How To Write A Powerpoint Powerpoint Commandbook For A Data Center

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1 Internatonal Journal of Innovatve Research n Scence, Engneerng and Technology (An ISO 3297: 2007 ertfed Organzaton) VM Assgnent Algorth Based ost Effectve achng n loud outng Raya.R 1 Assstant Professor,Det of outer Alcatons, Bannar Aan Insttute of Technology, Sathyaangala, Inda 1 Astract : loud alcatons are evolvng that offer data anageent servces. The alcatons that nvolved n heavy I/O actvtes n the loud Technology, utlzes ost of the servces fro achng. achng the data ay e ether satal data or teoral data. The Local volatle eory ght e an alternatve suort for ache, ut the caacty and the utlzaton of host achnes reduces ts usage. The exstng syste rovded the ache as a Servce (aas) odel as an addtonal servce along wth Infrastructure as a Servce (IaaS). Partcularly, the loud Provder sets a large collecton of eory that can e dynacally searated and allocated to standard nfrastructure servces as Dsk cache. An effectve cache echans known as the elastc cache syste rovdes the feaslty of aas usng dedcated reote eory servers. The novel rcng schee rovdes the axzaton of cloud roft whch gves the guarantee for user satsfacton. The erforance degradaton occurs due to ncreasng n the utlzaton of Energy. The roosed syste utlzes Vrtual Machnes (VM) and dong server consoldaton n a data center, y whch a loud rovder can reduce the total Energy consuton for servcng the clents as well as ncreasng the resource avalalty n the data center. Multle coes of VMs are created and lace these coes on the servers y usng dynac rograng to reduce the total energy consuton. The councaton araeters such as latency, andwdth, and dstance are consdered n akng the decson of assgnng VMs to the servers. The algorth s leented wth the hel of the sulaton tool (louds) and the result otaned fro ths reduces the energy utlzaton and also ncreases the erforance. Keywords - aas, Reote Meory, Energy Effcency, Vrtual Machne, VM Assgnent algorth I. INTRODUTION loud outng s a technology that uses the nternet and data centers to antan data as well as alcatons. loud outng allows usness and consuers to access ther ersonal fles fro any couter va nternet. The loud sly denotes the default syol of the nternet n dagras and the outng encoasses the coutaton and storage. Ths technology allows ore effcent outng y centralzed storage, rocessng, and andwdth. A sle exale for ths loud outng s Gal, yahooal etc. There s no need of software or server to use the. Just an nternet connecton s needed to start sendng an eal. There s no need to worry aout the nternal rocessng. A cloud servce rovder s the resonsle for all servers and e-al anageent. The analogy s If you want to stay n henna for one day, would you uy a house? The users get to use the software alone and enoyng the enefts of loud outng. For nstance, a we server (e.. a sngle couter)can run wthout a loud outng. It eans the couter can serve 500 ages er nute. If the weste ecoes oular, the audence wll deand for ore ages. At that te, the server ecae slow down and the audence loses ther nterest. For ths, a server should ove to the loud, you should rent oyrght to IJIRSET

