A New Distributed and Probabilistic Approach for Traffic Control in LPWANs

International audienceLow-Power Wide Area Networks (LPWANs) are wireless networks with very low power consumption and wide area coverage. They are capable of supporting the traffic of nearly a thousand nodes with a duty cycle of less than 1%. However, the gradual densification of nodes increases the number of collisions and makes it more difficult to manage the upstream traffic. To mitigate this problem, we propose a new distributed and probabilistic traffic control algorithm, DiPTC, which allows nodes to adapt their traffic according to the needs of the application (e.g., receiving K measurements over a time period) while being agnostic to the number of nodes and to the network topology. A control message is broadcast by the gateway to all nodes each period when the objective is not reached, so that nodes can re-adapt their traffic. We evaluate the proposed solution in simulation and we compare it with the LoRaWAN protocol. The results show that our algorithm is able to reach the objective while keeping a low number of collisions, with a longer network lifetime. Compared to LoRaWAN, our solution shows a three times increase in the success rate and a decrease by a factor of 10 in the collision rate

Contrôle du trafic dans un réseau LPWAN : approche distribuée et probabiliste

National audienceLes réseaux Low-Power Wide Area Networks (LPWAN) sont des réseaux sans filà très faible consommation d'énergie età large couverture. Capables de supporter le trafic de près d'un millier de noeuds avec un cycle d'activité de moins de 1%, ils deviennent la solution de référence pour l'Internet des Objets. Toutefois, la densification progressive des objets connectés rend le réseau inefficaceà cause de l'augmentation du nombre de collisions et de la gestion du trafic descendant. Dans ce travail, nous proposons un mécanisme distribué et probabiliste permettantà un objet connecté d'adapter son trafic au besoin applicatif, enétant agnostique du nombre d'objets présents dans le réseau. Nous l'appliquons au cas particulier de la collecte de données d'un phénomène physiqueà l'échelle d'une ville

Une note sur le routage et la tarification dans les réseaux SMS

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Distributed Multi-Link Auctions for Network Ressource Reservation and Pricing

International audienc

Pricing composite cloud services: The cooperative perspective

International audienceWe are interested in analyzing situations of competition among the providers in emerging service oriented networks where added value services may be obtained by composing services offered by cloud providers. Those activities are not regulated and may give rise to coalition formation. The comparison between different potential coalitions and their characterization in terms of stability and dominance can be considered using cooperative game concepts. Indeed, a fair revenue sharing mechanism such as the Shapley value can ensure the stability of the formed coalition. However, when the core is empty the grand coalition is no more stable, though other concepts from the bargaining theory may apply. We will investigate potential revenue sharing mechanisms that make alliances sustainable

Optimal Transit Price Negotiation: The Distributed Learning Perspective

We present a distributed learning algorithm for optimizing transit prices in the inter-domain routing framework. We present a combined game theoretical and distributed algorithmic analysis, where the notion of Nash equilibrium with the first approach meets the notion of stability in the second. We show that providers can learn how to strategically set their prices according to a Nash equilibrium; even when assuming incomplete information. We validate our theoretical model by simulations confirming the expected outcome. Moreover, we observe that some unilateral deviations from the proposed rule do not seem to affect the dynamic of the system