e-WASTE: Everything an ICT Scientist and Developer Should Know

[EN] Every dazzling announcement of a new smart phone or trendy digital device is the prelude to more tons of electronic waste (e-waste) being produced. This e-waste, or electronic scrap, is often improperly added to common garbage, rather than being separated into suitable containers that facilitate the recovery of toxic materials and valuable metals. We are beginning to become aware of the problems that e-waste can generate to our health and the environment. However, most of us are still not motivated enough to take an active part in reversing the situation. The aim of this article is to contribute to increase this motivation by pointing out the significant problem that e-waste represents and its social and environmental implications. We have chosen this forum in which multidisciplinary researchers in ICT from all countries access on regularly to explain the serious problems we are exposed to when we do not make a responsible and correct use of technology. In this paper, we also survey the composition of contemporary electronic devices and the possibilities and difficulties of recycling the elements they contain. As researchers, our contributions in science enable us to find solutions to current problems and to design more and more powerful intelligent devices. But responsible researchers must be aware of the negative effects that this industry causes us and, consequently, assume their commitment with more sustainable designs and developments. Therefore, the knowledge of e-waste issues is crucial also in the scientific world. Researchers should consider this problem and contribute to minimize it or find new solutions to manage it. These must be the additional challenges in our projects.This work was supported in part by the Spanish Ministry of Economy and Competitiveness under Grant TIN2013-43913-R.Pont Sanjuan, A.; Robles Martínez, A.; Gil, JA. (2019). e-WASTE: Everything an ICT Scientist and Developer Should Know. IEEE Access. 7:169614-169635. https://doi.org/10.1109/ACCESS.2019.2955008S169614169635

Monitoring E-commerce Adoption from Online Data

[EN] The purpose of this paper is to propose an intelligent system to automatically monitor the firms¿ engagement in e-commerce by analyzing online data retrieved from their corporate websites. The design of the proposed system combines web content mining and scraping techniques with learning methods for Big Data. Corporate websites are scraped to extract more than 150 features related to the e-commerce adoption, such as the presence of some keywords or a private area. Then, these features are taken as input by a classification model that includes dimensionality reduction techniques. The system is evaluated with a data set consisting of 426 corporate websites of firms based in France and Spain. The system successfully classified most of the firms into those that adopted e-commerce and those that did not, reaching a classification accuracy of 90.6%. This demonstrates the feasibility of monitoring e-commerce adoption from online data. Moreover, the proposed system represents a cost-effective alternative to surveys as method for collecting e-commerce information from companies, and is capable of providing more frequent information than surveys and avoids the non-response errors. This is the first research work to design and evaluate an intelligent system to automatically detect e-commerce engagement from online data. This proposal opens up the opportunity to monitor e-commerce adoption at a large scale, with highly granular information that otherwise would require every firm to complete a survey. In addition, it makes it possible to track the evolution of this activity in real time, so that governments and institutions could make informed decisions earlier.This work has been partially supported by the Spanish Ministry of Economy and Competitiveness with Grant TIN2013-43913-R, and by the Spanish Ministry of Education with Grant FPU14/02386.Blazquez, D.; Domenech, J.; Gil, JA.; Pont Sanjuan, A. (2018). 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!Vaya tela! Atrapados por la Web

De una forma similar a como lo fue en su día Ja introducción de la televisión en los hogares de nuestros padres, la Web se ha introducido en los nuestros y en nuestra vida de una forma explosiva. A diferencia de la televisión, este nuevo medio es interactivo y, precisamente por ello, evoluciona rápidamente a la par que lo hacen sus usuarios. En este artículo se examinan los cambios que ha sufrido desde su creación y se analiza cuáles pueden ser las tendencias futuras en función de los nuevos dispositivos, diseño y estándares aprobados recientementeGil Salinas, JA.; Pont Sanjuan, A. (2015). !Vaya tela! Atrapados por la Web. Novática. 41(234):102-104. http://hdl.handle.net/10251/65171S1021044123

A methodology for economic evaluation of cloud-based web applications

[EN] Cloud technology is an attractive infrastructure solution to optimize the scalability and performance of web applications. The workload of these applications typically fluctuates between peak and valley loads and sometimes in an unpredictable way. Cloud systems can easily deal with this fluctuation because they provide customers with an almost unlimited on-demand infrastructure capacity using a pay-per-use model, which enables internet-based companies to pay for the actual consumption instead of peak capacity. In this paradigm, this paper links the business model of an internet-based company to the performance evaluation of the infrastructure. To this end, the paper develops a new methodology for assessing the costs and benefits of implementing web-based applications in the cloud. Traditional performance models and indexes related to usage of the main system resources (such as processor, memory, storage, and bandwidth) have been reformulated to include new metrics (such as customer losses and service costs) that are useful for business managers. Additionally, the proposed methodology has been illustrated with a case study of a typical e-commerce scenario. Experimental results show that the proposed metrics enable internet-based companies to estimate the cost of adopting a particular cloud configuration more accurately in terms of the infrastructure cost and the cost of losing customers due to performance degradation. Consequently, the methodology can be a useful tool to assess the feasibility of business plans.This work has been partially supported by the Spanish Ministry of Economy and Competitiveness under Grant TIN2013-43913-R.Domenech, J.; Peña Ortiz, R.; Gil, JA.; Pont Sanjuan, A. (2016). A methodology for economic evaluation of cloud-based web applications. International Journal of Information Technology and Decision Making. 15(6):1555-1578. https://doi.org/10.1142/S021962201650036XS1555157815

