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

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

Authors

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 As these services tend to be published and withdrawn without restrictions, uncertainties, dynamisms and 'dilution of control' related to the decisions of selection and composition are complex problems.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.

Details

Original languageEnglish
Title of host publicationProceedings - 2017 IEEE 24th International Conference on Web Services, ICWS 2017
Publication statusE-pub ahead of print - 11 Sep 2017
Event24th IEEE International Conference on Web Services, ICWS 2017 - Honolulu, United States
Duration: 25 Jun 201730 Jun 2017

Conference

Conference24th IEEE International Conference on Web Services, ICWS 2017
CountryUnited States
CityHonolulu
Period25/06/1730/06/17

Keywords

  • self-adaptive, self-aware, service composition