Examinando por Autor "Arroyo-Valles, Rocio"

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A Bayesian Decision Model for Intelligent Routing in Sensor Networks
(3rd International Symposium on Wireless Communication Systems, 2006. ISWCS '06, 2006-09) Arroyo-Valles, Rocio; Garcia Marques, Antonio; Vinagre Díaz, Juan José; Cid Sueiro, Jesús
In this paper we propose an efficient energy-aware routing algorithm based on learning patterns. Energy and message importance are considered in a Bayesian model in order to establish intelligent decision rules that make the network economize in crucial resources.
A Learning Algorithm for Energy-Efficient Routing of Prioritized Messages in Wireless Sensor Networks
(2007-10-01T08:52:49Z) Arroyo-Valles, Rocio; Garcia Marques, Antonio; Cid Sueiro, Jesús
Energy is a valuable resource in wireless sensor networks since it constitutes a limiting factor for the network lifetime. In order to make an efficient use of its own energy resources, each node in the network should be aware of the energy resources at other nodes, which can be relevant to the success of their routing decisions. The proposal of this paper is twofold:(i)to design a routing algorithm based on learning patterns using geographic information and (ii) to focus on the cut down in energy consumption. We show that by exploiting local information from the signals detected at each node, sensor nodes can learn to route messages in order to improve the communication performance of the overall network and minimize the need of coordination or signalling protocols among nodes. Moreover, if messages are prioritized by some importance parameter, the overall importance of the successfully transmitted messages can be drastically improved. Experimental results highlight that our algorithm achieves a good performance in terms of successful delivery rate and maximizes the importance of the received messages.
Energy-efficient Selective Forwarding for Sensor Networks
(2008-06-01T09:24:16Z) Arroyo-Valles, Rocio; Garcia Marques, Antonio; Cid Sueiro, Jesús
In this paper a new energy-efficient scheme for data transmission in wireless sensor networks is proposed. It is based on the idea of selective forwarding: sensor nodes only transmit the most relevant messages, discarding the least important ones. To do so, messages are assumed to be graded with an importance value, and a forwarding threshold, which depends on the sensor consumption patterns, the available energy resources and the information obtained from the neighborhood, is applied to these values. In this approach, the sensor decision also depends on the expected behavior of neighboring nodes, so as to maximize not only the transmission efficiency, but also the performance of the whole communication up to the estination node. Simulation results show that the proposed scheme increases the network lifetime, and maximizes the global importance of the messages received by the sink node. Index Terms¿selective forwarding, energy-efficiency, message importance, sensor networks.
Optimal Selective Transmission under Energy Constraints in Sensor Networks
(2009-06-24T08:10:13Z) Arroyo-Valles, Rocio; Garcia Marques, Antonio; Cid Sueiro, Jesús
An optimum selective transmission scheme for energy-limited sensor networks where sensors send or forward messages of different importance (priority) is developed.Considering the energy costs, the available battery, the message importances and their statistical distribution, sensors decide whether to transmit or discard a message so that the importance sum of the effectively transmitted messages is maximized. It turns out that the optimal decision is made comparing the message importance with a time-variant threshold. Moreover, the gain of the selective transmission scheme, compared to a non-selective one, critically depends on the energy expenses, among other factors. Albeit suboptimal, practical schemes that operate under less demanding conditions than those for the optimal one are developed. Effort is placed into three directions: (i) the analysis of the optimal transmission policy for several stationary importance distributions; (ii) the design of a transmission policy with invariant threshold that entails asymptotic optimality; and (iii) the design of an adaptive algorithm that estimates the importance distribution from the actual received (or sensed) messages. Numerical results corroborating our theoretical claims and quantifying the gains of implementing the selective scheme close this paper.