Showing papers by "Alberto Sangiovanni-Vincentelli published in 2013"

Optimization of task allocation and priority assignment in hard real-time distributed systems

Abstract: The complexity and physical distribution of modern active safety, chassis, and powertrain automotive applications requires the use of distributed architectures. Complex functions designed as networks of function blocks exchanging signal information are deployed onto the physical HW and implemented in a SW architecture consisting of a set of tasks and messages. The typical configuration features priority-based scheduling of tasks and messages and imposes end-to-end deadlines. In this work, we present and compare formulations and procedures for the optimization of the task allocation, the signal to message mapping, and the assignment of priorities to tasks and messages in order to meet end-to-end deadline constraints and minimize latencies. Our formulations leverage worst-case response time analysis within a mixed integer linear optimization framework and are compared for performance against a simulated annealing implementation. The methods are applied for evaluation to an automotive case study of complexity comparable to industrial design problems.

Polynomial-Time Verification of PCTL Properties of MDPs with Convex Uncertainties

Abstract: We address the problem of verifying Probabilistic Computation Tree Logic (PCTL) properties of Markov Decision Processes (MDPs) whose state transition probabilities are only known to lie within uncertainty sets. We first introduce the model of Convex-MDPs (CMDPs), i.e., MDPs with convex uncertainty sets. CMDPs generalize Interval-MDPs (IMDPs) by allowing also more expressive (convex) descriptions of uncertainty. Using results on strong duality for convex programs, we then present a PCTL verification algorithm for CMDPs, and prove that it runs in time polynomial in the size of a CMDP for a rich subclass of convex uncertainty models. This result allows us to lower the previously known algorithmic complexity upper bound for IMDPs from co-NP to PTIME. We demonstrate the practical effectiveness of the proposed approach by verifying a consensus protocol and a dynamic configuration protocol for IPv4 addresses.

Synthesis of Finite State Machines : Functional Optimization

Abstract: Synthesis of Finite State Machines: Functional Optimization is one of two monographs devoted to the synthesis of Finite State Machines (FSMs). This volume addresses functional optimization, whereas the second addresses logic optimization. By functional optimization here we mean the body of techniques that: compute all permissible sequential functions for a given topology of interconnected FSMs, and select a `best' sequential function out of the permissible ones. The result is a symbolic description of the FSM representing the chosen sequential function. By logic optimization here we mean the steps that convert a symbolic description of an FSM into a hardware implementation, with the goal to optimize objectives like area, testability, performance and so on. Synthesis of Finite State Machines: Functional Optimization is divided into three parts. The first part presents some preliminary definitions, theories and techniques related to the exploration of behaviors of FSMs. The second part presents an implicit algorithm for exact state minimization of incompletely specified finite state machines (ISFSMs), and an exhaustive presentation of explicit and implicit algorithms for the binate covering problem. The third part addresses the computation of permissible behaviors at a node of a network of FSMs and the related minimization problems of non-deterministic finite state machines (NDFSMs). Key themes running through the book are the exploration of behaviors contained in a non-deterministic FSM (NDFSM), and the representation of combinatorial problems arising in FSM synthesis by means of Binary Decision Diagrams (BDDs). Synthesis of Finite State Machines: Functional Optimization will be of interest to researchers and designers in logic synthesis, CAD and design automation.

Security-aware mapping for CAN-based real-time distributed automotive systems

Abstract: Cyber-security is a rising issue for automotive electronic systems, and it is critical to system safety and dependability. Current in-vehicles architectures, such as those based on the Controller Area Network (CAN), do not provide direct support for secure communications. When retrofitting these architectures with security mechanisms, a major challenge is to ensure that system safety will not be hindered, given the limited computation and communication resources. We apply Message Authentication Codes (MACs) to protect against masquerade and replay attacks on CAN networks, and propose an optimal Mixed Integer Linear Programming (MILP) formulation for solving the mapping problem from a functional model to the CAN-based platform while meeting both the security and the safety requirements. We also develop an efficient heuristic for the mapping problem under security and safety constraints. To the best of our knowledge, this is the first work to address security and safety in an integrated formulation in the design automation of automotive electronic systems. Experimental results of an industrial case study show the effectiveness of our approach.

