英文云计算cloud-computing-外文翻译

毕业设计说明书英文文献及中文翻译

学生姓名: 学号学 院: 计算机与控制工程专 业: 计算机科学与技术

20 年6月

英文文献

Clud Coputig

 .Cloud Cmputig a aiger evel

In man ays, cloud computi  i  simly a m tphor for h nteret, the incr a  g m ement f cpute and  ta r soucs to te Web.Bt ter ’s a d fference:  loud ompu i  represets a nw tipi  oit fr th vlue o neto  computing.It del vers igher efficiecy, assive salabilit, an fa  e , e ier software developmen . It’s bout new rgramng model  , new ITinfrastucture,a  the enaling of nw busin  s models.

or to e ev l ers and eterp is  who ant to mrace  u computig, Sun is dev oping ritical  echn o  s to dl ver en erp ise scale and sstemic qu lit  s to this new pradi:

(1) Interoprabil  ty—w   e m  t curen  l    offer c se latfom and ven   loc-in, dv loprs claor for interopeail  t. Sn’  pen-sure produ  stratg and Jav™principl  are fcu e on provdin interoperail  t for larg-scale ompui    our s. Thik f t  exist ng c oud “i   nd ”mr ng into a  w ite oe ble “It  cloud”where applicati sc  b oved to nd operate c ossultiple plat rms

(  igh-ensity horio al com    g—un is p oeering high-poerdensity comp   -nde  rchitect  es nd etreme-scle Infinibad fbri  s part of ur top-tie HPC dpoym t  . Thi  h ghdens  ty tecnoogy is   ing   orora dinto u  a e-  cale c oud de   gs.

(3)Data in te cl d—or han jus  comute   il  ties, cloudcmu ng is increas ng  bot p tasc le daa S’s pe Stoa   odcts o f r yb id dat srers wit unreede

  d  ff  inc and p  rformanc  for the m ging  a a-intensive co tin apl  cation ha will beco  key part fhe  lo ud.

Thse tehnoogy bet   e focse on driingore  ff  ient lr -scale cloud ep ymn  t t an provide te inf   truc ur for ex -generati  bus nss opportni  ies: so i  ne wors, lgr  thmic trading,cotinuou  is anals  s and so on. .Why C oud Compting?

(1)Cl ds Much More Than Cheap Coputin

C oud  putin b ings a new  ev l of efficincy an eoomy t   l  er ng IT resoures o deand— a in the pocessit opens up new bsiness ode  s ad arket oportunities.

Whilen people  ink of current clu cput ng offe ings s p ely“ay by  e drink” ompute ltorm  the’ ereally a conve g c    major in erdepede  IT trnds

T ficiecy— Minimize costs hee companies re onvertinghei  T os  s from apitl expe  es to perating exese trouh  echnooie  suh a  vir ualia ion. lud omuting be n as  way to mprove ifr  tucture r surce elyment anduti  iatio,bt fully eploi  ng thi  ifra tucture ventual y  as o a ew aplicat o dev lpentd l

Bus ness Agility—M imize   ur using IT as a ompe  it v wapon through ap  time o markt in erated application staks, inst   machne imag de oymn , nd petscle par le  p  ramin. Cloud cmputing  s mbraced as a cr  tica wayto rvlt oni  time to serv c . Bu ievi  ably t   e srv ce  u  be built on equa  l  novati e ra id-de lymet-infrastructure mode  s

To e sre, these  rends hve existd in the IT ndu  ry f  yea

  . Hwe  , the recen emergne f ma  s v n twor bndwdt and irtual     i  tehologie  has e bled th  tan foma io to a new services-r  ented nfrast cture.

loud omputig eales IT  gniza ions o i ra e harwae utilization ra es dratical    d   sca e up tossivecapacities in an  s ant—witho  onstatly havn to invest in ne infrastructure, tain ew ersonnel r   ce  e ew sftwa  It a so creates nw oportuniti  to u l a bet  er beed   twrk serice  , in less t e for lss money.

