The Investment Decson-Makn Inex System an the Grey Comprehensve Evaluaton Metho uner Hybr Clou Donln Chen 1, Mn Fu 1, Xueron Jan 2, an Dawe Son 1 1 School o Economcs, WHUT, Wuhan, Chna 2 School o Manaement, WHU, Wuhan, Chna Abstract. Amn at the problems exstn n the current stuy on the uncertan evaluaton an nelecte quanttatve analyss when the enterprses makn nvestment ecsons uner hybr clou envronment, ths paper conclues ve ncators that mpact ther ecsons. Then, t ntrouces the Grey Comprehensve Evaluaton System an oranzes experts n ran, so that the qualtatve ncators wll be more quante an the analyss more ntutve. Fnally select the most sutable proram when makn nvestment ecsons. Keywors: hybr clou, evaluaton nex, rey comprehensve evaluaton metho, nvestment ecson-makn. 1 Introucton As a new IT elvery moel at ths stae an wth ts avantae o low cost, lare scale an vrtualzaton, clou computn has become the th utlty, toether wth water, electrcty, as an telecommuncatons [1]. Accorn to ts operatonal moe, Clou computn can be ve nto three types: Publc Clou, Prvate Clou an Hybr Clou. Whle most customers o not want to mrate the system to all busness on the publc clou because o the lack o securty n publc clou [2], so that the " hybr clou "moel whch contans part o "prvate clou" an part o "publc clou "has become the eal soluton or customers. Hybr clous combne the avantae o both publc an prvate clous, so that enterprses can not only retan ther prvate clou core systems, but also some o the servces. To make IT nvestment ecsons s the way to escrbe the process o entcaton an soluton o envronmental choce behavor o the ecson-makers n the process o nvestment. At ths stae, the research o hybr clou s manly base on systems an technoloy, such as Len usn ranom keys enetc alorthm to solve the problem o the lowest-cost mx o customers uner the clou resource allocaton an so on. But n the current stuy uner hybr clou there weren t an nex system whch aects the nterty o enterprses to make nvestment ecsons, or the current mpacts about the servce ncators an the relatve lack o ata have cause the exstence o some cultes. However, n contrast to the qualtatve ncators, quanttatve ncators are more ntutve an convncn. To aress the ssue, ths paper summarzes ve ncators that mpact the IT nvestment ecsons, an ntrouces the Grey Evaluaton System to comprehensvely evaluate relate nex, presentn a quanttatve moel o these qualtatve ncators. D. Jn an S. Ln (Es.): Avances n CSIE, Vol. 2, AISC 169, pp. 171 176. sprnerlnk.com Sprner-Verla Berln Heelber 2012
172 D. Chen et al. 2 Combnaton Metho o Investment Decson-Makn Inex uner Hybr Clou Uner hybr clou, the actors that aect enterprses n nvestment ecson-makn nclue cost an Clou QoS (qualty o servce). Costs manly represent the cost o clou computn an clou storae. An the latter nclues ata storae, retreval an transmsson costs, whle CQoS nclun executon tme, securty, avalablty, relablty an other actors. Takn example by the computn moel o r an web servces, we can ene the computn metho o cost an CQoS. 1) Dene the expresson o total cost o customers uner hybr clou whle usn Cc to show the cost o clou computn an Cs to show the cost o clou storae. TCO Cc Cs (1) 2) Dene the expresson o cost o clou storae whle usn CS1 to show the cost o ata storae an Ct to show the cost o Clou transmsson. Cs Cs1 Ct Cs2 (2) 3) The total cost can be also ene as: TCO Cc Cs1 Ct Cs2 (3) 3 The Investment Decson-Makn Inex System o Corporatons uner Hybr Clou Uner hybr clou, a combnaton o customer-orente qualty o servce HCQoS larely epens on the securty, avalablty, relablty an executon tme o servce platorm. 1) Securty. Snce ther ata are store n the clou, the control o customer s ata totally epens on ther supplers. Saety has always been the key ncator o customers to make nvestment ecsons. 2) Avalablty. It manly reers to customers accesson to clou servce n a certan tme an uner certan contons. 3) Relablty. It means the capabltes or corporatons to prove customers wth stable an accurate servce. 4) Executon tme. It also means watn tme, reerrn to the tme requre or the system rom recevn commans to nshn ata analyss. Thereore, base on the characterstcs o enterprses n nvestment ecson-makn uner hybr clou envronment, the nex system s esne to nclue cost an qualty o servce, whle qualty o servce also nclues securty, avalablty, an executon tme.