metroII: A design environment for cyber-physical systems

Abstract: Cyber-Physical Systems are integrations of computation and physical processes and as such, will be increasingly relevant to industry and people. The complexity of designing CPS resides in their heterogeneity. Heterogeneity manifest itself in modeling their functionality as well as in the implementation platforms that include a multiplicity of components such as microprocessors, signal processors, peripherals, memories, sensors and actuators often integrated on a single chip or on a small package such as a multi-chip module. We need a methodology, tools and environments where heterogeneity can be dealt with at all levels of abstraction and where different tools can be integrated. We present here Platform-Based Design as the CPS methodology of choice and metroII, a design environment that supports it. We present the metamodeling approach followed in metroII, how to couple the functionality and implementation platforms of CPS, and the simulation technology that supports the analysis of CPS and of their implementation. We also present examples of use and the integration of metroII with another popular design environment developed at Verimag, BIP.

Online Simultaneous State Estimation and Parameter Adaptation for Building Predictive Control

Abstract: Model-based control of building energy offers an attractive way to minimize energy consumption in buildings. Model-based controllers require mathematical models that can accurately predict the behavior of the system. For buildings, specifically, these models are difficult to obtain due to highly time varying, and nonlinear nature of building dynamics. Also, model-based controllers often need information of all states, while not all the states of a building model are measurable. In addition, it is challenging to accurately estimate building model parameters (e.g. convective heat transfer coefficient of varying outside air). In this paper, we propose a modeling framework for “on-line estimation ” of states and unknown parameters of buildings, leading to the Parameter-Adaptive Building (PAB) model. Extended Kalman filter (EKF) and unscented Kalman filter (UKF) techniques are used to design the PAB model which simultaneously tunes the parameters of the model and provides an estimate for all states of the model. The proposed PAB model is tested against experimental data collected from Lakeshore Center building at Michigan Tech University. Our results indicate that the new framework can accurately predict states and parameters of the building thermal model.

Duty-cycle optimization for IEEE 802.15.4 wireless sensor networks

Abstract: Most applications of wireless sensor networks require reliable and timely data communication with maximum possible network lifetime under low traffic regime. These requirements are very critical especially for the stability of wireless sensor and actuator networks. Designing a protocol that satisfies these requirements in a network consisting of sensor nodes with traffic pattern and location varying over time and space is a challenging task. We propose an adaptive optimal duty-cycle algorithm running on top of the IEEE 802.15.4 medium access control to minimize power consumption while meeting the reliability and delay requirements. Such a problem is complicated because simple and accurate models of the effects of the duty cycle on reliability, delay, and power consumption are not available. Moreover, the scarce computational resources of the devices and the lack of prior information about the topology make it impossible to compute the optimal parameters of the protocols. Based on an experimental implementation, we propose simple experimental models to expose the dependency of reliability, delay, and power consumption on the duty cycle at the node and validate it through extensive experiments. The coefficients of the experimental-based models can be easily computed on existing IEEE 802.15.4 hardware platforms by introducing a learning phase without any explicit information about data traffic, network topology, and medium access control parameters. The experimental-based model is then used to derive a distributed adaptive algorithm for minimizing the power consumption while meeting the reliability and delay requirements in the packet transmission. The algorithm is easily implementable on top of the IEEE 802.15.4 medium access control without any modifications of the protocol. An experimental implementation of the distributed adaptive algorithm on a test bed with off-the-shelf wireless sensor devices is presented. The experimental performance of the algorithms is compared to the existing solutions from the literature. The experimental results show that the experimental-based model is accurate and that the proposed adaptive algorithm attains the optimal value of the duty cycle, maximizing the lifetime of the network while meeting the reliability and delay constraints under both stationary and transient conditions. Specifically, even if the number of devices and their traffic configuration change sharply, the proposed adaptive algorithm allows the network to operate close to its optimal value. Furthermore, for Poisson arrivals, the duty-cycle protocol is modeled as a finite capacity queuing system in a star network. This simple analytical model provides insights into the performance metrics, including the reliability, average delay, and average power consumption of the duty-cycle protocol.