IT Ef   incy na Whole Ne Sa e

C    comuti  is  l  about effi   ency. It  ovides away o d  oy n aces  eveyting frm sigle systms  huge amoun s of IT rsourc s— o dmand in r a time, a  anaffordab e cost. I  k s high-performa e cop  e and h g-caac  ty st ae aailable t none  th a   dit card. nd  i e the e t clou  trategis ui   on c  ept  and tools thatdev l  rs lrad  w, clouds al o hae the potntial to edfine he relati  hip between  formation techo gy and the  velpe s and busin   nits t   dep d on   

educ cpi   l ependitres—lu comuting makes it ps ible or companie  to conve  t IT cs  s fromaital expense o oprt ng xpnse thouh technoogies  c as irt li t on.

ut t  co t of ruin a daaete —C ud comptingmprves infrastu tur t   i tion rates and  trealine re  ure manaement.For example, clus a lo for   lf-serv e provi onin hogh AIs, bring   a iher level of uomt onto the  tacn er    rducig man  mnt  sts.

El n   ov  rovis oning— loud coputing proide cal  g n demad,wich w   cbind with utility p i ing,

rem  s the eed to ove povisio toet demad. Wi h c oudcomputin, compnies can  c le u   mas   e capa itie  in anst t.

For thos wh  in cloud o ti  is ju  fluf akea  loser lo  at he c oud ferins tht are al eady avai  able.Majr It ne pr   ers mz .co, Google and ohes areleveragin t  ir infr   ructue inve  tmen   d “sharig” teirlarge-s ale ecnomics.  redy te andw th use by AaoWeb Services () e ed that associat  it  e   c  e e-tiling services. Forard- o i  enterp  se f all t e —roWeb 2.0 s  a tups  o gloa  n  rprises—a  e emba ingcloud compu ig to reduc inra  rcture costs.

Fas  er,More lexible Porammig

C ou comutin isn’t oly bo  hardare — t’  als aprorammng revolution.Agile,   y-toaces  , lightwe  ght Web prtocols— copld w th p rvasiv hriontall  c  ed a ch tctu e— c n   ce  er   eelop mnt yc les     im tomar  t with new pp  ict on nd services w u iess unctios ae nowju t a script awa.

Ac   a ed cy les— The cl d computing odel pr idesa fastr,mre effic  et a to   elp  e nw gen rtionof appl  atios a  se v ces.Faster d    pment nd t  t  g cycles means bsi sse ca accom  i h in hours what use to akedas e   r monts

Increas agility— Clod coputig acommdates hag likn ote  odel. or examp e,Animoto Prodc  ions, makers o a mshup tol ta  rea es vido frm images ad music usd clo comut ng to sca e up  om 50  erers to 3,500 in just three days.Cl   comuting can a  so po  de a w der  election o  mo  e

lightwe ight  d gi  e dve lpm t oo s s imp lify g nd speeig up th dev lopmen proce  s.

The imeiate ipct w ll be nprecee  ed   ex ilit in ervic reat  n nd  celrated develomen cycles.But a thesam time devel et f exiil  ty  uld  com con  aned   API  if they’re nottruly open C oud compu ing an uher ia nw era of roductivit fr evelopers if te bu ld on latformsthat ar designed to be fedra ed  thr tha en ra ized.But t re’s  jor shift nderway in  ogrming culture and the lnguag  that will be us  in clouds

oay, the intega ed, opti zd, open-sore A c ,MSQL, PH/erl/Pyt n(MP s ack is the peferred p   form  rbui din and eloin ew We plica ions and s vice  .Cloudomut  gill be te catalyst fr t  adoptio of   evn ewr tack f moe lighw  ght, gile too s   h as   ght  d no  en-s urc  eb serv r; Hadoop  h  ree Java so  wareframework that support  dt -intnsive dis  r buted ap  ica  ions; anMog  eFS, a tha  ables horiont l s a ing f  toag acrssa mbe  of m hines.

(2 Com el  ng New Oprtnitie  :The loud Ecosy tem

u clod coputing isn’t  ust bout a prolife  t on f Xen iage stack on a r   r  cted andfu o inrstru ue prider  . It’s also abut an emerging csystem of coplmnt y sric  s tha  provide comuting r sources suc as n-  p o clud as  act o, professional  rv cs o help in delomet,p  ial   d appli atio  o  t  uch a  dis   bute daaba s ad vir ual privte da cntrs fr he entie ran  o IT rviders and cnsumrs.

Thse  e ics pan the rane f ustoe requirmets, fr

indivdal developers nd sall startups to  re eterri     d thy cntinue to expn the leve  s f irtualization, a key arcit ctral opnent o   e c o  tha offr  ev -h ghr astrc   os of nderlyig servic s

()How d Cloud Coputin Stat

A a basic level,  loud copt ng is s mly a men   del ve  ig IT r soucs a   vices.Almost all IT reso   s a b d  ivered as a  oud serv   : pplications, compte ow , ora  ca   ity neto ing rogrammig to s, even comun ca  ns  ervices and colla  at  on too  .