The Investment Decson-Makn Inex System 173 F. 1. Investment Decson-makn system o Enterprses uner Hybr Clou 4 Inex Analyss o Investment Decsons Base on Gray Evaluaton Metho Four representatve optons are selecte as evaluaton objects, an the ray evaluaton metho s use to rate specal steps as ollows: Case I: rent all IaaS an SaaS publc clou. Case II: rent all IaaS publc clou, nclun vrtual servers an storae, bul prvate SaaS. Case III: rent vrtual servers o IaaS publc clou; bul the part o storae o IaaS clou an SaaS. Case IV: bul all IaaS an SaaS clou. (Consern the eprecaton o harware an sotware elements, all the ncators n the our cases are observe n 5 years.) 4.1 Bul Evaluaton Matrx Evaluaton o the actors o the rae s set at "hhest, hh, meum an low, assne to the scores o our, three, two an one, an the scores o 3.5, 2.5, an 1.5 are assne between them. Then oranze experts to score the actors n each case, constructn an evaluaton sample matrx. Assume that the number o the ray class s e (e=1,2,,). Snce there are our evaluaton ray class n ths case, e=1, 2, 3, 4.The corresponn our whtenn unctons are: 1 ( ) = / 4, 1, [4); [4, ); [ ). (4)
174 D. Chen et al. 2 ( ) = ( 6 ) 3 4 / 3, ( ) = ( 4 ) 1, / 2, / 3, / 2, ( ) = ( 2 ), [3); [3,6]; [6]. [2); [2,4]; [4]. [1); [1,2]; [2]. (5) (6) (7) I Ve represents the eth ray class o the actor V, the evaluaton-weht o the eth ray class o the V evaluaton nex n case S s: r e = (8) The ray evaluaton matrx n case S s: R ( re ) 4 = p (9) Table 1. The table o evaluaton quantzaton n nvestment proram Cost(ten thousan yuan) Securty Avalablty Relablty Executon tme Case I 1000 0.4 0.39 0.4 0.4 Case II 1500 0.52 0.49 0.49 0.5 Case III 2000 0.6 0.6 0.6 0.6 Case IV 4000 0.8 0.8 0.8 0.8 Then the weht vector s calculate as: λ= (0.3 0.2 0.1 0.25, 0.15). 4.2 Determne the Gray Correlaton Select the relatvely optmal value o every V n the evaluaton matrx, then compose the optmal reerence vector. The worst reerence vector s selecte n the same way. Fnally ntalze the matrx compose by these two vectors. Dene ξ ( k) = mn mn ( k) ( k) + ρ max max ( k) ( k) ( k) ( k) + ρ max max ( k) ( k) (10)
The Investment Decson-Makn Inex System 175 Then calculate the ray relatonal rae vector. In ths case, the ray correlaton actor relate to the optmal reerence vector s: γ x, x ) = (0.568, 0.4487, 0.581, 0.7061) ( b The ray correlaton actor relate to the worst reerence vector s: γ x, x ) = (0.568, 0.4487, 0.581, 0.7061) ( b 4.3 Comprehensve Evaluaton o the Four Cases Make an orer accorn to the two ray correlaton actors 1 v = 2 γ 1 + b γ The ray comprehensve evaluaton value o the our cases are: V=(0.5124,0.4384,0.3043,0.1408), the maxmum value o v s n Case I, so the best nvestment proram s case I. (11) 5 Concluson Ths paper rstly summarze the ncators o enterprses to make nvestment ecsons uner hybr clou envronment. Then evaluate each ncator by the ray evaluaton metho, takn ull avantae o the ambuty o experts to quanty these qualtatve ncators. Fnally prove the metho s practcally n actual project. Acknowleement. Ths research was supporte by the Natonal Natural Scence Fun o Chna uner Grant71172043, 71072077 an 70972094; the Natonal Technoloy R&D Proram 2011BAH16B02, the Funamental Research Funs or the Central Unverstes an Teachn an research projects o WHUT. Reerences 1. Buyya, R., Yeo, C.S.: Clou computn an emern IT platorms: Vson, hype, an realty or elvern computn as the 5th utlty. Future Generaton Computer Systems (25), 599 616 (2009) 2. Q, Z., Lu, C.: Clou Computn: State-o-the-Art an Research Challenes. Journal Internet Servces an Applcaton (1), 7 18 (2010) 3. B, X., Zhan, H.: Stuy on the Inluencn Factors an Moel o IT Investment Decson-makn Behavor. Journal o Intellence (3), 5 9 (2007) 4. L, X., Yan, H., Qu, N.: On the Theory o Sem-structure Decson-makn Fuzzy Optmzaton Metho o Investment Proram. Statstcs an Decson (14), 21 22 (2010)
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