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The group‐based preemptive scheduling provides a flexible mechanism to define the preemptive relations between tasks. However, this scheduling scheme together with a resource access synchronization protocol and the requirements of fault tolerance makes the predication of a real‐time system’s behaviors more difficult than traditional scheduling scheme. The major contribution of this work is an algorithm to calculate the worstcase response time for tasks under the group‐based preemptive scheduling. This algorithm supports both the fault‐free and the primary‐alternative fault‐tolerance scheduling mechanism. Moreover, a method to calculate the minimum allowed time between two consecutive faults is also introduced. The algorithm has been implemented in a time analysis tool and integrated into a system development platform, which is compatible with the OSEK/VDX operating system standard, to verify the temporal property in the early system design step.

The main purpose of the paper is timing analysis of mixed critical applications on the multicore system to identify an efficient task scheduling mechanism to achieve three main objectives improving schedulability, achieving reliability and minimizing the number of cores used. The rise in transient faults in embedded systems due to the use of low-cost processors has led to the use of fault-tolerant scheduling and mapping techniques.

The paper opted for a simulation-based study. The simulation of mixed critical applications, like air traffic control systems and synthetic workloads, is carried out using a litmus-real time testbed on an Ubuntu machine. The heuristic algorithms for task allocation based on utilization factors and task criticalities are proposed for partitioned approaches with multiple objectives.

Both partitioned earliest deadline first (EDF) with the utilization-based heuristic and EDF-virtual deadline (VD) with a criticality-based heuristic for allocation works well, as it schedules the air traffic system with a 98% success ratio (SR) using only three processor cores with transient faults being handled by the active backup of the tasks. With synthetic task loads, the proposed criticality-based heuristic works well with EDF-VD, as the SR is 94%. The validation of the proposed heuristic is done with a global and partitioned approach of scheduling, considering active backups to make the system reliable. There is an improvement in SR by 11% as compared to the global approach and a 17% improvement in comparison with the partitioned fixed-priority approach with only three processor cores being used.

The simulations of mixed critical tasks are carried out on a real-time kernel based on Linux and are generalizable in Linux-based environments.

The rise in transient faults in embedded systems due to the use of low-cost processors has led to the use of fault-tolerant scheduling and mapping techniques.

This paper fulfills an identified need to have multi-objective task scheduling in a mixed critical system. The timing analysis helps to identify performance risks and assess alternative architectures used to achieve reliability in terms of transient faults.

In modern integrated modular avionics (IMA), it plays an important role to guarantee safety and reliability of the system. The safety and reliability of communication scheduling plays a crucial role in this IMA platforms-based network system. To verify the safety and reliability of the communication scheduling in this network, sufficient and typical test data must be generated to input into the network, obtain and evaluate the corresponding output.

To generate communication scheduling data, this paper presents an iterative communication scheduling data generation algorithm for a configured network of IMA platforms. First, the algorithm generates all possible communication schedules for the first timestamp. Then, constraint is introduced to decrease the quantity of communication schedules to improve the efficiency. The communication schedules are gradually extended to the second timestamp until the final timestamp, i.e. length of communication scheduling sequence.

To verify the efficiency and feasibility of the algorithm, a model is built based on the architecture analysis and design language (AADL) by mapping the correlation time of generated communication scheduling data into task properties. Schedulability is analyzed by loading this model into AADL Inspector. The simulation result illustrates that the proposed algorithm is efficient and feasible.

The proposed method can provide data support for communication scheduling test for the network of IMA platforms.

A constraint-based iterative communication scheduling data generation algorithm is proposed for the network of IMA platforms automatically.

In recent years, it is imperative to establish the structure of manufacturing industry in the context of smart factory. Due to rising demand for exchange of information with various devices, and huge number of sensor nodes, the industrial wireless networks (IWNs) face network congestion and inefficient task scheduling. For this purpose, software-defined network (SDN) is the emerging technology for IWNs, which is integrated into cognitive industrial Internet of things for dynamic task scheduling in the context of industry 4.0.

In this paper, the authors present SDN based dynamic resource management and scheduling (DRMS) for effective devising of the resource utilization, scheduling, and hence successful transmission in a congested medium. Moreover, the earliest deadline first (EDF) algorithm is introduced in authors’ proposed work for the following criteria’s to reduce the congestion in the network and to optimize the packet loss.

The result shows that the proposed work improves the success ratio versus resource usage probability and number of nodes versus successful joint ratio. At last, the proposed method outperforms the existing myopic algorithms in terms of query response time, energy consumption and success ratio (packet delivery) versus number of increasing nodes, respectively.

The authors proposed a priority based scheduling between the devices and it is done by the EDF approach. Therefore, the proposed work reduces the network delay time and minimizes the overall energy efficiency.

The purpose of this paper is to make performance improvements and timely critical execution enhancements for operational flight program (OFP). The OFP is core software of autonomous control system of small unmanned helicopter.

In order to meet the time constraints and enhance control application performance, two major improvements were done at real‐time operating system (RTOS) kernel. They are thread scheduling algorithm and lock‐free thread message communication mechanism. Both of them have a direct relationship with system efficiency and indirect relationship with helicopter control application execution stability through improved deadline keeping characteristics.

In this paper, the suitability of earliest deadline first (EDF) scheduling algorithm and non‐blocking buffer (NBB) mechanism are illustrated with experimental and practical applications. Results of this work show that EDF contributes around 15 per cent finer‐timely execution and NBB enhances kernel's responsiveness around 35 per cent with respect to the number of thread context switch and CPU utilization. These apply for OFP implemented over embedded configurable operating system (eCos) RTOS on x86 architecture‐based board.

