Abstract

We have developed a new traffic measuring tool and applied it to the real-time simulation of a network. It monitors IP traffic on an ATM link and continuously transfers the length and timestamp of each IP packet to a post-processing system. The post-processing system receives the data, estimates the cell's arrival epoch at the transmission queue of the ATM link, and simulates the queueing behavior on-line if conditions differ from those of the actual system. The measuring tool and real-time simulation rep resent a new approach to traffic engineering. A new estimation problem, the arrival sequence estimation, is shown and some algorithms are proposed and evaluated. Document type: Part of book or chapter of book

Abstract

When developing real-time systems, the worst-case execution time (WCET) is a commonly used measure for predicting and analyzing program and system timing behavior. Such estimates should preferrably be provided by static WCET analysis tools. Their analysis is made difficult by features of common processors, such as pipelines and caches.This paper examines the properties of single-issue in-order pipelines, based on a mathematical model of temporal constraints. The key problem addressed is to determine the distance (measured in number of subsequent instructions) over which an instruction can affect the timing behavior of other instructions, and when this effect must be considered in static WCET analysis. We characterize classes of pipelines for which static analysis can safely ignore effects longer than some arbitrary threshold. For other classes of pipelines, pipeline effects can propagate across arbitrary numbers of instructions, making it harder to design safe and precise analysis methods.Based on our results, we discuss how to construct safe WCET analysis methods. We also prove when it is correct to use localworst-case approximations to construct an overall WCET estimate. Document type: Part of book or chapter of book

Abstract

Processor simulators are important parts of processor design toolsets in which they are used to verify and evaluate the properties of the designed processors. While simulating architectures with independent function unit pipelines using simulation techniques that avoid the overhead of instruction bit-string interpretation, such as compiled simulation, the simulation of function unit pipelines can become one of the new bottlenecks for simulation speed. This paper evaluates several resource conflict detection models, commonly used in compiler instruction scheduling, in the context of function unit pipeline simulation. The evaluated models include the conventional reservation table based-model, the dynamic collision matrix model, and an finite state automata (FSA) based model. In addition, an improvement to the simulation initialization time by means of lazy initialization of states in the FSA-based approach is proposed. The resulting model is faster to initialize and provides comparable simulation speed to the actively initialized FSA. Document type: Part of book or chapter of book

Abstract

Part 3: Computational Intelligence and Algorithms; International audience; Computational technologies under the domain of intelligent systems are expected to help the rapidly increasing traffic congestion problem in recent traffic management. Traffic management requires efficient and accurate forecasting models to assist real time traffic control systems. Researchers have proposed various computational approaches, especially in short-term traffic flow forecasting, in order to establish reliable traffic patterns models and generate timely prediction results. Forecasting models should have high accuracy and low computational time to be applied in intelligent traffic management. Therefore, this paper aims to evaluate recent computational modeling approaches utilized in short-term traffic flow forecasting. These approaches are evaluated by real-world data collected on the British freeway (M6) from 1st to 30th November in 2014. The results indicate that neural network model outperforms generalized additive model and autoregressive integrated moving average model on the accuracy of freeway traffic forecasting. Document type: Part of book or chapter of book

Abstract

To guarantee timeliness in hard real-time systems the knowledge of the worst-case execution time (WCET) for its time-critical tasks is mandatory. Accurate and correct WCET analysis for modern processor is a quite complex problem. Path analysis is required to identify a minimal set of possible execution paths. Further, the modeling of a processor’s internal states for features like caches or pipelines requires to consider possible interferences of these features. Document type: Part of book or chapter of book

Abstract

Micro-simulations for transport planning are becoming increasingly important in traffic simulation, traffic analysis, and traffic forecasting. In the last decades the shift from using typically aggregated data to more detailed, individual based, complex data (e.g. GPS tracking) andthe continuously growing computer performance on fixed price level leads to the possibility of using microscopic models for large scale planning regions. This chapter presents such a micro-simulation. The work is part of the research project MATSim (Multi Agent Transport Simulation, http://matsim.org). In the chapter here the focus lies on design and implementation issues as well as on computational performance of different parts of the system. Based on a study of Swiss daily traffic – ca. 2.3 million individuals using motorized individual transport producing about 7.1 million trips, assigned to a Swiss network model with about 60,000 links, simulated and optimized completely time-dynamic for a complete workday – it is shown that the system is able to generate those traffic patterns in about 36 hours computation time. Document type: Part of book or chapter of book

Abstract

The article considers the active safety system of road freight transport. The stereoscopic computer vision is the core of the system. The article also describes the major algorithms of active safety and the accuracy characteristics of algorithms’ application. Document type: Part of book or chapter of book

Abstract

Part 2: CONTROL SYSTEMS SECURITY International audience Industrial control systems are cyber-physical systems that supervise and control physical processes in critical infrastructures such as electric grids, water and wastewater treatment plants, oil and natural gas pipelines, transportation systems and chemical plants and refineries. Leveraging the stable and persistent control flow communications patterns in industrial control systems, this chapter proposes an innovative control system fingerprinting methodology that analyzes industrial control protocols to capture normal behavior characteristics. The methodology can be used to identify specific physical processes and control system components in industrial facilities and detect abnormal behavior. An experimental testbed that incorporates real systems for the cyber domain and simulated systems for the physical domain is used to validate the methodology. The experimental results demonstrate that the fingerprinting methodology holds promise for detecting anomalies in industrial control systems and cyber-physical systems used in the critical infrastructure. Document type: Part of book or chapter of book

Abstract

Pipeline morphing is a simple but effective technique for reconfiguring pipelined FPGA designs at run time. By overlapping computation and reconfiguration, the latency associated with emptying and refilling a pipeline can be avoided. We show how morphing can be applied to linear and mesh pipelines at both word-level and bit-level, and explain how this method can be implemented using Xilinx 6200 FPGAs. We also present an approach using morphing to map a large virtual pipeline onto a small physical pipeline, and the trade-offs involved are discussed. Document type: Part of book or chapter of book