Automatic detection of e-commerce availability from web data

Resumen de la ponencia[EN] In the transition to the digital economy, the implementation of e-commerce strategies contributes to foster economic growth and obtain competitive advantages. Indeed, national and supranational statistics offices monitor the adoption of e-commerce solutions by conducting periodic surveys to businesses. However, the information about e-commerce adoption is often available online in each company corporate website, which is usually public and suitable for being automatically retrieved and processed.In this context, this work proposes and develops an intelligent system for automatically detecting and monitoring e-commerce availability by analyzing data retrieved from corporate websites. This system combines web scraping techniques with some learning methods for Big Data, and has been evaluated with a data set consisting of 426 corporate websites of manufacturing firms based in France and Spain.Results show that the proposed model reaches a classification precision of about 85% in the test set. A more detailed analysis evidences that websites with e-commerce tend to include some specific keywords and have a private area. Our proposal opens up the opportunity to monitor e-commerce adoption at a large scale, with highly granular information that otherwise would have required every firm to complete a survey.Blázquez Soriano, MD.; Domenech, J.; Gil, JA.; Pont Sanjuan, A. (2016). Automatic detection of e-commerce availability from web data. En CARMA 2016: 1st International Conference on Advanced Research Methods in Analytics. Editorial Universitat Politècnica de València. 121-121. https://doi.org/10.4995/CARMA2016.2016.3603OCS12112

The impact of User-Browser Interaction on web performance

© ACM 2013. This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in ACM, In Proceedings of the 28th Annual ACM Symposium on Applied Computing (pp. 695-702). http://dx.doi.org/10.1145/2480362.2480497The user interaction with the current web contents is a major concern when defining web workloads in order to precisely estimate system performance. However, the intrinsic diffi- culty to represent this behavior in a workload model leads many research works to still use workloads non representative of the current web navigations. In contrast, in previous works we demonstrated that the use of an accurate workload model that considers user’s dynamism when navigating the web clearly affects system performance metrics. In this paper we analyze, for the first time, the effect of considering the User-Browser Interaction (UBI) as a part of user’s dynamic behavior on web workload characterization in performance studies. To this end, we evaluate a typical e-commerce scenario and compare the obtained results for different UBI behaviors, such as the use of the back button and parallel browsing originated by using browser tabs or opening new windows when surfing a website.This work has been partially supported by the Spanish Ministry of Science and Innovation under grant TIN-2009-08201.Peña Ortiz, R.; Gil Salinas, JA.; Sahuquillo Borrás, J.; Pont Sanjuan, A. (2013). The impact of User-Browser Interaction on web performance. ACM. https://doi.org/10.1145/2480362.2480497

