The Objective Function Value Optimization of Cloud Computing Resources Security

Transcription

1 Open Journal of Optmzaton, 2015, 4, Publshe Onlne June 2015 n ScRes. The Objectve Functon Value Optmzaton of Clou Computng Resources Securty Allocaton of Artfcal Frefly Algorthm Xaox Hu School of Computer an Communcaton Engneerng, Unversty of Scence an Technology Bejng, Bejng, Chna Emal: tnasabrna@126.com Receve 16 March 2015; accepte 12 May 2015; publshe 15 May 2015 Copyrght 2015 by author an Scentfc Research Publshng Inc. Ths work s lcense uner the Creatve Commons Attrbuton Internatonal Lcense (CC BY). Abstract Base on the current clou computng resources securty strbuton moel s problem that the optmzaton effect s not hgh an the convergence s not goo, ths paper puts forwar a clou computng resources securty strbuton moel base on mprove artfcal frefly algorthm. Frst of all, accorng to characterstcs of the artfcal frefles swarm algorthm an the complex metho, t ncorporates the eas of complex metho nto the artfcal frefly algorthm, uses the complex metho to gue the search of artfcal frefles n populaton, an then ntrouces local search operator n the frefly moble mechansm, n orer to mprove the searchng effcency an convergence precson of algorthm. Smulaton results show that, the clou computng resources securty strbuton moel base on mprove artfcal frefly algorthm propose n ths paper has goo convergence effect an optmum effcency. Keywors Clou Computng Resources, Securty Dstrbuton, Improve Artfcal Frefly Algorthm, Complex Metho, Local Search Operator 1. Introucton Clou computng servce moel can save a lot of nvestment cost, get r of resources such as regonal restrcton an tme lmtaton, an complete the nees of fferent users for varous calculatons, storage, etc. [1]. The ratonal selecton of workflow task scheulng strategy wll have mportant nfluence on clou computng effcency, performance, etc.; the unreasonable scheulng may result n resource waste an cannot meet the e- How to cte ths paper: Hu, X.X. (2015) The Objectve Functon Value Optmzaton of Clou Computng Resources Securty Allocaton of Artfcal Frefly Algorthm. Open Journal of Optmzaton, 4,

2 man of users. At the same tme, n the process of scheulng, because the resource noes jtter or lose effcacy, t wll prouce the securty threats such as tasks to perform or elay [2]-[4]. So through n-epth analyss of workflow clou envronment task scheulng problem, esgnng safe an reasonable workflow task scheulng algorthm s of great sgnfcance [5]. At present the latest research on the strbuton of moble clou computng resources s manly concentrate on the applcaton of clou computng n moble termnals. The recton of the present stuy was to make the applcaton of moble clou computng run on resource-constrane moble termnals, an t can also run on the clou base on the Internet [6]-[8]. So the lmte resources of moble termnal can easly gve the complex computng tasks, communcaton tasks an other busness whch nees larger resources to clou to complete. B. Chun manly ncrease the number of executons to confgure CloneClou clou resources, but wthout conserng the actual runnng conton of the user termnal. X. Zhang mae some prelmnary research on the resource management to flexble applcaton servces of clou computng network. Oberhere et al. through the clou computng resources optmzaton, transferre antvrus servces from moble termnal to clou computng network, an thus reuce the calculaton buren of moble termnal whch was resource-constrane. Goayl an Carter presente an encrypte search mechansm base on clou computng. D. Huang et al. put forwar the moble clou computng network archtecture. In ths archtecture, n orer to use the clou computng network an moble termnal resources more reasonably, the author proposes a moble termnal noe as a network noe n the clou servces ntegrate nto moble clou computng network. In orer to more effectvely use clou computng resources, some researchers have propose a kn of resource allocaton an economc optmzaton moel base on the moble clou computng network. In a gven allocaton of resources uner the conton of moble clou computng network, every ecson step of the moel can optmze the allocaton of resources to fferent servces, an accorng to the state of moble clou computng network resources, the clou computng tasks transfer between moble termnal an moble clou computng network. G. We et al. expoune a kn of resource allocaton management moel base on game theory; ths moel can ynamcally allocate the clou computng network resources accorng to the user s qualty of servce (QoS) requrements. Accorng to the epenences of task n Heterogeneous envronment, n orer to meet the eman of hgh performance an mprove the effcency of task executon, Topcuoglu et al. presente two new scheulng algorthms, the Earlest Completon Tme of Heterogeneous Scheulng Algorthm (Heterogeneous Earlest-Fnsh-Tme, HEFT) an Crtcal Path Scheulng Algorthm (Crtcal Path-on-a-Processor, CPOP). Lan an Sun propose the key task scheulng algorthm uner the heterogeneous envronment; ths algorthm frst efnes the key tasks an le tme, an makes the task ahea of tme through the crtcal tasks be cope to the free tme slce of resources. Buyya et al. propose clou computng archtecture base on market resources localzaton, an gave the resource management strategy base on the market, to support the resources localzaton of servce level negotaton [9]-[11]. Ths paper, accorng to the characterstcs of clou computng, puts forwar a clou computng resources securty strbuton moel base on mprove artfcal frefly algorthm, n orer to mprove the securty of clou computng resources allocaton. 2. Artfcal Frefly Algorthm The evoluton process of the basc artfcal frefly algorthm s completely nspre by nature frefles group behavor, the group nteracton s pushe by the ntensty of fluorescence ntensty an ts nfluence. In basc artfcal frefly algorthm, frst we strbute the frefles whch have the same content of fluorescen an same nepenent ecson oman n the target space we nee to search by ranom, they communcate n ther own ecson oman, thus affectng the nvual behavor of the frefles aroun. Accorng to the bologcal characterstcs of nature frefles an the matchng mofy rules of artfcal frefly algorthm, the basc artfcal frefly algorthm n the algorthm can be ve nto sx stages, etals are as follows: (1) The ntal eployment phase n frefles were ranomly strbute n D mensonal search space, each frefly has the same ntal raus r 0 of the nucton an fluorescence ntensty l. Among them the ntal raus 0 r 0 of the nucton s ece by the raus of sensor. 41

