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22 results on '"ANR-18-CE25-0012,MAESTRO5G,Gestion de slices dans le réseau d'accès mobile de la 5G(2018)"'

1. Information-Energy Regions in the Finite Block-Length Regime with Finite Channel Inputs

Author

Ul Zuhra, Sadaf, Perlaza, Samir, Poor, H. Vincent, Altman, Eitan, Skoglund, Mikael, Network Engineering and Operations (NEO ), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Department of Electrical and Computer Engineering [Princeton] (ECE), Princeton University, Laboratoire de Géométrie Algébrique et Applications à la Théorie de l'Information (GAATI), Université de la Polynésie Française (UPF), Laboratoire Informatique d'Avignon (LIA), Avignon Université (AU)-Centre d'Enseignement et de Recherche en Informatique - CERI, Laboratory of Information, Network and Communication Sciences (LINCS), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut Mines-Télécom [Paris] (IMT)-Sorbonne Université (SU), KTH School of Electrical Engineering, Royal Institute of Technology [Stockholm] (KTH ), ANR-18-CE25-0012,MAESTRO5G,Gestion de slices dans le réseau d'accès mobile de la 5G(2018), European Project: 872172,H2020-EU.1.3. - EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions,TESTBED2(2020), Zuhra, Sadaf ul, APPEL À PROJETS GÉNÉRIQUE 2018 - Gestion de slices dans le réseau d'accès mobile de la 5G - - MAESTRO5G2018 - ANR-18-CE25-0012 - AAPG2018 - VALID, and Testing and Evaluating Sophisticated information and communication Technologies for enaBling scalablE smart griD Deployment - TESTBED2 - - H2020-EU.1.3. - EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions2020-02-01 - 2025-07-31 - 872172 - VALID

Subjects
converse, finite channel inputs, SWIPT, [MATH.MATH-IT]Mathematics [math]/Information Theory [math.IT], finite block-length, information-energy regions, [MATH.MATH-IT] Mathematics [math]/Information Theory [math.IT], [INFO.INFO-IT]Computer Science [cs]/Information Theory [cs.IT], SIET, achievability, [INFO.INFO-IT] Computer Science [cs]/Information Theory [cs.IT], Simultaneous information and energy transmission, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, [SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing
Abstract

This paper provides a complete characterization of the information-energy region of simultaneous information and energy transmission over an additive white Gaussian noise channel in the finite block-length regime with finite sets of channel input symbols. Given a set of channel input symbols, the converse characterizes the tuples of information rate, energy rate, decoding error probability (DEP) and energy outage probability (EOP) that cannot be achieved by any code built using the given set of channel inputs. A novel method for constructing a family of codes that respects the given information rate, energy rate, DEP and EOP requirements is proposed. The achievable region identifies the set of tuples of information rate, energy rate, DEP and EOP that can be achieved by the constructed family of codes. The proposed construction proves to be information rate, energy rate, and EOP optimal. The achieved DEP is, however, sub-optimal, owing to the choice of the decoding regions made during the construction.

Published
2022

2. Information-Energy Trade-offs with EH Non-linearities in the Finite Block-Length Regime with Finite Constellations

Author

Sadaf Ul Zuhra, Samir M. Perlaza, H. Vincent Poor, Mikael Skoglund, Network Engineering and Operations (NEO ), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Department of Electrical and Computer Engineering [Princeton] (ECE), Princeton University, Laboratoire de Géométrie Algébrique et Applications à la Théorie de l'Information (GAATI), Université de la Polynésie Française (UPF), Royal Institute of Technology [Stockholm] (KTH ), in part by the U.S. National Science Foundation under Grant CCF-1908308, and in part by the French Government through the 'Plan de Relance' and 'Programme d’investissements d’avenir'., ANR-18-CE25-0012,MAESTRO5G,Gestion de slices dans le réseau d'accès mobile de la 5G(2018), and European Project: 872172,H2020-EU.1.3. - EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions,TESTBED2(2020)

Subjects
[INFO.INFO-IT]Computer Science [cs]/Information Theory [cs.IT], [MATH.MATH-IT]Mathematics [math]/Information Theory [math.IT], Data_CODINGANDINFORMATIONTHEORY, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, Computer Science::Information Theory
Abstract

International audience; This paper characterizes the trade-offs between the information and energy transmission rates, the decoding error probability, and the energy outage probability in simultaneous information and energy transmission over an additive white Gaussian noise channel. The results in this paper take into account the impact of energy harvester (EH) non-linearities on the harvested energy. The analysis is carried out in the finite block-length regime with finite constellations. Improved converse and achievability bounds that account for the EH non-linearities are presented.

Published
2022
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3. Strategic investments in distributed computing: A stochastic game perspective

Author

Swapnil Dhamal, Walid Ben-Ameur, Tijani Chahed, Eitan Altman, Albert Sunny, Sudheer Poojary, Network Engineering and Operations (NEO ), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Laboratoire Informatique d'Avignon (LIA), Avignon Université (AU)-Centre d'Enseignement et de Recherche en Informatique - CERI, Services répartis, Architectures, MOdélisation, Validation, Administration des Réseaux (SAMOVAR), Institut Mines-Télécom [Paris] (IMT)-Télécom SudParis (TSP), CNRS-périodiques (CP), Centre National de la Recherche Scientifique (CNRS), Institut Polytechnique de Paris (IP Paris), Département Réseaux et Services Multimédia Mobiles (TSP - RS2M), Méthodes et modèles pour les réseaux (METHODES-SAMOVAR), Institut Mines-Télécom [Paris] (IMT)-Télécom SudParis (TSP)-Institut Mines-Télécom [Paris] (IMT)-Télécom SudParis (TSP), Laboratory of Information, Network and Communication Sciences (LINCS), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut Mines-Télécom [Paris] (IMT)-Sorbonne Université (SU), Indian Institut of Technology [Palakkad] (ITT Palakkad), Université Côte d'Azur (UCA), and ANR-18-CE25-0012,MAESTRO5G,Gestion de slices dans le réseau d'accès mobile de la 5G(2018)

