Seminar Report Green Cloud

8/17/2019 Seminar Report Green Cloud

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Submitted by: Binaya Kumar PadhiRegd. No.: 1302001377


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BINAYA K!AR PA"#I 1302001377

Abstract

$%oud &om'uting i( o))ering uti%ity oriented I* (er+i&e( to u(er( ,or%d,ide. It enab%e(

ho(ting o) a''%i&ation( )rom &on(umer- (&ienti)i& and bu(ine(( domain(. #o,e+er data &enter(

ho(ting &%oud &om'uting a''%i&ation( &on(ume huge amount( o) energy- &ontributing to high

o'erationa% &o(t( and &arbon )oot'rint( to the en+ironment. ith energy (hortage( and g%oba%

&%imate &hange %eading our &on&ern( the(e day(- the 'o,er &on(um'tion o) data &enter( ha( be&ome

a /ey i((ue. *here)ore- ,e need green &%oud &om'uting (o%ution( that &an not on%y (a+e energy- but

a%(o redu&e o'erationa% &o(t(. *he +i(ion )or energy e))i&ient management o) &%oud &om'uting

en+ironment( i( 're(ented here. A green (&hedu%ing a%gorithm ,hi&h ,or/( by 'o,ering do,n

(er+er( ,hen they are not in u(e i( a%(o 're(ented.

Green Cloud computing i( en+i(ioned to a&hie+e not on%y e))i&ient 'ro&e((ing and

uti%i(ation o) &om'uting in)ra(tru&ture- but a%(o minimi(e energy &on(um'tion. *hi( i( e((entia% )or

en(uring that the )uture gro,th o) $%oud &om'uting i( (u(tainab%e. ther,i(e- $%oud &om'uting

,ith in&rea(ing%y 'er+a(i+e )rontend &%ient de+i&e( intera&ting ,ith ba&/end data &entre( ,i%%

&au(e an enormou( e(&a%ation o) energy u(age.

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Introduction

In 1- 4eonard K%einro&/ - one o) the &hie) (&ienti(t( o) the origina% Ad+an&ed Re(ear&h

Pro5e&t( Agen&y Net,or/ 6ARPAN*8 ,hi&h (eeded the Internet- (aid: “As of now, computer

networks are still in their infancy, but as they grow up and become sophisticated, we will probably

see the spread of „computer utilities which, like present electric and telephone utilities, will ‟

service individual homes and offices across the country.” *hi( +i(ion o) &om'uting uti%itie( ba(ed

on a (er+i&e 'ro+i(ioning mode% anti&i'ated the ma((i+e tran()ormation o) the entire &om'uting

indu(try in the 21(t &entury ,hereby &om'uting (er+i&e( ,i%% be readi%y a+ai%ab%e on demand- %i/e

other uti%ity (er+i&e( a+ai%ab%e in today9( (o&iety. Simi%ar%y- u(er( 6&on(umer(8 need to 'ay

'ro+ider( on%y ,hen they a&&e(( the &om'uting (er+i&e(. In addition- &on(umer( no %onger need toin+e(t hea+i%y or en&ounter di))i&u%tie( in bui%ding and maintaining &om'%e I* in)ra(tru&ture.

In (u&h a mode%- u(er( a&&e(( (er+i&e( ba(ed on their re;uirement( ,ithout regard to ,here

the (er+i&e( are ho(ted. *hi( mode% ha( been re)erred to a( utility computing - or re&ent%y a( Cloud

computing . *he %atter term denote( the in)ra(tru&ture a( a


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Need of Cloud Computing

*he need o) &%oud &om'uting &an be e'%ained ,ith the he%' o) an eam'%e. *he )o%%o,ing gra'h

(ho,( the number o) u(er( ,ho %og on to the Au(tra%ian 'en ,eb 'age.

fig 1monthly page views of australian open official website

*he ('i/e( &orre('ond to the month o) anuary during ,hi&h the tournament i( going on. *he (ite

remain( a%mo(t dormant during the re(t o) the year. It ,ou%d be ,a(te)u% to ha+e (er+er( ,hi&h &an

&ater to the maimum need-a( they ,ont be needed during the re(t o) the year. *he &on&e't o) &%oud

&om'uting &ome( to the re(&ue at thi( time. "uring the 'ea/ 'eriod- &%oud 'ro+ider( (u&h a(

?oog%e-Yahoo-!i&ro(o)t et&.&an be a''roa&hed to 'ro+ide the ne&e((ary (er+er &a'a&ity.

