Wireless Sensor Networks are composed of low cost and extremely power constrained sensor nodes scattered over a spatial region. They form multi-hop and self organized networks, making energy consumption a crucial design issue. Research has shown that clustering sensor nodes is an efficient method to manage energy consumption for prolonging the network lifetime, but most of routing protocols focus on homogeneous sensor networks and they are not optimized for the characteristics of heterogeneous networks, in which a percentage of the sensor nodes is equipped with additional energy capacities. In this paper we evaluate the performance of a new scalable architecture HARP, Hierarchical Adaptive and Reliable Routing Protocol, in a heterogeneous scenario. HARP provides efficient link fault tolerance and also supports node mobility management. Furthermore, a new cluster head election formulation protocol (s-HARP) has been adapted to heterogeneous networks. Our performance evaluation has shown that HARP and s-HARP can significantly reduce the energy consumption and prolong the useful lifetime of the network outperforming some popular existing clustering protocols.
In this paper a geostatistic wind direction model is applied to trace a wind speed map, based on data from official measurement weather stations distributed within the region of Andalucia-Spain. Each station's performance is assessed by comparing real measurements to those resulting from the linear interpolation of the rest. Once an error is associated to the station, the error is drawn in a map, in which minimum error zones can be delimited. Frequency and wind speed in each direction are the magnitudes of interest to get a first categorization of wind resources associated to the region. The interest of the method relies in the possibility of forecasting everywhere within the region with an error inside the tolerable margins.
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