# scheduling algorithms for grid computing

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Technical Report No. 2006-504

Scheduling Algorithms for Grid omputing!

State of the Art and "pen #ro\$lems

%angpeng &ong and Selim G. A'l

School of omputing(

)ueen*s +ni,ersit

ingston( "ntario /anuar 2006

A\$stract!

Than's to ad,ances in ide-area netor' technologies and the lo cost of computing

resources( Grid computing came into \$eing and is currentl an acti,e research area. "ne

moti,ation of Grid computing is to aggregate the poer of idel distri\$uted resources(

and pro,ide non-tri,ial ser,ices to users. To achie,e this goal( an efficient Grid scheduling

sstem is an essential part of the Grid. Rather than co,ering the hole Grid scheduling

area( this sur,e pro,ides a re,ie of the su\$1ect mainl from the perspecti,e of

scheduling algorithms. n this re,ie( the challenges for Grid scheduling are identified.

%irst( the architecture of components in,ol,ed in scheduling is \$riefl introduced to

pro,ide an intuiti,e image of the Grid scheduling process. Then ,arious Grid scheduling algorithms are discussed from different points of ,ie( such as static ,s. dnamic policies(

o\$1ecti,e functions( applications models( adaptation( )oS constraints( strategies dealing

ith dnamic \$eha,ior of resources( and so on. 3ased on a comprehensi,e understanding

of the challenges and the state of the art of current research( some general issues orth of

further eploration are proposed.

. ntroduction

The popularit of the nternet and the a,aila\$ilit of poerful computers and

high-speed netor's as lo-cost commodit components are changing the a e use

computers toda. These technical opportunities ha,e led to the possi\$ilit of using

geographicall distri\$uted and multi-oner resources to sol,e large-scale pro\$lems in

science( engineering( and commerce. Recent research on these topics has led to the

emergence of a ne paradigm 'non as Grid computing 78.

To achie,e the promising potentials of tremendous distri\$uted resources( effecti,e and

efficient scheduling algorithms are fundamentall important. +nfortunatel( scheduling

algorithms in traditional parallel and distri\$uted sstems( hich usuall run on

homogeneous and dedicated resources( e.g. computer clusters( cannot or' ell in the ne

circumstances 28. n this paper( the state of current research on scheduling algorithms for

the ne generation of computational en,ironments ill \$e sur,eed and open pro\$lems

ill \$e discussed.

The remainder of this paper is organi9ed as follos. An o,er,ie of the Gridscheduling pro\$lem is presented in Section 2 ith a generali9ed scheduling architecture. n

Section :( the progress made to date in the design and analsis of scheduling algorithms

for Grid computing is re,ieed. A summar and some research opportunities are offered in

Section 4.

2. ",er,ie of the Grid Scheduling #ro\$lem

A computational Grid is a hardare and softare infrastructure that pro,ides

capa\$ilities 458. t is a shared en,ironment implemented ,ia the deploment of a

persistent( standards-\$ased ser,ice infrastructure that supports the creation of( and resource

sharing ithin( distri\$uted communities. Resources can \$e computers( storage space(

instruments( softare applications( and data( all connected through the nternet and a middleare softare laer that pro,ides \$asic ser,ices for securit( monitoring( resource

management( and so forth. Resources oned \$ ,arious administrati,e organi9ations are

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shared under locall defined policies that specif hat is shared( ho is alloed to access

hat( and under hat conditions 4;8. The real and specific pro\$lem that underlies the Grid

concept is coordinated resource sharing and pro\$lem sol,ing in dnamic(

multi-institutional ,irtual organi9ations 448.

%rom the point of ,ie of scheduling sstems( a higher le,el a\$straction for the Grid

can \$e applied \$ ignoring some infrastructure components such as authentication(

authori9ation( resource disco,er and access control. Thus( in this paper( the folloing definition for the term Grid adopted! ualit-of-ser,ice re>uirements? 08.

To facilitate the discussion( the folloing fre>uentl used terms are defined!