In thi( &a(e- In)ra(tu&ture i( 'ro+ided a( a (er+i&e6IaaS8 through &%oud &om'uting.

4i/e,i(e-&%oud 'ro+ider( &an be a''roa&hed )or obtaing (o)t,are or '%at)orm a( a (er+i&e.

"e+e%o'er( ,ith inno+ati+e idea( )or ne, Internet (er+i&e( no %onger re;uire %arge &a'ita% out%ay(

in hard,are to de'%oy their (er+i&e or human e'en(e to o'erate it . $%oud &om'uting o))er(

(igni)i&ant bene)it( to I* &om'anie( by )reeing them )rom the %o,%e+e% ta(/ o) (etting u' ba(i&

hard,are and (o)t,are in)ra(tru&ture( and thu( enab%ing )o&u( on inno+ation and &reating bu(ine((

+a%ue )or their (er+i&e(.

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Green Computing

?reen &om'uting i( de)ined a( the (tudy and 'ra&ti&e o) de(igning - manu)a&turing- u(ing-and di('o(ing o) &om'uter(- (er+er(- and a((o&iated (ub(y(tem((u&h a( monitor(- 'rinter(-

(torage de+i&e(- and net,or/ing and &ommuni&ation( (y(tem(e))i&ient%y and e))e&ti+e%y ,ith

minima% or no im'a&t on the en+ironment.C *he goa%( o) green &om'uting are (imi%ar to green

&hemi(tryD redu&e the u(e o) haEardou( materia%(- maimiEe energy e))i&ien&y during the 'rodu&tF(

%i)etime- and 'romote the re&y&%abi%ity or biodegradabi%ity o) de)un&t 'rodu&t( and )a&tory ,a(te.

Re(ear&h &ontinue( into /ey area( (u&h a( ma/ing the u(e o) &om'uter( a( energye))i&ient a(

'o((ib%e- and de(igning a%gorithm( and (y(tem( )or e))i&ien&yre%ated &om'uter te&hno%ogie(.

*here are (e+era% a''roa&he( to green &om'uting-name%y

• Produ&t %ongeti+ity

• A%gorithmi& e))i&ein&y

• Re(our&e a%%o&ation

• >irtua%i(ation

• Po,er management et&.

Need of Green Computing In Clouds

!odern data &enter(- o'erating under the $%oud &om'uting mode% are ho(ting a +ariety o)

a''%i&ation( ranging )rom tho(e that run )or a )e, (e&ond( 6e.g. (er+ing re;ue(t( o) ,eb

a''%i&ation( (u&h a( e&ommer&e and (o&ia% net,or/( 'orta%( ,ith tran(ient ,or/%oad(8 to tho(e

that run )or %onger 'eriod( o) time 6e.g. (imu%ation( or %arge data (et 'ro&e((ing8 on (hared

hard,are '%at)orm(. *he need to manage mu%ti'%e a''%i&ation( in a data &enter &reate( the &ha%%enge

o) ondemand re(our&e 'ro+i(ioning and a%%o&ation in re('on(e to time+arying ,or/%oad(.

Norma%%y- data &enter re(our&e( are (tati&a%%y a%%o&ated to a''%i&ation(- ba(ed on 'ea/ %oad

&hara&teri(ti&(- in order to maintain i(o%ation and 'ro+ide 'er)orman&e guarantee(. nti% re&ent%y-

high 'er)orman&e ha( been the (o%e &on&ern in data &enter de'%oyment( and thi( demand ha( been

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)u%)i%%ed ,ithout 'aying mu&h attention to energy &on(um'tion. *he a+erage data &enter &on(ume(

a( mu&h energy a( 2H-000 hou(eho%d( 20J. A( energy &o(t( are in&rea(ing ,hi%e a+ai%abi%ity

d,ind%e(- there i( a need to (hi)t )o&u( )rom o'timi(ing data &enter re(our&e management )or 'ure

'er)orman&e to o'timi(ing )or energy e))i&ien&y ,hi%e maintaining high (er+i&e %e+e% 'er)orman&e.