Subjects
[INFO.INFO-GT]Computer Science [cs]/Computer Science and Game Theory [cs.GT], Artificial Intelligence, Computer Networks and Communications, Hardware and Architecture, Markov perfect equilibrium, Blockchain mining, [INFO.INFO-DC]Computer Science [cs]/Distributed, Parallel, and Cluster Computing [cs.DC], Stochastic games, Software, Distributed computing, Theoretical Computer Science
Abstract

International audience; We study a stochastic game with a dynamic set of players, for modeling and analyzing their computational investment strategies in distributed computing. Players obtain a certain reward for solving a problem, while incurring a certain cost based on the invested time and computational power. We present our framework while considering a contemporary application of blockchain mining, and show that the framework is applicable to certain other distributed computing settings as well. For an in-depth analysis, we consider a particular yet natural scenario where the rate of solving the problem is proportional to the total computational power invested by the players. We show that, in Markov perfect equilibrium, players with cost parameters exceeding a certain threshold, do not invest; while those with cost parameters less than this threshold, invest maximal power. We arrive at an interesting conclusion that the players need not have information about the system state as well as each others' parameters, namely, cost parameters and arrival/departure rates. With extensive simulations and insights through mean field approximation, we study the effects of players' arrival/departure rates and the system parameters on the players' utilities.

Published
2022
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4. Mobile Traffic Forecasting for Network Slices: A Federated-Learning Approach

Author

Hnin Pann Phyu, Diala Naboulsi, Razvan Stanica, Ecole de Technologie Supérieure [Montréal] (ETS), AlGorithmes et Optimisation pour Réseaux Autonomes (AGORA), CITI Centre of Innovation in Telecommunications and Integration of services (CITI), Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Inria Lyon, Institut National de Recherche en Informatique et en Automatique (Inria), ANR-18-CE25-0011,CANCAN,Adaptation basée sur le contenu et le contexte dans les réseaux mobiles(2018), and ANR-18-CE25-0012,MAESTRO5G,Gestion de slices dans le réseau d'accès mobile de la 5G(2018)

Subjects
Machine Learning, [INFO.INFO-NI]Computer Science [cs]/Networking and Internet Architecture [cs.NI], Traffic Forecasting, [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG], Data Privacy, Network Slicing
Abstract

International audience; Network slicing is one of the cornerstones for next-generation mobile communication systems. Specifically, it enables Mobile Virtual Network Operators (MVNOs) to offer various types of services over the same physical infrastructure owned by an Infrastructure Provider (InP). To satisfy the dynamic user requirements and ensure resource efficiency, MVNOs need to estimate the future traffic demand in advance, to pre-allocate/reconfigure the resources at the base stations. However, this per-slice traffic forecasting exploits information that is clearly sensitive for the MVNOs from a business point of view, and which might even disclose private data regarding some users. Hence, it is vital for MVNOs to ensure data privacy while conducting traffic forecasting. Bearing this in mind, we propose the Federated Proximal Long Short-Term Memory (FPLSTM) framework, which allows MVNOs to train their local models with their private dataset at each base station without compromising data privacy. Simultaneously, an InP global model is updated through the aggregation of local models weights. Prediction results obtained by training the models on a real-world dataset indicate that the forecasting performance of FPLSTM is as accurate as state-of-the-art solutions, while ensuring data privacy, computation and communication cost efficiency.

Published
2022

5. An Open Dataset for Beyond-5G Data-driven Network Automation Experiments

Author

Chi-Dung Phung, Nour-El-Houda Yellas, Salah Bin Ruba, Stefano Secci, CEDRIC. Réseaux et Objets Connectés (CEDRIC - ROC), Centre d'études et de recherche en informatique et communications (CEDRIC), Ecole Nationale Supérieure d'Informatique pour l'Industrie et l'Entreprise (ENSIIE)-Conservatoire National des Arts et Métiers [CNAM] (CNAM), HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-Ecole Nationale Supérieure d'Informatique pour l'Industrie et l'Entreprise (ENSIIE)-Conservatoire National des Arts et Métiers [CNAM] (CNAM), HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM), IA/AMI-5G INFLUENCE, ANR-18-CE25-0011,CANCAN,Adaptation basée sur le contenu et le contexte dans les réseaux mobiles(2018), ANR-18-CE25-0012,MAESTRO5G,Gestion de slices dans le réseau d'accès mobile de la 5G(2018), and European Project: 101015922,H2020-EU.2.1.1. - INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies - Information and Communication Technologies (ICT),AI@EDGE(2021)

Subjects
[INFO.INFO-NI]Computer Science [cs]/Networking and Internet Architecture [cs.NI], ComputingMilieux_MISCELLANEOUS
Abstract

International audience

Published
2022
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6. Poster: Privacy-Aware Decentralized Multi-Slice Traffic Forecasting

Author

Pann Phyu, Hnin, Naboulsi, Diala, Stanica, Razvan, Ecole de Technologie Supérieure [Montréal] (ETS), AlGorithmes et Optimisation pour Réseaux Autonomes (AGORA), CITI Centre of Innovation in Telecommunications and Integration of services (CITI), Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Inria Lyon, Institut National de Recherche en Informatique et en Automatique (Inria), ANR-18-CE25-0011,CANCAN,Adaptation basée sur le contenu et le contexte dans les réseaux mobiles(2018), and ANR-18-CE25-0012,MAESTRO5G,Gestion de slices dans le réseau d'accès mobile de la 5G(2018)

Subjects
traffic forecasting, data privacy, [INFO.INFO-NI]Computer Science [cs]/Networking and Internet Architecture [cs.NI], machine learning, network slicing, [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG]
Abstract

International audience; In this work, taking the perspective of Mobile Virtual Network Operators (MVNOs), we tackle the multi-slice traffic forecasting problem, while respecting the data privacy of users. To this end, we propose the Federated Proximal Long Short-Term Memory (FPLSTM) framework, which allows MVNOs to train at each base station their local models with their private datasets, without compromising data privacy. Prediction results obtained by evaluating the models on a real-world dataset indicate that the forecast of FPLSTM is as accurate as state-of-the-art solutions while ensuring data privacy as well as computation and communication costs efficiency.

