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

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Standard

Self-awareness for dynamic knowledge management in self-adaptive volunteer services. / Elhabbash, Abdessalam; Bahsoon, Rami; Tino, Peter.

Proceedings - 2017 IEEE 24th International Conference on Web Services, ICWS 2017. Institute of Electrical and Electronics Engineers (IEEE), 2017. p. 180-187 8029760.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Harvard

Elhabbash, A, Bahsoon, R & Tino, P 2017, Self-awareness for dynamic knowledge management in self-adaptive volunteer services. in Proceedings - 2017 IEEE 24th International Conference on Web Services, ICWS 2017., 8029760, Institute of Electrical and Electronics Engineers (IEEE), pp. 180-187, 24th IEEE International Conference on Web Services, ICWS 2017, Honolulu, United States, 25/06/17. https://doi.org/10.1109/ICWS.2017.31

APA

Elhabbash, A., Bahsoon, R., & Tino, P. (2017). Self-awareness for dynamic knowledge management in self-adaptive volunteer services. In Proceedings - 2017 IEEE 24th International Conference on Web Services, ICWS 2017 (pp. 180-187). [8029760] Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/ICWS.2017.31

Vancouver

Elhabbash A, Bahsoon R, Tino P. Self-awareness for dynamic knowledge management in self-adaptive volunteer services. In Proceedings - 2017 IEEE 24th International Conference on Web Services, ICWS 2017. Institute of Electrical and Electronics Engineers (IEEE). 2017. p. 180-187. 8029760 https://doi.org/10.1109/ICWS.2017.31

Author

Elhabbash, Abdessalam ; Bahsoon, Rami ; Tino, Peter. / Self-awareness for dynamic knowledge management in self-adaptive volunteer services. Proceedings - 2017 IEEE 24th International Conference on Web Services, ICWS 2017. Institute of Electrical and Electronics Engineers (IEEE), 2017. pp. 180-187

Bibtex

@inproceedings{88a720ec8351435589229412db42b322,
title = "Self-awareness for dynamic knowledge management in self-adaptive volunteer services",
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 As these services tend to be published and withdrawn without restrictions, uncertainties, dynamisms and 'dilution of control' related to the decisions of selection and composition are complex problems.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.",
keywords = "self-adaptive, self-aware, service composition",
author = "Abdessalam Elhabbash and Rami Bahsoon and Peter Tino",
year = "2017",
month = sep,
day = "11",
doi = "10.1109/ICWS.2017.31",
language = "English",
isbn = "9781538607534",
pages = "180--187",
booktitle = "Proceedings - 2017 IEEE 24th International Conference on Web Services, ICWS 2017",
publisher = "Institute of Electrical and Electronics Engineers (IEEE)",
note = "24th IEEE International Conference on Web Services, ICWS 2017 ; Conference date: 25-06-2017 Through 30-06-2017",

}

RIS

TY - GEN

T1 - Self-awareness for dynamic knowledge management in self-adaptive volunteer services

AU - Elhabbash, Abdessalam

AU - Bahsoon, Rami

AU - Tino, Peter

PY - 2017/9/11

Y1 - 2017/9/11

N2 - 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.

AB - 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.

KW - self-adaptive

KW - self-aware

KW - service composition

U2 - 10.1109/ICWS.2017.31

DO - 10.1109/ICWS.2017.31

M3 - Conference contribution

AN - SCOPUS:85032385193

SN - 9781538607534

SP - 180

EP - 187

BT - Proceedings - 2017 IEEE 24th International Conference on Web Services, ICWS 2017

PB - Institute of Electrical and Electronics Engineers (IEEE)

T2 - 24th IEEE International Conference on Web Services, ICWS 2017

Y2 - 25 June 2017 through 30 June 2017

ER -