This paper illustrates an applicability of deadline‐based real‐time scheduling algorithm and lock‐free kernel communication mechanism for performance enhancement and timely critical execution of autonomous unmanned aerial vehicle control system.

This paper illustrates a novel approach to extend RTOS kernel modules based on unmanned aerial vehicle control application execution scenario. Lock‐free thread communication mechanism is implemented, and tested for applicability at RTOS. Relationship between UAV physical and computation modules are clearly illustrated via an appropriate unified modelling language (UML) collaboration and state diagrams. As experimental tests are conducted not only for a particular application, but also for various producer/consumer scenarios, these adequately demonstrate the applicability of extended kernel modules for general use.

Underwater shuttle is widely used in scenarios of deep sea transportation and observation. As messages are transmitted via the limited network, high transmission time-delay often leads to information congestion, worse control performance and even system crash. Moreover, due to the nonlinear issues with respect to shuttle’s heading motion, the delayed transmission also brings extra challenges. Hence, this paper aims to propose a co-designed method, for the purpose of network scheduling and motion controlling.

First, the message transmission scheduling is modeled as an optimization problem via adaptive genetic algorithm. The initial transmission time and the genetic operators are jointly encoded and adjusted to balance the payload in network. Then, the heading dynamic model is compensated for the delayed transmission, in which the parameters are unknown. Therefore, the adaptive sliding mode controller is designed to online estimate the parameters, for enhancing control precision and anti-interference ability. Finally, the method is evaluated by simulation.

The messages in network are well scheduled and the time delay is thus reduced, which increases the quality of service in network. The unknown parameters are estimated online, and the quality of control is enhanced. The control performance of the shuttle control system is thus increased.

The paper is the first to apply co-design method of message scheduling and attitude controlling for the underwater unmanned vehicle, which enhaces the control performance of the network control system.

The purpose of this article is to provide conceptual provocation in the context of collective expertise on the identification of time‐space constraints – a conceptual provocation that pushes understandings of routines and practices and the tensions that exist around schedulability and social efficiency when the collective dimension of all social action is ignored by social policy, be it in the developing or developed context.

The article examines time‐space constraints in three distinctive environments – low‐income children in urban Ghana, women's space in the North West Frontier province of Pakistan and low‐income elderly sick within the National Health system of the UK. A case study approach is taken.

The analysis draws attention to the impact of mobility constraints on dignity and social functioning in policy environments that maximise rather than address and redress such constraints.

A time‐space constraint approach leads towards more fundamental practices of process investigation rather than a parading of apparent patterns of outcomes, and this in turn leads towards a practice of process correction. There are significant policy implications from this research.

Identifying time‐space constraints represents a woefully neglected element of the development discourse, and it is time for the correction of this neglect with detailed analysis of time‐space constraints across the range of social action. This paper addresses this.

With the continuous technological development of automated driving and expansion of its application scope, the types of on-board equipment continue to be enriched and the computing capabilities of on-board equipment continue to increase and corresponding applications become more diverse. As the applications need to run on on-board equipment, the requirements for the computing capabilities of on-board equipment become higher. Mobile edge computing is one of the effective methods to solve practical application problems in automated driving.

In this study, in accordance with practical requirements, this paper proposed an optimal resource management allocation method of autonomous-vehicle-infrastructure cooperation in a mobile edge computing environment and conducted an experiment in practical application.

The design of the road-side unit module and its corresponding real-time operating system task coordination in edge computing are proposed in the study, as well as the method for edge computing load integration and heterogeneous computing. Then, the real-time scheduling of highly concurrent computation tasks, adaptive computation task migration method and edge server collaborative resource allocation method is proposed. Test results indicate that the method proposed in this study can greatly reduce the task computing delay, and the power consumption generally increases with the increase of task size and task complexity.

The results showed that the proposed method can achieve lower power consumption and lower computational overhead while ensuring the quality of service for users, indicating a great application prospect of the method.

The purpose of this paper is to focus on the reference model of a grid-like supply network that enables formulation of delivery routing and scheduling problems in the context of the periodic vehicle routing problem.

The conditions for seamless (collision-free) synchronization of periodically executed local transport processes presented in this paper guarantee cyclic execution of supply processes, thereby preventing traffic flow congestion.

Systems that satisfy this characteristic, cyclic deliveries executed along supply chains are given and what is sought is the number of vehicles needed to operate the local transport processes in order to ensure delivery from and to specific loading/unloading points on given dates. Determination of sufficient conditions guaranteeing the existence of feasible solutions that satisfy these constraints makes it possible to solve the considered class of problems online.

The computer experiments reported in this paper show the possibilities of practical application of the proposed approach in the construction of decision support systems for food supply chain management.

The aim of the present work is to develop a methodology for the synthesis of regularly structured supply networks that would ensure fixed cyclic execution of local transport processes. The proposed methodology, which implements sufficient conditions for the synchronization of local cyclic processes, allows one to develop a method for rapid prototyping of supply processes that satisfies the time windows constraints given.

Proposes a heuristic iterative scheduling algorithm for the resource constrained project scheduling problem. Considers a general model where activities are represented by multiple operating modes and each operating mode is constituted of different activity durations and resource requirements. The performance measures considered are the minimization of project duration and the maximization of net present value (NPV). In the cash flow model assumed, activity expenditures take place at their start times and the project payment is made on its completion. The iterative scheduling algorithm consists of forward/ backward scheduling passes, where consecutive scheduling passes are linked by updated activity time windows. The iterative algorithm is supported by a conflict‐based activity selection technique called local constraint based analysis (LCBA). A considerable amount of improvement in both performance criteria is observed when the results of the iterative algorithm are compared with the results given by the initial forward schedule.