This paper proposes a smart system for managing the operations of grid-connected charging stations for electric vehicles (EV) that use photovoltaic (PV) sources. This system consists of a mobile application for EV drivers to make charging reservations, an algorithm to optimize the charging schedule, and a remote execution module of charging operations based on the open charge point protocol (OCPP). The optimal charging schedule was obtained by solving a binary integer programming problem. The merits of our solution are illustrated by simulating different charging demand scenarios.

Over the last few years, there has been a rising trend towards the field of distributed testing where the implementation under test (IUT) has physical distributed ports. However, running several testers in such ports can lead to a number of coordination and synchronisation issues between these remote testers. We suggest in previous works to cope with these problems by enhancing the test architecture with some timing constraints. In this paper, we introduce a new algorithm to generate local timed test sequences so as to describe the behaviour of the test at each port. We aim through this algorithm to reduce the number of messages exchanged among the testers. Moreover, we illustrate our approach through a case study using MapReduce architecture with several worker components. These systems commonly encounter failures as a result of several circumstances, such as hardware faults, power outages, or network connection delays. To this end, we set the temporal properties in the specification of these systems. Then, we apply our algorithm to derive the related timed local test sequences. Furthermore, we explain how to apply our approach in the case of MapReduce testing to identify faulty workers, in order to reschedule their tasks to a healthy worker. GRAPHICAL ABSTRACT