A&&ording to &ertain re'ort(-the tota% e(timated energy bi%% )or data &enter( in 2010 i( 11.H bi%%ion

and energy &o(t( in a ty'i&a% data &enter doub%e e+ery )i+e year(.

"ata &enter( are not on%y e'en(i+e to maintain- but a%(o un)riend%y to the en+ironment. "ata

&enter( no, dri+e more in &arbon emi((ion( than both Argentina and the Nether%and( . #igh energy

&o(t( and huge &arbon )oot'rint( are in&urred due to ma((i+e amount( o) e%e&tri&ity needed to

'o,er and &oo% numerou( (er+er( ho(ted in the(e data &enter(. $%oud (er+i&e 'ro+ider( need to

ado't mea(ure( to en(ure that their 'ro)it margin i( not dramati&a%%y redu&ed due to high energy&o(t(. Lor in(tan&e- ?oog%e- !i&ro(o)t- and Yahoo are bui%ding %arge data &enter( in barren de(ert

%and (urrounding the $o%umbia Ri+er- SA to e'%oit &hea' and re%iab%e hydroe%e&tri& 'o,er .

*here i( a%(o in&rea(ing 're((ure )rom ?o+ernment( ,or%d,ide to redu&e &arbon )oot'rint(- ,hi&h

ha+e a (igni)i&ant im'a&t on &%imate &hange. Lor eam'%e- the a'ane(e go+ernment ha( e(tab%i(hed

the a'an "ata $enter $oun&i% to addre(( the (oaring energy &on(um'tion o) data &enter( . 4eading

&om'uting (er+i&e 'ro+ider( ha+e a%(o re&ent%y )ormed a g%oba% &on(ortium /no,n a( *he ?reen

?rid to 'romote energy e))i&ien&y )or data &enter( and minimi(e their en+ironmenta% im'a&t.

4o,ering the energy u(age o) data &enter( i( a &ha%%enging and &om'%e i((ue be&au(e &om'uting

a''%i&ation( and data are gro,ing (o ;ui&/%y that in&rea(ing%y %arger (er+er( and di(/( are needed

to 'ro&e(( them )a(t enough ,ithin the re;uired time 'eriod. Green Cloud computing i(

en+i(ioned to a&hie+e not on%y e))i&ient 'ro&e((ing and uti%i(ation o) &om'uting in)ra(tru&ture- but

a%(o minimi(e energy &on(um'tion. *hi( i( e((entia% )or en(uring that the )uture gro,th o) $%oud

&om'uting i( (u(tainab%e. ther,i(e- $%oud &om'uting ,ith in&rea(ing%y 'er+a(i+e )rontend &%ient

de+i&e( intera&ting ,ith ba&/end data &enter( ,i%% &au(e an enormou( e(&a%ation o) energy u(age.

*o addre(( thi( 'rob%em- data &enter re(our&e( need to be managed in an energye))i&ient manner to

dri+e ?reen $%oud &om'uting. In 'arti&u%ar- $%oud re(our&e( need to be a%%o&ated not on%y to

(ati()y @oS re;uirement( ('e&i)ied by u(er( +ia Ser+i&e 4e+e% Agreement( 6S4A8- but a%(o to

redu&e energy u(age.

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Ar&hite&ture o) a green &%oud &om'uting '%at)orm

!ig " architecture of a green cloud computing environment

Ligure 2 (ho,( the high%e+e% ar&hite&ture )or (u''orting energye))i&ient (er+i&e a%%o&ation

in ?reen $%oud &om'uting in)ra(tru&ture. *here are ba(i&a%%y )our main entitie( in+o%+ed:

a) Consumers/Brokers: $%oud &on(umer( or their bro/er( (ubmit (er+i&e re;ue(t( )rom any,here

in the ,or%d to the $%oud. It i( im'ortant to noti&e that there &an be a di))eren&e bet,een $%oud

