Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
139 tokens/sec
GPT-4o
47 tokens/sec
Gemini 2.5 Pro Pro
43 tokens/sec
o3 Pro
4 tokens/sec
GPT-4.1 Pro
47 tokens/sec
DeepSeek R1 via Azure Pro
28 tokens/sec
2000 character limit reached

Requirements-Driven Dynamic Adaptation to Mitigate Runtime Uncertainties for Self-Adaptive Systems (1704.00419v1)

Published 3 Apr 2017 in cs.SE and cs.SY

Abstract: Self-adaptive systems are capable of adjusting their behavior to cope with the changes in environment and itself. These changes may cause runtime uncertainty, which refers to the system state of failing to achieve appropriate reconfigurations. However, it is often infeasible to exhaustively anticipate all the changes. Thus, providing dynamic adaptation mechanisms for mitigating runtime uncertainty becomes a big challenge. This paper suggests solving this challenge at requirements phase by presenting REDAPT, short for REquirement-Driven adAPTation. We propose an adaptive goal model (AGM) by introducing adaptive elements, specify dynamic properties of AGM by providing logic based grammar, derive adaptation mechanisms with AGM specifications and achieve adaptation by monitoring variables, diagnosing requirements violations, determining reconfigurations and execution. Our approach is demonstrated with an example from the Intelligent Transportation System domain and evaluated through a series of simulation experiments.

Citations (2)

Summary

We haven't generated a summary for this paper yet.