Clou omputing bean as large-s    Interet serv ce prvers such s Google,Amzon,and ohers built out th  r i ra tru ture.An architectur erged mass vely scaled, orio all dist  uted syste esurces, as  rated as   rt  l IT  ervi s anmaaged   c tinuously c    gured,p     re ources. hs arc   ctual m el wa mmort lized byeorge G ldr in isOc obe  006 ired agazne ar   c   t  t  ed “The Information

Fctorie  .”The s  e  farms Gilder wrte abo  were rchi  ectrlly si la o gr d omutig,bthe e g d ar u ed o lo se y oup ed,   hni   coputig applictios, th sne  ou m   l wa beig pplied to In ernet se    cs.

oth cluds and grids are bi   to  cale horiontal y ve y efic entl.Both are uilt to withs and fa lures of indivdual elemnts o node . Both    hargd on  per-use    i  . ut whil   idstypical y procss batch jobs,with a defie   at  d   point, loud servics can be con nu s hat’  more, clus x n he type  f resour s avai  ab e—, atbass, nd Web s r  ce—and extend the appl   ab      t  Web nd  nterpr   eapplications

At te sm t , the oncep f ut  lity  put ng b ae a oc  of T design and perat  ons. As Nick Car obsered n his bok Te B  Si  c cmputing se vices infras  ruc   e wa eginin to  ra  l l th devel met o elect icity  s autility. Woudn’  it b gr t if ou cud purcha e compute re ourcs on dmad,  ly p   g for wht yu eed,whe yo  ed i  ?

Fo e     s,  loud comutin eas tere are no hardare acqu    ion costs, o sofware licnses or upgraes   mange,n new eployees o cnsul  ats t ir , o acilitie  to  ese,no cp ta co ts f any  nd—nd n  dde cs  s Js a me  rd,per-u  rate or a  xd subscr  tion f   U e only whato nt,pay  l forhat you us .

C oud computing actuall taes th utility model to the nxt lvel I  ’s a new an ev lved or o  uti   t  mp  ing inwhich mny di ern types of esoure (adwar  softarestorage cmunica o   ad so n can b combine ad rcoined o he fly nt he specif c capabilities or srvices c  om rs requi  e. From CPU cyc  es for HPC projects to  torag c pacity f  en rprise-rae backups o cop   e IDEs for sofwre deve   et  oud computing ca deliver v rtu l y any Tcapbility in real time Une th circustances i  is a  t se tha a broad r ge o rgan zations and indvidua s w ld  ik to  rhse “compting”   a  er  ce, and thos irms a rady builing hyersc   i  tri t  dat ete s woud neitbly cose t ein off rig  is     struct   as a ervice.

(4)Harns  ing Cloud  ting

So how des an individa o  bs  ess tke avant e o

he clou comuting tred? I  ’  ot ju t aout oading machne iages cnsi   ing of yor entie sofwae stack on  a p lic c oud    WS—ther ar svera di e nt ways t xploi  this ifrstrcture and xplor th ecosyst f new usines  odels.Use t  Cou

Te nmbr ad qalit f pub ic, comme  cia   vilablclou-base servic  offe  ng  s growing f  t. Using the cloud is   en the  st opti  for  ta  t   , resear h projct  ,Wb

2.0 d  lop s,or iche players who wat  siple ow-  s way   “load a  go.”  f ou’r an nternet startu toay ouwil  b madated by our ives   s t keep ou I p d toa minimum This  s c r a ly w t the cloud is or.

Le vera g t  C u

Typ cal y en rprises ar us ng pblic clus fo specifi fuctions ororklads. he c oud   an attactie altern  ive for

Deelopment and t sting —t  s   pe hap the  asi  t loud use case or nt rprises (not  ust s  artu  ve  oers) Whywait to o er s rves when you don’t even knw if te projec  wil  pas the proofof ocept

unction l offlodin—you can u e te cloud for sp cif c w kloads For exa  e mugMug oe   t  ige   mbnailig asa batch  o in the c oud.

Augenation— ous give yo a e op    fo anding pe k load or an ic pted s kes in dad fr   vies Tis  s a very tta tiv optio for ent rpr   e  ,bt a s ptentially on of the mst difficlt us cases. Succes  is depenenton the  tteulness of he pplica ion a he interdepndenc ith ther dat  e  s tht may need t b  ep ica ed  d load-balaned  ros  the two sit s.