Robotics are generally subject to stringent operational conditions that impose a high degree of criticality on the allocation of resources and the schedule of operations in mission planning. In this regard the so-called cost of a mission must be considered as an additional criterion when designing optimal task schedules within the mission at hand. Such a cost can be conceived as the impact of the mission on the robotic resources themselves, which range from the consumption of battery to other negative effects such as mechanic erosion. This manuscript focuses on this issue by presenting experimental results obtained over realistic scenarios of two heuristic solvers (MOHS and NSGA-II) aimed at efficiently scheduling tasks in robotic swarms that collaborate together to accomplish a mission. The heuristic techniques resort to a Random-Keys encoding strategy to represent the allocation of robots to tasks whereas the relative execution order of such tasks within the schedule of certain robots is computed based on the Traveling Salesman Problem (TSP). Experimental results in three different deployment scenarios reveal the goodness of the proposed technique based on the Multi-objective Harmony Search algorithm (MOHS) in terms of Hypervolume (HV) and Coverage Rate (CR) performance indicators.

Current data sharing architectures, like International Data Space – IDS, still lack maturity and certain requirements or functionalities that prevent them from being complete solutions when it comes to implementing intelligent, exploitable, secure, and reliable data spaces on which to develop a healthy data economy. One of these main shortcomings is the treatment of personal data and it is that these reference models are highly oriented to guarantee the sovereignty of the data for industrial data, and therefore the access control and exploitation of personal data is out of their scope, forgetting the exceptional privacy and usage conditions that must be considered in this type of data. In this paper we present the DataVaults project, and the platform implemented to allow the discovery of this kind of data and at the same time, control that only those who have been specified by the owner user have access and under the terms that he has previously established. Our approach allows the exchange of information not to be limited to industrial or business domains, where sharing is focused only on impersonal industrial data. The validation will be carried out in cases of use started in Smart Cities for the treatment of data and decision-making of citizens. Key Words: Data sharing, International Data Spaces, personal data privacy, access and usage control.