Self-awareness for dynamic knowledge management in self-adaptive volunteer services

Elhabbash, Abdessalam and Bahsoon, Rami and Tino, Peter (2017) Self-awareness for dynamic knowledge management in self-adaptive volunteer services. In: 2017 IEEE International Conference on Web Services (ICWS). IEEE, pp. 180-187. ISBN 9781538607534

[img]
Preview
PDF (Self-awareness for dynamic knowledge management in self-adaptive volunteer services)
ICWS2017.pdf - Accepted Version
Available under License Creative Commons Attribution-NonCommercial.

Download (672kB)

Abstract

Engineering volunteer services calls for novel self-adaptive approaches for dynamically managing the process of selecting volunteer services. As these services tend to be published and withdrawn without restrictions, uncertainties, dynamisms and 'dilution of control' related to the decisions of selection and composition are complex problems. These services tend to exhibit periodic performance patterns, which are often repeated over a certain time period. Consequently, the awareness of such periodic patterns enables the prediction of the services performance leading to better adaptation. In this paper, we contribute to a self-adaptive approach, namely time-awareness, which combines self-aware principles with dynamic histograms to dynamically manage the periodic trends of services performance and their evolution trends. Such knowledge can inform the adaptation decisions, leading to increase in the precision of selecting and composing services. We evaluate the approach using a volunteer storage composition scenario. The evaluation results show the advantages of dynamic knowledge management in self-adaptive volunteer computing in selecting dependable services and satisfying higher number of requests.

Item Type:
Contribution in Book/Report/Proceedings
Additional Information:
©2017 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
ID Code:
127403
Deposited By:
Deposited On:
26 Sep 2018 12:32
Refereed?:
Yes
Published?:
Published
Last Modified:
31 Mar 2020 01:03