Cost-Effective Dynamic Optimisation for Multi-Cloud Queries - Optimisation Dynamique de Requêtes Réparties à grande échelle Access content directly
Conference Papers Year : 2021

Cost-Effective Dynamic Optimisation for Multi-Cloud Queries


The provision of public data through various Database-as-a-Service (DBaaS) providers has recently emerged as a significant trend, backed by major organisations. This paper introduces Nebula, a non-profit middleware providing multicloud querying capabilities by fully outsourcing its users' queries to the involved DBaaS providers. First, we propose a quoting procedure for those queries, whose need stems from the pay-perquery policy of the providers. Those quotations contain monetary cost and response time estimations, and are computed using provider-generated tenders. Then, we present an agent-based dynamic optimisation engine that orchestrates the outsourced execution of the queries. Agents within this engine cooperate in order to meet the quoted values. We evaluated Nebula over simulated providers by using the Join Order Benchmark (JOB). Experimental results showed Nebula's approach is, in most cases, more competitive in terms of monetary cost and response time than existing work in the multi-cloud DBMS literature.
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Dates and versions

hal-03428073 , version 1 (14-11-2021)
hal-03428073 , version 2 (14-12-2021)



Damien T Wojtowicz, Shaoyi Yin, Franck Morvan, Abdelkader Hameurlain. Cost-Effective Dynamic Optimisation for Multi-Cloud Queries. IEEE 14th International Conference on Cloud Computing (CLOUD 2021), IEEE Computer Society under the auspice of the Technical Committee on Services Computing (TCSVC), Sep 2021, Chicago (virtual), United States. pp.387-397, ⟨10.1109/CLOUD53861.2021.00052⟩. ⟨hal-03428073v2⟩
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