Open Access
Cloud continuum testbeds and next-generation ICTs: trends, challenges, and perspectives
(Elsevier, 2024-12-06) Casino, Fran; López Iturri, Peio; Patsakis, Constantinos ; Ingeniería Eléctrica, Electrónica y de Comunicación; Ingeniaritza Elektrikoa, Elektronikoa eta Telekomunikazio Ingeniaritza
As society's dependence on Information and Communication Technologies (ICTs) grows, providing efficient and resourceful services entails many complexities that require, among others, scalable systems that are provided with intelligent and automated management. In parallel, the different components of cloud computing are continuously evolving to enhance their capabilities towards leveraging the next generation of ICTs. Due to the substantial investment in resources required to provide efficient services, suitable research and experimentation platforms to test and validate cloud technologies before releasing them into operational versions are crucial to delivering sound systems with sustainable cost/benefit ratios. In this article, we review the current state of the art by analysing cloud testbeds devoted to studying the capabilities of the cloud continuum. Instead of recalling a component-wise or architectural discussion of these systems, this article explores the full spectrum of the cloud continuum testbeds and their features, providing a taxonomy that can be practically used as an entry point to identify each testbed's scope. Moreover, we extract the challenges found in the literature to deliver a profound discussion, correlating the analysed testbeds and their features. Our findings highlight the main gaps and potential roadmaps to provide effective testbeds considering the next generation of ICTs.
Open Access
Enhanced wireless channel estimation through parametric optimization of hybrid ray launching-collaborative filtering technique
(IEEE, 2020) Casino, Fran; López Iturri, Peio; Aguirre Gallego, Erik; Azpilicueta Fernández de las Heras, Leyre; Falcone Lanas, Francisco; Solanas, Agustí; Ingeniaritza Elektrikoa, Elektronikoaren eta Telekomunikazio Ingeniaritzaren; Institute of Smart Cities - ISC; Ingeniería Eléctrica, Electrónica y de Comunicación
In this paper, an enhancement of a hybrid simulation technique based on combining collaborative filtering with deterministic 3D ray launching algorithm is proposed. Our approach implements a new methodology of data depuration from low definition simulations to reduce noisy simulation cells. This is achieved by processing the maximum number of permitted reflections, applying memory based collaborative filtering, using a nearest neighbors' approach. The depuration of the low definition ray launching simulation results consists on discarding the estimated values of the cells reached by a number of rays lower than a set value. Discarded cell values are considered noise due to the high error that they provide comparing them to high definition ray launching simulation results. Thus, applying the collaborative filtering technique both to empty and noisy cells, the overall accuracy of the proposed methodology is improved. Specifically, the size of the data collected from the scenarios was reduced by more than 40% after identifying and extracting noisy/erroneous values. In addition, despite the reduced amount of training samples, the new methodology provides an accuracy gain above 8% when applied to the real-world scenario under test, compared with the original approach. Therefore, the proposed methodology provides more precise results from a low definition dataset, increasing accuracy while exhibiting lower complexity in terms of computation and data storage. The enhanced hybrid method enables the analysis of larger complex scenarios with high transceiver density, providing coverage/capacity estimations in the design of heterogeneous IoT network applications.
Open Access
Optimized wireless channel characterization in large complex environments by hybrid ray launching-collaborative filtering approach
(IEEE, 2017) Casino, Fran; Azpilicueta Fernández de las Heras, Leyre; López Iturri, Peio; Aguirre Gallego, Erik; Falcone Lanas, Francisco; Solanas, Agustí; Ingeniería Eléctrica y Electrónica; Ingeniaritza Elektrikoa eta Elektronikoa
Simulation techniques based on deterministic methods such as Ray Tracing and Ray Launching, are widely used to perform radioplanning tasks. However, the quality of the simulations depends on the number of rays and the angular resolution. The computational cost of these simulations in High Definition prevents their use in complex environments and their Low Definition counterparts are used instead. In this article we propose a technique based on collaborative filtering to lessen the poor quality problems of Low Definition simulations. We show that our approach obtains results very similar to those of High Definition in much less time. Also, we compare our approach with other well-known techniques and we show that it performs better in terms of accuracy and precision. The use of combined deterministic/collaborative filtering techniques allows the estimation of radioplanning tasks in large, complex scenarios with a potentially large amount of transceivers.
Open Access
Performance analysis of ZigBee wireless networks for AAL through hybrid ray launching and collaborative filtering
(Hindawi, 2016) López Iturri, Peio; Casino, Fran; Aguirre Gallego, Erik; Azpilicueta Fernández de las Heras, Leyre; Falcone Lanas, Francisco; Solanas, Agustí; Ingeniaritza Elektrikoa eta Elektronikoa; Institute of Smart Cities - ISC; Ingeniería Eléctrica y Electrónica
This paper presents a novel hybrid simulation method based on the combination of an in-house developed 3D ray launching algorithm and a collaborative filtering (CF) technique, which will be used to analyze the performance of ZigBee-based wireless sensor networks (WSNs) to enable ambient assisted living (AAL). The combination of Low Definition results obtained by means of a deterministic ray launching method and the application of a CF technique leads to a drastic reduction of the time and computational cost required to obtain accurate simulation results. The paper also reports that this kind of AAL indoor complex scenario withmultiple wireless devices needs a thorough and personalized radioplanning analysis as radiopropagation has a strong dependence on the network topology and the specific morphology of the scenario. The wireless channel analysis performed by our hybrid method provides valuable insight into network design phases of complex wireless systems, typical in AAL-oriented environments.Thus, it results in optimizing network deployment, reducing overall interference levels, and increasing the overall system performance in terms of cost reduction, transmission rates, and energy efficiency.

López Iturri, Peio

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