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Ph.D de

Ph.D
Group : Graphs, ALgorithms and Combinatorics

Conception et analyse de protocoles, pour les réseaux de capteurs sans fil, prenant en compte la consommation d'énergie

Starts on 01/10/2013
Advisor : LISSER, Abdel

Funding : Bourse pour étudiant étranger
Affiliation : Université Paris-Sud
Laboratory : LRI-Graphes

Defended on 15/12/2017, committee :
Directeur de thèse :
- M. Joffroy BEAUQUIER Université Paris Sud, Saclay

Co-encadrante :
- Mme. Janna BURMAN Université Paris Sud, Saclay

Rapporteurs :
- M. Luís E. T. RODRIGUES, Université de Lisbonne
- M. Alexandre CAMINADA, Université de Technologie de Belfort-Montbéliard

Examinateurs :
- M. Abdel LISSER Université Paris Sud, Saclay
- Mme. Janny LEUNG Université chinoise de Hong Kong

Invité :
- M. Thomas NOWAKUniversité Paris Sud, Saclay

Research activities :

Abstract :
In this thesis, we propose a formal energy model which allows an analytical study of energy consumption, for the first time in the context of population protocols. Population protocols model sensor networks where anonymous and uniformly bounded memory sensors move unpredictably and communicate in pairs. To illustrate the power and the usefulness of the proposed energy model, we present formal analyses on time and energy, for the worst and the average cases, for the fundamental task of data collection. Two power-aware population protocols, (deterministic) EB-TTFM and (randomized) lazy-TTF, are proposed and studied for two different fairness conditions, respectively. Moreover, to obtain the best parameters in lazy-TTF, we adopt optimization techniques and evaluate the resulting performance by experiments. Then, we continue the study on optimization for the power-aware data collection problem in wireless body area networks. A minmax multi-commodity netflow formulation is proposed to optimally route data packets by minimizing the worst power consumption. Then, a variable neighborhood search approach is developed and the numerical results show its efficiency. At last, a stochastic optimization model, namely the chance constrained semidefinite programs, is considered for the realistic decision making problems with random parameters. A novel simulation-based algorithm is proposed with experiments on a real control theory problem. We show that our method allows a less conservative solution, than other approaches, within reasonable time.

Ph.D. dissertations & Faculty habilitations
DECODING THE PLATFORM SOCIETY: ORGANIZATIONS, MARKETS AND NETWORKS IN THE DIGITAL ECONOMY
The original manuscript conceptualizes the recent rise of digital platforms along three main dimensions: their nature of coordination devices fueled by data, the ensuing transformations of labor, and the accompanying promises of societal innovation. The overall ambition is to unpack the coordination role of the platform and where it stands in the horizon of the classical firm – market duality. It is also to precisely understand how it uses data to do so, where it drives labor, and how it accommodates socially innovative projects. I extend this analysis to show continuity between today’s society dominated by platforms and the “organizational society”, claiming that platforms are organized structures that distribute resources, produce asymmetries of wealth and power, and push social innovation to the periphery of the system. I discuss the policy implications of these tendencies and propose avenues for follow-up research.

DISTRIBUTED COMPUTING WITH LIMITED RESOURCES


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