Rights statement: ©2016 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.
Accepted author manuscript, 354 KB, PDF document
Available under license: CC BY-NC: Creative Commons Attribution-NonCommercial 4.0 International License
Final published version
Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
}
TY - GEN
T1 - Interaction-awareness for self-adaptive volunteer computing
AU - Elhabbash, Abdessalam
AU - Bahsoon, Rami
AU - Tino, Peter
N1 - ©2016 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.
PY - 2016/12/8
Y1 - 2016/12/8
N2 - In this paper, we contribute to a self-adaptive approach, namely interaction-awareness which adopts self-aware principles to dynamically manage and maintain the knowledge on the interactions between volunteer services in the volunteer computing paradigm. Such knowledge can inform the adaptation decisions, leading to increase in the precision of selecting and composing services. We evaluate the approaches using a volunteer storage composition scenario. The evaluation results show the advantages of dynamic knowledge management in self-adaptive VC in selecting dependable services and satisfying higher number of requests.
AB - In this paper, we contribute to a self-adaptive approach, namely interaction-awareness which adopts self-aware principles to dynamically manage and maintain the knowledge on the interactions between volunteer services in the volunteer computing paradigm. Such knowledge can inform the adaptation decisions, leading to increase in the precision of selecting and composing services. We evaluate the approaches using a volunteer storage composition scenario. The evaluation results show the advantages of dynamic knowledge management in self-adaptive VC in selecting dependable services and satisfying higher number of requests.
U2 - 10.1109/SASO.2016.24
DO - 10.1109/SASO.2016.24
M3 - Conference contribution/Paper
SN - 9781509035359
SP - 148
EP - 149
BT - 2016 IEEE 10th International Conference on Self-Adaptive and Self-Organizing Systems (SASO)
PB - IEEE
ER -