrvd Pag 98

7 Gulia t al, Intrnational Journal of Advancd Rsarch in Computr Scinc and Softwar Enginring 3(6), Jun , pp ths prioritis ar arrangd in dscnding ordr, with th highst priority givn to that paramtr that is most important TABLE IV PRIORITY TABLE Rquirmnt Scurit Availabilit Procsso Procssor RAM Storag Cost s y y r cors spd(pr cor) Rquirmnt 3 rd 7 th 5 th 2 nd 6 th 1 st 4 th 1 Rquirmnt 3 rd 2 nd 4 th 5 th 1 st 7 th 4 th 2 Rquirmnt 0 3 rd 1 st 3 rd 0 2 nd 4 th 3 Rquirmnt 0 3 rd 3 rd 4 th 1 st 2 nd 4 th 4 Rquirmnt 1 st 6 th 6 th 2 nd 4 th 3 rd 5 th 5 Rquirmnt 5 th 3 rd 4 th 2 nd 1 st 0 1 st 6 Rquirmnt 0 1 st nd 7 Rquirmnt 5 th 5 th 1 sts 6 th 3 rd 4 th 2 nd 8 Rquirmnt 3 rd 6 th 5 th 4 th 2 nd 1 st 7 th 9 Rquirmnt 4 th 0 4 th 0 1 st 2 nd 3 rd 10 Rquirmnt 2 nd rd 0 1 st 11 Rquirmnt nd 1 st 12 Rquirmnt st rd 2 nd 13 Rquirmnt 0 3 rd 2 nd 0 4 th 1 st 1 st 14 V RESULTS Th following tabl shows th rsults obtaind by applying abov algorithm REQUIRE MENTS Googl Compu t Engin Rac kspa c HP TABLE V RESULT TABLE GoGri Opsou Npho d rc scal Bit Rfin ry Windo ws Azur Savvisdir ct Joynt Rquirm nt 1 Rquirm nt 2 Rquirm nt 3 Rquirm nt 4 2 nd 3 rd 1 st 1 st 2 nd 4 h 3 rd 4 th 6 th 3 rd 5 th 7 th 2 nd 2 nd 4 th 1 st 3 rd 5 th 1 st Rquirm nt 5 2 nd 1 st 2013, IJARCSSE All Rights Rsrvd Pag 99

8 Gulia t al, Intrnational Journal of Advancd Rsarch in Computr Scinc and Softwar Enginring 3(6), Jun , pp Rquirm 3 rd 2 nd 1 st 6 th 5 th 4 th nt 6 Rquirm nt 7 Rquirm nt 8 Rquirm nt 9 Rquirm nt 10 Rquirm nt 11 1 st 4 th 3 rd 6 th 7 th 3 rd 4 th 2 nd 1 st 5 th 7 th 2 nd 1 st 3 rd 3 rd 4 th 1 st Eligi bl 1 st 5 th 4 th 2 nd 5 th 2 nd 3 rd 6 th 5 th Rquirm nt 12 1 st 4 th 6 th 5 th 2 nd 3 rd Rquirm nt 13 1 st 6 th 5 th 2 nd 4 th 3 rd Rquirm nt 14 3 rd 2 nd 1 st 4 th Th abov tabl shows th ranks obtaind on applying th abov algorithm ligibl mans that givn cloud dos not mt all th rquirmnts In Rquirmnt 1 only four clouds namly Rackspac, HP, GoGrid and Nphoscal ar ligibl and rmaining ar inligibl Th rasons for th sam ar xplaind as follows: Googl comput ngin dos not provid srvic on monthly basis as rquird by 1 st rquirmnt and has no mntion of procssor spd (21 GHz spd is rquird by Rquirmnt 1) Opsourc dos not provid 22 GHz procssor spd and hnc is not ligibl Bit rfinry dos not provid rquird RAM (20 GB), storag (600 GB) and procssor spd (22 GHz) Windows Azur ngin dos not to provid rquird procssor spd (22 GHz) Saavisdirct dos not provid rquird RAM (20 GB), storag (600 GB) Joynt also dos not provid 22 GHz procssor spd All th rmaining clouds ar ligibl and ar rankd according to th algorithm discussd abov out of which GoGrid achivs th first rank Similarly rsults can b obtaind for othr rquirmnts also VI CONCLUSIONS Th approach dvlopd in this papr ranks all th clouds providrs and finds th bst cloud providr for th usr Th sam work whn don manually by a consumr bcoms quit tdious and difficult Hnc, this approach maks th work of providr slction quit simpl for a usr by automatically slcting th bst cloud for a usr as pr his rquirmnts and prioritis In spit of th fact that this task of providr slction is quit complicatd whn prformd by a consumr manually, thr is hardly any automatic slction of cloud providrs in ral world and th srvic lvl agrmnts ar still offrd as manual documnts on wbsits of various providrs Hnc, this approach provids an answr to on of th drawbacks facd by cloud computing It also hlps th providr to idntify its waknss by comparing its srvics with th srvics offrd by othr clouds in markt W hop that this ffort of ours will hlp thos working in th ara of cloud computing with thir futur works REFRENCES [1] Goudarzi, Hadi, Mohammad Ghasmazar, and Massoud Pdram "SLA-basd optimization of powr and migration cost in cloud computing" in Proc Clustr, Cloud and Grid Computing (CCGrid), th IEEE/ACM Intrnational Symposium on IEEE, 2012 [2] Th Wikipdia wbsit(onlin) [3] L Badgr, Tim Granc, Robrt Patt-Cornr and Jff Voas, Cloud Computing Synopsis and Rcommndations, NIST Spcial Publication 800 (2012): , IJARCSSE All Rights Rsrvd Pag 100