Published
2022

7. Achievable Information-Energy Region in the Finite Block-Length Regime with Finite Constellations

Author

Zuhra, Sadaf Ul, Perlaza, Samir M., Poor, H. Vincent, Altman, Eitan, Network Engineering and Operations (NEO ), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Laboratoire de Géométrie Algébrique et Applications à la Théorie de l'Information (GAATI), Université de la Polynésie Française (UPF), Department of Electrical and Computer Engineering [Princeton] (ECE), Princeton University, Laboratoire Informatique d'Avignon (LIA), Avignon Université (AU)-Centre d'Enseignement et de Recherche en Informatique - CERI, Laboratory of Information, Network and Communication Sciences (LINCS), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut Mines-Télécom [Paris] (IMT)-Sorbonne Université (SU), by the U.S. National Science Foundation under Grant CCF-1908308, and in part by the French Government through the 'Plan de Relance' and 'Programme d’investissements d’avenir'., ANR-18-CE25-0012,MAESTRO5G,Gestion de slices dans le réseau d'accès mobile de la 5G(2018), and European Project: 872172,H2020-EU.1.3. - EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions,TESTBED2(2020)

Subjects
FOS: Computer and information sciences, [INFO.INFO-IT]Computer Science [cs]/Information Theory [cs.IT], Information Theory (cs.IT), Computer Science - Information Theory, [MATH.MATH-IT]Mathematics [math]/Information Theory [math.IT], [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
Abstract

International audience; This paper characterizes an achievable information-energy region of simultaneous information and energy transmission over an additive white Gaussian noise channel. This analysis is performed in the finite block-length regime with finite constellations. More specifically, a method for constructing a family of codes is proposed and the set of achievable tuples of information rate, energy rate, decoding error probability (DEP) and energy outage probability (EOP) is characterized. Using existing converse results, it is shown that the construction is information rate, energy rate, and EOP optimal. The achieved DEP is, however, sub-optimal.

Published
2022
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8. Function splitting, isolation, and placement trade-offs in network slicing

Author

Stefano Secci, Amal Benhamiche, Nancy Perrot, Wesley da Silva Coelho, CEDRIC. Réseaux et Objets Connectés (CEDRIC - ROC), Centre d'études et de recherche en informatique et communications (CEDRIC), Ecole Nationale Supérieure d'Informatique pour l'Industrie et l'Entreprise (ENSIIE)-Conservatoire National des Arts et Métiers [CNAM] (CNAM)-Ecole Nationale Supérieure d'Informatique pour l'Industrie et l'Entreprise (ENSIIE)-Conservatoire National des Arts et Métiers [CNAM] (CNAM), Orange Labs, and ANR-18-CE25-0012,MAESTRO5G,Gestion de slices dans le réseau d'accès mobile de la 5G(2018)

Subjects
Optimization problem, Computer Networks and Communications, Computer science, media_common.quotation_subject, Distributed computing, Trade offs, 020206 networking & telecommunications, Provisioning, 02 engineering and technology, Slicing, functional split, [INFO.INFO-NI]Computer Science [cs]/Networking and Internet Architecture [cs.NI], sharing policy, 0202 electrical engineering, electronic engineering, information engineering, Isolation (database systems), Electrical and Electronic Engineering, Function (engineering), Core function, 5G, Network slicing, media_common
Abstract

International audience; We model the network slice provisioning as an optimization problem including novel mapping and provisioning requirements rising with new radio and core function placement policies. We propose an open-access framework based on an MILP formulation that encompasses flexible functional splitting, with possibly different splitting for different slices and slice subnets, while taking into account different network sharing policies from 5G specifications. We also consider novel mapping and continuity constraints specific to the 5G architectures and beyond. We show by numerical simulations the impact of taking into full and partial consideration these peculiar novel technical constraints.

Published
2021
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9. Transmission simultanée d’information et d’énergie avec des constellations finies

Author

Samir M. Perlaza, Eitan Altman, Sadaf ul Zuhra, Network Engineering and Operations (NEO ), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Laboratoire de Géométrie Algébrique et Applications à la Théorie de l'Information (GAATI), Université de la Polynésie Française (UPF), Department of Electrical Engineering [Princeton] (EE), Princeton University, Laboratoire Informatique d'Avignon (LIA), Centre d'Enseignement et de Recherche en Informatique - CERI-Avignon Université (AU), Laboratory of Information, Network and Communication Sciences (LINCS), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut Mines-Télécom [Paris] (IMT)-Sorbonne Université (SU), Inria Sophia Antipolis - Méditerranée, Avignon Université (AU)-Centre d'Enseignement et de Recherche en Informatique - CERI, and ANR-18-CE25-0012,MAESTRO5G,Gestion de slices dans le réseau d'accès mobile de la 5G(2018)

Subjects
FOS: Computer and information sciences, Computer Science - Information Theory, Information Theory (cs.IT), [MATH.MATH-IT]Mathematics [math]/Information Theory [math.IT], 020206 networking & telecommunications, 02 engineering and technology, Data_CODINGANDINFORMATIONTHEORY, Constellations finies, Topology, Set (abstract data type), Electric power transmission, Transmission (telecommunications), [INFO.INFO-IT]Computer Science [cs]/Information Theory [cs.IT], Bounded function, 0202 electrical engineering, electronic engineering, information engineering, Code (cryptography), Finite constellations, Simultaneous information and energy transmission, Transmission simultanée d’information et d’énergie, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, Energy (signal processing), Mathematics, Communication channel, Block (data storage), Computer Science::Information Theory
Abstract