2 Internatonal Journal of Innovatve Research n Scence, Engneerng and Technology (An ISO 3297: 2007 ertfed Organzaton) couter ower fro the loud servce rovder who has thousands of servers, that all connected together allows sharng of work aong each other. Ths solves the revous roles. It rovdes Pay-as-you-go odel whch denotes you have to ay for how uch you use. We have to ay ore rent for the extra usage. The ultate goal of loud econoy s to otze 1) user satsfacton and 2) loud roft. A. loud Storage: Over the decades, the g nternet ased coanes lke Aazon and Google etc dentfed that only a sall aount of data storage caacty s used. Ths leads to the rentng out of sace and storage of nforaton on reote servers. Inforaton s then cached on ether deskto couters or ole hones or other nternet-lnked devces. Aazon Elastc coute (E2) and the sle storage solutons (s3) are the current est avalale facltes. In the cloud, there are three searate level on whch you can cache. They are the server, load alancer and ontent Delvery Network (DN). In ths aer, the data s cached on the server. The Energy Effcency s low n ache servces. That can e roved wth the hel of Energy Effcent algorths whch has een descred elow. II. RELATED WORKS A. I/O Vrtualzaton Vrtualzaton defnes the searaton of a resource or request for a servce fro the hyscal entty whch s underlyng. I/O Vrtualzaton s a ethodology to rove the erforance of servers. Due to Vrtualzaton overhead, I/O oeratons are ore exensve than a natve syste. The sgnfcant I/O overhead wth the age flng technque can e relaced y the ecy functons to avod the overheads [10]. The I/O erforance can e otzed wth the hel ofa Vrtual Machne Montorr (VMM). The I/O erforance overhead can e tackled y dong full functonal reakdown wth the hel of roflng tools [5]. After the ortance of Vrtualzaton s known, hardware level features ecoe oular. It has een evaluated to seek for near Natve erforance. The Intel Vrtualzaton technology s used to rovde etter I/O erforance [7]. All these focuses only on Network I/O. The dsk I/O wll e consdered n cache devce to rove the low dsk I/O erforance. To handle ultle alcatons, Vrtualzed servers requre ore network andwdth connectons to ore networks and storage. In vrtualzed data centers, I/O erforance roles are occurrng y runnng ultle Vrtual Machnes (VMs) on one server. Ths can e overcoe wth the hel of I/O Vrtualzaton. B. ache Devce ooeratve ache s a knd of Reote eory cache whch roves the erforance of a networked fle syste. It uses clent eory as a cache. Ths cachng schee s effectve ecause Reote Meory s faster than a local dsk of the clent who s requested. The advanced Buffer anageent technque for ooeratve cachng has een ntroduced ased on the degree of localty. Ths ehaszes the data that has hgh localty should e laced n the hgh-level cache and the data that has low localty should e laced n a low-level cache. The ooeratve cachng syste s also desgned at the Vrtualzaton layer reduces the dsk I/O oeratons for shared workng sets of vrtual achnes. To rove the I/O erforance of a local dsk nstead of a reote dsk y usng Reote Meory as a ache n storage area network, Reote Drect Meory Access (RDMA) s used. The data anageent syste utlzes ether Sold State Drve (SSD) or the Hyrd Dsk Drve (HDD) accordng to data usage atterns. However latency of an SSD s stll hgher than Reote Meory (RM). A new aroach called RAM loud whch reduces the latency y storng the data entrely n DRAM of dstruted systes [9]. But RAMloud ncurs ore cost and hgh usage of Energy. The low dsk I/O Perforance can e enhanced wth the hel of ache as a Servce (aas) odel. Ths s an addtonal servce wth IaaS. oyrght to IJIRSET

3 Internatonal Journal of Innovatve Research n Scence, Engneerng and Technology (An ISO 3297: 2007 ertfed Organzaton). ache as a Servce Exstng loud focus on the aas odel whch conssts of two echanss: an elastc cache syste and a servce odel wth rcng schee. The elastc cache uses RM ased cache at the lock devce level whch s exorted fro dedcated eory servers. The elastc roertes are On-deand allocaton and reducton of storage and outng resources. The elastc cache syste can use any of the ache relaceent algorths. VMs utlze RM to rovde a necessary aount of cache on deand. The exorted eory can e seen as avalale eory ool. The elastc cache uses ths eory ool for VMs. To deloy the elastc cache syste, servce coonents are necessary. The users can choose ther cache servce accordng to ther cache requreent. The elastc cache syste conssts of two coonents.e. VM and a cache server. A VM deands RM to use as a dsk cache. A server can have several chunks. The chunk denotes the eory sace. If VM wants to access RM, a VM should ark ther rghts on assgned chunks and then t uses that chunk as a cache. When ultle VMs try to ark ther rghts on the sae chunk concurrently, the conflct can e elnated wth safe and Atoc chunk allocaton ethod. It roves the erforance and rovdes relale envronent. The effectve use of caacty and utlzaton s not lted n ths odel. The servce odel descres the odelng cache servces and rcng odel. Ths servce odel descres two aas tyes. They are Hgh Perforance (HP) whch uses LM as a ache and Best Value (BV) whch uses RM as a cache. The goal of servce odel s to reduce the actve nuer of hyscal achnes. The cost eneft of ths aas odel s Proft Maxzaton and Perforance roveent. But t consues ore Energy to rove the erforance effectveness. The total cost of the syste wll e hgh as well as t gves hgh colexty. D. Energy Effcent Algorths The aor ssues n loud coutng are rovng the Energy Effcency. It can e done wth the hel of 1) Energy Aware onsoldaton Technque 2) Dynac VM Manageent Algorth 3) Power and Mgraton cost aware Alcaton laceent and 4) Server onsoldaton. Energy Aware onsoldaton Ths technque s used to reduce the total Energy consuton n a loud outng syste. The server s odeled as a functon of PU and dsk utlzaton. The erforance can e deterned only for sall nut sze. It focuses only on the scalalty of the syste and t does not nvolve n the nzaton of oeratonal cost durng the role of assgnng VMs on hyscal servers rovdes a aor drawack of the syste. Dynac VM Manageent Algorth Ths algorth reduces the total ower consuton wth a restrcton on SLA of each VM or nzes the SLA volaton rates y consderng a fxed set of actve servers. Power-Aware VM Placeent Ths algorth s desgned for heterogeneous servers to reduce the total Energy consuton. It does not consder ultle coes of VM and consders only one denson of resource n the servers rovdes a aor drawack of ths algorth. The roosed aer focuses on Server onsoldaton to overcoe all the drawacks whch are descred aove. III. ENERGY EFFIIENT ASSIGNMENT ALGORITHM The Energy consuton can e reduced wth the hel of an Energy Effcent Assgnent algorth and ncreases the resource avalalty n the data center. A. Data enter Manageent A data center conssts of a nuer of heterogeneous servers fro a well-known server tyes. The servers of a gven tye are desgned y ther rocessng caacty or PU ycles ( c ) or Meory Bandwdth (M ). The Energy cost s oyrght to IJIRSET

