Matlab2Trace: A Matlab to Trace translator to visualise and analyse concurrent system activities and execution traces

Matlab provides an environment to analyse and visualise data and develop algorithms. However, there is limited support for visualising and analysing system activities executing concurrently, for instance, on a multiprocessor platform. Trace (https://esi.nl/research/output/tools/trace) is software that specialises in visualising and analysing concurrent system activities and execution traces. We present a Matlab to Trace translator that directly generates a trace-input file from the Matlab environment. Concurrent system activities and execution traces of the algorithms developed inside the Matlab environment can be visualised and analysed in Trace using the generated trace-input file. The translator takes as input the logical or absolute starting and ending time of the algorithmic execution, and the number (and labels) of processing cores. TRACE visualizes concurrent activities in a Gantt-chart-like view which provides colouring, grouping and filtering options. TRACE also provides several analysis methods, which sets it apart from the many other Gantt-chart visualization tools: i) Critical-path analysis can be used to detect tasks and resources that are bottlenecks for performance; ii) Distance analysis can be used to compare execution traces with respect to structure, e.g. to check a model trace against an implementation trace; iii) MTL checking provides a means to formally specify and verify properties of execution traces using Metric Temporal Logic. It is useful to express and check, for instance, performance properties such as the “processing latency is at most 50 ms”; iv) The streaming performance DSL is a domain-specific language that captures often-used performance properties for stream-processing systems (e.g., image or video processing), and which eases the use of the MTL checker; and v) The resource usage feature can quickly give insight in the details of the resource usage. The Matlab2Trace can be downloaded from https://github.com/TUE-EE-ES/Matlab2Trace

Model-driven quality and resource management for CPSs

A Cyber-Physical System (CPS) integrates cyber systems, human users, networks and physical systems. Thus, a CPS needs visual context and awareness to make autonomous and correct decisions. Advanced image and video processing is computationally intensive and challenging. Moreover, a CPS comprises increasingly complex and distributed configurations, which is reflectedin the growing number of sensors, actuators and other smart devices. This leadsto an exponential number of dynamic system configurations. To make mattersworse, a CPS needs to simultaneously satisfy many rigorous constraints, e.g.,hard deadlines, safety, quality, and performance. Hence, the system designeris confronted with an immense number of potential configurations of which anumber meet the constraints and only a fraction are optimal regarding certainqualities. This makes finding the optimal configurations hard, especially duringrun-time. A domain-specific language (DSL) for quality and resource managment (QRM) is presented to specify these configurations conveniently and reasonabout them in an automated manner

Control of platooned vehicles in presence of traffic shock waves

Vehicle platooning has been attracting attention recently because of its ability to improve road capacity, safety and fuel efficiency. Vehicles communicate using Vehicle-toVehicle (V2V) wireless communication, making their status (acceleration, position, etc.) available to other vehicles. Shock waves, i.e. zones of reduced traffic speed that propagate upstream, are a well known emergent traffic phenomenon. Since vehicles entering such a zone need to decelerate sharply, shock waves cause a deterioration of fuel economy, driving comfort, and safety. While typically caused by bad driving behavior, recent studies have shown that it is possible to diminish or dissipate shock waves by applying certain good driving behavioral patterns. In this work, we use the information about the traffic situation to adapt the reference speed profile of the platoon we control, in order to mitigate the effect of a shock wave coming from downstream. The platoon leader receives the velocity of the vehicles downstream of the platoon and distance gap between them using V2V communication and it computes the shock wave speed. We show that by doing this we reduce the fuel consumption of the vehicles in the platoon, and improve the traffic situation by helping dissipate the shock wave. We validate our results using microscopic models with the help of a toolchain composed of Matlab, and the SUMO traffic simulator

A Compositional Model for Multi-Rate Max-Plus Linear Systems

The timing of discrete-event systems with synchronization is naturally modeled with canonical multi-rate max-plus linear equations. The main objectives of these models are to analyze and control the systems. As a system becomes more complex, determining its canonical model becomes more complicated. Moreover, these systems may change over time which demands the model to be recalculated. Motivated by the compositional structure of many systems, we propose operations to determine the canonical model for composed multi-rate max-plus linear systems. The operations allow efficient (re-)calculation of the canonical models from constituent canonical models. These models can be utilized to analyze and/or control complex systems using existing methods

Receiver Design with an Adjustable Energy-Signal-Quality Trade-off for IoT Networks

