Dynamic Query Optimization in Large-Scale Distributed Environments
Head : Pr. Abdelkader Hameurlain
In parallel and distributed large-scale environments (Cluster, Grid, Cloud), the Pyramid team addresses the main problems of query processing and optimization, targeting large volumes of data distributed in large-scale.
More precisely, the research activities of the Pyramid team focuses on the design and development of new elastic resource allocation models for dynamic query optimization, while maximizing the exploration of fundamental results obtained in parallel and distributed systems, particularly the aspects relative to parallelism types (partitioned, independent and pipeline parallelisms) and the minimization of inter-operation communication costs.
Our approach is based on the best trade-off between : (i) efficiency (multi-tenant satisfaction/QoS) and (ii) cost-effectiveness (Service Providers with respect to IaaS/SaaS and meeting SLA (Service Level Agreement)). The originality of these new resource allocation models lies in : (i) the introduction of the profitability dimension (i.e. economic model) in the objective function, and (ii) the decentralization of control to insure the scalability by the integration of pro-active migration policy.
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