4 Internatonal Journal of Innovatve Research n Scence, Engneerng and Technology (An ISO 3297: 2007 ertfed Organzaton) related wth Power utlzaton. The oeratonal cost of the syste s the total Energy cost for servcng all clent requests. The Energy cost can e calculated y the server Energy consuton y the duraton of te n seconds (T S ). The ower cost of councaton resources s also ncluded n the data center ower cost. The clent s assued as VM. The aount of resources whch s needed for each clent s deterned wth the hel of workload redcton. Each VM can e coed to dfferent servers whch ly the requests can e assgned to ore than one server that s generated y a sngle clent. Therefore uer ound L lt the axu nuer of coes of VM n the data center. If ultle coes of VM have to e laced n dfferent server eans, t should satsfy the condtons whch are gven elow y Where c c...( 1) and...( 2) denotes the orton of the th server PU ycles and Meory BW assgned to the VM whch s related to the th clent. c, c - Requred total rocessng caacty and eory BW for the th clent, - Total PU ycle and Meory BW of the th server. y - a seudo- Boolean factor to dentfy whether VM related to a clent s assgned to the server or not. PU PU VM1 VM1 1 ST OPY BW BW PU VM1 2 nd OPY BW Fg 1.An exale of ultle coes of VM The onstrant (1) shows the suaton of the reserved PU cycles on the assgned servers to e equal to the requred PU cycles for a clent. The onstrant (2) shows the rovded eory BW on assgned servers to e equal to the requred eory BW for the orgnal VM. Ths condton enforces not to gve u the Qualty of Servce (Quos) for the clents. B. Reducng Energy ost of Data enter oyrght to IJIRSET

