Generating Adaptation Plans Based on Quality Models for Cloud Platforms
| Autor: | Cecília M. F. Rubira, Breno Bernard Nicolau de França, Jorge Luiz Machado da Silva |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Data processing
Information privacy business.industry Computer science Scale (chemistry) media_common.quotation_subject 020206 networking & telecommunications Cloud computing Provisioning 02 engineering and technology Plan (drawing) Risk analysis (engineering) 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Quality (business) business Adaptation (computer science) media_common |
| Zdroj: | SBES |
| Popis: | Cloud computing brought up several benefits concerning cost and scale, offering support services for infrastructure provisioning targeting data processing and storage according to application demands. However, it is not trivial to ensure the trustworthiness of associated resources, i.e., the trust of a client in a cloud service and its provider. Hence, one of the main barriers is to warrant the nonfunctional properties of trustworthiness during runtime. This paper presents a new infrastructure to generate adaptation plans based on quality models to ensure different trustworthiness properties. On detecting the degradation of cloud resources regarding the monitored properties, an adaptation plan is generated and executed during runtime to ensure that cloud resources can work under proper trustworthiness levels. The proposed solution intends to be general, possibly being applied to several trustworthiness properties simultaneously. Finally, we evaluated the solution in a feasibility study under a scenario considering data privacy and performance as trustworthiness properties. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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