Multicore emulation-in-the-loop in the Khronosim project

Demo in 6th International workshop on the “Integration of mixed-criticality subsystems on multi-core and manycore processors” (MCS 2018). 23, Jan, 2018, Embedded parallel architectures for mixed-criticality. Manchester.MCS 2018 was held as part of the High Performance and Embedded Architecture and Compilation Conference (HiPEAC 2018), January 22-24, 2018.info:eu-repo/semantics/publishedVersio

Scheduling Parallel Real-Time Tasks in Multiprocessor Platforms

CPS Student Forum Portugal was held as part of the Cyber-Physical Systems Week (CPS Week 2018), 10-13 April, Porto-Portugal.• Computing systems are gradually becoming multiprocessor • Opportunity for an increase in application performance, throughput and responsiveness • Real-time systems may take advantage of platform parallelism to distribute workload among the cores for simultaneous executioninfo:eu-repo/semantics/publishedVersio

QoS-based surrogates selection and service proposal formulation in offloading environments

Resource constraints are becoming a problem as many of the wireless mobile devices have increased generality. Our work tries to address this growing demand on resources and performance, by proposing the dynamic selection of neighbor nodes for cooperative service execution. This selection is in uenced by user's quality of service requirements expressed in his request, tailoring provided service to user's speci c needs. In this paper we improve our proposal's formulation algorithm with the ability to trade o time for the quality of the solution. At any given time, a complete solution for service execution exists, and the quality of that solution is expected to improve overtime

Flexible and dynamic replication control for interdependent distributed real-time embedded systems, in

Abstract Replication is a proven concept for increasing the availability of distributed systems. However, actively replicating every software component in distributed embedded systems may not be a feasible approach. Not only the available resources are often limited, but also the imposed overhead could significantly degrade the system's performance. This paper proposes heuristics to dynamically determine which componentsto replicate based on their significance to the system as a whole, its consequent number of passive replicas, and where to place those replicas in the network. The activation of passive replicas is coordinated through a fast convergence protocol that reduces the complexity of the needed interactions among nodes until a new collective global service solution is determined. Abstract. Replication is a proven concept for increasing the availability of distributed systems. However, actively replicating every software component in distributed embedded systems may not be a feasible approach. Not only the available resources are often limited, but also the imposed overhead could significantly degrade the system's performance. This paper proposes heuristics to dynamically determine which components to replicate based on their significance to the system as a whole, its consequent number of passive replicas, and where to place those replicas in the network. The activation of passive replicas is coordinated through a fast convergence protocol that reduces the complexity of the needed interactions among nodes until a new collective global service solution is determined

IoT for Energy-Efficiency: connecting a serious game with energy metering in the EnerGAware project

The Internet of Things (IoT) emerged with the potential to change our daily lives and the way we interact and operate with our environment. However, in practice, IoT mixes a multitude of devices and subsystems, which are required to work together to provide the user with the expected quality of service. This leads to considerable development challenges, which are exacerbated by the speed of development and heterogeneity of IoT devices. This communication describes an IoT solution being implemented in the setting of a serious game application, connected to real homes energy consumption. The solution follows a publish-subscribe architecture to decouple the components of the system.info:eu-repo/semantics/publishedVersio

Exploiting a Throttle Mechanism for QEMU

This paper proposes the implementation of a throttle mechanism for QEMU in order to allow the testing of Cyber-Physical Systems via emulation.info:eu-repo/semantics/publishedVersio

The EnerGAware Middleware Platform

IECON 2017, 43rd Annual Conference of the IEEE Industrial Electronics Society (IES). Beijing, China.More and more cyber-physical systems and the internet of things push for a multitude of devices and systems, which need to work together to provide the services as required by the users. Nevertheless, the speed of development and the heterogeneity of devices introduces considerable challenges in the development of such systems. This paper describes a solution being implemented in the setting of a serious game scenario, connected to real homes energy consumption. The solution provides a publish-subscribe middleware which is able to seamlessly connect all the components of the system.info:eu-repo/semantics/publishedVersio

Timing Analysis Methodology

This chapter focuses on the analysis of the timing behavior of software applications that expose real-time (RT) requirements. The state-of-the-art methodologies to timing analysis of software programs are generally split into four categories, referred to as static, measurement-based, hybrid, and probabilistic analysis techniques. First, we present an overview of each of these methodologies and discuss their advantages and disadvantages. Next, we explain the choices made by our proposed methodology in Section 5.2 and present the details of the solution in Section 5.3. Finally, we conclude the chapter in Section 5.4 with a summary.info:eu-repo/semantics/publishedVersio

Framework for the Analysis and Configuration of Real-Time OpenMP Applications

High-performance cyber-physical applications impose several requirements with respect to performance, functional correctness and non-functional aspects. Nowadays, the design of these systems usually follows a model-driven approach, where models generate executable applications, usually with an automated approach. As these applications might execute in different parallel environments, their behavior becomes very hard to predict, and making the verification of non-functional requirements complicated. In this regard, it is crucial to analyse and understand the impact that the mapping and scheduling of computation have on the real-time response of the applications. In fact, different strategies in these steps of the parallel orchestration may produce significantly different interference, leading to different timing behaviour.Tuning the application parameters and the system configuration proves to be one of the most fitting solutions. The design space can however be very cumbersome for a developer to test manually all combinations of application and system configurations. This paper presents a methodology and a toolset to profile, analyse, and configure the timing behaviour of high-performance cyber-physical applications and the target platforms. The methodology leverages on the possibility of generating a task dependency graph representing the parallel computation to evaluate, through measurements, different mapping configurations and select the one that minimizes response time.This work has been co-funded by the European commission through the AMPERE (H2020 grant agreement N° 745601) project.Peer ReviewedPostprint (author's final draft

Heuristic-based task-to-thread mapping in multi-core processors

OpenMP can be used in real-time applications to enhance system performance. However, predictability of OpenMP applications is still a challenge. This paper investigates heuristics for the mapping of OpenMP task graphs in underlying threads, for the development of time-predictable OpenMP programs. These approaches are based on a global scheduling queue, as well as per-thread allocation queues. The proposed method is divided into scheduling and allocation phases. In the former phase, OpenMP task-parts are discovered from OpenMP graph and placed in the scheduling queue. Afterwards, an appropriate allocation queue is selected for each task-part using four heuristic algorithms. In the latter phase, the best task-part is selected from the allocation queue to be allocated to and executed by an idle thread. Preliminary simulation results show that the new method overcomes BFS and WFS in terms of scheduling time and idle time.This work has been co-funded by the European commission through the AMPERE (H2020 grant agreement N° 745601) project.Peer ReviewedPostprint (author's final draft