5 Internatonal Journal of Innovatve Research n Scence, Engneerng and Technology (An ISO 3297: 2007 ertfed Organzaton) Data center anageent s resonsle for allowng the VMs n to the data center to reduce the Energy cost of the data center. The VM ontroller (VM) s resonsle for dentfyng the resource requreents of the VMs and lacng these on the servers as well as VM graton to nze the erforance overhead. The VM erfors these oeratons ased on two dfferent otzaton rocedures. They are 1) se-statc otzaton and 2) Dynac otzaton. Se-Statc otzaton has to e done erodcally whereas dynac otzaton can e done only whenever t s requred. Here, se-statc otzaton rocedure s focused. In ths technque, the resource requreents for VMs are assued to e dentfed ased on the SLA secfcaton for the next decson erod. The Energy cost of ths otzaton can e done wthout consderng the revous decson erod [11]. The functon of se-statc otzaton n the VM s to decde whether to create several coes of VMs on dfferent servers and assgn VMs to the servers. By consderng the fxed ayents y the clent for loud servces they use, the total Energy cost of actve servers n data center gets reduced. Ths wll ncrease the resource avalalty n the data center.. VM Mgraton VM graton rovdes a aor advantage n loud outng va load alance n data centers. It s ost enefcal n case of certan workload changes. VM graton s erfored to nze the workload changes n a loud outng envronent. VM graton reduces the graton cost wth the hel of se-statc otzaton. D. Dynac rograng A local search ethod s roosed to fnd out the nuer of coes for each VM and lace these coes on servers to nze the total cost n the syste. Intally the threshold can e set y the loud rovder. The all servers wth utlzaton less than the threshold eans, the total Energy consuton wll e reduced. The utlzaton of the server s defned as the axu resource utlzaton n dfferent agntude. The forula of the role s gven y y L c...( 3)......( 4) Where L denotes the axu nuer of servers whch s allowed to serve the clent. The constrant (3) descres the needed rocessng caacty s gven. The constrant (4) guarantees that the nuer of coes of VM does not exceed the hghest ossle nuer of coes. To dentfy the under-utlzed servers, each of the servers s turned off one y one. Wth the hel of dynac rograng ethod, the total Energy cost of utlzaton s deterned y lacng ther VMs on other actve servers. The dynac rograng s ntroduced to dentfy the nuer of coes of each VM and assgn these VMs to the servers. Ths wll reduce the total Energy consuton of a syste n a loud outng envronent. E. Server onsoldaton Server onsoldaton s defned as the assgnent of ultle VMs to a sngle hyscal server. In a loud outng Syste, Server onsoldaton s an effcent aroach to nze the total Energy consuton and rovdes the etter utlzaton of resources. A sngle server s enough to consoldate VMs whch s located n ultle under-utlzed servers wth the hel of VM graton technology and the reanng servers can e set to the ower-savng state.e. y turnng of the unused achnes. Server onsoldaton should consder the SLA constrants. The SLA constrants ay e resource related (e.g. eory sace, storage sace, network andwdth) or erforance related (e.g. Throughut, relalty, scalalty). The stes nvolved n an Energy Effcent Assgnent algorth s oyrght to IJIRSET

6 Internatonal Journal of Innovatve Research n Scence, Engneerng and Technology (An ISO 3297: 2007 ertfed Organzaton) Ste 1: Intally and for each server s set to zero. Ste 2: VMs are sorted ased on ther rocessng requreents n decreasng order. Ste 3: For every VM, a ethod ased on DP s used to dentfy the nuer of coes laced on the server. Ste 4: The Energy cost can e calculated for assgnng a coy of the th VM to a server k s k ( ) P P o c....(5) Where α denotes the sze of the assgned VM to the server. The frst ter n (5) s the cost related to PU utlzaton of the server. The second ter denotes the relaceent of the constant Energy cost of the actve server. The can e calculated as ( u Ste 5: Fnd the actve and nactve servers. For actve servers, value of cost s decreented y ε. Ste 6: alculate cost for each assgnent w.r.to L ) Mn y c y L... (6) ()......( 7) (8) Where P denotes the server whch s oth actve or nactve servers and y α k denotes the assgnent araeter. The councaton resources lke latency, andwdth and dstance araeters are consdered here n decson akng. Dynac Prograng s used to fnd the est assgnent decson. VM Assgnent Algorth The algorth shows the assgnent soluton for each VM. Inuts: o o T, B, D, T d,, P, P, c, c, L, c, c, c,,,, B, D, Oututs: d d,,,, ( s constant n ths alg) P= { }, B= { }, D= { }, T= { } For (k = 1 to nuer of server tyes) ON=0; OFF=0; For (α = 1 to L ) = (α / L ) / = (α / L ) / = (α / L ) / = (α / L ) / t d t o o oyrght to IJIRSET

7 Internatonal Journal of Innovatve Research n Scence, Engneerng and Technology (An ISO 3297: 2007 ertfed Organzaton) k (α) = ) J ON = { s k (1- ) ; (1- ) ; (1- ) ; (1- ) } J OFF = { s k =0, (1- ) =0, (1- ) =0, (1- ) =0,(1- ) } Foreach ( s k ) If ( J ON & ON< L ) P = P {}, ON++, cost (α) = c k (α) - ε B = B {}, ON++, cost (α) = c k (α) - ε D = D {}, ON++, cost (α) = c k (α) - ε T = T {}, ON++, cost (α) = c k (α) - ε Else f ( J OFF & OFF< L ) P = P {}, OFF++, cost (α) = c k (α) B = B {}, OFF++, cost (α) = c k (α) D = D {}, OFF++, cost (α) = c k (α) T = T {}, OFF++, cost (α) = c k (α) X = L, and Y = axsze (P, B, D, T) Foreach ( (P, B, D, T)) For (x = 1 to X) D[x,y]= nfnty; //Auxlary X Y atrx used for DP For (z=1 to x) D[x,y]=n(D[x,y],D[x 1,y z]+ cost(z)) D[x,y]=n(D[x,y], D[x 1,y]) Back-track and udate s IV. SIMULATION RESULTS In cloud coutng, Sulaton can e done wth the hel of louds. oare wth the tradtonal VM Placeent Algorth, the roosed odel of the VM Assgnent algorth s effcent. The councaton araeters such as andwdth, dstance, and latency are consdered n akng decson of assgnng VMs to servers. Ths wll rove the erforance of the syste y reducng the energy cost of the server. oyrght to IJIRSET

