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Gradient-based Self-organisation Patterns of Anticipative Adaptation

Sara Montagna, Danilo Pianini, Mirko Viroli
The self-organisation Gradient pattern is known to be a key spatial data structure to make information local to its source become global knowledge, and to dynamically and adaptively steer agents to that source even in mobile and faulty environments – e.g. when obstacles unpredictably appear. In this paper we conceive new self-organisation mechanisms built upon this pattern to tackle anticipative adaptation. We ensure that the retrieval of a target of interest proactively reacts to locally-available information about future events, namely, the knowledge about future obstacles (e.g., expected jams or road interruption in a traffic control scenario) is used to emergently compute alternative and faster paths.
Keywords: Anticipative adaptation, Pervasive service ecosystem, Gradient pattern
Proceedings of 6th IEEE International Conference on Self-Adaptive and Self-Organizing Systems (SASO 2012), May 2012, IEEE Computer Society
@inproceedings{anticipativegradient-SASO12,
	location = {Lyon, France},
	booktitle = {Proceedings of 6th IEEE International Conference on Self-Adaptive and Self-Organizing Systems (SASO 2012)},
	author = {Montagna, Sara and Pianini, Danilo and Viroli, Mirko},
	title = {Gradient-based Self-organisation Patterns of Anticipative Adaptation},
	year = 2012,
	keywords = {Anticipative adaptation, Pervasive service ecosystem, Gradient pattern},
	venue = {SASO},
	month = {September},
        isbn = {978-0-7695-4851-7},
        doi = {10.1109/SASO.2012.25},
        ee = {http://doi.ieeecomputersociety.org/10.1109/SASO.2012.25},
        pages = {169--174}
}