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conflictive objectives can be both optimized. We
have to check which multi-objective optimization
approach is applicable for our problem. One general
approach was described by Beume et al. (2008).
4 FUTURE WORK
The described concept still has to be proven and
tested. Preparations for experiments are under way,
an adequate software framework for mobile real-
time robotic systems with a plethora of modules and
sophisticated algorithms is available (Web, 2011). A
good candidate for gathering first experimental
results is the Monte Carlo Localization (MCL) as
described in Section 3. In addition to the need for
parallel computation resources during global
localization, the position tracking of the MCL needs
high iterative computing power. Therefore we have
to consider that situations exist where balancing the
algorithmic load is not an appropriate evolution
objective but rather a minor loaded computing
resource to carry out a high number of algorithmic
iterations.
The autonomic self-manager which is
responsible for finding distribution patterns by
means of the presented Genetic Algorithm as well as
constructing the self-model and online-optimization
has to be implemented and integrated into the
robotic framework RACK (Web, 2011). An open
issue is the way the online-optimization will be
realized. We have to evaluate whether the approach
of Stein et al. (2006) (see also Section 2) is viable
for us or whether the scheduling analysis algorithms
SymTA/S is based on (Henia et al., 2005) will be
directly integrated into our self-manager.
5 CONCLUSIONS
In this paper, we presented the idea of a system
capable of autonomously distributing tasks to
available computing resources. The system will be
able to generate correct and optimal distribution
patterns in order to set up the system. During this
procedure a self-model of the system is obtained and
used while the system operates to further optimize
the distribution pattern currently in use. We
described how the system performs self-healing in
case of failing components. The need for more
research in the field of the proposed optimization
approach as well as future work for getting
experimental results were outlined as well. The
system is well suited for mobile autonomous
networked robots which are employed for various
duties in complex environments where localization
algorithms are used as well as alternate requirements
cause differing calculation times of the involved
algorithms.
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