Co-design of control algorithm and embedded platform for building HVAC systems

Abstract: The design of heating, ventilation and air conditioning (HVAC) systems is crucial for reducing energy consumption in buildings. As complex cyber-physical systems, HVAC systems involve three closely-related subsystems - the control algorithm, the physical building and environment and the embedded implementation platform. In the traditional top-down approach, the control algorithm and the embedded platform are in general designed separately leading to suboptimal systems. We propose a co-design approach that analyzes the interaction between the control algorithm and the embedded platform through a set of interface variables (in this paper we address in particular sensing accuracy). We present six control algorithms that take into account the sensing error, and model the relation of control performance and cost versus sensing error. We also capture the relation of embedded platform cost versus sensing error by analysis of the collected data from a test bed. Based on these models, we explore the co-design of the control algorithm and the temperature sensing subsystem of the embedded platform to optimize with respect to energy cost and monetary cost while satisfying the constraints for user comfort level.

Flexibility of Commercial Building HVAC Fan as Ancillary Service for Smart Grid

Abstract: In this paper, we model energy use in commercial buildings using empirical data captured through sMAP, a campus building data portal at UC Berkeley. We conduct at-scale experiments in a newly constructed building on campus. By modulating the supply duct static pressure (SDSP) for the main supply air duct, we induce a response on the main supply fan and determine how much ancillary power flexibility can be provided by a typical commercial building. We show that the consequent intermittent fluctuations in the air mass flow into the building does not influence the building climate in a human-noticeable way. We estimate that at least 4 GW of regulation reserve is readily available only through commercial buildings in the US. Based on predictions this value will reach to 5.6 GW in 2035. We also show how thermal slack can be leveraged to provide an ancillary service to deal with transient frequency fluctuations in the grid. We consider a simplified model of the grid power system with time varying demand and generation and present a simple control scheme to direct the ancillary service power flow from buildings to improve on the classical automatic generation control (AGC)-based approach. Simulation results are provided to show the effectiveness of the proposed methodology for enhancing grid frequency regulation.

BAG: a designer-oriented integrated framework for the development of AMS circuit generators

Abstract: We introduce BAG, the Berkeley Analog Generator, an integrated framework for the development of generators of Analog and Mixed Signal (AMS) circuits. Such generators are parameterized design procedures that produce sized schematics and correct layouts optimized to meet a set of input specifications. BAG extends previous work by implementing interfaces to integrate all steps of the design flow into a single environment and by providing helper classes -- both at the schematic and layout level -- to aid the designer in developing truly parameterized and technology-independent circuit generators. This simplifies the codification of common tasks including technology characterization, schematic and testbench translation, simulator interfacing, physical verification and extraction, and parameterized layout creation for common styles of layout. We believe that this approach will foster design reuse, ease technology migration, and shorten time-to-market, while remaining close to the classical design flow to ease adoption. We have used BAG to design generators for several circuits, including a Voltage Controlled Oscillator (VCO) and a Switched-Capacitor (SC) voltage regulator in a CMOS 65nm process. We also present results from automatic migration of our designs to a 40nm process.

Optimal load management system for Aircraft Electric Power distribution

Abstract: Aircraft Electric Power Systems (EPS) route power from generators to vital avionic loads by configuring a set of electronic control switches denoted as contactors. In this paper, we address the problem of designing a hierarchical optimal control strategy for the EPS contactors in the presence of system faults. We first formalize the system connectivity, safety and performance requirements in terms of mathematical constraints. We then show that the EPS control problem can be formulated as a Mixed-Integer Linear Program (MILP) and efficiently solved to yield load shedding, source allocation, contactor switching and battery charging policies, while optimizing a number of performance metrics, such as the number of used generators and shed loads. This solution is then integrated into a hierarchical control scheme consisting of two layers of controllers. The high-level controller provides control optimality by solving the MILP within a receding horizon approach. The low-level controller handles system faults, by directly actuating the EPS contactors, and implements the solution from the high-level controller only if it is safe. Simulation results confirm the effectiveness of the proposed approach.

