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@InProceedings{Glazier:2019:metamanagement,
AUTHOR = {Glazier, Thomas J. and Garlan, David},
TITLE = {An Automated Approach to Management of a Collection of Autonomic Systems},
YEAR = {2019},
MONTH = {16 June},
BOOKTITLE = {Proceedings of the 4th eCAS Workshop on Engineering Collective Adaptive Systems},
ADDRESS = {Umea, Sweden},
PDF = {http://acme.able.cs.cmu.edu/pubs/uploads/pdf/eCASEv1.pdf},
ABSTRACT = {Modern enterprise IT systems are increasingly becoming
compositions of many subsystems each of which is
an autonomic system. These individual autonomic systems act
independently to maintain their locally defined SLAs but can take
actions which are inconsistent with and potentially detrimental
to the global system objective. Currently, human administrators
intervene to resolve these conflicts but are challenged by
complexity in the prediction of current and future states of
the constituent systems and their managers, multiple conflicting
quality dimensions which may change over time, combinatorially
large configuration space across the set of constituent systems,
and the time critical nature of the decisions to be made to prevent
further degradation. To address these challenges, this paper
proposes an approach that enables the creation of a higher level
autonomic system, referred to as a meta-manager, that does not
subsume the control functions nor does it directly orchestrate the
actions of the sub-autonomic managers. Instead, we encapsulate
and abstract the behavior of each subsystem as a parameterized
adaptation policy which can be adjusted by the meta-manager
to tune the adaptive behavior of the subsystem adaptation. We
can effectively instantiate this idea by considering each of the
subsystems as a player in a stochastic multi-player game against
it’s local environment, and synthesize an adaptation strategy
using off-the-shelf tools for stochastic game analysis.},
KEYWORDS = {Meta-management, Self-adaptation}
}
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