Key factors in web latency savings in an experimental prefetching system

Although Internet service providers and communications companies are continuously offering higher and higher bandwidths, users still complain about the high latency they perceive when downloading pages from the web. Therefore, latency can be considered as the main web performance metric from the user's point of view. Many studies have demonstrated that web prefetching can be an interesting technique to reduce such latency at the expense of slightly increasing the network traffic. In this context, this paper presents an empirical study to investigate the maximum benefits that web users can expect from prefetching techniques in the current web. Unlike previous theoretical studies, this work considers a realistic prefetching architecture using real traces. In this way, the influence of real imple- mentation constraints are considered and analyzed. The results obtained show that web prefetching could improve page latency up to 52% in the studied traces. ©Springer Science+Business Media, LLC 2011De La Ossa Perez, BA.; Sahuquillo Borrás, J.; Pont Sanjuan, A.; Gil Salinas, JA. (2012). Key factors in web latency savings in an experimental prefetching system. Journal of Intelligent Information Systems. 39(1):187-207. doi:10.1007/s10844-011-0188-xS187207391Balamash, A., Krunz, M., & Nain, P. (2007). Performance analysis of a client-side caching/prefetching system for web traffic. Computer Networks, 51(13), 3673–3692.Bestavros, A. (1995). Using speculation to reduce server load and service time on the www. In Proc. of the 4th ACM international conference on information and knowledge management. Baltimore, USA.Bestavros, A., & Cunha, C. (1996). Server-initiated document dissemination for the WWW. In IEEE data engineering bulletin. [Online]. Available: http://citeseer.ist.psu.edu/viewdoc/summary?doi=10.1.1.128.266 . Accessed 29 November 2011.Bouras, C., Konidaris, A., & Kostoulas, D. (2004). Predictive prefetching on the web and its potential impact in the wide area. In World Wide Web: Internet and web information systems (Vol. 7, No. 2, pp. 143–179). The Netherlands: Kluwer Academic.Changa, T., Zhuangb, Z., Velayuthamc, A., & Sivakumara, R. (2008). WebAccel: Accelerating web access for low-bandwidth hosts. Computer Networks, 52(11), 2129–2147.Davison, B. D. (2002). The design and evaluation of web prefetching and caching techniques. Ph.D. dissertation, Rutgers University.de la Ossa, B., Gil, J. A., Sahuquillo, J., & Pont, A. (2007). Delfos: The oracle to predict next web user’s accesses. In Proc. of the IEEE 21st international conference on advanced information networking and applications. Niagara Falls, Canada.de la Ossa, B., Pont, A., Sahuquillo, J., & Gil, J. A. (2010). Referrer graph: A low-cost web prediction algorithm. In Proc. of the 25th ACM symposium on applied computing (pp. 831–838). doi: 10.1145/1774088.1774260 .de la Ossa, B., Sahuquillo, J., Pont, A., & Gil, J. A. (2009). An empirical study on maximum latency saving in web prefetching. In Proc. of the 2009 IEEE/WIC/ACM international conference on web intelligence (WI’09).Dom̀enech, J., Gil, J. A., Sahuquillo, J., & Pont, A. (2006a). DDG: An efficient prefetching algorithm for current web generation. In Proc. of the 1st IEEE workshop on hot topics in web systems and technologies (HotWeb). Boston, USA.Domènech, J., Gil, J. A., Sahuquillo, J., & Pont, A. (2006b). Web prefetching performance metrics: A survey. Performance Evaluation, 63(9–10), 988–1004.Domènech, J., Sahuquillo, J., Gil, J. A., & Pont, A. (2006c). The impact of the web prefetching architecture on the limits of reducing user’s perceived latency. In Proc. of the international conference on web intelligence. Piscataway: IEEE.de la Ossa, B., Gil, J. A., Sahuquillo, J., & Pont, A. (2007). Improving web prefetching by making predictions at prefetch. In Proc. of the 3rd EURO-NGI conference on next generation internet networks design and engineering for heterogeneity (NGI’07) (pp. 21–27).Duchamp, D. (1999). Prefetching hyperlinks. In Proc. of the 2nd USENIX symposium on internet technologies and systems. Boulder, USA.Fan, L., Cao, P., Lin, W., & Jacobson, Q. (1999). Web prefetching between low-bandwidth clients and proxies: Potential and performance. In Proc. of the ACM SIGMETRICS conference on measurement and modeling of computer systems (pp. 178–187).HTTP/1.1. [Online]. Available: http://www.faqs.org/rfcs/rfc2616.html . Accessed 29 November 2011.Kroeger, T. M., Long, D., & Mogul, J. C. (1997). Exploring the bounds of web latency reduction from caching and prefetching. In Proc. of the 1st USENIX symposium on internet technologies and systems. Monterrey, USA.Link prefetching in mozilla faq (2011). [Online]. Available: https://developer.mozilla.org/en/Link_prefetching_FAQ .Markatos, E., & Chronaki, C. (1998). A top-10 approach to prefetching on the web. In Proc. of INET. Geneva, Switzerland.Márquez, J., Domènech, J., Pont, A., & Gil, J. A. (2008). Exploring the benefits of caching and prefetching in the mobile web. In Second IFIP symposium on wireless communications and information technology for developing countries (WCITD 2008).Padmanabhan, V., & Mogul, J. C. (1996). Using predictive prefetching to improve World Wide Web latency. In Proc. of the ACM SIGCOMM conference. Stanford University, USA.Palpanas, T., & Mendelzon, A. (1999). Web prefetching using partial match prediction. In Proc. of the 4th international web caching workshop. San Diego, USA.Schechter, S., Krishnan, M., & Smith, M. D. (1998). Using path profiles to predict http requests. In Proc. of the 7th international World Wide Web conference. Brisbane, Australia.Teng, W., Chang, C., & Chen, M. (2005). Integrating web caching and web prefetching in client-side proxies. IEEE Transactions on Parallel and Distributed Systems, 16(5), 444–455

