Title
Framework for Building Self-Adaptive Component Applications Based on Reinforcement Learning
Abstract
Component-based applications entail a composition of heterogeneous components often running in different contexts. The complexity and dynamic nature of their contexts result in an increasing maintenance efforts. Autonomic computing came to provide systems with an autonomic behavior based on predefined policies. However, in addition to being knowledge-intensive, the constructed policies may easily become obsolete due to context changes. Decision policies should be dynamically learned to self-adapt to context dynamics. However, currently built autonomic systems are tailored to specific management needs, neither reusable for other management concerns nor endowed with learning abilities. In this paper, we introduce a generic framework that facilitates building self-adaptive component-based applications. Unlike the existing initiatives, our framework provides means to transform an existing application by equipping it with a self-adaptive behavior to dynamically learn an optimal policy at runtime. To validate our approach, we have developed a realistic application and used the framework to render it self-adaptive. The experimental results have shown a negligible overhead and a dynamic adjustment of the transformed application to its changing context. They have also shown less frequent time spent in SLA (Service Level Agreement) violations during the learning phase and a better performing application after convergence.
Year
DOI
Venue
2018
10.1109/SCC.2018.00010
2018 IEEE International Conference on Services Computing (SCC)
Keywords
Field
DocType
Autonomic Computing,Self-Adaptive Decision Making,Component-based Applications,Reinforcement Learning
Convergence (routing),Autonomic computing,Computer science,Service-level agreement,Self adaptive,Context dynamics,Distributed computing,Reinforcement learning
Conference
ISSN
ISBN
Citations 
2474-8137
978-1-5386-7251-8
0
PageRank 
References 
Authors
0.34
1
3
Name
Order
Citations
PageRank
Nabila Belhaj100.34
Djamel Belaïd29012.76
Hamid Mukhtar3559.15