In this report, the fundamental limits on the rates at which information and energy can be simultaneously transmitted over an additive white Gaussian noise channel are studied under the following assumptions: (a) the channel is memoryless; (b) the number of channel input symbols (constellation size) and block length are finite; and (c) the decoding error probability (DEP) and the energy outage probability (EOP) are bounded away from zero. In particular, it is shown that the limits on the maximum information and energy transmission rates; and the minimum DEP and EOP, are essentially set by the type induced by the code used to perform the transmission. That is, the empirical frequency with which each channel input symbol appears in the codewords. Using this observation, guidelines for optimal constellation design for simultaneous energy and information transmission are presented.; Dans ce rapport, les limites fondamentales des débits auxquelles l’information et l’énergie peuvent être transmises simultanément sur un canal de bruit gaussien blanc additif sont étudiées sous les hypothèses suivantes : (a) le canal est sans mémoire; (b) le nombre de symboles d’entrée du canal (taille de la constellation) et la durée de la transmission sont finis ; et (c) la probabilité d’erreur de décodage (DEP) et la probabilité de coupure d’énergie (EOP) sont limitées par des bornes inférieures strictement positives. En particulier, il est montré que les limites sur les débits maximaux de transmission d’information et d’énergie et les DEP et EOP minimaux, sont essentiellement fixés par le type induit par le code utilisé pour effectuer la transmission. C’est-à-dire la fréquence empirique à laquelle chaque symbole d’entrée de canal apparaît dans les mots de code. En utilisant cette observation, des recommandations pour la conception optimale des constellations pour la transmission simultanée dinformation et d’énergie sont présentées.

Published
2021
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10. A Math-Heuristic for Network Slice Design

Author

Da Silva Coelho, Wesley, Benhamiche, Amal, Perrot, Nancy, Secci, Stefano, Secci, Stefano, APPEL À PROJETS GÉNÉRIQUE 2018 - Gestion de slices dans le réseau d'accès mobile de la 5G - - MAESTRO5G2018 - ANR-18-CE25-0012 - AAPG2018 - VALID, CEDRIC. Réseaux et Objets Connectés (CEDRIC - ROC), Centre d'études et de recherche en informatique et communications (CEDRIC), Ecole Nationale Supérieure d'Informatique pour l'Industrie et l'Entreprise (ENSIIE)-Conservatoire National des Arts et Métiers [CNAM] (CNAM)-Ecole Nationale Supérieure d'Informatique pour l'Industrie et l'Entreprise (ENSIIE)-Conservatoire National des Arts et Métiers [CNAM] (CNAM), Orange Labs, Orange Labs [Meylan], Orange Labs [Belfort] (Orange Labs), France Télécom, and ANR-18-CE25-0012,MAESTRO5G,Gestion de slices dans le réseau d'accès mobile de la 5G(2018)

Subjects
[INFO.INFO-NI]Computer Science [cs]/Networking and Internet Architecture [cs.NI], flexible splitting, [INFO.INFO-NI] Computer Science [cs]/Networking and Internet Architecture [cs.NI], [INFO.INFO-RO] Computer Science [cs]/Operations Research [cs.RO], math-heuristic, [INFO.INFO-RO]Computer Science [cs]/Operations Research [cs.RO], Network slicing
Abstract

International audience; In this paper, we address the Network Slice Design problem, which arises from blueprinting end-to-end communication networks using fifth-generation (5G) radio access technology. With regard to new sharing policies and radio-access integration, it shows peculiar requirements with respect to conventional function placement and routing problems. To address the underlying optimization problem, we propose an open-access framework based on a math-heuristic that encompasses control-plane and data-plane separation and novel mapping and decomposition dimensions influencing the placement and interconnection of slices. Our framework also incorporates flexible functional splitting, with possibly different splitting for different slices while taking into consideration dependency factors such as varying network latency and data volume throughout the virtual access networks. Numerical results are then presented to assess the efficiency of our approach.

Published
2021

11. Strategic Resource Management in 5G Network Slicing. (Invited paper)

Author

Datar, Mandar, Altman, Eitan, datar, mandar, APPEL À PROJETS GÉNÉRIQUE 2018 - Gestion de slices dans le réseau d'accès mobile de la 5G - - MAESTRO5G2018 - ANR-18-CE25-0012 - AAPG2018 - VALID, Network Engineering and Operations (NEO ), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Laboratoire Informatique d'Avignon (LIA), Avignon Université (AU)-Centre d'Enseignement et de Recherche en Informatique - CERI, Laboratory of Information, Network and Communication Sciences (LINCS), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut Mines-Télécom [Paris] (IMT)-Sorbonne Université (SU), Nokia Bell Labs, MAESTRO-5G-ANR, ANR-18-CE25-0012,MAESTRO5G,Gestion de slices dans le réseau d'accès mobile de la 5G(2018), Centre d'Enseignement et de Recherche en Informatique - CERI-Avignon Université (AU), and CERI/LIA - University of Avignon

Subjects
game theory, 5G network slicing, trading post mechanism, tullock contest, resource allocation, [INFO]Computer Science [cs], Communication service market, [INFO] Computer Science [cs]
Abstract

International audience; Network Slicing is one of the essential concepts that has been introduced in 5G networks design to support demand expressed by next generation services. Network slicing will also bring new business opportunities for service providers (SPs) and virtual network operators, allowing them to run their virtual, independent business operations on shared physical infrastructure. We consider a marketplace where service providers (SPs) i.e., slice tenants lease the resources from an infrastructure provider (InP) through a network slicing mechanism. They compete to offer a certain communication service to end-users. We show that the competition between SPs can be model using the multiresource Tullock contest (TC) framework, where SPs exert effort by expending costly resource to attract users. We study the competition between the SPs under a static and dynamic resource sharing scheme. In a dynamic resource sharing scheme, SPs are pre-assigned with fixed shares (budgets) of infrastructure, and they are allowed to redistribute their shares and customise their allocation to maximise their profit. The decision problem of SPs is analysed using non-cooperative game theory, and it is shown that the resultant game admits a unique Nash Equilibrium (NE). Furthermore, a distributed reinforcement algorithm is proposed that allows each SP to reach the game's unique Nash equilibrium. Finally, simulations results are conducted to analyse the interaction between market players and the economic efficacy of the network sharing mechanism.

