Project-Team:CQFD

Project-Team Cqfd

Members

Overall Objectives

Presentation

Research Program

Application Domains

Dependability and safety

New Software and Platforms

New Results

Highlights of the Year
Approximate Kalman–Bucy filter for continuous-time semi-Markov jump linear systems
Modeling and optimization of a launcher integration process
Numerical approximation for optimal stopping of MDP under partial observation
Classification of EEG signals by evolutionary algorithm
Probabilistic low-rank matrix completion with adaptive spectral regularization algorithms
Variable selection to construct indicators of quality of life for data structured in groups
Efficiency of simulation in monotone hyper-stable queueing networks
Control of parallel non-observable queues: asymptotic equivalence and optimality of periodic policies
The economics of the cloud: price competition and congestion
Generalized Nash Equilibria for Platform-as-a-Service Clouds
Stochastic approximations of constrained discounted Markov decision processes
Non-Parametric Estimation of the Conditional Distribution of the Interjumping Times for Piecewise-Deterministic Markov Processes
Approximation of average cost Markov decision processes using empirical distributions and concentration inequalities
Piecewise Deterministic Markov Processes based approach applied to an offshore oil production system
Optimal Trajectories for Underwater Vehicles by Quantization and Stochastic control
Multi-Objective Design and Maintenance Optimization of the Heated Hold-Up Tank Modeled by Piecewise Deterministic Markov Processes
Conditional quantile estimation through optimal quantization
Conditional quantile estimator based on optimal quantization: from theory to practice
QuantifQuantile : an R package for performing quantile regression trough optimal quantization
Transcriptome profile analysis reveals specific signatures of pollutants in Atlantic eels
Comparaison of kernel density estimators with assumption on number of modes : application on environmental monitoring data
A new sliced inverse regression method for multivariate response
An introduction to dimension reduction in nonparametric kernel regression
Hidden Markov Model for the detection of a degraded operating mode of optronic equipment
On the asymptotic behavior of the Nadaraya-Watson estimator associated with the recursive SIR method
Evolving Genetic Programming Classifiers with Novelty Search
Detecting mental states of alertness with genetic algorithm variable selection
A comparison of fitness-case sampling methods for Symbolic Regression
Geometric Semantic Genetic Programming with Local Search

Bilateral Contracts and Grants with Industry

Partnerships and Cooperations

Dissemination

Bibliography

Inria | Raweb 2014 | Presentation of the Project-Team CQFD


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Section: New Results

The economics of the cloud: price competition and congestion

Participants : Jonatha Anselmi, Danilo Ardagna, Jonh C.s. Lui, Adam Wierman, Yunjian Xu, Zichao Yang.

This work proposes a model to study the interaction of price competition and congestion in the cloud computing marketplace. Specifically, we propose a three-tier market model that captures a marketplace with users purchasing services from Software-as-Service (SaaS) providers, which in turn purchase computing resources from either Provider-as-a-Service (PaaS) providers or Infrastructure-as-a-Service (IaaS) providers. Within each level, we define and characterize competitive equilibria. Further, we use these characterizations to understand the relative profitability of SaaSs and PaaSs/IaaSs, and to understand the impact of price competition on the user experienced performance, i.e., the `price of anarchy' of the cloud marketplace. Our results highlight that both of these depend fundamentally on the degree to which congestion results from shared or dedicated resources in the cloud. This work has been submitted to an international journal. A preliminary has been published in [10] .

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