PhD "A game-theoretic approach to efficient and sustainable cloud computing systems." M/F
il y a 1 mois
about the role
Your role is to carry out a PhD on “a game-theoretic approach to efficient and sustainable cloud computing”.
Context and problemHuman societies and technologies must evolve under the pressure of various factors such as natural resources depletion, limited availability of energy or the growth of the population and its needs (including in the digital domain where demand is strongly increasing).
In this context, cloud computing solutions are large-scale systems typically distributed and with high energy and resource consumptions. These systems must be modified or redesigned to be more efficient and more sustainable, explicitly taking into account constraints on resources or energy and their usages.
Scientific objectivesThis thesis aims at using game theory to analyze and propose solutions to the previous problem. However, existing equilibrium concepts with constraints [I], such as the generalized Nash equilibria [II][III] or (more recently) constrained correlated equilibria [IV] (combining correlation, stability and constraints), are not necessarily suitable for dynamic games, do not allow for some classes of constraints or must be adapted to more general assumptions on the players’ information. Furthermore, these solutions are typically not suitable for implementation on large-scale systems (such as networks and clouds) where distributed architectures must be considered.
The main challenges to address are
model the problem as a game with constraints assess the relevance of constrained correlated equilibria & related developments or define and analyze a suitable solution concept propose algorithmic solutions to compute the equilibria assess the performances of the solution.References
Kulkarni, Games and teams with shared constraints, Phil. Trans. R. Soc., 2017. Rosen, Existence and uniqueness of equilibrium points for concave n-person games, Econometrica, 1965. Facchinei et al., Generalized Nash equilibrium problems. 4OR, Sep 2007. Aumann, Correlated Equilibrium as an Expression of Bayesian Rationality. Econometrica, 1987.
about you
Skills (scientific and technical) and personal qualities required for the position
Strong expertise in mathematics. Applied mathematics, particularly in decision-taking domains: game theory, optimal control and optimization. The candidate must be motivated by the mathematical study of the problem (modelling and analysis) and by algorithmic aspects. Programming in Python. A good level in english is required. Autonomy, curiosity, patience, rigor, motivation and team spirit.Required Education (Master's degree, engineering degree, PhD, scientific and technical ):
Engineering degree or Master’s degree in mathematics, applied mathematics and decision-taking sciences.
Expériences souhaitées (stages, …)
Internship in mathematics and decision-taking sciences (game theory, optimization,...) A first experience in game theory is preferred (internship or project) and a first approach of the domain (lectures or readings at master’s degree level) is required.
additional information
Within the Networks department of Orange Innovation, you will take part in a dynamic and multidisciplinary research environment including experts and researchers in applied mathematics (operations research, artificial intelligence, game theory), networks (radio technologies), and energy domains (technical environment).
You will contribute to providing mathematical and algorithmic tools based on state-of-the-art mathematical methods to address a key issue for the Orange group.
You will have the opportunity to showcase your research through scientific communications in conferences or international journals, as well as internally within the Orange Group, with possible interactions in France or other subsidiaries internationally.
department
Orange Innovation brings together the research and innovation activities and expertise of the Group's entities and countries. We work every day to ensure that Orange is recognized as an innovative operator by its customers and we create value for the Group and the Brand in each of our projects. With 720 researchers, thousands of marketers, developers, designers and data analysts, it is the expertise of our 6,000 employees that fuels this ambition every day.
Orange Innovation anticipates technological breakthroughs and supports the Group's countries and entities in making the best technological choices to meet the needs of our consumer and business customers.
At Orange Innovation, you will take part in a research team specialized in mathematical modelling, data science and network technologies. This team aims at analyzing network performances, model and solve decision-taking problems and design algorithmic solutions based on optimization, game theory and artificial intelligence.
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