Flexibility of Commercial Building HVAC Fan as Ancillary Service for Smart Grid

Abstract: Flexibility of Commercial Building HVAC Fan as Ancillary Service for Smart Grid Mehdi Maasoumy † , Jorge Ortiz ∗ , David Culler ∗ and Alberto Sangiovanni-Vincentelli ∗ Abstract—In this paper, we model energy use in commercial buildings using empirical data captured through sMAP, a cam- pus building data portal at UC Berkeley. We conduct at-scale experiments in a newly constructed building on campus. By modulating the supply duct static pressure (SDSP) for the main supply air duct, we induce a response on the main supply fan and determine how much ancillary power flexibility can be provided by a typical commercial building. We show that the consequent intermittent fluctuations in the air mass flow into the building does not influence the building climate in a human-noticeable way. We estimate that at least 4 GW of regulation reserve is readily available only through commercial buildings in the US. Based on predictions this value will reach to 5.6 GW in 2035. We also show how thermal slack can be leveraged to provide an ancillary service to deal with transient frequency fluctuations in the grid. We consider a simplified model of the grid power system with time varying demand and generation and present a simple control scheme to direct the ancillary service power flow from buildings to improve on the classical automatic generation control (AGC)-based approach. Simulation results are provided to show the effectiveness of the proposed methodology for enhancing grid frequency regulation. I. I NTRODUCTION Total primary energy consumption in the world increased more than 27% over the last decade; from 400 Quadrillion Btu in 2000 to 510 Quadrillion Btu in 2010 [1]. A sustainable energy future requires significant and widespread penetra- tion of renewable energy sources (RES) than the current level. However, the volatility, uncertainty, and intermittency of renewable energy sources present a daunting challenge to integrate them into the power grid at large scale. Balancing generation and load instantaneously and continu- ously, given the randomness in the dynamics of generation and demand, is difficult. Minute-to-minute load variability results from random de/activation of millions of individual loads. Long-term variability results from predictable factors such as the daily and seasonal load patterns as well as more random events like shifting weather patterns. Generators also introduce unexpected fluctuations because they do not follow their generation schedules exactly and they trip unexpectedly due to a range of equipment failures [2]. Significant deviation in supply-demand balance can lead to large frequency deviation, which in turn jeopardizes the stability of the grid. To avoid this catastrophic event, several so called “ancillary services” such as regulation and load following, have been formalized to better manage supply- demand balance at all time. The Federal Energy Regulatory † Department of Mechanical Engineering, University of California, Berkeley, CA 94720-1740, USA. Corresponding author. Email: mehdi@me.berkeley.edu ∗ Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, CA 94720-1740, USA. Commission (FERC) has defined such services as those “nec- essary to support the transmission of electric power from seller to purchaser given the obligations of control areas and transmitting utilities within those control areas to maintain reliable operation of the interconnected transmission system.” This quote highlights the importance of ancillary services for both bulk-power reliability and support of commercial transactions [2]. Buildings consume about 75% of US electricity, with roughly equal shares for residential and commercial build- ings [3]. Commercial buildings are suitable for providing ancillary services due to the following reasons: 1) More than 30% of commercial buildings have adopted Building Energy Management System (BEMS) technology [4] which facilitates the communication with the grid system operators for providing real-time ancillary services. The majority of these buildings are also equipped with variable frequency drives, which in coordination with BEMS, can manipulate the heating, ventilation and air conditioning (HVAC) system power consumption very frequently (in the order of several seconds). 2) Compared to typical residential buildings, commercial buildings have larger HVAC systems and therefore consume more electricity and present an opportunity for manipulating and controlling the buildings power draw. HVAC system fans account for about 15% of electricity consumed in commercial buildings. Since we can directly control their power-draw rate, upward or downward fans are an ideal candidate for ancillary service. A. Related Works Model-based optimal control strategies such as Model Pre- dictive Control (MPC) are promising for energy efficiency in buildings and for integrating time-of-use rates for shifting loads [5]–[10]. In a more recent paper [11] simulation data show that commercial buildings can provide significant ancil- lary service for more robust operation of the grid. The same paper postulates 6.6 GW of regulation capacity from about 5 million commercial buildings in the US. In this paper, we attempt to verify this claim via experiments on a real building. Regulation is a zero-energy service, making it an ideal candidate for supply by storage. In [2], storage technologies are acknowledged to be ideal suppliers of several ancillary services, including regulation. Storage using chemical batteries however, has two important drawbacks: 1) It is expensive and 2) it is not environmentally-friendly. There is an emerging consensus that flexible loads with thermal storage capabilities, also known as Thermostatically Controllable Loads (TCL) will play an important role in regulating grid frequency and in effect, enable deep penetration of RES.

