Mul iagen Sys em P oduc Lines: Challenges and Bene i s
Joaquin Pe˜
na
Uni e si y o Se ille
Spain
[email p o ec ed]
Michael G. Hinchey
NASA Godda d Space Fligh Cen e
USA
Michael.G.Hinche[email p o ec ed]
An onio Ruiz-Co ´
es
Uni e si y o Se ille
Spain
[email p o ec ed]
1 In oduc ion
On he one hand, he ield o So wa e P oduc Lines
(SPL), as desc ibed elsewhe e in his special issue, co e s
all he so wa e de elopmen li ecycle necessa y o de elop
a amily o p oduc s whe e he de i a ion o conc e e p od-
uc s is made sys ema ically and apidly [10]. On he o he
hand, Agen -O ien ed So wa e Enginee ing (AOSE) is a
new so wa e enginee ing pa adigm ha a ose o apply bes
p ac ice in he de elopmen o complex Mul i-Agen Sys-
ems (MAS) by ocusing on he use o agen s, and o ganiza-
ions (communi ies) o agen s as he main abs ac ions [7].
Following a a he alse s a , agen echnology has be-
gun o come in o i s own. Wi h he ad en o biologically-
inspi ed, pe asi e, and au onomic compu ing, he ad an-
ages o , and necessi y o , agen -based echnologies and
MASs has become ob ious. Un o una ely, cu en AOSE
me hodologies a e dedica ed o de eloping single MASs.
Clea ly, many MASs will make use o signi ican ly he
same echniques, adap a ions, and app oaches. The ield is
hus ipe o exploi ing he bene i s o SPL: educed cos s,
imp o ed ime- o-ma ke , e c., and enhancing agen ech-
nology in such a way ha i is mo e indus ially applicable.
We belie e ha he e is much ha can be achie ed by
combining he wo app oaches: applying he SPL philoso-
phy o building a MAS will a o d all o he ad an ages o
SPLs and make MAS de elopmen mo e p ac ical. Thus,
he con ibu ion o his wo k is wo old: s ess he easibil-
i y and bene i s o wha we call Mul i-Agen Sys ems P od-
uc Lines (MAS-PL); and show eade s he main esea ch
challenges in he de elopmen o MAS-PLs.
2 Feasibili y o MAS-PL and bene i s
The so wa e p ocess p oposed in AOSE p esen s many
simila i ies wi h he p ocess ollowed in SPL o he i s
ac i i ies o he domain enginee ing, which is in cha ge o
p o iding he eusable co e asse s ha a e exploi ed du -
ing he de i a ion o p oduc s, done a he applica ion en-
ginee ing [10]. Following he nomencla u e used in [10],
he ac i i ies, usually pe o med i e a i ely and in pa allel,
o domain enginee ing ha p esen co ela ion wi h AOSE
a e:
Domain Requi emen s Enginee ing. Bo h app oaches
use models based on simila concep s: ea u es in
he case o SPLs, and sys em-goals in he case o
AOSE [3, 4]. Bo h ep esen equi emen s obse able
by he end use . Bo h app oaches use hie a chical dia-
g ams whe e ea u es/goals a e decomposed in o ine
g ain ones. Howe e , SPL emphasizes he analysis o
he scope o he SPL, i.e. he p oduc s inside i , and
he analysis o common and a iable ea u es ac oss
he SPL, which is no ca ied ou by AOSE. In [5, 9],
a i s s ep owa d adap ing sys em-goals o MAS-PL
and documen ing a iabili y is shown.
Domain Design. Bo h app oaches de elop a chi ec u e-
independen models ha a emp o analyze how ea-
u es and i s a iabili y can be ma e ialized. In AOSE,
ole models a e used wi h his pu pose [12], and
some app oaches in SPL also p opose he same ap-
p oach [6, 11]. Howe e , agen - ocused models show
addi ional in o ma ion ha is no needed in SPL- ole
models, such as he goals o he agen s, o whe he hey
a e used o abs ac IA echniques, while no showing
how hese ole models can be eused o di e en p od-
uc s.
