Teemu Leppänen, Claudio Savaglio, Giancarlo Fortino, Service modeling for opportunistic edge computing systems with feature engineering, Computer Communications, Volume 157, 2020, Pages 308-319, ISSN 0140-3664, https://doi.org/10.1016/j.comcom.2020.04.011
Service modeling for opportunistic edge computing systems with feature engineering
|Author:||Leppänen, Teemu1; Savaglio, Claudio2; Fortino, Giancarlo2|
1Center for Ubiquitous Computing, University of Oulu, Finland
2Department of Informatics, Modeling, Electronics and Systems, University of Calabria, Italy
|Online Access:||PDF Full Text (PDF, 0.9 MB)|
|Persistent link:|| http://urn.fi/urn:nbn:fi-fe202103036393
|Publish Date:|| 2022-04-14
The complex and opportunistic environment in which edge computing systems operate, poses a fundamental challenge for online edge system orchestration, resource provisioning and real-time responsiveness in response to user movement. Such a challenge needs to addressed throughout the edge system lifecycle, starting from the software development methodologies. In this paper, we propose a novel development process for modeling opportunistic edge computing services, which rely on (i) ETSI MEC reference architecture and Opportunistic Internet of Things Service modeling for the early stage of system analysis and design, i.e. domain model and service metamodel; and on (ii) feature engineering for evaluating those opportunistic aspects with data analysis. To address the identified opportunistic properties, at the service design phase we construct (both automatically and through domain expertise) Opportunistic Feature Vectors for Edge, containing the numerical representations of those properties. Such vectors enable further data analysis and machine learning techniques in the development of distributed, effective and efficient edge computing systems. Lastly, we exemplify the integrated process with a microservice-based user mobility management service, based on a real-world data set, for online analysis in MEC systems.
|Pages:||308 - 319|
|Type of Publication:||
A1 Journal article – refereed
|Field of Science:||
113 Computer and information sciences
213 Electronic, automation and communications engineering, electronics
The authors would like to thank Mr. Tommi Järvenpää and Mr. Lauri Lovén for providing the initial user mobility data set used to built MECMMS service prototype and the illustrations. This work is supported by the Academy of Finland 6Genesis Flagship (grant 318927) research program, the Future Makers program of the Jane and Aatos Erkko Foundation and the Technology Industries of Finland Centennial Foundation and the Italian Ministry of Education, University and Research, PRIN - Research Projects of National Relevance 2017 project Fluidware (CUP H24I17000070001).
|Academy of Finland Grant Number:||
318927 (Academy of Finland Funding decision)
© 2020 Elsevier B.V. All rights reserved. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/.