@ A tas' is an atomic unit to \$e scheduled \$ the scheduler and assigned to a

resource.

@ The properties of a tas' are parameters li'e #+memor re>uirement( deadline(

priorit( etc.

@ A 1o\$ Bor metatas'( or applicationC is a set of atomic tas's that ill \$e carried out

on a set of resources. /o\$s can ha,e a recursi,e structure( meaning that 1o\$s are composed of su\$-1o\$s andor tas's( and su\$-1o\$s can themsel,es \$e decomposed

further into atomic tas's. n this paper( the term 1o\$( application and metatas' are

interchangea\$le.

@ A resource is something that is re>uired to carr out an operation( for eample! a

processor for data processing( a data storage de,ice( or a netor' lin' for data

transporting.

@ A site Bor nodeC is an autonomous entit composed of one or multiple resources.

@ A tas' scheduling is the mapping of tas's to a selected group of resources hich

ma \$e distri\$uted in multiple administrati,e domains.

2

2. The Grid Scheduling #rocess and omponents

A Grid is a sstem of high di,ersit( hich is rendered \$ ,arious applications(

middleare components( and resources. 3ut from the point of ,ie of functionalit( e

can still find a logical architecture of the tas' scheduling su\$sstem in Grid. %or eample(

Dhu 2:8 proposes a common Grid scheduling architecture. Ee can also generali9escheduling

process in the Grid into three stages! resource disco,ering and filtering(

resource selecting and scheduling according to certain o\$1ecti,es( and 1o\$ su\$mission 748.

As a stud of scheduling algorithms is our primar concern here( e focus on the second

step. 3ased on these o\$ser,ations( %ig.  depicts a model of Grid scheduling sstemshich

functional components are connected \$ to tpes of data flo! resourceapplication information

flo and tas' or tas' scheduling command flo.a

in

or

%ig. ! A logical Grid scheduling architecture! \$ro'en lines sho resource or application

information

flos and real lines sho tas' or tas' scheduling command flos.

3asicall( a Grid scheduler BGSC recei,es applications from Grid users( selects feasi\$le

resources for these applications according to ac>uired information from the Grid

nformation Ser,ice module( and finall generates application-to-resource mappings( \$ased

on certain o\$1ecti,e functions and predicted resource performance. +nli'e their

counterparts in traditional parallel and distri\$uted sstems( Grid schedulers usuall cannot control Grid resources directl( \$ut or' li'e \$ro'ers or agents:8( or e,en tightl

coupled ith the applications as the application-le,el scheduling scheme proposes 8(

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058. The are not necessaril located in the same domain ith the resources hich are

,isi\$le to them. %ig.  onl shos one Grid scheduler( \$ut in realit multiple such

schedulers might \$e deploed( and organi9ed to form different structures Bcentrali9ed(

hierarchical and decentrali9ed 558C according to different concerns( such as performance

or scala\$ilit. Although a Grid le,el scheduler Bor Fetascheduler as it is sometime referred

to in the literature( e.g.( in 8C is not an indispensa\$le component in the Grid

: infrastructure Be.g.( it is not included in the Glo\$us Tool'it 258( the defacto standardthe Grid

computing communitC( there is no dou\$t that such a scheduling componentcrucial for harnessing

the potential of Grids as the are epanding >uic'l( incorporating

resources from supercomputers to des'tops. "ur discussion on scheduling algorithms\$ased on the

assumption that there are such schedulers in a Grid.

nformation a\$out the status of a,aila\$le resources is ,er important for a Grid

scheduler to ma'e a proper schedule( especiall hen the heterogeneous and dnamic

nature of the Grid is ta'en into account. The role of the Grid information ser,ice BGSCto pro,ide

such information to Grid schedulers. GS is responsi\$le for collecting and

predicting the resource state information( such as #+ capacities( memor si9e( netor'

\$andidth( softare a,aila\$ilities and load of a site in a particular period. GS can anser  >ueries for resource information or push information to su\$scri\$ers. The Glo\$us

Fonitoring and &isco,e