On Money as a Means of Coordination between Network Packets

In this work, we apply a common economic tool, namely money, to coordinate network packets. In particular, we present a network economy, called PacketEconomy, where each flow is modeled as a population of rational network packets, and these packets can self-regulate their access to network resources by mutually trading their positions in router queues. Every packet of the economy has its price, and this price determines if and when the packet will agree to buy or sell a better position. We consider a corresponding Markov model of trade and show that there are Nash equilibria (NE) where queue positions and money are exchanged directly between the network packets. This simple approach, interestingly, delivers improvements even when fiat money is used. We present theoretical arguments and experimental results to support our claims

Federated Learning for 5G Base Station Traffic Forecasting

Mobile traffic prediction is of great importance on the path of enabling 5G mobile networks to perform smart and efficient infrastructure planning and management. However, available data are limited to base station logging information. Hence, training methods for generating high-quality predictions that can generalize to new observations on different parties are in demand. Traditional approaches require collecting measurements from different base stations and sending them to a central entity, followed by performing machine learning operations using the received data. The dissemination of local observations raises privacy, confidentiality, and performance concerns, hindering the applicability of machine learning techniques. Various distributed learning methods have been proposed to address this issue, but their application to traffic prediction has yet to be explored. In this work, we study the effectiveness of federated learning applied to raw base station aggregated LTE data for time-series forecasting. We evaluate one-step predictions using 5 different neural network architectures trained with a federated setting on non-iid data. The presented algorithms have been submitted to the Global Federated Traffic Prediction for 5G and Beyond Challenge. Our results show that the learning architectures adapted to the federated setting achieve equivalent prediction error to the centralized setting, pre-processing techniques on base stations lead to higher forecasting accuracy, while state-of-the-art aggregators do not outperform simple approaches

Scheduling UWB Ranging and Backbone Communications in a Pure Wireless Indoor Positioning System

International audienceIn this paper, we present and evaluate an ultra-wideband (UWB) indoor processing architecture that allows the performing of simultaneous localizations of mobile tags. This architecture relies on a network of low-power fixed anchors that provide forward-ranging measurements to a localization engine responsible for performing trilateration. The communications within this network are orchestrated by UWB-TSCH, an adaptation to the ultra-wideband (UWB) wireless technology of the time-slotted channel-hopping (TSCH) mode of IEEE 802.15.4. As a result of global synchronization, the architecture allows deterministic channel access and low power consumption. Moreover, it makes it possible to communicate concurrently over multiple frequency channels or using orthogonal preamble codes. To schedule communications in such a network, we designed a dedicated centralized scheduler inspired from the traffic aware scheduling algorithm (TASA). By organizing the anchors in multiple cells, the scheduler is able to perform simultaneous localizations and transmissions as long as the corresponding anchors are sufficiently far away to not interfere with each other. In our indoor positioning system (IPS), this is combined with dynamic registration of mobile tags to anchors, easing mobility, as no rescheduling is required. This approach makes our ultra-wideband (UWB) indoor positioning system (IPS) more scalable and reduces deployment costs since it does not require separate networks to perform ranging measurements and to forward them to the localization engine. We further improved our scheduling algorithm with support for multiple sinks and in-network data aggregation. We show, through simulations over large networks containing hundreds of cells, that high positioning rates can be achieved. Notably, we were able to fully schedule a 400-cell/400-tag network in less than 11 s in the worst case, and to create compact schedules which were up to 11 times shorter than otherwise with the use of aggregation, while also bounding queue sizes on anchors to support realistic use situations

Stratégies d'ancêtre commun pour les réseaux RPL multi-chemins

National audienceThe IPv6 Routing Protocol for Low-Power and Lossy Networks (RPL) networks is designed for Internet of Things (IoT) networks to generate routes between devices with minimal processing. This protocol creates a DODAG (Destination Oriented Directed Acyclic Graph) network topology through the use of DODAG Information Object (DIO) control packets. The DODAG routes the data packets upstream to the destination device. In order to obtain a reliable network, we implement Packet Replication and Elimination (PRE) to perform multi-path data transmission via multiple parent devices. However, there is no standard way to select an alternative path. This document presents three types of Alternative Parent (AP) selection following a braided model. We focus on analyzing its performance in terms of delay and compromise between network traffic and reliability.Le protocole de routage IPv6 pour les réseaux à faible puissance et fort taux de pertes (RPL) est conçu pour les réseaux Internet des objets (IoT) afin de générer des itinéraires entre les appareils avec un traitement minimal. Ce protocole crée une topologie de réseau DODAG (Destination Oriented Directed Acyclic Graph) grâce à l'utilisation de paquets de contrôle DODAG Information Object (DIO). Le DODAG achemine les paquets de données en amont vers le périphérique de destination. Afin d'obtenir un réseau fiable, nous implémentons la réplication et l'élimination des paquets (PRE) pour effectuer une transmission de données à chemins multiples via plusieurs périphériques parents. Cependant, il n'existe aucun moyen standard de sélectionner un chemin alternatif. Ce document présente trois types de sélection de parent alternatif (AP) suivant un modèle triangulaire. Nous nous concentrons sur l'analyse de ses performances en termes de retard et de compromis entre trafic réseau et fiabilité