A Comparison of Prediction Algorithms for Prefetching in the Current Web

[EN] This paper reviews a representative subset of the prediction algorithms used for Web prefetching classifying them according to the information gathered. Then, the DDG algorithm is described. The main novelty of this algorithm lies in the fact that, unlike previous algorithms, it creates a prediction model according to the structure of the current web. To this end, the algorithm distinguishes between container objects and embedded objects. Its performance is compared against important existing algorithms, and results show that, for the same amount of extra requests to the server, DDG always outperforms those algorithms by reducing the perceived latency up to 70% more without increasing the complexity order.This work has been partially supported by the Spanish Ministry of Science and Innovation under Grant TIN2009-08201, the Generalitat Valenciana under Grant GV/2011/002 and the Universitat Politecnica de Valencia under Grant PAID-06-10/2424.Josep Domenech; Sahuquillo Borrás, J.; Gil Salinas, JA.; Pont Sanjuan, A. (2012). A Comparison of Prediction Algorithms for Prefetching in the Current Web. Journal of Web Engineering. 11(1):64-78. http://hdl.handle.net/10251/44349S647811

Retroinformática para la enseñanza y el aprendizaje en la Ingeniería Informática

[ES] En este trabajo mostramos cómo a través de la retroinformática tratamos de motivar a nuestros estudiantes en el estudio de la asignatura Estructura de Computadores. A ello contribuye el Museo de Informática de la Universitat Politècnica de València que se ha convertido durante los dos últimos cursos en un instrumento didáctico adicional para la docencia, además de cumplir con la importante misión de difundir la cultura e historia de la informática entre los estudiantes de grado de ingeniería informática. La experiencia se ha llevado a cabo durante el pasado y el actual curso con los alumnos de segundo año del mencionado grado y en el ámbito de las tareas académicas de la asignatura. El artículo explica los detalles de la articulación de las actividades en una asignatura con más de cuatrocientos alumnos matriculados y organizados en siete grupos de aula, lo que ya es de por sí un reto nada desdeñable. Parte de estas actividades se han llevado a cabo directamente por parte del profesorado y otras lo han sido de forma autodirigida mediante cuestionarios en papel y herramientas online. Por último, este trabajo muestra la manera en que se han evaluado las experiencias en ambos cursos y las conclusiones extraídas de las mismas para poder mejorarlas en futuras ediciones e incorporar nuevos retos para el futuro.[EN] In this work we show how retrocomputing can be used to motivate and encourage our students to address Computer Organization subject. The Museum of Informatics of the UPV contributes to this purpose and during the last two academic years has become an additional teaching tool for the mentioned subject besides of its important mission for patrimonial and cultural dissemination among students of Computer Engineering Degree. The experience has been carried out during the last and the current academic year in this degree in the scope of the academic tasks related to the subject. This paper explains how the experience was organized and carried out for more than 400 students organized into 7 class groups, which is by itself an important challenge. Some of the related activities were directly performed by the teaching staff and others were planned in a self-guided way, both using online tools and paper and pencil surveys. Finally, this work show how the experience has been evaluated in both years, the main conclusions got to improve it for new future editions and how to include new challenges.Molero Prieto, X.; Pont Sanjuan, A.; Robles Martínez, A.; Martínez Díaz, M. (2015). Retroinformática para la enseñanza y el aprendizaje en la Ingeniería Informática. Enseñanza y Aprendizaje de Ingenieria de Computadores. (5):49-68. http://hdl.handle.net/10251/61650S4968

Surfing the web using browser interface facilities: a performance evaluation approach

[EN] The user interaction with the current web contents is a major concern when defining web workloads in order to precisely estimate system performance. However, the intrinsic difficulty to represent this dynamic behavior with a workload model has caused that many research studies are still using non representative workloads of the current web navigations. In contrast, in previous works we demonstrated that the use of an accurate workload model which considers user s dynamism when navigating the web clearly affects system performance metrics. In this paper we analyze, for the first time, the effect of considering the User-Browser Interaction as a part of user s dynamic behavior on web workload characterization in performance studies. To this end, we evaluate a typical e-commerce scenario and compare the obtained results for different behaviors that take the user interaction into account, such as the use of the back button and parallel browsing originated by using browser tabs or opening new windows when surfing a website. Experimental results show that these interaction patterns allow users to achieve their navigation objectives sooner, so increasing their productivity up to 200% when surfing the Web. In addition, results prove that when this type of navigations is taken into account, performance indexes can widely differ and relax the stress borderline of the server. For instance, the server utilization drops as much as 45% due to parallel browsing behavior.This work has been partially supported by the Spanish Ministry Economy and Competitiveness under grant TIN-2013-43913-R.Peña Ortiz, R.; Gil Salinas, JA.; Sahuquillo Borrás, J.; Pont Sanjuan, A. (2015). Surfing the web using browser interface facilities: a performance evaluation approach. Journal of Web Engineering. 14(1-2):3-21. http://hdl.handle.net/10251/63834321141-