Cost optimization component selection approach for component based self-adaptive software architecture using component repository

2016 ◽  
Author(s):  
Y. Mohana Roopa ◽  
A. RamaMohan Reddy
Keyword(s):  
Software Architecture ◽  
Cost Optimization ◽  
Adaptive Software ◽  
Component Selection ◽  
Selection Approach ◽  
Self Adaptive ◽  
Component Repository

Towards Multiple-Layer Self-Adaptations of Multi-Agent Organizations Using Reinforcement Learning

2018 ◽  
pp. 66-95 ◽  
Author(s):  
Xinjun Mao ◽  
Menggao Dong ◽  
Haibin Zhu
Keyword(s):  
Reinforcement Learning ◽  
Software Architecture ◽  
Coarse Grain ◽  
Adaptive Software ◽  
Organization Model ◽  
Fine Grain ◽  
Adaptation Mechanisms ◽  
Multi Agent ◽  
Self Adaptation ◽  
Self Adaptive

This chapter proposes a multi-agent organization model for self-adaptive software to examine the autonomous components and their self-adaptation that can be occurred at either the fine-grain behavior layer of a software agent or the coarse-grain organization layer of the roles that the agent plays. The authors design two-layer self-adaptation mechanisms and combine them with reinforcement learning together to tackle the uncertainty issues of self-adaptation, which enables software agents to make decisions on self-adaptation by learning at run-time to deal with various unanticipated changes. The reinforcement learning algorithms supporting fine-grain and coarse-grain adaptation mechanisms are designed. In order to support the development of self-adaptive software, the software architecture for individual agents, the development process and the software framework are proposed. A sample is developed in detail to illustrate our method and experiments are conducted to evaluate the effectiveness and efficiency of the proposed approach.

Applying Bigraph Theory to Self-Adaptive Software Architecture

2009 ◽  
Vol 32 (1) ◽  
pp. 97-106 ◽  
Author(s):  
Zhi-Ming CHANG ◽  
Xin-Jun MAO ◽  
Zhi-Chang QI
Keyword(s):  
Software Architecture ◽  
Adaptive Software ◽  
Self Adaptive
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