Data caps and service degradation are techniques used to control subscribers’ data consumption. These techniques have emerged mainly due to the growing demands placed on the networking stack created by the continuous increase in the number of connected users and their feature-rich, bandwidth-heavy Over-the-Top (OTT) applications. In the mobile network’s scope, where traditional operators offer user data plans with limited resources, service degradation is a standard mechanism used to throttle consumption. Limiting user data usage helps to utilize resources better and to ensure the network’s reliable performance. Nevertheless, this degradation is applied in a generalized way, affecting all user applications without considering behavior. In this paper, we propose a reference model aiming to address this constraint. Specifically, we attempt to personalize service degradation policies by providing a guideline for users’ OTT consumption behavior classification based on Incremental Learning (IL). We evaluated our model’s viability in a case study by investigating the efficacy of several IL algorithms on a dataset containing real-world users’ OTT application consumption behavior. The algorithms include Naive Bayes (NB), K-Nearest Neighbor (KNN), Adaptive Random Forest (ARF), Leverage Bagging (LB), Oza Bagging (OB), Learn++, and Multilayer Perceptron (MLP). The obtained results show that ARF and a composition between LB and ARF achieve the best performance yielding a classification precision and recall of over 90%. Based on the obtained results, we propose service degradation policies to support decision making in mission-critical systems. We argue the strong applicability of our model in real-world scenarios, especially in user consumption profiling. Our reference model offers a conceptual basis for the tasks that need to be performed when defining personalized service degradation policies in current and future networks like 5G. To the best of our knowledge, this work is the first effort in this matter.

Recent years have witnessed a massive penetration of cellular systems in developing countries. However, isolated rural areas (sparsely inhabited by low-income population) have been disregarded because classical access and backhaul technologies do not ensure the return on investment. This article presents innovative techno-economical solutions to provide these areas with cellular voice and data services. We first analyze the general characteristics of isolated rural communities, and based on this information, low-cost solutions are designed for both access (using 3G access points) and backhaul networks (using non-carrier grade equipment as WiFi for long distances or WiMAX in non-licensed bands). Subsequently, a study of population-dependent income vs. costs is presented, and a new business model is proposed involving mobile network operators, rural operators, and infrastructure providers. In order to test these solutions, we have built two demonstration platforms in the Peruvian jungle that have allowed validation of the technical feasibility of the solution, verifying the business model assumptions and the scalability of the initiative.

The development of telemedicine programs for the public health network of the Department of Cauca, Colombia, (Department is the major political and territorial division of the country. The Department of Cauca is located on the Pacific coast in the southwest of the country.) would make it possible to satisfy many identified needs such as medical coordination, continuing education, epidemiologic surveillance, patient referral and counterreferral, and an end to the feeling of isolation among professionals who work in rural health centers. Nevertheless, geographic, economic, and social difficulties, and the lack of a telecommunication infrastructure in areas with these characteristics present a challenge of such magnitude that the majority of existing telemedicine projects in Colombia have been centered in urban or other areas which present fewer difficulties. In the municipality of Silvia, the University of Cauca has established a prototype network using the "Hispano-American Health Link" (EHAS in Spanish) program technologies, which uses very high frequency (VHF) and wireless fidelity, (WiFi, a set of standards for wireless local area networks) radio systems for the deployment of low-cost voice and data networks. Over this network information access and exchange services have been developed, in order to meet the needs identified above. The objectives were to obtain information about the development of the project's activities and their possible impact. Project telecommunication network and information services are described, and the results and conclusions of the first evaluation are presented.

This paper presents two technological developments oriented to increase the efficiency of the epidemiologic surveillance system and to improve the diagnostic and therapeutic capabilities of the rural establishments with only e-mail connectivity through wireless systems. The Telematics Department of the University of Cauca has developed a computerized epidemiologic surveillance system for the collecting, sending, processing, visualization, and feedback of epidemiologic information at national level. The use of the system in a pilot area has solved the problems of subregister, increasing the volume of data colection in 15%. The complete epidemiologic system is currently being implemented in 22 health care establishments in the Department of Cauca in Colombia. Likewise, the Technical University and Carlos III University of Madrid have developed a distance training system with a high-usability interface both for students and teachers. The system includes authoring, distribution, tracking, and visualization of courses synchronized through electronic mail messages in a clear way for the user. Both systems use a creative combination of e-mail and XML (eXtensible Markup Language)-based technologies, ready to be used through slow, intermittent, and asynchronous communication systems.