&on(umer( and u(er( o) de'%oyed (er+i&e(. Lor in(tan&e- a &on(umer &an be a &om'any de'%oying a

eb a''%i&ation- ,hi&h 're(ent( +arying ,or/%oad a&&ording to the number o) u(er( a&&e(ing it.

b) Green Resource Allocator : A&t( a( the inter)a&e bet,een the $%oud in)ra(tru&ture and

&on(umer(. It re;uire( the intera&tion o) the )o%%o,ing &om'onent( to (u''ort energye))i&ient

re(our&e management:


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#reen $egotiator : Negotiate( ,ith the &on(umer(Mbro/er( to )ina%iEe the S4A ,ith

('e&i)ied 'ri&e( and 'ena%tie( 6)or +io%ation( o) S4A8 bet,een the $%oud 'ro+ider and

&on(umer de'ending on the &on(umer9( @oS re;uirement( and energy (a+ing (&heme(. In

&a(e o) eb a''%i&ation(- )or in(tan&e- @oS metri& &an be H o) re;ue(t( being (er+ed in

%e(( than 3 (e&ond(.

%ervice Analyser : Inter'ret( and ana%y(e( the (er+i&e re;uirement( o) a (ubmitted re;ue(t

be)ore de&iding ,hether to a&&e't or re5e&t it. #en&e- it need( the %ate(t %oad and energy

in)ormation )rom >! !anager and nergy !onitor re('e&ti+e%y.

Consumer &rofiler : ?ather( ('e&i)i& &hara&teri(ti&( o) &on(umer( (o that im'ortant

&on(umer( &an be granted ('e&ia% 'ri+i%ege( and 'rioriti(ed o+er other &on(umer(

&ricing : "e&ide( ho, (er+i&e re;ue(t( are &harged to manage the (u''%y and demand o)

&om'uting re(our&e( and )a&i%itate in 'rioriti(ing (er+i&e a%%o&ation( e))e&ti+e%y.

'nergy (onitor : b(er+e( and determine( ,hi&h 'hy(i&a% ma&hine( to 'o,er onMo)).

%ervice %cheduler : A((ign( re;ue(t( to >!( and determine( re(our&e entit%ement( )or

a%%o&ated >!(. It a%(o de&ide( ,hen >!( are to be added or remo+ed to meet demand.

)( (anager : Kee'( tra&/ o) the a+ai%abi%ity o) >!( and their re(our&e entit%ement(. It i(

a%(o in &harge o) migrating >!( a&ro(( 'hy(i&a% ma&hine(

Accounting : !aintain( the a&tua% u(age o) re(our&e( by re;ue(t( to &om'ute u(age &o(t(.

#i(tori&a% u(age in)ormation &an a%(o be u(ed to im'ro+e (er+i&e a%%o&ation de&i(ion(.

&8 VMs: !u%ti'%e >!( &an be dynami&a%%y (tarted and (to''ed on a (ing%e 'hy(i&a% ma&hine to

meet a&&e'ted re;ue(t(- hen&e 'ro+iding maimum )%eibi%ity to &on)igure +ariou( 'artition( o)

re(our&e( on the (ame 'hy(i&a% ma&hine to di))erent ('e&i)i& re;uirement( o) (er+i&e re;ue(t(.

!u%ti'%e >!( &an a%(o &on&urrent%y run a''%i&ation( ba(ed on di))erent o'erating (y(tem

en+ironment( on a (ing%e 'hy(i&a% ma&hine. In addition- by dynami&a%%y migrating >!( a&ro(( 'hy(i&a% ma&hine(- ,or/%oad( &an be &on(o%idated and unu(ed re(our&e( &an be 'ut on a %o,'o,er

(tate- turned o)) or &on)igured to o'erate at %o,'er)orman&e %e+e%( 6e.g.- u(ing ">LS8 in order to

(a+e energy.

d8 Physical Machines: *he under%ying 'hy(i&a% &om'uting (er+er( 'ro+ide hard,are in)ra(tru&ture

)or &reating +irtua%i(ed re(our&e( to meet (er+i&e demand(.

