Grégory François

dblp:90/9916 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2011
0000-0002-0315-8722ORCID · verified

Domains — the database's venue-derived domains; a paper can count in several

Databases, data management, data science and information retrieval · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer architecture, parallel and distributed computing, and storage systems
1 paper
Cloud and datacenter computing · 100%
Computer networks
1 paper
Network optimization and economics · 100%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Cloud and datacenter computing
cloud caching
0.112011
Optimal Service Pricing for a Cloud Cache · IEEE Trans. Knowl. Data Eng. 2011
Cloud and datacenter computing › resource management
cloud resource management
0.112011
Optimal Service Pricing for a Cloud Cache · IEEE Trans. Knowl. Data Eng. 2011
Cloud and datacenter computing › cloud economics
service pricing
0.112011
Optimal Service Pricing for a Cloud Cache · IEEE Trans. Knowl. Data Eng. 2011
Network optimization and economics › pricing
dynamic pricing
0.012011
Optimal Service Pricing for a Cloud Cache · IEEE Trans. Knowl. Data Eng. 2011

Methods — techniques the papers use, named apart from their topics

price-demand modeling · 0.2correlation estimation · 0.2
YearPublicationVenuePosition
2011 Optimal Service Pricing for a Cloud Cache
abstract
Cloud applications that offer data management services are emerging. Such clouds support caching of data in order to provide quality query services. The users can query the cloud data, paying the price for the infrastructure they use. Cloud management necessitates an economy that manages the service of multiple users in an efficient, but also, resource-economic way that allows for cloud profit. Naturally, the maximization of cloud profit given some guarantees for user satisfaction presumes an appropriate price-demand model that enables optimal pricing of query services. The model should be plausible in that it reflects the correlation of cache structures involved in the queries. Optimal pricing is achieved based on a dynamic pricing scheme that adapts to time changes. This paper proposes a novel price-demand model designed for a cloud cache and a dynamic pricing scheme for queries executed in the cloud cache. The pricing solution employs a novel method that estimates the correlations of the cache services in an time-efficient manner. The experimental study shows the efficiency of the solution.
Verena Kantere, Debabrata Dash, Grégory François, Sofia Kyriakopoulou, Anastasia Ailamaki
IEEE Trans. Knowl. Data Eng.3