Published
2021

12. On the impact of novel function mappings, sharing policies, and split settings in network slice design

Author

Wesley da Silva Coelho, Stefano Secci, Amal Benhamiche, Nancy Perrot, Orange Labs [Chatillon], Orange Labs, CEDRIC. Réseaux et Objets Connectés (CEDRIC - ROC), Centre d'études et de recherche en informatique et communications (CEDRIC), Ecole Nationale Supérieure d'Informatique pour l'Industrie et l'Entreprise (ENSIIE)-Conservatoire National des Arts et Métiers [CNAM] (CNAM)-Ecole Nationale Supérieure d'Informatique pour l'Industrie et l'Entreprise (ENSIIE)-Conservatoire National des Arts et Métiers [CNAM] (CNAM), and ANR-18-CE25-0012,MAESTRO5G,Gestion de slices dans le réseau d'accès mobile de la 5G(2018)

Subjects
Mathematical optimization, Optimization problem, Noise measurement, network slicing, Computer science, media_common.quotation_subject, Joins, 020206 networking & telecommunications, Cascading Style Sheets, Provisioning, 02 engineering and technology, functional split, [INFO.INFO-NI]Computer Science [cs]/Networking and Internet Architecture [cs.NI], sharing policy, 0202 electrical engineering, electronic engineering, information engineering, 020201 artificial intelligence & image processing, [MATH]Mathematics [math], Function (engineering), computer, Core function, 5G, computer.programming_language, media_common
Abstract

International audience; In this work, we model the network slice provi-sioning as an optimization problem including novel mapping and provisioning requirements rising with new 5G radio and core function placement policies. We propose an MILP-based formulation that joins different functional splitting strategies with different network function sharing policies and novel mapping continuity constraints from 5G specifications. We show by numerical simulations the impact of taking into full and partial consideration these peculiar sets of novel technical constraints.

Published
2020
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13. Mathematical Formulation for the Network Slice Design Problem

Author

da Silva Coelho, Wesley, Benhamiche, Amal, Perrot, Nancy, Secci, Stefano, CEDRIC. Réseaux et Objets Connectés (CEDRIC - ROC), Centre d'études et de recherche en informatique et communications (CEDRIC), Ecole Nationale Supérieure d'Informatique pour l'Industrie et l'Entreprise (ENSIIE)-Conservatoire National des Arts et Métiers [CNAM] (CNAM)-Ecole Nationale Supérieure d'Informatique pour l'Industrie et l'Entreprise (ENSIIE)-Conservatoire National des Arts et Métiers [CNAM] (CNAM), Orange Labs, ANR-18-CE25-0012,MAESTRO5G,Gestion de slices dans le réseau d'accès mobile de la 5G(2018), da Silva Coelho, Wesley, APPEL À PROJETS GÉNÉRIQUE 2018 - Gestion de slices dans le réseau d'accès mobile de la 5G - - MAESTRO5G2018 - ANR-18-CE25-0012 - AAPG2018 - VALID, and ANR-18-CE25-0012,MAESTRO5G,MANAGEMENT OF SLICES IN THE RADIO ACCESS OF 5G NETWORKS(2018)

Subjects
[MATH.MATH-CO] Mathematics [math]/Combinatorics [math.CO], [MATH.MATH-CO]Mathematics [math]/Combinatorics [math.CO], [MATH] Mathematics [math], [MATH]Mathematics [math]
Abstract

In this document, we provide a Mixed Integer Linear Program to the Network Slice Design problem, which includes novel mapping decision points rising with new 5G radio and core function placement policies. The model in particular encompasses flexible functional splitting, with possibly different splitting for different slices, and sub-slice and network function decomposition.

Published
2020

14. Network Function Mapping: from 3G Entities to 5G Service-Based Functions Decomposition

Author

Wesley da Silva Coelho, Amal Benhamiche, Nancy Perrot, Stefano Secci, CEDRIC. Réseaux et Objets Connectés (CEDRIC - ROC), Centre d'études et de recherche en informatique et communications (CEDRIC), Ecole Nationale Supérieure d'Informatique pour l'Industrie et l'Entreprise (ENSIIE)-Conservatoire National des Arts et Métiers [CNAM] (CNAM)-Ecole Nationale Supérieure d'Informatique pour l'Industrie et l'Entreprise (ENSIIE)-Conservatoire National des Arts et Métiers [CNAM] (CNAM), Orange Labs, and ANR-18-CE25-0012,MAESTRO5G,Gestion de slices dans le réseau d'accès mobile de la 5G(2018)

Subjects
010302 applied physics, Service (systems architecture), Standardization, Computer Networks and Communications, Computer science, 3rd Generation Partnership Project 2, Quality of service, Mobile broadband, Legacy system, 020206 networking & telecommunications, 02 engineering and technology, Technical documentation, 01 natural sciences, Data science, Identification (information), [INFO.INFO-NI]Computer Science [cs]/Networking and Internet Architecture [cs.NI], Management of Technology and Innovation, 0103 physical sciences, 0202 electrical engineering, electronic engineering, information engineering, Safety, Risk, Reliability and Quality, Law
Abstract

International audience; The Third Generation Partnership Project (3GPP) was established to bring together several standards organization to address the needs related to the specification of mobile broadband. Originally targeting the evolution from 2G to 3G, 3GPP continues at the forefront of the standardization effort leading to 5G and beyond. Given the growing diversity of services and the explosion of mobile users year by year, evolving architectures have then been successively proposed by the group in order to expand the limits of legacies systems. We overview this evolution, summarizing the transformation of core systems and their related decomposition, aggregation, and mapping operations from 3G to 5G systems. We also present an in-depth description of 5G Core based on recent technical documents delivered by 3GPP. We end with the identification of potential operational and technical challenges in 5G systems.