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!a/ing &%oud &om'uting more green

!ain%y three a''roa&he( ha+e been tried out to ma/e &%oud &om'uting en+ironment( more

en+ironmenta% )riend%y. *he(e a''roa&he( ha+e been tried out in the data &entre( under

e'erimenta% &ondition(. *he 'ra&ti&a% a''%i&ation o) the(e method( are (ti%% under (tudy. *he

method( are:

• Dynamic Voltage frequency scaling technique(DV!): +ery e%e&troni& &ir&utory ,i%%

ha+e an o'erating &%o&/ a((o&iated ,ith it. *he o'eratin )re;uen&y o) thi( &%o&/ i( ad5u(ted

(o that the (u''%y +o%tage i( regu%ated. *hu(- thi( method hea+i%y de'end( on the hard,are

and i( not &ontro%%aba%e a&&ording to the +arying need(. *he 'o,er (a+ing( are a%(o %o,

&om'ared to other a''roa&he(. *he 'o,er (a+ing( to &o(t in&urred ratio i( a%(o %o,.• Resource allocation or "irtual machine migration techniques: In a &%oud &om'uting

en+ironment-e+ery 'hy(i&a% ma&hine ho(t( a number o) +irtua% ma&hine( u'on ,hi&h the

a''%i&ation( are run. *he(e +irtua% ma&hine( &an be tran()ered a&ro(( the ho(t( a&&ording to

the +arying need( and a+aia%b%e re(our&e(.*he >! migration method )o&u((e( on

tran()erring >!( in (u&h a ,ay that the 'o,er in&rea(e i( %ea(t. *he mo(t 'o,er e))i&ient

node( are (e%e&ted and the >!( are tran()ered a&ro(( to them. *hi( method i( dea%t in detai%

%ater.• Algorithmic a##roaches: It ha( been e'eriment%y determined that an idea% (er+er

&on(ume( about 70 o) the 'o,er uti%i(ed by a )u%%y uti%i(ed (er+er. 6See )igure 38.

!ig * &ower consumption under different work loads.

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(ing a neura% net,or/ 'redi&tor-the green (&hedu%ing a%gorithm( )ir(t e(timate( re;uired

dynami& ,or/%oad on the (er+er(. *hen unne&e((ary (er+er( are turned o)) in order to minimiEe the

number o) running (er+er(- thu( minimiEing the energy u(e at the 'oint( o) &on(um'tion to 'ro+ide

bene)it( to a%% other %e+e%(. A%(o-(e+era% (er+er( are added to he%' a((ure (er+i&e%e+e% agreement.

*he bottom %ine i( to 'rote&t the en+ironment and to redu&e the tota% &o(t o) o,ner(hi' ,hi%e

en(uring ;ua%ity o) (er+i&e.


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>! !igration

*he 'rob%em o) >! a%%o&ation &an be di+ided in t,o: the )ir(t 'art i( admi((ion o) ne,

re;ue(t( )or >! 'ro+i(ioning and '%a&ing the >!( on ho(t(- ,herea( the (e&ond 'art i(

o'timiEation o) &urrent a%%o&ation o) >!(.

'timiEation o) &urrent a%%o&ation o) >!( i( &arried out in t,o (te'(: at the )ir(t (te' ,e

(e%e&t >!( that need to be migrated- at the (e&ond (te' &ho(en >!( are '%a&ed on ho(t( u(ing

!BL" a%gorithm. e 'ro'o(e )our heuri(ti&( )or &hoo(ing >!( to migrate. *he )ir(t heuri(ti&-

Single Threshold (ST)- i( ba(ed on the idea o) (etting u''er uti%iEation thre(ho%d )or ho(t( and

'%a&ing >!( ,hi%e /ee'ing the tota% uti%iEation o) $P be%o, thi( thre(ho%d. *he aim i( to 're(er+e

)ree re(our&e( to 're+ent S4A +io%ation due to &on(o%idation in &a(e( ,hen uti%iEation by >!(

in&rea(e(. At ea&h time )rame a%% >!( are rea%%o&ated u(ing !BL" a%gorithm ,ith additiona%&ondition o) /ee'ing the u''er uti%iEation thre(ho%d not +io%ated. *he ne, '%a&ement i( a&hie+ed by

%i+e migration o) >!( .