The energy efficiency of an Internet-of-Things (IoT) receiver can be improved by introducing an adjustable trade-off between signal-quality and energy consumption. In good channel conditions, the receiver can be set to consume less energy per bit, without compromising signal quality in bad channel conditions. We propose a system-level receiver design that enables adequate configuration and combination of signal-quality and energy trade-offs in multiple receiver components. Co-design of all components is essential. We identify the most energy-efficient configurations in our system-level design under different channel conditions. With those configurations, the proposed receiver outperforms a state-of-the-art adjustable receiver with only an adjustable analog front end by several tens of percent in energy per successfully received bit and by 2x in energy-sensitivity configuration range. To show the efficacy of the proposed approach, we integrate a model of the proposed design into the OMNeT++ simulator and show the benefits on an environmental monitoring scenario. In this scenario, we report up to 6x energy savings for the entire transceiver compared to the conventional transceiver design without adjustable receiver

Delay-aware Multi-layer Multi-rate Model Predictive Control for Vehicle Platooning under Message-rate Congestion Control

Vehicle platooning is an enabler technology for increasing road capacity, improving safety and reducing fuel consumption. Platoon control is a two-layered system where each layer runs under a different communication standard and rate – (i) the upper-layer operates under a specific V2V communication standard such as IEEE 802.11p and (ii) the lower-layer operates over high-speed in-vehicle communication networks such as FlexRay, CAN. The upper-layer, under 802.11p, uses periodic Cooperative Awareness Messages (CAMs) for exchanging vehicle motion information (i.e., acceleration, velocity and so on), the rate of which is adapted depending on the network congestion level.With over 70% channel load, the CAMs experience significant delay and packet loss, jeopardizing the stability of the platoon control. Under such high congestion, the European Telecommunications Standard Institute (ETSI) proposes to engage Decentralized Congestion Control (DCC) to control the channel load. We propose a platoon control and DCC scheme to tackle this scenario. Our contribution is three-fold. First, we propose a multi-layer platoon model explicitly augmenting the communication delay in the state-space. Second, the augmented delay-aware platoon model is integrated in the state-of-the-art multi-layer multi-rate model predictive control (MPC) for the upper-layer. Third, we adopt a message-rate congestion control scheme to keep the channel load under a given threshold. We use the proposed delay-aware MPC scheme under the message-rate congestion control scheme which may lead to switching under dynamic network conditions. Using the proposed technique, we show that platoon performance can be maintained under high network congestion while maintaining string stability

Modeling and analysis of switching max-plus linear systems with discrete-event feedback

Switching max-plus linear system (SMPLS) models are an apt formalism for performance analysis of discrete-event systems. SMPLS analysis is more scalable than analysis through other formalisms such as timed automata, because SMPLS abstract pieces of determinate concurrent system behavior into atomic modes with fixed timing. We consider discrete-event systems that are decomposed into a plant and a Supervisory Controller (SC) that controls the plant. The SC needs to react to events, concerning e.g. the successful completion or failure of an action, to determine the future behavior of the system, for example, to initiate a retrial of the action. To specify and analyze such system behavior and the impact of feedback on timing properties, we introduce an extension to SMPLS with discrete-event feedback. In this extension, we model the plant behavior with system modes and capture the timing of discrete-event feedback emission from plant to SC in the mode matrices. Furthermore, we use I/O automata to capture how the SC responds to discrete-event feedback with corresponding mode sequences of the SMPLS. We define the semantics of SMPLS with events using new state-space equations that are akin to classical SMPLS with dynamic state-vector sizes. To analyze the extended models, we formulate a transformation from SMPLS with events to classical SMPLS with equivalent semantics and properties such that performance properties can be analyzed using existing techniques. Our approach enables the specification of discrete-event feedback from the plant to the SC and its performance analysis. We demonstrate our approach by specifying and analyzing the makespan of a flexible manufacturing system

Control of platooned vehicles in presence of traffic shock waves

Vehicle platooning has been attracting attention recently because of its ability to improve road capacity, safety and fuel efficiency. Vehicles communicate using Vehicle-toVehicle (V2V) wireless communication, making their status (acceleration, position, etc.) available to other vehicles. Shock waves, i.e. zones of reduced traffic speed that propagate upstream, are a well known emergent traffic phenomenon. Since vehicles entering such a zone need to decelerate sharply, shock waves cause a deterioration of fuel economy, driving comfort, and safety. While typically caused by bad driving behavior, recent studies have shown that it is possible to diminish or dissipate shock waves by applying certain good driving behavioral patterns. In this work, we use the information about the traffic situation to adapt the reference speed profile of the platoon we control, in order to mitigate the effect of a shock wave coming from downstream. The platoon leader receives the velocity of the vehicles downstream of the platoon and distance gap between them using V2V communication and it computes the shock wave speed. We show that by doing this we reduce the fuel consumption of the vehicles in the platoon, and improve the traffic situation by helping dissipate the shock wave. We validate our results using microscopic models with the help of a toolchain composed of Matlab, and the SUMO traffic simulator