Published
2020
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15. A Mechanism for Price Differentiation and Slicing in Wireless Networks

Author

Datar, M., Altman, E., Pellegrini, F., El Azouzi, R., Touati, C., Network Engineering and Operations (NEO ), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Laboratoire Informatique d'Avignon (LIA), Avignon Université (AU)-Centre d'Enseignement et de Recherche en Informatique - CERI, Laboratory of Information, Network and Communication Sciences (LINCS), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut Mines-Télécom [Paris] (IMT)-Sorbonne Université (SU), Fondazione Bruno Kessler [Trento, Italy] (FBK), Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria), This work was supported by the National French Research Agency project MAnagEment of Slices in The Radio access Of 5G networks (MAESTRO 5G), and ANR-18-CE25-0012,MAESTRO5G,Gestion de slices dans le réseau d'accès mobile de la 5G(2018)

Subjects
game theory, Kelly mechanism, wireless Network slicing, Index Terms-Game theory, [INFO.INFO-GT]Computer Science [cs]/Computer Science and Game Theory [cs.GT], normalised equilibrium, ressource allocation, normalised equi- librium, primal-dual algorithms
Abstract

International audience; Slicing is emerging as a promising technique to support new differentiated services in 5G networks. It provides the necessary flexility and scalability associated with future services. To maintain satisfactory services requirements and high profit for service providers, a slice may be designing according to the varying demands and resource availability. This paper develops a framework for resources allocation between slicing and business layer for multi-tenant slicing, e.g. virtual wireless operators, service providers and smart cities services. This paper proposes a flexible mechanism based on a biding scheme for slicing allocation, which achieve desirable fairness and efficiency among the network slices of the different tenants and their associated users. We then design a practical algorithms to realise the proposed desired solution. We also show through the simulation the efficiency of our approach in term of efficiency and fairness.

Published
2020

16. Joint Pricing and Resources Allocation for 5G Network Slicing

Author

Datar, Mandar, Altman, Eitan, de Pellegrini, Francesco, Azouzi, Rachid, Touati, Corinne, Network Engineering and Operations (NEO ), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Laboratoire Informatique d'Avignon (LIA), Avignon Université (AU)-Centre d'Enseignement et de Recherche en Informatique - CERI, Laboratory of Information, Network and Communication Sciences (LINCS), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut Mines-Télécom [Paris] (IMT)-Sorbonne Université (SU), Fondazione Bruno Kessler [Trento, Italy] (FBK), Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria), This work was supported by the National French Research Agency project MAnagEment of Slices in The Radio access Of 5G networks (MAESTRO 5G), ANR-18-CE25-0012,MAESTRO5G,Gestion de slices dans le réseau d'accès mobile de la 5G(2018), Altman, Eitan, and APPEL À PROJETS GÉNÉRIQUE 2018 - Gestion de slices dans le réseau d'accès mobile de la 5G - - MAESTRO5G2018 - ANR-18-CE25-0012 - AAPG2018 - VALID

Subjects
game theory, Kelly mechanism, Index Terms-Game theory, wireless Network slicing, [INFO.INFO-GT]Computer Science [cs]/Computer Science and Game Theory [cs.GT], [INFO.INFO-GT] Computer Science [cs]/Computer Science and Game Theory [cs.GT], normalised equilibrium, ressource allocation, normalised equi- librium, primal-dual algorithms
Abstract

International audience; Slicing is emerging as a promising technique to support new differentiated services in 5G networks. It provides the necessary flexility and scalability associated with future services. To maintain satisfactory services requirements and high profit for service providers, a slice may be designing according to the varying demands and resource availability. This paper develops a framework for resources allocation between slicing and business layer for multi-tenant slicing, e.g. virtual wireless operators, service providers and smart cities services. This paper proposes a flexible mechanism based on a biding scheme for slicing allocation, which achieve desirable fairness and efficiency among the network slices of the different tenants and their associated users. We then design a practical algorithms to realise the proposed desired solution. We also show through the simulation the efficiency of our approach in term of efficiency and fairness.

Published
2020

17. Decentralization of 5G slice resource allocation

Author

Francesca Fossati, Stefano Moretti, Stephane Rovedakis, Stefano Secci, CEDRIC. Réseaux et Objets Connectés (CEDRIC - ROC), Centre d'études et de recherche en informatique et communications (CEDRIC), Ecole Nationale Supérieure d'Informatique pour l'Industrie et l'Entreprise (ENSIIE)-Conservatoire National des Arts et Métiers [CNAM] (CNAM)-Ecole Nationale Supérieure d'Informatique pour l'Industrie et l'Entreprise (ENSIIE)-Conservatoire National des Arts et Métiers [CNAM] (CNAM), Laboratoire d'analyse et modélisation de systèmes pour l'aide à la décision (LAMSADE), Université Paris Dauphine-PSL, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS), and ANR-18-CE25-0012,MAESTRO5G,Gestion de slices dans le réseau d'accès mobile de la 5G(2018)