Domain Realiza ion. Bo h app oaches ocus on designing
a de ailed a chi ec u e. In he case o SPL, a common
a chi ec u e o all p oduc s and a se o eusable as-
se s. In he case o AOSE, a single a chi ec u e ha
ul ills all o he sys em-goals o he MAS. Some ap-
p oaches in bo h ields base he cons uc ion o he
a chi ec u e on ole model composi ion [6, 11]. In
[9], au ho s p esen ed he i s s eps owa d building
he co e a chi ec u e o a MAS-PL based on au o-
ma ic analysis o sys em-goals models adap ed o ea-
u e models using [2].
This, along wi h he shown i s esea ch pape s de el-
oped unde his ield, shows ha he bene i s o enabling
MAS-PL a e eachable. The main bene i is s aigh o -
wa d: AOSE can bene i s o all SPL ad an ages helping
i o each he indus ial wo ld. Howe e , as we show in
he nex sec ion, he e exis also a numbe o esea ch chal-
lenges ha mus cons i u e he esea ch agenda needed o
allow MAS-PL o become a eali y.
3 Fu u e Challenges
SPL o dis ibu ed sys ems. Dis ibu ed sys ems ha e
no been a ho opic in he SPL ield. Howe e , MASs
a e dis ibu ed sys ems ha will need new adap ed
echniques o be co e ed. Al hough ce ainly i will
a ec o he whole de elopmen cycle, one o he i s
s eps we o esee is he need o in es ing in he use
o in e ac ion-based models, such as ole models. The
esea ch unde aken o e his opic may ex end he ap-
plicabili y o SPL no only o MASs, bu also o o he
kind o dis ibu ed sys ems such as web se ices[1].
AOSE de iciencies. As shown be o e, AOSE does no
co e some o he ac i i ies o SPL. These a e mainly
concen a ed on commonali y analysis, and i s impli-
ca ions a whole SPL app oach. Ano he ho opic can
be ound in he p oduc managemen ac i i y ha is
pe o med in pa allel wi h domain and applica ion en-
ginee ing. I is in cha ge o managing he economic
aspec s o a SPL. Gi en ha he p oduc s and he ma -
ke s o MASs a e qui e di e en om he ones yp-
ically used in SPL, a deal o e o mus be pu on
s udying hese aspec s. Finally, as AOSE is de o ed
o de elop single p oduc s, applica ion enginee ing is
no p esen in AOSE. Resea che s should also in es
e o s on s udying his ac i i y.
Managemen o e ol ing sys ems. Agen -based e ol ing
sys ems esul s on la ge so wa e sys ems ha adap
and lea ns o m changes in he en i onmen . The de-
elopmen o hese sys ems esul s in a complex ask
whe e sys ems usually become unmanageable om an
enginee ing poin o iew. SPL can help his ask by
iewing an e ol ing sys em as a SPL whe e a di e -
en s a e in he sys em is iewed as a sepa a e p oduc
[8]. This decomposes he sys em in o well iden i ied
chunks and a well de ined con ex whe e each p oduc
will appea , wha helps o deal wi h he inhe en com-
plexi y o MASs.
Sel -* p ope ies o agen s We belie e ha agen echnol-
ogy may b ing also ad an ages o SPL. Gi en esea ch
e o s in es ed in p o iding agen s wi h he capabil-
i ies o communica e wi h each o he a he seman ic
le el, o o p o ide capabili ies o sel -o ganiza ion,
sel -op imiza ion, sel -healing, e c., he main enance
and e olu ion o he co e a chi ec u e may be simpli-
ied. Addi ionally, he in eg a ion cos s o new ea u es
o a ce ain p oduc , o e en he en i e SPL, may be
dec eased.
4 Conclusions
MAS-PL, d awing bene i s om bo h SPL and AOSE,
will help in he indus ial exploi a ion o agen echnology,
sa ing bo h e o and cos . We ha e iden i ied se e al chal-
lenges, such as adap ing cu en AOSE enginee ing ech-
niques o he SPL philosophy, which in many cases equi es
he de elopmen o new ac i i ies/models om sc a ch.
Howe e , a symbiosis be ween bo h AOSE and SPL a ises
when AOSE also p o ides bene i s o SPL, mainly h ough
encou aging and imp o ing esea ch on SPL o complex
dis ibu ed sys ems. As can be seen, MAS-PLs ep esen
a g ea , and wo hwhile, challenge ha will ce ainly a ac
he in e es o many p ac i ione s and esea che s.
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