*he other three heuri(ti&( are ba(ed on the idea o) (etting u''er and %o,er uti%iEation

thre(ho%d( )or ho(t( and /ee'ing tota% uti%iEation o) $P by a%% >!( bet,een the(e thre(ho%d(. I)

the uti%iEation o) $P )or a ho(t goe( be%o, the %o,er thre(ho%d- a%% >!( ha+e to be migrated )rom

thi( ho(t and the ho(t ha( to be (,it&hed o)) in order to e%iminate the id%e 'o,er &on(um'tion. I) the

uti%iEation goe( o+er the u''er thre(ho%d- (ome >!( ha+e to be migrated )rom the ho(t to redu&e

uti%iEation in order to 're+ent 'otentia% S4A +io%ation. e 'ro'o(e three 'o%i&ie( )or &hoo(ing >!(

that ha+e to be migrated )rom the ho(t.

!inimiEation o) !igration( 6!!8 migrating the %ea(t number o) >!( to minimi(e

migration o+erhead.

#ighe(t Potentia% ?ro,th 6#P?8 migrating >!( that ha+e the %o,e(t u(age o)

$P re%ati+e%y to the re;ue(ted in order to minimi(e tota% 'otentia% in&rea(e o) the

uti%iEation and S4A +io%ation

Random $hoi&e 6R$8 &hoo(ing the ne&e((ary number o) >!( by 'i&/ing them

a&&ording to a uni)orm%y di(tributed random +ariab%e.

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$%#erimental !etu#

A( the targeted (y(tem i( a generi& $%oud &om'uting en+ironment- it i( e((entia% to e+a%uate it

on a %arge(&a%e +irtua%i(ed data &enter in)ra(tru&ture. #o,e+er- it i( di))i&u%t to &ondu&t %arge(&a%e

e'eriment( on a rea% in)ra(tru&ture- e('e&ia%%y ,hen it i( ne&e((ary to re'eat the e'eriment ,ith

the (ame &ondition( 6e.g. ,hen &om'aring di))erent a%gorithm(8. *here)ore- (imu%ation( ha+e been

&ho(en a( a ,ay to e+a%uate the 'ro'o(ed heuri(ti&(. *he $%oudSim too%/it ha( been &ho(en a( a

(imu%ation '%at)orm a( it i( a modern (imu%ation )rame,or/ aimed at $%oud &om'uting

en+ironment(. In &ontra(t to a%ternati+e (imu%ation too%/it( 6e.g. Sim?rid- ?andSim8- it (u''ort(

mode%ing o) ondemand +irtua%iEation enab%ed re(our&e and a''%i&ation management. It ha( been

etended in order to enab%e 'o,era,are (imu%ation( a( the &ore )rame,or/ doe( not 'ro+ide thi(

&a'abi%ity. A'art )rom the 'o,er &on(um'tion mode%ing and a&&ounting- the abi%ity to (imu%ate(er+i&e a''%i&ation( ,ith +ariab%e o+er time ,or/%oad ha( been in&or'orated.

*here are a )e, a((um'tion( that ha+e been made to (im'%i)y the mode% o) the (y(tem and

enab%e (imu%ationdri+en e+a%uation. *he )ir(t a((um'tion i( that the o+erhead o) >! migration i(

&on(idered a( neg%igib%e. !ode%ing the &o(t o) migration o) >!( i( another re(ear&h 'rob%em and i(

being &urrent%y in+e(tigated . #o,e+er- it ha( been (ho,n that a''%i&ation o) %i+e migration o) >!(

&an 'ro+ide rea(onab%e 'er)orman&e o+erhead. !oreo+er- ,ith ad+an&ement( o) +irtua%iEation

te&hno%ogie(- the e))i&ien&y o) >! migration i( going to be im'ro+ed. Another a((um'tion i( that

due to un/no,n ty'e( o) a''%i&ation( running on >!(- it i( not 'o((ib%e to bui%d the ea&t mode% o)

(u&h a mied ,or/%oad . *here)ore- rather than (imu%ating 'arti&u%ar a''%i&ation(- the uti%iEation o)