8 Internatonal Journal of Innovatve Research n Scence, Engneerng and Technology (An ISO 3297: 2007 ertfed Organzaton) Fg 2. Noralzed total energy cost of VM assgnent technques for dfferent servers Fg 2. descres the no of orgnal VMs versus the Energy cost whch shows the reducton n energy cost u to 10-15% than revous aroaches. V. ONLUSION AND FUTURE WORK In ths aer, an algorth s roosed to nze the total Energy cost y consderng the councaton resources araeters such as latency, andwdth and dstance whle akng decson n assgnng VMs to servers. Ths ethod also ncreases the resource avalalty n the data center. loud rovder can decde how to servce VMs wth g rocessng resource requreents and how to dstrute the clent request. For future work, other resources such as secondary storage can also e consdered n ths decson akng. Moreover, dfferent ethods can e rovsoned for consstency etween VM coes and falure recovery. REFERENES [1] Hyuck Han, Young hoon Lee, Woong Shn, Hyungsoo Jung, Heon Y. Yeo and Alert Y. Zoaya, Fellow, ashng n on the ache n the loud, VOL. 23, NO. 8, August [2] M.D. Dahln, R.Y. Wang, T.E. Anderson, and D.A. Patterson, ooeratve achng: Usng Reote lent Meory to Irove Fle Syste Perforance, Proc. Frst USENIX onf. Oeratng Systes Desgn and Ileentaton (OSDI 94), [3] T.E. Anderson, M.D. Dahln, J.M. Neefe, D.A. Patterson, D.S.Rosell, and R.Y. Wang, Serverless Network Fle Systes, AM Trans. outer Systes, vol. 14, , Fe [4] H. K, H. Jo, and J. Lee, XHve: Effcent ooeratve achng for Vrtual Machnes, IEEE Trans. outers, vol. 60, no. 1, , Jan [5] A. Menon, J.R. Santos, Y. Turner, G.J. Janakraan, and W.Zwaeneoel, Dagnosng Perforance Overheads n the Xen Vrtual Machne Envronent, Proc. Frst AM/USENIX Int l onf. Vrtual Executon Envronents (VEE 05), [6] L. herkasova and R. Gardner, Measurng PU Overhead for I/O Processng n the Xen Vrtual Machne Montor, Proc. Ann. onf.usenix Ann. Techncal onf. (AT 05), [7] X. Zhang and Y. Dong, Otzng Xen VMM Based on Intel Vrtualzaton Technology, Proc. IEEE Int l onf. Internet outng n Scence and Eng. (IISE 08), [8] J. Lu, W. Huang, B. Aal, and D.K. Panda, Hgh Perforance VMMByass I/O n Vrtual Machnes, Proc. Ann. onf. USENIX Ann. Techncal onf. (AT 06), oyrght to IJIRSET

9 Internatonal Journal of Innovatve Research n Scence, Engneerng and Technology (An ISO 3297: 2007 ertfed Organzaton) [9] J. Ousterhout, P. Agrawal, D. Erckson,. Kozyraks, J. Leverch, D. Maze`res, S. Mtra, A. Narayanan, G. Parulkar, M. Rosenlu, S.M. Rule, E. Stratann, and R. Stutsan, The ase for RAMlouds: Scalale Hgh-Perforance Storage Entrely n DRAM, AM SIGOPS Oeratng Systes Rev., vol. 43, , Jan [10] E.R. Red, Drual Perforance Iroveent va SSD Technology, techncal reort, Sun Mcrosystes, Inc., 2009 [11] S. Srkantaah, A. Kansal, and F. Zhao, Energy aware consoldaton for loud outng, In roc. of the 2008 conference on Power aware outng and systes (HotPower'08) [12] A. Verrna, P. Ahua and A. Neog, Maer: Power and graton cost aware alcaton laceent n vrtualzed systes, In roc. Of the 9th AM/IFIP/USENIX Internatonal Mddleware onference oyrght to IJIRSET