Energy efficiency of some non-cooperative, cooperative and hybrid communication schemes in multi-relay WSNs

In this paper we analyze the energy efficiency of single-hop, multi-hop, cooperative selective decode-and-forward, cooperative incremental decode-and-forward, and even the combination of cooperative and non-cooperative schemes, in wireless sensor networks composed of several nodes. We assume that, as the sensor nodes can experience either non line-of-sight or some line-of-sight conditions, the Nakagami-m fading distribution is used to model the wireless environment. The energy efficiency analysis is constrained by a target outage probability and an end-to-end throughput. Our results show that in most scenarios cooperative incremental schemes are more energy efficient than the other methods

ZAP: a distributed channel assignment algorithm for cognitive radio networks

International audienceWe propose ZAP, an algorithm for the distributed channel assignment in cognitive radio (CR) networks. CRs are capable of identifying underutilized licensed bands of the spectrum, allowing their reuse by secondary users without interfering with primary users. In this context, efficient channel assignment is challenging as ideally it must be simple, incur acceptable communication overhead, provide timely response, and be adaptive to accommodate frequent changes in the network. Another challenge is the optimization of network capacity through interference minimization. In contrast to related work, ZAP addresses these challenges with a fully distributed approach based only on local (neighborhood) knowledge, while significantly reducing computational costs and the number of messages required for channel assignment. Simulations confirm the efficiency of ZAP in terms of (i) the performance tradeoff between different metrics and (ii) the fast achievement of a suitable assignment solution regardless of network size and density

GrAnt: Inferring Best Forwarders from Complex Networks' Dynamics through a Greedy Ant Colony Optimization

This paper presents a new prediction-based forwarding protocol for the complex and dynamic Delay Tolerant Networks (DTN). The proposed protocol is called GrAnt (Greedy Ant) as it uses a greedy transition rule for the Ant Colony Optimization (ACO) metaheuristic to select the most promising forwarder nodes or to provide the exploitation of good paths previously found. The main motivation for the use of ACO is to take advantage of its population-based search and of the rapid adaptation of its learning framework. Considering data from heuristic functions and pheromone concentration, the GrAnt protocol includes three modules: routing, scheduling, and buffer management. To the best of our knowledge, this is the first unicast protocol that employs a greedy ACO which: (1) infers best promising forwarders from nodes' social connectivity, (2) determines the best paths to be followed to a message reach its destination, while limiting the message replications and droppings, (3) performs message transmission scheduling and buffer space management. GrAnt is compared to Epidemic and PROPHET protocols in two different scenarios: a working day and a community mobility model. Simulation results obtained by ONE simulator show that in both environments, GrAnt achieves higher delivery ratio, lower messages redundancy, and fewer dropped messages than Epidemic and PROPHET.Cet article porte sur la proposition d'un protocole d'acheminement pour les réseaux complexes et dynamiques du type tolérants aux délais (DTN), qui est basé sur l'estimation de possibilités futures de contact. Le protocole proposé est appelé GrAnt (Greedy Ant) car il utilise une règle de transition greedy pour la méta-heuristique d'optimisation par colonies de fourmis (ACO). Cette méta-heuristique donne à GrAnt la possibilité de sélectionner les relais les plus prometteuses ou d'exploiter les bons chemins préalablement trouvé. La motivation principale pour l'utilisation de l'ACO est de profiter de son mécanisme de recherche basée sur population et de son apprentissage et adaptation rapide. En utilisant des simulations basées sur des modèles synthétiques de mobilité, nous montrons que GrAnt est en mesure d'adapter conformément son acheminement dans des différents scénarios et possède une meilleure performance comparée à des protocoles comme Epidemic et PROPHET, en plus de la génération de faible surcharge

Towards spatiotemporal integration of bus transit with data-driven approaches

This study aims to propose an approach for spatiotemporal integration of bus transit, which enables users to change bus lines by paying a single fare. This could increase bus transit efficiency and, consequently, help to make this mode of transportation more attractive. Usually, this strategy is allowed for a few hours in a non-restricted area; thus, certain walking distance areas behave like "virtual terminals." For that, two data-driven algorithms are proposed in this work. First, a new algorithm for detecting itineraries based on bus GPS data and the bus stop location. The proposed algorithm's results show that 90% of the database detected valid itineraries by excluding invalid markings and adding times at missing bus stops through temporal interpolation. Second, this study proposes a bus stop clustering algorithm to define suitable areas for these virtual terminals where it would be possible to make bus transfers outside the physical terminals. Using real-world origin-destination trips, the bus network, including clusters, can reduce traveled distances by up to 50%, making twice as many connections on average.Comment: 20 pages, 16 FIGURE

A Social-aware Routing Protocol for Opportunistic Networks

International audienceThis work proposes the Cultural Greedy Ant (CGrAnt) protocol to solve the problem of data delivery in opportunistic and intermittently connected networks referred to as Delay Tolerant Networks (DTNs). CGrAnt is a hybrid Swarm Intelligence-based forwarding protocol designed to address the dynamic and complex environment of DTNs. CGrAnt is based on: (1) Cultural Algorithms (CA) and Ant Colony Optimization (ACO) and (2) operationalmetrics that characterize the opportunistic social connectivity between wireless users. The most promising message forwarders are selected via a greedy transition rule based on local and global information captured from the DTN environment. Using simulations, we rst analyze the inuence of the ACO operators and CA knowledge on the CGrAnt performance. We then compare the performance of CGrAnt with the PROPHET and Epidemic protocols under varying networking parameters. The results show that CGrAnt achieves the highest delivery ratio (gains of 99.12% compared with PROPHET and 40.21% compared with Epidemic) and the lowest message replication (63.60% lower than PROPHET and 60.84% lower than Epidemic)

Le support de la qualité de service dans les réseaux sans fil et ad hoc

PARIS-BIUSJ-Thèses (751052125) / SudocVILLEURBANNE-DOC'INSA LYON (692662301) / SudocPARIS-BIUSJ-Mathématiques rech (751052111) / SudocSudocFranceF

QoS Policy-based Management for IEEE 802.11 Wireless ISPs

International audienc

Qualité de Service dans les réseaux IEEE 802.11

National audienc

Routing and Quality of Service Support for Mobile Ad Hoc Networks

International audienceOLSR is an optimization over classical link state protocols tailored for mobile ad hoc networks. In this paper, we propose the QOLSR protocol which includes quality parameters to the standard OLSR. Three variants of QOLSR are introduced, taking into account the delay measurement together with the hop count metric. Then, we analyze new heuristics for the multipoint relay selection, and evaluate our proposed approaches comparing them with the standard OLSR protocol. Simulation results show that an increased load-balancing and a reduced dropped packets rate are achieved due to the inclusion of the delay information