3 (2) On the bass of the objectve functon mathematcal expresson f to calculate the objectve functon value F of all frefles locatons, an n accorance wth the followng formula, we transform t nto the corresponng fluorescence ntensty value: ( 1) 1 ( 1) J t+ = F t+ (1) ( 1) ( 1 ) ( ) γ ( 1) l t+ = p l t + J t+ (2) (3) Determne the neghbor At ths stage, artfcal nucton frefles search the stance neghbor R n the sensng raus, the brghtness neghbor L n the sensng raus, eventually etermne the neghbor set N : { } ( ) : ( ) ( ) && (, ) ( ) N t = j R t L t j < r t (3) As can be seen from the Fgure 1, for frefly, the stance neghbor have j, k n the sensng raus, an then by calculatng ts brghtness an probablty to etermne the recton of movement; For frefly j, there s j only stance neghbor n ts sensng raus r ; For frefly k, t belongs to the empty set. (4) Choose the movng objects Accorng to the surely neghbor set N ( t ), calculate the roulette probablty ρ j, compare the value of each ρ, calculate an etermne a movng object j : j ρ = j lj ( t) l( t) lk ( t) l( t) k N ( t) (4) (5) Move the frefles Move the frefly accorng to the movng recton O j = j j O j to the selecte object j : ( ) ( ) ( ) ( ) x t x t x t x t (5) Fgure 1. Neghbor efnton fgure. 42

4 ( 1) ( ) x t+ = x t + s O (6) j (6) Aaptve sensng raus After frefly movng, we wll mofy the next teraton of the sensng raus number of neghbor collecton: { 0 { ( )}} ( 1) mn, max 0, ( ) β ( ) t r aaptvely accorng to the r t+ = r r t + n N t (7) The change of r change the local ecson oman, to select ts neghbors n the form of ths change, the nvual sensng raus changes, n vew of the entre group, group behavor of multple nvuals show as the separate group behavor, the number of the clusterng theory s equal to the number of clusterng. 3. Artfcal Frefly Algorthm Optmzaton 3.1. Populaton Search Optmzaton Base on the Complex Metho Increase wth the mensons of the functon, the soluton space of the functon s expanng raply, cause the complexty of the functon. So n the later stages of artfcal frefly algorthm, there wll be a lot of ba frefles aroun the optmal frefles, frustrate the optmzaton of the algorthm precson, so that the algorthm n the fnal optmzaton precson wll have very bg efects. Accorng to characterstcs of the artfcal frefles swarm algorthm an the complex metho, ncorporate the eas of complex metho nto the artfcal frefly algorthm, use the complex metho to gue the search of artfcal frefles n populaton. Algorthm thought graph escrpton as shown n Fgure 2. In the teraton, we wll use the mprove equaton n ths paper: 1 k x k = 1 x = (8) ( ) x = x + λ x x (9) r D D On the base of the complex metho of populaton search optmzaton steps as follows: (1) Ranom ntalzaton k( k = 2n) frefles an menson wthn the scope of the feasble regon, the parameters whch s neee to ntalze; (2) Ranom ntalzaton ( = 1,, k) frefles n the poston of the objectve functon search space; (3) Use the formula (8) to get the center x of the kth ponts; (4) Each frefly wthn ther own ecson-makng oman x, through the comparng makes sure the set of N t whch has hgher lucfern; frefly ( ) Fgure 2. Schematc agram of the complex metho. 43

