We present an analytical model that matches scientific applications to effective Cloud instances for high application performance. The model constructs two vectors namely, the application vector and the Cloud vector. The application vector consists of application performance components such as the number of single-precision (SP) floating-point operations (FLOPs) and double-precision (DP) FLOPs, main memory accesses, and disk accesses. The Cloud vector comprises corresponding Cloud instance performance components such as the benchmarked SP and DP floating-point operations per second (FLOPS), memory bandwidth, and disk bandwidth. The model performs an inner product of the two vectors to produce an Application-to-Cloud (A2Cloud) score, which quantifies the application-to-Cloud match. We encapsulate the A2Cloud model in a user-friendly A2Cloud framework that inputs a test application and a target Cloud instance, profiles them, and executes the A2Cloud model to generate the A2Cloud score. We demonstrate the model by conducting 162 application executions across nine Cloud instances. Our tests yield an average A2Cloud matching rate of 6 for every 9 application-instance pairs with a mean absolute difference of ±1.08 ranks.

Scattering signals on wind turbines may lead to degradation problems on the communication systems provided in the UHF band, such as terrestrial television broadcasting, broadband wireless systems or public safety services. To date, despite the continuous requests from the International Telecommunication Union for studies on this field, no channel model has been developed to characterize signal propagation under these particular conditions. In response to this necessity, this paper presents a complete Tapped Delay Line (TDL) channel model to characterize multipath propagation in presence of a wind farm, including novel scattering modeling and Doppler spectra characterization. As proved later, this channel model, which is based on both theoretical development and empirical data obtained in the surroundings of a real wind farm, is adaptable to the particular features of any case under study: wind turbine dimensions, working frequency, and relative location of the wind farm, transmitter and receivers.

The digital broadcasting systems (DRM and HD radio/ IBOC) developed in the last decade have renewed the interest for the MW band. The planning requirements of the digital services require more accurate channel models and a significant improvement in the coverage estimation algorithms. The variability of the local median values (sigmaL) is a key parameter in the estimation process of the coverage percentage within a certain service area. Similar studies are scarce in the bibliography, mainly because analogue service planning requirements have been much more flexible. This paper presents the first set of sigmaL values for the MW band, and analyzes the influence of several factors related to the channel model and the coverage estimation techniques, such as frequency, distance to the transmitter, path profile and relevant features of the reception area.

This paper presents attenuation values due to the influence of orography in the MW band, based on an analysis of data recorded in a measurement campaign. The decisive influence of the distance of the obstacle from the receiver is demonstrated, and this parameter has been considered in the analysis. Values for the range of the influence are indicated for different values of the height of a single obstacle. These attenuation values are greater than the ones assumed in classical methods, and coincide with measurement campaigns developed by DRM (digital radio mondiale) consortium members. Accuracy in calculating the attenuation due to the irregular terrain is necessary in planning the coverage of digital services, where it is necessary to provide adequate field strength in a high percentage of locations.