$P by a >! i( generated a( a uni)orm%y di(tributed random +ariab%e. In the (imu%ation( ,e ha+e

de)ined that S4A +io%ation o&&ur( ,hen a >! &annot get amount o) !IPS that are re;ue(ted. *hi(

&an ha''en in &a(e( ,hen >!( (haring the (ame ho(t re;uire higher $P 'er)orman&e that &annot

be 'ro+ided due to &on(o%idation. *o &om'are e))i&ien&y o) the a%gorithm( ,e u(e a &hara&teri(ti&

&a%%ed S4A +io%ation 'er&entage- or (im'%y S4A +io%ation- ,hi&h i( de)ined a( a 'er&entage o) S4A

+io%ation e+ent( re%ati+e%y to the tota% number o) mea(urement(.

A data &enter that &om'ri(e( 100 heterogeneou( 'hy(i&a% node( ,a( (imu%ated. a&h node

i( mode%ed to ha+e one $P &ore ,ith 'er)orman&e e;ui+a%ent to 1000- 2000 or 3000 !i%%ion

In(tru&tion( Per Se&ond 6!IPS8- O ?b o) RA! and 1 *B o) (torage. A&&ording to thi( mode%- a

ho(t &on(ume( )rom 17H ,ith 0 $P uti%iEation and u' to 2H0 ,ith 100 $P uti%iEation.

a&h >! re;uire( one $P &ore ,ith 2H0- H00- 7H0 or 1000 !IPS- 12O !B o) RA! and 1 ?B o)

(torage. *he u(er( (ubmit re;ue(t( )or 'ro+i(ioning o) 20 heterogeneou( >!( that )i%%( the )u%%

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&a'a&ity o) the (imu%ated data &enter. a&h >! run( a ,eba''%i&ation or any /ind o) a''%i&ation

,ith +ariab%e ,or/%oad- ,hi&h i( mode%ed to &reate the uti%iEation o) $P a&&ording to a uni)orm%y

di(tributed random +ariab%e. *he a''%i&ation run( )or 1H0-000 !IPS that e;ua%( to 10 minute( o)

ee&ution on 2H0 !IPS $P ,ith 100 uti%iEation. Initia%%y- >!( are a%%o&ated a&&ording to the

re;ue(ted &hara&teri(ti&( a((uming 100 uti%iEation. a&h e'eriment ha( been run 10 time( and

the 're(ented re(u%t( are bui%t u'on the mean +a%ue(.

!imulation Results

Lor the ben&hmar/ e'erimenta% re(u%t( ,e ha+e u(ed a Non Po,er A,are 6NPA8 'o%i&y. *hi(

'o%i&y doe( not a''%y any 'o,er a,are o'timiEation( and im'%ie( that a%% ho(t( run at 100 $P

uti%iEation and &on(ume maimum 'o,er. *he (e&ond 'o%i&y a''%ie( ">LS- but doe( not 'er)orm

any ada'tation o) a%%o&ation o) >!( in runtime. Lor the (imu%ation (etu' de(&ribed abo+e- u(ingthe NPA 'o%i&y %ead( to the tota% energy &on(um'tion o) .1H Kh- ,herea( ">LS a%%o,(

de&rea(ing thi( +a%ue to G.G Kh.

*he (imu%ation re(ut( o) +ariou( 'o%i&ie( are e'%ained in the net (e&tion(.

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nergy $on(um'tion and S4A +ioa%tion o) S* 'o%i&y

ig &'simulation results of ! #olicy

*o e+a%uate S* 'o%i&y ,e &ondu&ted (e+era% e'eriment( ,ith di))erent +a%ue( o) the

uti%iEation thre(ho%d. *he (imu%ation re(u%t( are 're(ented in Ligure G. *he re(u%t( (ho, that energy

&on(um'tion &an be (igni)i&ant%y redu&ed re%ati+e%y to NPA and ">LS 'o%i&ie( by 77 and H3

re('e&ti+e%y ,ith H.G o) S4A +io%ation(. *hey (ho, that ,ith the gro,th o) the uti%iEation

thre(ho%d energy &on(um'tion de&rea(e(- ,herea( 'er&entage o) S4A +io%ation( in&rea(e(. *hi( i(

due to the )a&t that higher uti%iEation thre(ho%d a%%o,( more aggre((i+e &on(o%idation o) >!(-

ho,e+er- by the &o(t o) the in&rea(ed ri(/ o) S4A +io%ation(.

