In this work we introduce a novel queueing model with two classes of users in which, instead of accessing a resource, users wait in the system to match with a candidate from the other class. The users are selective and the matchings occur probabilistically. This new model is useful for analysing the traffic in web portals that match people who provide a service with people who demand the same service, e.g. employment portals, matrimonial and dating sites and rental portals. We first provide a Markov chain model for these systems and derive the probability distribution of the number of matches up to some finite time given the number of arrivals. We then prove that if no control mechanism is employed these systems are unstable for any set of parameters. We suggest four different classes of control policies to assure stability and conduct analysis on performance measures under the control policies. Contrary to the intuition that the rejection rate should decrease as the users become more likely to be matched, we show that for certain control policies the rejection rate is insensitive to the matching probability. Even more surprisingly, we show that for reasonable policies the rejection rate may be an increasing function of the matching probability. We also prove insensitivity results related to the average queue lengths and waiting times. Further, to gain more insight into the behaviour of probabilistic matching systems, we propose approximation methods based on fluid and diffusion limits using different scalings. We analyse the basic properties of these approximations and show that some performance measures are insensitive to the matching probability agreeing with the results found by the exact analysis. Finally we study the optimal control and revenue management for the systems with the objective of profit maximization. We formulate mathematical models for both unobservable and observable systems. For an unobservable system we suggest a deterministic optimal control, while for an observable system we develop an optimal myopic state dependent pricing.

Mobile Ad hoc NETworks (MANETs) aim at making communication between mobile nodes feasible without any infrastructure support. Sparse MANETs fall into the class of Delay Tolerant Networks which are intermittently connected networks and where there is no contemporaneous end-to-end path at any given time. We first, propose a new reliable transport scheme for DTNs based on the use of ACKnowledgments and random linear coding. We model the evolution of the network under our scheme using a fluid-limit approach. We optimize our scheme to obtain mean file transfer times on certain optimal parameters obtained through differential evolution approach. Secondly, we propose and study a novel and enhanced ACK to improve reliable transport for DTNs covering both unicast and multicast flows. We make use of random linear coding at relays so that packets can reach the destination faster. We obtain reliability based on the use of so-called Global Selective ACKnowledgment. We obtain significant improvement through G-SACKs and coding at relays. Finally, we tackle the problem of estimating file-spread in DTNs with direct delivery and epidemic routing. We estimate and track the degree of spread of a message in the network. We provide analytical basis to our estimation framework alongwith insights validated with simulations. We observe that the deterministic fluid model can indeed be a good predictor with a large of nodes. Moreover, we use Kalman filter and Minimum- Mean-Squared-Error (MMSE) to track the spreading process and find that Kalman filter provides more accurate results as compared to MMSE

Les réseaux mobiles Ad hoc (MANETs) visent à permettent à des noeuds mobiles de communiquer sans aucun support d'infrastructure. Les MANETs dispersés entrent dans la catégorie des réseaux tolérants aux délais (DTN), qui sont des réseaux connectés par intermittence et où il n'y a aucun chemin de bout-en-bout persistant à n'importe quel temps donné. Nous proposons, d'abord, un nouveau protocole de transport fiable pour les DTNs basé sur l'utilisation d'accusés de réception ainsi que le codage linéaire aléatoire. Nous modélisons l'évolution du réseau conformément à notre plan en utilisant l'approche fluide. Nous obtenons le temps de transfert d'un fichier en fonction de certains paramètres optimaux obtenus par l'approche d'évolution différentielle. Deuxièmement, Nous proposons ainsi et étudions un nouveau mécanisme d'ACK augmenté, pour améliorer le transport fiable pour les DTNs, pour les cas unicast et multicast. Nous nous servons du codage linéaire aléatoire aux relais pour que les paquets puissent atteindre la destination plus rapidement. Nous obtenons la fiabilité basée sur l'utilisation Global Sélective ACKnowledgement. Enfin, nous abordons le problème de l'estimation de propagation des fichiers dans les DTNs avec livraison directe et le routage épidémique. Nous estimons et suivons le degré de propagation d'un message dans le réseau. Nous fournissons la base analytique à notre cadre d'évaluation avec des aperçus validés en se basant sur des simulations. En plus, nous utilisons le filtre de Kalman et Minimum- Mean-Squared Error (MMSE) pour suivre le processus de propagation et trouvons que le filtre de Kalman fournit des résultats plus précis par rapport à MMSE / Mobile Ad hoc NETworks (MANETs) aim at making communication between mobile nodes feasible without any infrastructure support. Sparse MANETs fall into the class of Delay Tolerant Networks which are intermittently connected networks and where there is no contemporaneous end-to-end path at any given time. We first, propose a new reliable transport scheme for DTNs based on the use of ACKnowledgments and random linear coding. We model the evolution of the network under our scheme using a fluid-limit approach. We optimize our scheme to obtain mean file transfer times on certain optimal parameters obtained through differential evolution approach. Secondly, we propose and study a novel and enhanced ACK to improve reliable transport for DTNs covering both unicast and multicast flows. We make use of random linear coding at relays so that packets can reach the destination faster. We obtain reliability based on the use of so-called Global Selective ACKnowledgment. We obtain significant improvement through G-SACKs and coding at relays. Finally, we tackle the problem of estimating file-spread in DTNs with direct delivery and epidemic routing. We estimate and track the degree of spread of a message in the network. We provide analytical basis to our estimation framework alongwith insights validated with simulations. We observe that the deterministic fluid model can indeed be a good predictor with a large of nodes. Moreover, we use Kalman filter and Minimum- Mean-Squared-Error (MMSE) to track the spreading process and find that Kalman filter provides more accurate results as compared to MMSE