Towards Energy-Aware Federated Traffic Prediction for Cellular Networks

Cellular traffic prediction is a crucial activity for optimizing networks in fifth-generation (5G) networks and beyond, as accurate forecasting is essential for intelligent network design, resource allocation and anomaly mitigation. Although machine learning (ML) is a promising approach to effectively predict network traffic, the centralization of massive data in a single data center raises issues regarding confidentiality, privacy and data transfer demands. To address these challenges, federated learning (FL) emerges as an appealing ML training framework which offers high accurate predictions through parallel distributed computations. However, the environmental impact of these methods is often overlooked, which calls into question their sustainability. In this paper, we address the trade-off between accuracy and energy consumption in FL by proposing a novel sustainability indicator that allows assessing the feasibility of ML models. Then, we comprehensively evaluate state-of-the-art deep learning (DL) architectures in a federated scenario using real-world measurements from base station (BS) sites in the area of Barcelona, Spain. Our findings indicate that larger ML models achieve marginally improved performance but have a significant environmental impact in terms of carbon footprint, which make them impractical for real-world applications.Comment: International Symposium on Federated Learning Technologies and Applications (FLTA), 202

Αποκεντρωμένη διαχείριση ανταγωνιστικής πρόσβασης σε κοινόχρηστους πόρους με αλγοριθμική θεωρία παιγνίων

