Rodrigues, G.S., Felipe, P.G., Rodrigues, G.N., Knauss, A., de Araújo, J.P.C., Andrade, H. and Ali, R., 2019. GoalD: A Goal-Driven Deployment Framework for Dynamic and Heterogeneous Computing Environments. Information and software technology, 111 (July), 159 - 176.
Full text available as:
|
PDF
Gabriel_GoalD_IST_Journal[1].pdf - Accepted Version Available under License Creative Commons Attribution Non-commercial No Derivatives. 1MB | |
Copyright to original material in this document is with the original owner(s). Access to this content through BURO is granted on condition that you use it only for research, scholarly or other non-commercial purposes. If you wish to use it for any other purposes, you must contact BU via BURO@bournemouth.ac.uk. Any third party copyright material in this document remains the property of its respective owner(s). BU grants no licence for further use of that third party material. |
DOI: 10.1016/j.infsof.2019.04.003
Abstract
Context: Emerging paradigms like Internet of Things and Smart Cities utilize advanced sensing and communication infrastructures, where heterogeneity is an inherited feature. Applications targeting such environments require adaptability and context-sensitivity to uncertain availability and failures in resources and their ad-hoc networks. Such heterogeneity is often hard to predict, making the deployment process a challenging task. Objective: This paper proposes GoalD as a goal-driven framework to support autonomous deployment of heterogeneous computational resources to fulfill requirements, seen as goals, and their correlated components on one hand, and the variability space of the hosting computing and sensing environment on the other hand. Method: GoalD comprises an offline and an online stage to fulfill autonomous deployment by leveraging the use of goals. Deployment configuration strategies arise from the variability structure of the Contextual Goal Model as an underlying structure to guide autonomous planning by selecting available as well as suitable resources at runtime. Results: We evaluate GoalD on an existing exemplar from the selfadaptive systems community – the Tele Assistance Service provided by Weyns and Calinescu [1]. Furthermore, we evaluate the scalability of GoalD on a repository consisting of 430,500 artifacts. The evaluation results demonstrate the usefulness and scalability of GoalD in planning the deployment of a system with thousands of components in a few milliseconds.
Item Type: | Article |
---|---|
ISSN: | 0950-5849 |
Uncontrolled Keywords: | Autonomous deployment; Contextual goal modelling; Heterogeneous computational resources; Deployment planning |
Group: | Faculty of Science & Technology |
ID Code: | 32183 |
Deposited By: | Symplectic RT2 |
Deposited On: | 23 Apr 2019 09:40 |
Last Modified: | 14 Mar 2022 14:15 |
Downloads
Downloads per month over past year
Repository Staff Only - |