Several research programs are tackling the use of Wireless Sensor Networks (WSN) at specific fields, such as e-Health, e-Inclusion or e-Sport. This is the case of the project “Ambient Intelligence Systems Support for Athletes with Specific Profiles”, which intends to assist athletes in their training. In this paper, the main developments and outcomes from this project are described. The architecture of the system comprises a WSN deployed in the training area which provides communication with athletes’ mobile equipments, performs location tasks, and harvests environmental data (wind speed, temperature, etc.). Athletes are equipped with a monitoring unit which obtains data from their training (pulse, speed, etc.). Besides, a decision engine combines these real-time data together with static information about the training field, and from the athlete, to direct athletes’ training to fulfill some specific goal. A prototype is presented in this work for a cross country running scenario, where the objective is to maintain the heart rate (HR) of the runner in a target range. For each track, the environmental conditions (temperature of the next track), the current athlete condition (HR), and the intrinsic difficulty of the track (slopes) influence the performance of the athlete. The decision engine, implemented by means of (m, s)-splines interpolation, estimates the future HR and selects the best track in each fork of the circuit. This method achieves a success ratio in the order of 80%. Indeed, results demonstrate that if environmental information is not take into account to derive training orders, the success ratio is reduced notably.

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This work was supported by MINECO grant TEC 2016-76465-C2-2-R and Xunta de Galicia grant GRC 2018/053, Spain. The authors are indebted to Asociación de Familiares de enfermos de Alzheimer y otras demencias de Galicia (AFAGA) for providing us with gerontology expertise and valuable design recommendations.

In this paper we identify and discuss the main issues and challenges to implement a Delay Tolerant Network (DTN) to allow multi-hop Car2Car (C2C) -also known as Vehicle2Vehicle (V2V)-and car2infrastructure (C21) communications. C2C communications are designed to increase automobile security and comfort, but a single hop is not enough [1]. Efficient network layers are necessary to overcome these limitations'.

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Multi-Access Edge Computing (MEC) is one of the prominent 5G concepts that will allow service requirements that were not feasible so far due to the high communications latency and rigidness of cellular networks. The ETSI and the 3GPP are working towards the standardization of MEC applications integration in 5G networks, and how to route user traffic to a Local Area Data Network where local applications are deployed. Nevertheless, there are no practical implementations that facilitate the dynamic relocation of applications from the core to a MEC host, or from a MEC host to another without interruption and transparently to User Equipment (UE). Furthermore, the MEC concept can also be included in a 4G network to provide new advanced services with existing infrastructures. In this paper we propose to use Software-Defined Networking (SDN) to create a new instance of the IP anchor point to dynamically redirect the UE traffic to a new physical location (e.g. an edge infrastructure) while maintaining session and service continuity. We also present a novel, completely distributed approach based on SDN to maintain the previous context of the connection in the new instance of the IP anchor point, and we analyze the performance of this mechanism in comparison to other possible alternatives to keep the session state. This approach can be used to implement edge services in a 4G or 5G network.

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