The Internet is today an inextricable part of daily personal, educational and business activity, turning any problems in its operation or availability into a significant interruption of these activities and their users. The resources offered by the Internet (capacity, coverage) are continuously increasing but at the same time the users and their demands are increasing at an even larger pace. If measures for the efficient and fair management of the network resources are not taken, the Internet will cease to be able to support new users and applications with high quality. Internet users operate in an independent manner, by creating data flows (sending and receiving network packets) which satisfy their demands. Each user prefers for his needs to be served in the best possible way but the resources of the network are shared and finite, making it often impossible to provide the best service to everyone. This leads to users competing amongst themselves for access to the network resources and its services. Whenever the demands placed on the services by the users exceed the capacity of the services, a means of selecting which users and to which degree they will be served is required. In the case of the Internet, the resources are network capacity, the demands of the users are requests for transferring network packets and the functionality of selecting which users are served and how they are served is generally referred to as Quality of Service (QoS). One feature of the Internet which significantly affects the possible solutions to providing QoS is its decentralized structure: there exists no central authority which is responsible for the whole operation of the network and which could centrally perform the resource allocation. Instead, resources are allocated locally at each network node to the users which access it. In this work, we address the issue of managing competitive access to common resources through the use of algorithmic game theory. This approach is validated by the competitive, selfish and independent nature of the users. Additionally, in the case of QoS provision for the Internet, our solutions have to be distributed in order to be applicable. Specifically, we start by proposing the Prince mechanism for distributing network flow throughput in a (MaxMin-resembling) fair manner. We then propose an efficient data structure and algorithm set for implementing Prince on a network router queue. We continue by providing the theoretical description and first simple experimental implementation of PacketEconomy, a network economy where each flow is modelled as a population of rational network packets, and these packets can self-regulate their access to network resources by mutually trading their positions in router queues. This theoretical model is then adapted to the OMNET++ simulator and via thorough experimentation we present the validation of the efficacy of our solution in a realistic context. Applying the same principles of game-theoretic analysis to realistic service provision problems, we also study an Internet-based VoIP service access problem in the context of the prevention of SPIT (SPam over Internet Telephony).Το Διαδίκτυο σήμερα αποτελεί αναπόσπαστο μέρος καθημερινής ιδιωτικής, εκπαιδευτικής και επιχειρηματικής δραστηριότητας, με αποτέλεσμα προβλήματα στη λειτουργία του να προκαλούν σημαντικές διαταραχές σε αυτές τις δραστηριότητες και να επηρεάζονται οι χρήστες του. Οι πόροι που διαθέτει το Διαδίκτυο (χωρητικότητα, συνδέσεις) αυξάνονται διαρκώς αλλά ταυτόχρονα, με μεγαλύτερο ρυθμό, αυξάνονται οι χρήστες του και οι απαιτήσεις των εφαρμογών τις οποίες καλείται να υποστηρίξει. Αν δεν ληφθούν μέτρα για την αποδοτική διαχείριση και την δίκαιη κατανομή των πόρων δικτύου, το Διαδίκτυο θα πάψει να έχει την δυνατότητα να υποστηρίζει νέους χρήστες και εφαρμογές και να διασφαλίζει υψηλή ποιότητα παροχής υπηρεσιών. Οι χρήστες του Διαδικτύου λειτουργώντας ανεξάρτητα ο ένας από τον άλλο δημιουργούν ροές δεδομένων (στέλνοντας και λαμβάνοντας πακέτα δεδομένων) οι οποίες χρησιμοποιούν τους κοινόχρηστους και πεπερασμένους πόρους του Διαδικτύου. Καθώς κάθε χρήστης προτιμά την καλύτερη δυνατή εξυπηρέτηση για τις ροές του και καθώς η χωρητικότητα του δικτύου επιτρέπει συχνά μόνο ένα υποσύνολο των πακέτων να εξυπηρετηθούν, δημιουργείται ανταγωνισμός κατά την πρόσβαση στους κοινόχρηστους πόρους. Καθώς δεν υπάρχει κάποια κεντρική αρχή που να είναι υπεύθυνη για την ανάθεση πρόσβασης στους πόρους του δικτύου, η πρόσβαση ανατίθεται με αποκεντρωμένο τρόπο σε κάθε δρομολογητή. Οι χρήστες του δικτύου μπορούν να υποβάλουν ένα αυθαίρετο πλήθος από πακέτα ανά πάσα στιγμή στο δίκτυο και ο κάθε δρομολογητής αποφασίζει πόσα και ποια θα δεχθεί και πως θα τα εξυπηρετήσει. Η έλλειψη συντονισμού μεταξύ των ανεξάρτητων ροών οδηγεί το Διαδίκτυο να εμφανίζει μια "άναρχη" μορφή λειτουργίας και δημιουργεί προβλήματα τα οποία μπορούν να αντιμετωπιστούν με έννοιες και εργαλεία από την αλγοριθμική θεωρία παιγνίων. Πιο συγκεκριμένα, ο στόχος είναι να βρεθούν οι προϋποθέσεις και ο τρόπος επίτευξης δίκαιης, αποδοτικής και υπολογιστικά εφικτής (tractable) αποκεντρωμένης διαχείρισης πόρων σε δίκτυα υπολογιστών. Στα παιγνιοθεωρητικά μοντέλα αυτό που ενδιαφέρει συνήθως είναι να διερευνηθεί ποιες είναι οι καταστάσεις ισορροπίας του συστήματος. Μια από τις πιο σημαντικές κατηγορίες καταστάσεων ισορροπίας είναι οι ισορροπία Nash (Nash Equilibrium). Στην ισορροπία Nash κανένας παίκτης/χρήστης δεν έχει κίνητρο να αλλάξει τη στρατηγική του οπότε από τη στιγμή που θα επιτευχθεί αυτή η ισορροπία το σύστημα σταθεροποιείται σε αυτή την κατάσταση. Είναι συχνά επιθυμητό ένα παίγνιο να τείνει προς μια τέτοια ισορροπία αλλά έχει αποδειχθεί πως η υπολογιστική πολυπλοκότητα εύρεσης των Ισορροπιών Nash ακόμα και σε απλά μοντέλα είναι PPAD-complete, κάνοντάς τις ενδεχομένως δύσκολο να επιτευχθούν. Επιπλέον, η έρευνα στο χώρο στην συντριπτική της πλειοψηφία έχει ασχοληθεί με θεωρητικά μοντέλα δικτυακών παιγνίων τα οποία απέχουν σημαντικά από την δομή και την λειτουργία των πραγματικών δικτύων. Για τους παραπάνω λόγους καθίσταται σημαντική η μελέτη αυτών των μοντέλων όχι μόνο θεωρητικά αλλά και πειραματικά, ώστε να αποδειχθεί η πρακτική υλοποιησιμότητα του μοντέλου και η ρεαλιστική μελέτη των επιδόσεων και των χαρακτηριστικών του. Η παρούσα διδακτορική έρευνα περιλαμβάνει τη διερεύνηση των τρόπων αξιοποίησης της αλγοριθμικής θεωρίας παιγνίων για την κατασκευή αποκεντρωμένων μηχανισμών διαχείρισης πρόσβασης σε πόρους δικτύου. Βασική αρχή της έρευνας είναι ότι η δημιουργία κατάλληλων αλγορίθμων διαχείρισης των πόρων, τέτοιων που να δίνουν κίνητρο στους χρήστες να ρυθμίζουν σωστά τις ροές δεδομένων τους, οδηγούν στα επιθυμητά αποτελέσματα για όλους τους χρήστες. Χωρίς τα κατάλληλα κίνητρα οι χρήστες, συμπεριφερόμενοι εγωιστικά, κάνουν κατάχρηση των κοινών πόρων και ζημιώνουν και τρίτους χρήστες. Στόχος είναι η σχεδίαση, υλοποίηση και μελέτη της συμπεριφοράς τέτοιων αλγορίθμων σε θεωρητικό και πειραματικό επίπεδο