5 (5) Through the comparson of fluorescen value, fn out the worst frefly lucfern values, then accorng to the formula (9) to reflect; (6) Accorng to the formula (4) calculatng the probablty of frefly move to the neghborhoo frefly j. Usng roulette metho to select nvual j, then move the frefly, an accorng to the formula (6) to upate locaton; (7) Accorng to the formula (7), ynamc upate ecson oman raus of frefles Optmzaton Effcency an Convergence Precson Optmzaton In basc GSO algorthm, each frefly n ts ecson-makng oman fns the frefly whch has brghter lucfern, then they move to t, they use roulette metho to move to t base on a certan probablty, ths wll make the frefly moble poston s not the best locaton n ecson oman, t wll reuce the optmzaton effcency an convergence precson of the algorthm. In ths paper, the frefly moble mechansm s ntrouce n local search operator, algorthm thought graphcs can be escrbe n Fgure 3. The concrete mplementaton steps of GSO algorthm wth local search operator are: (1) Intalzes the frefles number an menson of search space, the parameters whch s neee to ntalze; (2) Accorng to the formula (2) calculate the frefly s values of fluorescen l ( ) poston x ( t ) at tme t ; (3) Each frefly wthn ther own ecson-makng oman r ( ) of frefly N ( ) t at the corresponng t, through the comparng makes sure the set t whch has hgher value of fluorescen; (4) Accorng to the formula (4) calculate the probablty that frefly move to the neghborhoo frefly j. Usng roulette metho to choose nvual j ; (5) Make the nvual j as the current optmal poston to local search; (6) Make sure the new movng recton by local searchng, an accorng to the formula (6) to upate the locaton; (7) Accorng to the formula (7), ynamc upate ecson oman raus of frefles. 4. Algorthm Smulaton In orer to verfy the effectveness of the mprove algorthm propose n ths paper, we o the smulaton experments on t. We o the clou computng resources securty strbuton optmzaton effcency an convergence precson test to the stanar artfcal frefly algorthm an mprove artfcal frefly algorthm. The result s shown n Fgure 4 an Fgure 5. Fgure 3. Moble agram of the mprove algorthm. 44

6 Fgure 4. Contrast optmzaton algorthm effcency stanars an mprove algorthm. Fgure 5. Comparson of convergence between the stanar algorthm an mprove algorthm. 45

7 From the smulaton results showe that the propose mprove artfcal frefly algorthm has better convergence an optmzaton effcency, an the applcaton n the clou computng resources securty strbuton s goo. 5. Concluson Clou computng s a way of calculaton whch s evelope wth the evelopment of computng an communcatons technology n recent years. How to make full use of the exstng clou computng resources, through the reasonable allocaton of clou computng resources between fferent areas to mprove the qualty of the clou computng securty servce an system returns of the clou computng network system, so as to mprove the rato of revenue an expenture of clou computng network, has become an ncreasngly promnent research topc n the clou computng network. The smulaton expermental results show that the mprove moel propose n ths paper has hgher optmzaton effcency an convergence, an t has goo applcaton effect. Funng Ths work was supporte by the Natonal Natural Scence Founaton of Chna (Grant No ). References [1] Yn, B. (2014) Clou Resource Allocaton Metho Base on Elastc Resource Ajustment. Telecommuncatons Scence, 11, [2] Sun, H. (2014) Desgn of Task-Resource Allocaton Moel Base on Q-Learnng an Double Orentaton ACO Algorthm for Clou Computng. Computer Measurement & Control, 10, [3] Zhou, Y. (2014) Resource Allocaton Controller Desgn Base on Feeback Control n Content Delvery Networks. Computer Measurement & Control, 10, [4] Zhou, X.B. (2014) An Optmzaton Approach of Vrtual Resources Allocaton Base on Partcle Swarm Algorthm. Journal of Chongqng Unversty of Posts an Telecommuncatons, 5, [5] Tan, G.Z. (2014) Evolutonary Algorthm towars Resource Allocaton of Concurrent Scheulng Multple DAGs n Clous. Applcaton Research of Computers, 9, [6] Chen, X.J. (2014) Vrtual Machne Resource Allocaton Algorthm n Clou Envronment. Applcaton Research of Computers, 9, [7] Sun, J.J. (2014) Resource Allocaton Scheme Base on Neural Network an Group Search Optmzaton n Clou Envronment. Journal of Software, 8, [8] Zhao, G.G. (2014) Energy Effcent Rao Resource Allocaton n Two-Ter Macro-Femto Cellular for Moble Clou Computng. Telecommuncatons Scence, 7, [9] Lu, D. (2014) Enhance Farness-Base Mult-Resource Allocaton Algorthm for Clou Computng. Journal of Xan Unversty, 3, [10] Zhou, J.C. (2014) User-Aware Resource Provson Polcy for Clou Computng. Journal of Computer Research an Development, 5, [11] Zhang, Y.F. (2014) Servce Resource Allocaton Base on Servce Level Protocol an Double Aucton Mechansm Desgn. Computer Measurement & Control, 4,