An Analytical Solution for Probabilistic Guarantees of Reservation Based Soft Real-Time Systems

We show a methodology for the computation of the probability of deadline miss for a periodic real-time task scheduled by a resource reservation algorithm. We propose a modelling technique for the system that reduces the computation of such a probability to that of the steady state probability of an infinite state Discrete Time Markov Chain with a periodic structure. This structure is exploited to develop an efficient numeric solution where different accuracy/computation time trade-offs can be obtained by operating on the granularity of the model. More importantly we offer a closed form conservative bound for the probability of a deadline miss. Our experiments reveal that the bound remains reasonably close to the experimental probability in one real-time application of practical interest. When this bound is used for the optimisation of the overall Quality of Service for a set of tasks sharing the CPU, it produces a good sub-optimal solution in a small amount of time.Comment: IEEE Transactions on Parallel and Distributed Systems, Volume:27, Issue: 3, March 201

A Software-based Low-Jitter Servo Clock for Inexpensive Phasor Measurement Units

This paper presents the design and the implementation of a servo-clock (SC) for low-cost Phasor Measurement Units (PMUs). The SC relies on a classic Proportional Integral (PI) controller, which has been properly tuned to minimize the synchronization error due to the local oscillator triggering the on-board timer. The SC has been implemented into a PMU prototype developed within the OpenPMU project using a BeagleBone Black (BBB) board. The distinctive feature of the proposed solution is its ability to track an input Pulse-Per-Second (PPS) reference with good long-term stability and with no need for specific on-board synchronization circuitry. Indeed, the SC implementation relies only on one co-processor for real-time application and requires just an input PPS signal that could be distributed from a single substation clock

Cooperative UAVs Gas Monitoring using Distributed Consensus

This paper addresses the problem of target detection and localisation in a limited area using multiple coordinated agents. The swarm of Unmanned Aerial Vehicles (UAVs) determines the position of the dispersion of stack effluents to a gas plume in a certain production area as fast as possible, that makes the problem challenging to model and solve, because of the time variability of the target. Three different exploration algorithms are designed and compared. Besides the exploration strategies, the paper reports a solution for quick convergence towards the actual stack position once detected by one member of the team. Both the navigation and localisation algorithms are fully distributed and based on the consensus theory. Simulations on realistic case studies are reported.Comment: 7 pages, 6 figure

Verifying a stochastic model for the spread of a SARS-CoV-2-like infection: opportunities and limitations

There is a growing interest in modeling and analyzing the spread of diseases like the SARS-CoV-2 infection using stochastic models. These models are typically analyzed quantitatively and are not often subject to validation using formal verification approaches, nor leverage policy syntheses and analysis techniques developed in formal verification. In this paper, we take a Markovian stochastic model for the spread of a SARSCoV-2-like infection. A state of this model represents the number of subjects in different health conditions. The considered model considers the different parameters that may have an impact on the spread of the disease and exposes the various decision variables that can be used to control it. We show that the modeling of the problem within state-of-the-art model checkers is feasible and it opens several opportunities. However, there are severe limitations due to i) the espressivity of the existing stochastic model checkers on one side, and ii) the size of the resulting Markovian model even for small population sizes.Comment: Accepted for pubblication in AIxIA 202

A Servo-Clock Model for Chains of Transparent Clocks Affected by Synchronization Period Jitter

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Efficient Reinforcement Learning for Jumping Monopods

In this work, we consider the complex control problem of making a monopod reach a target with a jump. The monopod can jump in any direction and the terrain underneath its foot can be uneven. This is a template of a much larger class of problems, which are extremely challenging and computationally expensive to solve using standard optimisation-based techniques. Reinforcement Learning (RL) could be an interesting alternative, but the application of an end-to-end approach in which the controller must learn everything from scratch, is impractical. The solution advocated in this paper is to guide the learning process within an RL framework by injecting physical knowledge. This expedient brings to widespread benefits, such as a drastic reduction of the learning time, and the ability to learn and compensate for possible errors in the low-level controller executing the motion. We demonstrate the advantage of our approach with respect to both optimization-based and end-to-end RL approaches