An Efficient Hierarchical Scheduling Framework for the Automotive Domain
نویسندگان
چکیده
Modern real-time systems have become exceedingly complex. A typical car is controlled by over 100 million lines of code executing on close to 100 Electronic Control Units (ECU). With more and more functions being implemented in software, the traditional approach of implementing each function (such as engine control, ABS, windows control) on a dedicated ECU is no longer viable, due to increased manufacturing costs, weight, power consumption, and decreased reliability and serviceability (Nolte et al., 2009). With the ECUs having increasingly more processing power, it has become feasible to integrate several functions on a single ECU. However, this introduces the challenge of supporting independent and concurrent development and analysis of individual functions which are later to be integrated on a shared platform. A popular approach in the industry and literature is component based engineering, where the complete system is divided into smaller software components which can be developed independently. The Automotive Open System Architecture (AUTOSAR) (AUTOSAR, 2011) standard is an example of such an approach in the automotive domain. It relies on a formal specification of component interfaces to verify the functional properties of their composition. Many functions in automotive systems, however, also have real-time constraints, meaning that their correct behavior is not only dependent on their functional correctness but also their temporal correctness. AUTOSAR does not provide temporal isolation between components. Verifying the temporal properties of an integrated system requires complete knowledge of all functions comprising the components mapped to the same ECU, and therefore violates the requirement for independent development and analysis.
منابع مشابه
A Hierarchical Production Planning and Finite Scheduling Framework for Part Families in Flexible Job-shop (with a case study)
Tendency to optimization in last decades has resulted in creating multi-product manufacturing systems. Production planning in such systems is difficult, because optimal production volume that is calculated must be consistent with limitation of production system. Hence, integration has been proposed to decide about these problems concurrently. Main problem in integration is how we can relate pro...
متن کاملA Lean Manufacturing Roadmap for an Automotive Body Assembly Line within Axiomatic Design Framework
In this paper we are to present a practical application of Axiomatic Design (AD) methodology, as a roadmap to lean production, in redesigning a car body assembly line. Axiomatic Design theory provides a framework to simplify the whole problem. According to the AD principles, a hierarchical structure has been developed. The developed structure originated in lean manufacturing principles and exis...
متن کاملAn application of principal component analysis and logistic regression to facilitate production scheduling decision support system: an automotive industry case
Production planning and control (PPC) systems have to deal with rising complexity and dynamics. The complexity of planning tasks is due to some existing multiple variables and dynamic factors derived from uncertainties surrounding the PPC. Although literatures on exact scheduling algorithms, simulation approaches, and heuristic methods are extensive in production planning, they seem to be ineff...
متن کاملAn integrated approach for scheduling flexible job-shop using teaching–learning-based optimization method
In this paper, teaching–learning-based optimization (TLBO) is proposed to solve flexible job shop scheduling problem (FJSP) based on the integrated approach with an objective to minimize makespan. An FJSP is an extension of basic job-shop scheduling problem. There are two sub problems in FJSP. They are routing problem and sequencing problem. If both the sub problems are solved simultaneously, t...
متن کاملAn Efficient Framework for Accurate Arterial Input Selection in DSC-MRI of Glioma Brain Tumors
Introduction: Automatic arterial input function (AIF) selection has an essential role in quantification of cerebral perfusion parameters. The purpose of this study is to develop an optimal automatic method for AIF determination in dynamic susceptibility contrast magnetic resonance imaging (DSC-MRI) of glioma brain tumors by using a new preprocessing method.Material and Methods: For this study, ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2012