Self-Organising Semantic Resource Discovery for Pervasive Systems
 |
 |
 |
abstract = {Pervasive context-aware computing networks call for designing algorithms for information propagation and reconfiguration that promote self-adaptation, namely, which can guarantee - at least to a probabilistic extent - certain reliability and robustness properties in spite of unpredicted changes and conditions. The possibility of formally analysing their properties is obviously an essential engineering requirement, calling for general-purpose models and tools. As proposed in recent works, several such algorithms can be modelled by the notion of "computational field": a dynamically evolving spatial data structure mapping every node of the network to a data value. Based on this idea, as a contribution toward formally verifying properties of pervasive computing systems, in this article we propose a specification language to model computational fields, and a framework based on PRISM stochastic model checker explicitly targeted at supporting temporal property verification, exploited for quantitative analysis of systems running on networks composed of hundreds of nodes.},
apice = {SelforgSasow2012},
author = {Stevenson, Graeme and Ye, Juan and Dobson, Simon and Viroli, Mirko and Montagna, Sara},
booktitle = {Self-Adaptive and Self-Organizing Systems Workshops (SASOW)},
doi = {10.1109/SASOW.2012.39},
editor = {Pitt, Jeremy},
isbn = {978-1-4673-5153-9},
keywords = {bio-inspired, resource discovery, semantic matching},
month = apr,
note = {2012 IEEE Sixth International Conference (SASOW 2012), Lyon, France, 10-14~} # sep # {~2012. Proceedings},
pages = {181--186},
publisher = {IEEE CS},
title = {Self-Organising Semantic Resource Discovery for Pervasive Systems},
year = 2013
}