9 Gulia t al, Intrnational Journal of Advancd Rsarch in Computr Scinc and Softwar Enginring 3(6), Jun , pp [4] Cloud ; SLAs for cloud srvic ETSI TR V111 ( )Tchnical rport [5] Practical Guid to Cloud Srvic Lvl Agrmnts,cloud standard customr council, vrsion 10April 10, 2012 [6] Tjas Chauhan, Sanjay Chaudhary, Vikas Kumar, and Minal Bhis, Srvic Lvl Agrmnt paramtr matching in Cloud Computing, Information and communication tchnologis (WICT), in proc 2011 World congrss on IEEE, 2011 [7] Saurabh Kumar Garg, Stv Vrstg and Rajkumar Buyya, "SMICloud: a framwork for comparing and ranking cloud srvics" In proc Utility and Cloud Computing (UCC) 2011 Fourth IEEE Intrnational Confrnc on IEEE, 2011 [8] Th Amazon wbsit (onlin) Availabl: [9] Th Wikipdia wbsit (onlin) Availabl: [10] Th Googl wbsit (onlin) Availabl: https://dvloprsgooglcom/comput/docs/sla [11] Th Googl wbsit (onlin) Availabl: https://cloudgooglcom/pricing/comput-ngin [12] Th Rackspac wbsit (onlin) Availabl: [13] Th Rackspac wbsit (onlin) Availabl: [14] Th HP wbsit (onlin) Availabl: https://wwwhpcloudcom/sla [15] Th HP wbsit (onlin) Availabl: https://wwwhpcloudcom/pricing [16] Th GoGrid wbsit (onlin) Availabl: [17] Th GoGrid wbsit (onlin) Availabl: [18] Th Opsourc wbsit (onlin) Availabl: Agrmnt [19] Th Opsourc wbsit (onlin) Availabl: [20] Th Nphoscal wbsit (onlin) Availabl: [21] Th Nphoscal wbsit (onlin) Availabl: [22] Th Bit rfinry wbsit (onlin) Availabl: [23] Th Bit rfinry wbsit (onlin) Availabl: [24] Th Microsoft wbsit (onlin) Availabl: [25] Th Microsoft wbsit (onlin) Availabl: [26] Th savvisdirct wbsit (onlin) Availabl: [27] Th savvisdirct wbsit (onlin) Availabl: [28] Th Joynt wbsit (onlin) Availabl:http://joyntcom/company/policis/cloud-hosting-srvic-lvlagrmnt [29] Th Joynt wbsit (onlin) Availabl: 2013, IJARCSSE All Rights Rsrvd Pag 101

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