Name
Abstract | ||
|---|---|---|
Many service-oriented systems (SoS) operate in uncertain and changing environments. Hence, SoSs should be able to adapt itself during runtime to ensure that they maintain user-expected quality indicators. In real-world environments, some adaptations may have non-negligible latency, and take some lead time to produce their effect. Adapting reactively is an after-the-fact approach, which starts when the system deviates from the expected indicators. It can result in inefficiency and instability due to without anticipating the subsequent adaptation needs. To solve this problem, we propose a novel proactive adaptation solution - LetPa, which makes decisions based on predictions about how adaptations will unfold up to its completion. LetPa divides control parameters into three levels according to the SoS architecture and rates the adaptations considering both goal satisfaction and action penalties. We design a dynamic programming based decision mechanism in LetPa that enables SoS to determine which adaptations need be performed that can prevent and mitigate upcoming problems in the near-future time series. Simulation result implies that LetPa shows good stability and efficiency in SoSs. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1109/ICWS49710.2020.00071 | 2020 IEEE International Conference on Web Services (ICWS) |
Keywords | DocType | ISBN |
Self-adaptation,Proactive adaptation,Lead time-aware,Markv decision process,Service-oriented systems | Conference | 978-1-7281-8787-7 |
Citations | PageRank | References |
0 | 0.34 | 22 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jingbin Zhang | 1 | 2 | 2.41 |
| Meng Ma | 2 | 78 | 15.71 |
| Ping Wang | 3 | 93 | 44.15 |