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without the installation of a GoalProxy. The average time added by the proxy service
management to each service goal was 0.15 milliseconds.
7
Related Work
A number of works have looked at leveraging both component and agent approaches
for the development of adaptive software systems.
A component-based approach in the construction of multi agent systems has been
supported by numerous researchers in the past. This typically considers the components
to be simply the building blocks from which agents are constructed [10]. An advantage
of this approach is the ability to take domain-specific issues into account at the compo-
nent level. The decisions made on these issues can therefore be separated from the task
of constructing the multi agent system as a whole, thus simplifying the process. The
resulting agent applications inherit some of the (functional/non-functional) properties
from the underlying component framework. However, this form of technical integration
does not contribute much to a conceptual combination of both paradigms as, once they
are built, agents remain the only primary entity form.
A different integration approach is advocated in SoSAA [11], in which an high-level
agent framework supervises a low-level component-based framework. The latter pro-
vides a computational environment to the first, which then augments its capabilities
with its multi-agent organisation, ACL communication, and goal-oriented, BDI-style
reasoning. A SoSAA Adapter interface provides meta-level sensors and meta-level ac-
tuators to operate on the component layer, to load, unload, configure components, ob-
serve their internal status, and bind their provided/required interfaces. Components are
left to automatically carry out lower-level behaviours and can interact through a vari-
ety of non-ACL collaboration styles, including method calls, messages and events. The
deliberative layer makes decisions about when such behaviours and communication
mechanisms are necessary or desirable in order to satisfy overall system and applica-
tion requirements. However, keeping neatly separated components and agents fails to
contribute much in consolidating both paradigms. Furthermore, the use of two separate
frameworks means that the resulting systems are subjected to both development and
run-time overheads.
Removing the need for a separate infrastructure shared by a large number of dis-
tributed applications is what motivates the approach followed in the M&M framework
[8]. In contrast to application development centred upon agent platforms, M&M appli-
cations become agent-enabled by incorporating well-defined binary software compo-
nents into their code. These components give the applications the capability of sending,
receiving and interacting with mobile agents. The applications themselves are devel-
oped using the current industry best practice software methods ( JavaBeans ) and become
agent-enabled by integrating the mobility components. Such an approach succeeds in
moving some agent mechanisms into the middleware layer. However, M&M only ad-
dresses agent mobility while components are not equipped with goal-oriented reasoning
capabilities.
More recently, the Active Component (AC) concept [9] has been proposed as a way to
integrate successful concepts from agents and components as well as active objects and
 
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