Subjects
Computer science, Distributed computing, 05 social sciences, 050801 communication & media studies, 020206 networking & telecommunications, Provisioning, 02 engineering and technology, Variety (cybernetics), [INFO.INFO-NI]Computer Science [cs]/Networking and Internet Architecture [cs.NI], 0508 media and communications, Resource (project management), Scalability, 0202 electrical engineering, electronic engineering, information engineering, Key (cryptography), Orchestration, Systems design, Resource allocation, [INFO.INFO-DC]Computer Science [cs]/Distributed, Parallel, and Cluster Computing [cs.DC]
Abstract

International audience; The 5G infrastructure brings a key novelty in net-worked systems design that is a new resource provisioning entity, the so-called "network slice". A network slice is meant to serve end-to-end services as a composition of different network and system resources as the radio, the link and a variety of computing resources (CPU, RAM, storage), generally each managed by a distinct decision-maker (platform, provider, orchestrator or controller). Naturally, centralized slice orchestration approaches have been proposed, where a multi-domain orchestrator allocates the resources, using a multi-resource allocation rule. Nonetheless, while simplifying the algorithmic approach, centralization can come at the expense of scalability and performance. In this paper, we propose new ways to decentralize the slice resource allocation problem, using cascade or parallel resource allocations. We provide an exhaustive analysis of the advantages and disadvantages of the different approaches together with a numerical analysis in a realistic environment.

Published
2020
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18. Multi-Resource Allocation for Network Slicing

Author

Stefano Moretti, Patrice Perny, Stefano Secci, Francesca Fossati, CEDRIC. Réseaux et Objets Connectés (CEDRIC - ROC), Centre d'études et de recherche en informatique et communications (CEDRIC), Ecole Nationale Supérieure d'Informatique pour l'Industrie et l'Entreprise (ENSIIE)-Conservatoire National des Arts et Métiers [CNAM] (CNAM)-Ecole Nationale Supérieure d'Informatique pour l'Industrie et l'Entreprise (ENSIIE)-Conservatoire National des Arts et Métiers [CNAM] (CNAM), Laboratoire d'analyse et modélisation de systèmes pour l'aide à la décision (LAMSADE), Université Paris Dauphine-PSL, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS), DECISION, LIP6, Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), and ANR-18-CE25-0012,MAESTRO5G,Gestion de slices dans le réseau d'accès mobile de la 5G(2018)

Subjects
Service (systems architecture), Computer Networks and Communications, Computer science, Distributed computing, media_common.quotation_subject, 020206 networking & telecommunications, 02 engineering and technology, Index Terms-multi-resource allocation, multi-resource allocation, [INFO.INFO-RO]Computer Science [cs]/Operations Research [cs.RO], Computer Science Applications, Set (abstract data type), [INFO.INFO-NI]Computer Science [cs]/Networking and Internet Architecture [cs.NI], 5G slicing, OWA, 0202 electrical engineering, electronic engineering, information engineering, Bandwidth (computing), Resource allocation, Resource management, Electrical and Electronic Engineering, Function (engineering), Software, 5G, media_common
Abstract

International audience; Among the novelties introduced by 5G networks, the formalization of the 'network slice' as a resource allocation unit is an important one. In legacy networks, resources such as link bandwidth, spectrum, computing capacity are allocated independently of each other. In 5G environments, a network slice is meant to directly serve end-to-end services, or verticals: behind a network slice demand, a tenant expresses the need to access a precise service type, under a fully qualified set of computing and network requirements. The resource allocation decision encompasses, therefore, a combination of different resources. In this paper, we address the problem of fairly sharing multiple resources between slices, in the critical situation in which the network does not have enough resources to fully satisfy slice demands. We model the problem as a multi-resource allocation problem, proposing a versatile optimization framework based on the Ordered Weighted Average (OWA) operator. We show how, adapting the OWA utility function, our framework can generalize classical single-resource allocation methods, existing multi-resource allocation solutions at the state of the art, and implement novel multi-resource allocation solutions. We compare analytically and by extensive simulations the different methods in terms of fairness and system efficiency. We conclude the paper adapting the proposed framework to Service Level Agreement (SLA)-driven services. Two algorithms, considering minimum capacity requirements and time-fairness are proposed and tested.

Published
2020
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19. Error Estimate and Fairness in Resource Allocation with Inaccurate Information Sharing

Author

Deep Medhi, Francesca Fossati, Stefano Secci, Stefano Moretti, CEDRIC. Réseaux et Objets Connectés (CEDRIC - ROC), Centre d'études et de recherche en informatique et communications (CEDRIC), Ecole Nationale Supérieure d'Informatique pour l'Industrie et l'Entreprise (ENSIIE)-Conservatoire National des Arts et Métiers [CNAM] (CNAM)-Ecole Nationale Supérieure d'Informatique pour l'Industrie et l'Entreprise (ENSIIE)-Conservatoire National des Arts et Métiers [CNAM] (CNAM), Phare, LIP6, Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), National Science Foundation [Arlington] (NSF), University of Missouri [Kansas City] (UMKC), University of Missouri System, Laboratoire d'analyse et modélisation de systèmes pour l'aide à la décision (LAMSADE), Université Paris Dauphine-PSL, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS), and ANR-18-CE25-0012,MAESTRO5G,Gestion de slices dans le réseau d'accès mobile de la 5G(2018)

Subjects
Information management, 021103 operations research, Operations research, Computer science, Information sharing, 0211 other engineering and technologies, ComputerApplications_COMPUTERSINOTHERSYSTEMS, 020206 networking & telecommunications, 02 engineering and technology, General Medicine, Telecommunications network, [INFO.INFO-NI]Computer Science [cs]/Networking and Internet Architecture [cs.NI], Robustness (computer science), Resource allocation systems, 0202 electrical engineering, electronic engineering, information engineering
Abstract

International audience; In resource allocation systems, inaccurate information sharing situations are such that users can be aware, up to a small error, about the other users' demands and the available global resource (which can be insufficient to meet the overall demand). Consequently, given an allocation rule, users can predict an allocation that will not necessarily coincide with the actual one. In this work, we provide an estimation of the error for a number of allocation rules and compare their robustness in inaccurate information sharing settings.