A Centralized Controller for Reliable and Available Wireless Schedules in Industrial Networks

International audienceThis paper describes our work on a flexible centralized controller for scheduling wireless networks. The context of this work encompasses wireless networks within the wider Internet of Things (IoT) field and in particular addresses the requirements and limitations within the narrower Industrial Internet of Things (IIoT) sub-field. The overall aim of this work is to produce wireless networking solutions for industrial applications. The challenges include providing high reliability and low latency guarantees, comparable to existing wired solutions, within a noisy wireless medium and using generally computationally-and energy-restrained network nodes. We describe the development of a centralized controller for Wireless Industrial Networks, currently aimed at IEEE Std 802.15.4-2015 Time Slotted Channel Hopping protocol. Our controller takes a high-level network-centric problem description as input, translates it to a low-level representation and uses that to retrieve a solution from a Satisfiability Modulo Theories (SMT) solver, translating the solution back to a higher-level network-centric representation. The advantages of our solution are the ability to gain the added flexibility, higher ease of deployment, and lower deployment cost offered by wireless networks by generating configurable and flexible schedules for these applications

RPL DAG Metric Container Node State and Attribute object type extension

Implementing Packet Replication and Elimination from / to the RPL root requires the ability to forward copies of packets over different paths via different RPL parents. Selecting the appropriate parents to achieve ultra-low latency and jitter requires information about a node's parents. This document details what information needs to be transmitted and how it is encoded within a packet to enable this functionality

Common Ancestor Objective Function and Parent Set DAG Metric Container Extension

Implementing Packet Replication and Elimination from/to the RPL root requires the ability to forward copies of packets over different paths via different RPL parents. Selecting the appropriate parents to achieve ultra-low latency and jitter requires information about a node's parents. This document details what information needs to be transmitted and how it is encoded within RPL control packets to enable this functionality. This document also describes Objective Function which take advantage of this information to implement multi-path routing. Status of This Memo This Internet-Draft is submitted in full conformance with the provisions of BCP 78 and BCP 79

Thorough Performance Evaluation & Analysis of the 6TiSCH Minimal Scheduling Function (MSF)

International audienceIEEE Std 802.15.4-2015 Time Slotted Channel Hopping (TSCH) is the de facto Medium Access Control (MAC) mechanism for industrial applications. It renders communications more resilient to interference by spreading them over the time (time-slotted) and the frequency (channel-hopping) domains. The 6TiSCH architecture bases itself on this new MAC layer to enable high reliability communication in Wireless Sensor Networks (WSNs). In particular, it manages the construction of a distributed communication schedule that continuously adapts to changes in the network. In this paper, we first provide a thorough description of the 6TiSCH architecture, the 6TiSCH Operation Sublayer (6top), and the Minimal Scheduling Function (MSF). We then study its behavior and reactivity from low to high traffic rates by employing the Python-based 6TiSCH simulator. Our performance evaluation results demonstrate that the convergence pattern of MSF is the root cause of the majority of packet losses observed in the network. We also show that MSF is prone to over-provisioning of the network resources, especially in the case of varying traffic load. We propose a mathematical model to predict the convergence pattern of MSF. Finally we investigate the impact of varying parameters on the behavior of the scheduling function