Real-time and fault tolerance in distributed control software

Closed loop control systems typically contain multitude of spatially distributed sensors and actuators operated simultaneously. So those systems are parallel and distributed in their essence. But mapping this parallelism onto the given distributed hardware architecture, brings in some additional requirements: safe multithreading, optimal process allocation, real-time scheduling of bus and network resources. Nowadays, fault tolerance methods and fast even online reconfiguration are becoming increasingly important. All those often conflicting requirements, make design and implementation of real-time distributed control systems an extremely difficult task, that requires substantial knowledge in several areas of control and computer science. Although many design methods have been proposed so far, none of them had succeeded to cover all important aspects of the problem at hand. [1] Continuous increase of production in embedded market, makes a simple and natural design methodology for real-time systems needed more then ever

Towards an HLA Run-time Infrastructure with Hard Real-time Capabilities

Our work takes place in the context of the HLA standard and its application in real-time systems context. The HLA standard is inadequate for taking into consideration the different constraints involved in real-time computer systems. Many works have been invested in order to providing real-time capabilities to Run Time Infrastructures (RTI) to run real time simulation. Most of these initiatives focus on major issues including QoS guarantee, Worst Case Transit Time (WCTT) knowledge and scheduling services provided by the underlying operating systems. Even if our ultimate objective is to achieve real-time capabilities for distributed HLA federations executions, this paper describes a preliminary work focusing on achieving hard real-time properties for HLA federations running on a single computer under Linux operating systems. Our paper proposes a novel global bottom up approach for designing real-time Run time Infrastructures and a formal model for validation of uni processor to (then) distributed real-time simulation with CERTI

Macroservers: An Execution Model for DRAM Processor-In-Memory Arrays

The emergence of semiconductor fabrication technology allowing a tight coupling between high-density DRAM and CMOS logic on the same chip has led to the important new class of Processor-In-Memory (PIM) architectures. Newer developments provide powerful parallel processing capabilities on the chip, exploiting the facility to load wide words in single memory accesses and supporting complex address manipulations in the memory. Furthermore, large arrays of PIMs can be arranged into a massively parallel architecture. In this report, we describe an object-based programming model based on the notion of a macroserver. Macroservers encapsulate a set of variables and methods; threads, spawned by the activation of methods, operate asynchronously on the variables' state space. Data distributions provide a mechanism for mapping large data structures across the memory region of a macroserver, while work distributions allow explicit control of bindings between threads and data. Both data and work distributuions are first-class objects of the model, supporting the dynamic management of data and threads in memory. This offers the flexibility required for fully exploiting the processing power and memory bandwidth of a PIM array, in particular for irregular and adaptive applications. Thread synchronization is based on atomic methods, condition variables, and futures. A special type of lightweight macroserver allows the formulation of flexible scheduling strategies for the access to resources, using a monitor-like mechanism

ERIGrid Holistic Test Description for Validating Cyber-Physical Energy Systems

Smart energy solutions aim to modify and optimise the operation of existing energy infrastructure. Such cyber-physical technology must be mature before deployment to the actual infrastructure, and competitive solutions will have to be compliant to standards still under development. Achieving this technology readiness and harmonisation requires reproducible experiments and appropriately realistic testing environments. Such testbeds for multi-domain cyber-physical experiments are complex in and of themselves. This work addresses a method for the scoping and design of experiments where both testbed and solution each require detailed expertise. This empirical work first revisited present test description approaches, developed a newdescription method for cyber-physical energy systems testing, and matured it by means of user involvement. The new Holistic Test Description (HTD) method facilitates the conception, deconstruction and reproduction of complex experimental designs in the domains of cyber-physical energy systems. This work develops the background and motivation, offers a guideline and examples to the proposed approach, and summarises experience from three years of its application.This work received funding in the European Community’s Horizon 2020 Program (H2020/2014–2020) under project “ERIGrid” (Grant Agreement No. 654113)

Formal and Informal Methods for Multi-Core Design Space Exploration

We propose a tool-supported methodology for design-space exploration for embedded systems. It provides means to define high-level models of applications and multi-processor architectures and evaluate the performance of different deployment (mapping, scheduling) strategies while taking uncertainty into account. We argue that this extension of the scope of formal verification is important for the viability of the domain.Comment: In Proceedings QAPL 2014, arXiv:1406.156

Power Load Management as a Computational Market

Power load management enables energy utilities to reduce peak loads and thereby save money. Due to the large number of different loads, power load management is a complicated optimization problem. We present a new decentralized approach to this problem by modeling direct load management as a computational market. Our simulation results demonstrate that our approach is very efficient with a superlinear rate of convergence to equilibrium and an excellent scalability, requiring few iterations even when the number of agents is in the order of one thousand. Aframework for analysis of this and similar problems is given which shows how nonlinear optimization and numerical mathematics can be exploited to characterize, compare, and tailor problem-solving strategies in market-oriented programming