Browsing by Keyword "Routing"
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Item A bio-inspired approach for collaborative exploration with mobile battery recharging in swarm robotics(Springer Verlag, 2018) Carrillo, Maria; Gallardo, Ian; Del Ser, Javier; Osaba, Eneko; Sanchez-Cubillo, Javier; Bilbao, Miren Nekane; Gálvez, Akemi; Iglesias, Andrés; Melab, Nouredine; Korosec, Peter; Talbi, El-Ghazali; IA; Quantum; Tecnalia Research & InnovationSwarm Robotics are widely conceived as the development of new computationally efficient tools and techniques aimed at easing and enhancing the coordination of multiple robots towards collaboratively accomplishing a certain mission or task. Among the different criteria under which the performance of Swarm Robotics can be gauged, energy efficiency and battery lifetime have played a major role in the literature. However, technological advances favoring power transfer among robots have unleashed new paradigms related to the optimization of the battery consumption considering it as a resource shared by the entire swarm. This work focuses on this context by elaborating on a routing problem for collaborative exploration in Swarm Robotics, where a subset of robots is equipped with battery recharging functionalities. Formulated as a bi-objective optimization problem, the quality of routes is measured in terms of the Pareto trade-off between the predicted area explored by robots and the risk of battery outage in the swarm. To efficiently balance these conflicting two objectives, a bio-inspired evolutionary solver is adopted and put to practice over a realistic experimental setup implemented in the VREP simulation framework. Obtained results elucidate the practicability of the proposed scheme, and suggest future research leveraging power transfer capabilities over the swarm.Item Joint topology optimization, power control and spectrum allocation for intra-vehicular multi-hop sensor networks using dandelion-encoded heuristics(Springer Verlag, 2016) Del Ser, Javier; Bilbao, Miren Nekane; Perfecto, Cristina; Gonzalez-Pardo, Antonio; Campos-Cordobes, Sergio; Burelli, Paolo; Squillero, Giovanni; IA; LABORATORIO DE TRANSFORMACIÓN URBANA; SMART_TRANSPORTIn the last years the interest in multi-hop communications has gained momentum within the research community due to the challenging characteristics of the intra-vehicular radio environment and the stringent robustness imposed on critical sensors within the vehicle. As opposed to point-to-point network topologies, multi-hop networking allows for an enhanced communication reliability at the cost of an additional processing overhead. In this context this manuscript poses a novel bi-objective optimization problem aimed at jointly minimizing (1) the average Bit Error Rate (BER) of sensing nodes under a majority fusion rule at the central data collection unit; and (2) the mean delay experienced by packets forwarded by such nodes due to multi-hop networking, frequency channel switching time multiplexing at intermediate nodes. The formulated paradigm is shown to be computationally tractable via a combination of evolutionary meta-heuristic algorithms and Dandelion codes, the latter capable of representing tree-like structures like those modeling the multi-hop routing approach. Simulations are carried out for realistic values of intra-vehicular radio channels and co-channel interference due to nearby IEEE 802.11 signals. The obtained results are promising and pave the way towards assessing the practical performance of the proposed scheme in real setups.Item Machine-Learning methodology for energy efficient routing(2012) Demestichas, K.; Masikos, M.; Adamopoulou, E.; Dreher, S.; Diaz De Arkaya, A.; WEATHER AND CLIMATE INTELLIGENCE FOR BUSINESSEco-driving assistance systems encourage economical driving behaviours and support the driver in optimizing his driving style to achieve fuel economy and consequently emission reduction. Energy efficient routing is one of the especially pertinent issues related to the autonomy of Fully Electric Vehicles (FEVs). This paper introduces a novel methodology for energy efficient routing, based on the realization of dependable energy consumption predictions for the various road segments constituting an actual or potential vehicle route, and it is mainly performed by means of machine-learning functionality, through the use of the so-called Machine-Learning Engines. The proposed methodology, the functional architecture implementing it, as well as first experimental results are presented in detail.Item Performance analysis of position-based routing approaches in VANETS(2007) De La Fuente, Miguel Garcia; Labiod, Houda; Centros PRE-FUSION TECNALIA - (FORMER)This article presents a performance analysis between two location-based routing protocols: SIFT (Simple Forwarding over Trajectory), a novel, scalable, spatial-aware, trajectory-based approach, and DREAM (Distance Routing Effect Algorithm for Mobility), a stable, largely tested position-based scheme. The study was accomplished under a realistic urban mobility model for VANETS (Vehicular Ad hoc NETworks), within a highly deployed evaluation network of up to 1000 nodes. Classical ad hoc routing schemes do not perform well in VANETS because they were not designed to handle efficiently mobility handicaps. Position-based techniques perform better in dynamic scenarios, but in some highly dynamic scenarios, like VANETS, they do not always perform efficiently. Trajectory-based protocols perform more efficiently in VANETS since they are spatial-aware. We demonstrate that SIFT performs better than DREAM in a realistic VANET scenario concerning delivery ratio, control overhead, delivery delay, and route length.Item A performance comparison of position-based routing approaches for mobile ad hoc networks(2007) De La Fuente, Miguel Garcia; Ladiod, Houda; Centros PRE-FUSION TECNALIA - (FORMER)In this work we present a performance comparison study between SIFT (Simple Forwarding over Trajectory), an innovative and scalable trajectory-based approach, and DREAM (Distance Routing Effect Algorithm for Mobility), a stable, largely tested position-based scheme. In the literature, the latest studies indicate that control overhead is the most important drawback that routing protocols must face. Classical ad hoc routing schemes do not perform well in MANETS (Mobile Ad hoc Networks) because they were not designed to handle efficiently mobility handicaps. Position-based forwarding techniques perform better in highly dynamic scenarios, reducing control overhead consequences, but there may be some highly dynamic scenarios where they do not perform efficiently. Trajectory-based forwarding protocols solve the overhead problem and, thus, they perform efficiently in MANETS. Our study demonstrates that SIFT performs better than DREAM concerning delivery ratio, control overhead and route length in terms of number of hops. Its main handicap could be, a priori, the delivery delay. However, even if delay may be high in SIFT, control overhead may also causes even higher delivery delay in DREAM.Item SiFT: An efficient method for trajectory based forwarding(2005) Capone, A.; Pizziniaco, L.; Filippini, I.; García De La Fuente, M. Á; Centros PRE-FUSION TECNALIA - (FORMER)Trajectory Based Forwarding (TBF) is a new approach for routing in ad hoc wireless networks. It assumes that nodes know their position and, similarly to source routing, requires the source node to encode a trajectory into the packet header. However, trajectories are just geometrical lines and the routing process does not require specifying forwarding nodes. As a matter of fact, forwarding nodes are dynamically selected while packets cross the network according to their position with respect to the trajectory. Therefore, this new approach is particularly suitable for application scenarios where network topology is fast varying, due to node mobility (e.g. inter-vehicular networks) or to energy management schemes (e.g. sensor networks), whereas the stability of the trajectories is guaranteed by the physical characteristics of the service area (roads, building aisles, etc.). In this paper we propose a new TBF scheme that exploits broadcast transmissions at the MAC layer and does not require maintaining a list of active neighbours positions in every node. We consider piecewise lines connecting source node to destination area and we extend the approach to the multicast case defining trajectory-trees.