Gradient-based Self-organisation Patterns of Anticipative Adaptation


pagemagnifierBibTeX_logo.pngmagnifierpage_white_acrobatmagnifier

Sara Montagna, Danilo Pianini, Mirko Viroli

“Proceedings of 6th IEEE International Conference on Self-Adaptive and Self-Organizing Systems (SASO 2012)”
IEEE Computer Society
May 2012

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

Tags: Alchemist

Publication

— authors

— status

published

— sort

paper in proceedings

— publication date

May 2012

— volume

Proceedings of 6th IEEE International Conference on Self-Adaptive and Self-Organizing Systems (SASO 2012)

— location

Lyon, France

identifiers

— DOI

1109/SASO.2012.25

— ISBN–13

978-0-7695-4851-7/12

Partita IVA: 01131710376 — Copyright © 2008–2023 APICe@DISI – PRIVACY