Published
2019
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20. Multi-Resource Allocation for Network Slicing under Service Level Agreements

Author

Stefano Moretti, Francesca Fossati, Stefano Secci, CEDRIC. Réseaux et Objets Connectés (CEDRIC - ROC), Centre d'études et de recherche en informatique et communications (CEDRIC), Ecole Nationale Supérieure d'Informatique pour l'Industrie et l'Entreprise (ENSIIE)-Conservatoire National des Arts et Métiers [CNAM] (CNAM)-Ecole Nationale Supérieure d'Informatique pour l'Industrie et l'Entreprise (ENSIIE)-Conservatoire National des Arts et Métiers [CNAM] (CNAM), Phare, LIP6, Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Laboratoire d'analyse et modélisation de systèmes pour l'aide à la décision (LAMSADE), Université Paris Dauphine-PSL-Centre National de la Recherche Scientifique (CNRS), Université Paris Dauphine-PSL, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS), and ANR-18-CE25-0012,MAESTRO5G,Gestion de slices dans le réseau d'accès mobile de la 5G(2018)

Subjects
Computer science, Quality of service, Distributed computing, 05 social sciences, 050801 communication & media studies, 020206 networking & telecommunications, 02 engineering and technology, Slicing, Partition (database), Scheduling (computing), Service-level agreement, [INFO.INFO-NI]Computer Science [cs]/Networking and Internet Architecture [cs.NI], 0508 media and communications, Service level, Multi resource, 0202 electrical engineering, electronic engineering, information engineering, 5G
Abstract

International audience; Network slicing in 5G aims to provide an end-to-end partition of the physical network that is optimized for the service it has to supply. Each slice needs to fulfill a Service Level Agreement (SLA), that is a contract between the slice provider and the tenants on the quality of service and reliability, expressed for a diverse set of physical resources (spectrum, link capacity, computing power, etc). For the multi-resource allocation problem in network slicing, we provide two scheduling algorithms that take into account SLA requirements in terms of minimum and nominal resource quantity demands. We show that the algorithm that considers the availability rate of the service, in addition to providing the minimum capacity, has better performances in terms of time-fairness. For both scheduling algorithms we consider a user delaying policy able to take into account SLA priority and latency requirements.

Published
2019
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21. Minimum-Cost Virtual Network Function Resilience

Author

Carlinet, Yannick, Perrot, Nancy, Alves-Tzitas, Anderson, Physics Laboratory (NIST), National Institute of Standards and Technology [Gaithersburg] (NIST), Orange Labs [Issy les Moulineaux], France Télécom, and ANR-18-CE25-0012,MAESTRO5G,Gestion de slices dans le réseau d'accès mobile de la 5G(2018)

Subjects
[INFO.INFO-RO]Computer Science [cs]/Operations Research [cs.RO]
Abstract

International audience; In the future 5G networks, a wide range of new services with strong requirements will be delivered in the form of chains of service functions on independent virtual networks. These virtual networks will be deployed on demand, each one adapted to the specific service requirements. For infrastructure providers a real challenge consists in providing and setting up the required virtual networks (network slices) while guaranteeing strict Service Level Agreements. One of the major stakes is to be able to provide failure protection for the service function chains at minimal cost. In this work, we consider a set of deployed service chains, and we study the best strategy to protect them at minimal cost. We propose mathematical formulations that provide optimal backup functions placement over a network, and the associated backup paths for each VNF of all the chains. We develop an efficient ILP-based heuristic relying on a separation of the problem into smaller ones to solve large scale instances. We show that our heuristic is competitive, both regarding the solution quality and the solving time.

Published
2019
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22. Optimal Blind and Adaptive Fog Orchestration under Local Processor Sharing

Author

Pellegrini, Francesco, Faticanti, Francescomaria, Mandar, Datar, Eitan, Altman, Domenico Siracusa, Laboratoire Informatique d'Avignon (LIA), Avignon Université (AU)-Centre d'Enseignement et de Recherche en Informatique - CERI, Fondazione Bruno Kessler [Trento, Italy] (FBK), University of Trento [Trento], Network Engineering and Operations (NEO ), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Laboratory of Information, Network and Communication Sciences (LINCS), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut Mines-Télécom [Paris] (IMT)-Sorbonne Université (SU), and ANR-18-CE25-0012,MAESTRO5G,Gestion de slices dans le réseau d'accès mobile de la 5G(2018)

Subjects
game theory, [INFO.INFO-NI]Computer Science [cs]/Networking and Internet Architecture [cs.NI], Kelly mechanism, processor sharing, stochastic approximation, [INFO]Computer Science [cs], normalised equi- librium, primal-dual algorithms, Index Terms-fog computing, convex opti- misation
Abstract

International audience; This paper studies the tradeoff between running cost and processing delay in order to optimally orchestrate multiple fog applications. Fog applications process batches of objects' data along chains of containerised microservice modules, which can run either for free on a local fog server or run in cloud at a cost. Processor sharing techniques, in turn, affect the applications' processing delay on a local edge server depending on the number of application modules running on the same server. The fog orchestrator copes with local server congestion by offloading part of computation to the cloud trading off processing delay for a finite budget. Such problem can be described in a convex optimisation framework valid for a large class of processor sharing techniques. The optimal solution is in threshold form and depends solely on the order induced by the marginal delays of N fog applications. This reduces the original multidimensional problem to an unidimensional one which can be solved in O(N 2) by a parallelised search algorithm under complete system information. Finally, an online learning procedure based on a primal-dual stochastic approximation algorithm is designed in order to drive optimal reconfiguration decisions in the dark, by requiring only the unbiased estimation of the marginal delays. Extensive numerical results characterise the structure of the optimal solution, the system performance and the advantage attained with respect to baseline algorithmic solutions.

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