A tool integration approach for architectural exploration of aircraft electric power systems

Abstract: For emerging safety-critical systems, it is beneficial to cope with design validation, performance estimation, and design space exploration in early design stages. In this paper, we explore the architectural choices of an aircraft electric power system (EPS) controller using Ptolemy II and Metro II. The design is modeled in separate aspects: the functional aspect models the logics and behaviors that fulfill the functionality of the controller, and the architectural aspect models the behaviors of the platform that implements the controller. The co-design benefits from the rigorous Model of Computation (MoC) in Ptolemy II, which facilitates the analysis and validation of functional aspect, as well as the flexibility and expressiveness provided by Metro II, in which complex architectural models can be built with the flexibility of changing the mapping. Co-simulation integrates the functional model and the architectural model using Metro II semantics. By clearly separating the functional aspect and the architectural aspect, the performance can be estimated at an early design stage, and the architectural exploration can be done in a more efficient manner.We show the effectiveness and extensibility of our approach using experiments and results with example candidates for the aircraft EPS controller.

Timing analysis of process graphs with finite communication buffers

Abstract: Real-Time Calculus (RTC) is a modular performance analysis framework for real-time embedded systems. It can be used to compute the worst-case and best-case response times of tasks with general activation patterns and configurations, such as pipelines of tasks that are connected via finite buffers. In this paper, we extend the existing RTC framework to analyze arbitrary graph configurations of tasks and messages, with mixed periodic and event-based activation models and finite buffers between any pair of nodes. Our extension also improves upon several sources of pessimism in the existing analysis. We present an application of the extended RTC to the Loosely Time-Triggered Architecture (LTTA) implementation of synchronous models, commonly used in the development of embedded automotive, avionics and control systems. We show how our method can be used to model scheduling and communication delays in an LTTA mapping, which gives tighter analysis bounds on the output rate and the latency compared to existing techniques. The evaluation on automotive workloads shows that our approach is scalable and outperforms existing techniques in terms of analysis accuracy.

Platform-Based Design Methodology and Modeling for Aircraft Electric Power Systems.

Abstract: In an aircraft electric power system (EPS), a supervisory control unit must actuate a set of switches to distribute power from generators to loads, while satisfying safety, reliability and real-time performance requirements To reduce expensive re-design steps in current design methodologies, such a control problem is generally addressed based on minor incremental changes on top of consolidated solutions, since it is difficult to estimate the impact of earlier design decisions on the final implementation In this paper, we introduce a methodology for the design space exploration and virtual prototyping of EPS supervisory control protocols, following the platform-based design (PBD) paradigm Moreover, we describe the modeling infrastructure that supports the methodology In PBD, design space exploration is carried out as a sequence of refinement steps from the initial specification towards a final implementation, by mapping higher-level behavioral models into a set of library components at a lower level of abstraction In our flow, the system specification is captured using SysML requirement and structure diagrams State-machine diagrams enable verification of the control protocol at a high level of abstraction, while lowerlevel hybrid models, implemented in Simulink, are used to verify properties related to physical quantities, such as time, voltage and current values The effectiveness of our approach is illustrated on a prototype EPS control protocol design