nergy &on(um'tion and S4A +io%ation( o) other 'o%i&ie(

e ha+e &om'ared !! 'o%i&y ,ith #P? and R$ 'o%i&ie( +arying ea&t +a%ue( o) the

thre(ho%d( but 're(er+ing G0 inter+a% bet,een them. *he re(u%t( 6Ligure( H Q 8 (ho, that the(e

'o%i&ie( a%%o, the a&hie+ement o) a''roimate%y the (ame +a%ue( o) energy &on(um'tion and S4A

+io%ation(. herea( the number o) >! migration( 'rodu&ed by !! 'o%i&y i( redu&ed in

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&om'ari(on to #P? 'o%i&y by maimum o) H7 and G0 on a+erage and in &om'ari(on to R$

'o%i&y by maimum o) G and 27 on a+erage.

ig 'energy consum#tion of *ifferent #olicies

ig+'!,A "iolations of *ifferent #olicies un*er *ifferent threshol*s

1G


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Com#arison -ith res#ect to CP. utilisation

ig 'com#arison of *iff #olicies un*er *ifferent -orkloa*s -ith res#ect to c#u utilsation

A( &an be (een-the Non Po,er A,are 6NPA8 'o%i&y ,hi&h i( &urrent%y being )o%%o,ed

re(u%t( in higher 'o,er %o((-e+en though it doe(nt re(u%t in S4A +io%ation(. *he o'tima% &a(e o&&ur(

,hen !! 'o%i&y under a ,or/%oad o) 3070i( u(ed.

$on&%u(ion

A''%ying green te&hno%ogie( i( high%y e((entia% )or the (u(tainab%e de+e%o'ment o) &%oud

&om'uting. ) the +ariou( green methodo%ogie( en;uired- the ">LS te&hno%ogy i( a high%y

hard,are oriented a''roa&h and henn&e %e(( )%eib%e. *he reu(%t o) +ariou( >! migration

(imu%ation( (ho, that !! 'o%i&y %ead( to the be(t energy (a+ing(: by O3- and 23 %e((

energy &on(um'tion re%ati+e%y to NPA- ">LS and S* 'o%i&ie( re('e&ti+e%y ,ith thre(ho%d( 3070

and en(uring 'er&entage o) S4A +io%ation( o) 1.1D and by O7- 7G and G3 ,ith thre(ho%d( H0

0 and .7 o) S4A +io%ation(. !! 'o%i&y %ead( to more than 10 time( %e(( >! migration( than

S* 'o%i&y. *he re(u%t( (ho, )%eibi%ity o) the a%gorithm- a( the thre(ho%d( &an be ad5u(ted a&&ording

to S4A re;uirement(. Stri&t S4A 61.118 a%%o, the a&hie+ement o) the energy &on(um'tion o) 1.GO

Kh. #o,e+er- i) S4A are re%aed 6.8- the energy &on(um'tion i( )urther redu&ed to 1.1G

Kh. Sing%e thre(ho%d 'o%i&ie( &an (a+e 'o,er u'to 20-but they a%(o &au(e a %arge number o)

1H


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S4A +io%ation(. ?reen (&hedu%ing a%gorithm( ba(ed on neura% 'redi&tor( &an %ead to a 70 'o,er

(a+ing(. *he(e 'o%i&ie( a%(o enab%e u( to &ut do,n data &entre energy &o(t(- thu( %eading to a

(trong-&om'etiti+e &%oud &om'uting indu(try. nd u(er( ,i%% a%(o bene)it )rom the de&rea(ed energy

bi%%(.

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Re)eren&e(

1. inh *roung "uy-Yu/inori Sato-Ya(hu(hi Inogu&hi ''' 0plore,

(arch "1

*. ,,,.,i/i'edia.&omMgreen&om'uting.

. ,,,.ibm.&omMde+e%o'er,or/(M,eb('hereMEone(Mhi'od(

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