Dynamic constraint and objective generation approach for real-time train rescheduling model under human-computer interaction

Real-time train rescheduling plays a vital role in railway transportation as it is crucial for maintaining punctuality and reliability in rail operations.In this paper,we propose a rescheduling model that incorporates constraints and objectives generated through human-computer interaction.This approach ensures that the model is aligned with practical requirements and daily operational tasks while facilitating iterative train rescheduling.The dispatcher’s empirical knowledge is integrated into the train rescheduling process using a human-computer interaction framework.We introduce six interfaces to dynamically construct constraints and objectives that capture human intentions.By summarizing rescheduling rules,we devise a rule-based conflict detection-resolution heuristic algorithm to effectively solve the formulated model.A series of numerical experiments are presented,demonstrating strong performance across the entire system.Furthermore,theflexibility of rescheduling is enhanced through secondary analysis-driven solutions derived from the outcomes of humancomputer interactions in the previous step.This proposed interaction method complements existing literature on rescheduling methods involving human-computer interactions.It serves as a tool to aid dispatchers in identifying more feasible solutions in accordance with their empirical rescheduling strategies.

Real-time scheduling strategy for microgrids considering operation interval division of DGs and batteries

Real-time scheduling as an on-line optimization process must output dispatch results in real time. However, the calculation time required and the economy have a trade-off relationship. In response to a real-time scheduling problem, this paper proposes a real-time scheduling strategy considering the operation interval division of distributed generators(DGs) and batteries in the microgrid. Rolling scheduling models, including day-ahead scheduling and hours-ahead scheduling, are established, where the latter considers the future state-of-charge deviations. For the real-time scheduling, the output powers of the DGs are divided into two intervals based on the ability to track the day-ahead and hours-ahead schedules. The day-ahead and hours-ahead scheduling ensure the economy, whereas the real-time scheduling overcomes the timeconsumption problem. Finally, a grid-connected microgrid example is studied, and the simulation results demonstrate the effectiveness of the proposed strategy in terms of economic and real-time requirements.

Long-release-interval-first real-time scheduling algorithm and its schedulability test

To fulfill the requirements for hybrid real-time system scheduling, a long-release-interval-first （LRIF） real-time scheduling algorithm is proposed. The algorithm adopts both the fixed priority and the dynamic priority to assign priorities for tasks. By assigning higher priorities to the aperiodic soft real-time jobs with longer release intervals, it guarantees the executions for periodic hard real-time tasks and further probabilistically guarantees the executions for aperiodic soft real-time tasks. The schedulability test approach for the LRIF algorithm is presented. The implementation issues of the LRIF algorithm are also discussed. Simulation result shows that LRIF obtains better schedulable performance than the maximum urgency first （MUF） algorithm, the earliest deadline first （EDF） algorithm and EDF for hybrid tasks. LRIF has great capability to schedule both periodic hard real-time and aperiodic soft real-time tasks.

SWARM INTELLIGENCE BASED DYNAMIC REAL-TIME SCHEDULING APPROACH FOR SEMICONDUCTOR WAFER FAB

Based on the analysis of collective activities of ant colonies, the typicalexample of swarm intelligence, a new approach to construct swarm intelligence basedmulti-agent-system (SMAS) for dynamic real-time scheduling for semiconductor wafer fab is proposed.The relevant algorithm, pheromone-based dynamic real-time scheduling algorithm (PBDR), is given.MIMAC test bed data set mini-fab is used to compare PBDR with FIFO (first in first out),SRPT(shortest remaining processing time) and CR(critical ratio) under three different release rules,i.e. deterministic rule, Poisson rule and CONWIP (constant WIP). It is shown that PBDR is prior toFIFO, SRPT and CR with better performance of cycle time, throughput, and on-time delivery,especially for on-time delivery performance.

A Model Predictive Scheduling Algorithm inReal-Time Control Systems

Abstract-The ineffective utilization of power resources has attracted much attention in current years. This paper proposes a real-time distributed load scheduling algorithm considering constraints of power supply. Firstly, an objective function is designed based on the constraint, and a base load forecasting model is established when aggregating renewable generation and non-deferrable load into a power system, which aims to transform the problem of deferrable loads scheduling into a distributed optimal control problem. Then, to optimize the objective function, a real-time scheduling algorithm is presented to solve the proposed control problem. At every time step, the purpose is to minimize the variance of differences between power supply and aggregate load, which can thus ensure the effective utilization of power resources. Finally, simulation examples are provided to illustrate the effectiveness of the proposed algorithm.

Application of predictive control scheduling method to real-time periodic control tasks overrun

Based on the abort strategy of fixed periods, a novel predictive control scheduling methodology was proposed to efficiently solve overrun problems. By applying the latest control value in the prediction sequences to the control objective, the new strategy was expected to optimize the control system for better performance and yet guarantee the schedulability of all tasks under overrun. The schedulability of the real-time systems with p-period overruns was analyzed, and the corresponding stability criteria was given as well. The simulation results show that the new approach can improve the performance of control system compared to that of conventional abort strategy, it can reduce the overshoot and adjust time as well as ensure the schedulability and stability.

FEL-H Robust Control Real-Time Scheduling

The existing scheduling algorithms cannot adequately support modern embedded real-time applications. An important challenge for future research is how to model and introduce control mechanisms to real-time systems to improve real-time performance, and to allow the system to adapt to changes in the environment, the workload, or to changes in the system architecture due to failures. In this paper, we pursue this goal by formulating and simulating new real-time scheduling models that enable us to easily analyse feedback scheduling with various constraints, overload and disturbance, and by designing a robust, adaptive scheduler that responds gracefully to overload with robust H∞ and feedback error learning control.

Real-time online rescheduling for multiple agile satellites with emergent tasks

The emergent task is a kind of uncertain event that satellite systems often encounter in the application process.In this paper,the multi-satellite distributed coordinating and scheduling problem considering emergent tasks is studied.Due to the limitation of onboard computational resources and time,common online onboard rescheduling methods for such problems usually adopt simple greedy methods,sacrificing the solution quality to deliver timely solutions.To better solve the problem,a new multi-satellite onboard scheduling and coordinating framework based on multi-solution integration is proposed.This method uses high computational power on the ground and generates multiple solutions,changing the complex onboard rescheduling problem to a solution selection problem.With this method,it is possible that little time is used to generate a solution that is as good as the solutions on the ground.We further propose several multi-satellite coordination methods based on the multi-agent Markov decision process(MMDP)and mixed-integer programming(MIP).These methods enable the satellite to make independent decisions and produce high-quality solutions.Compared with the traditional centralized scheduling method,the proposed distributed method reduces the cost of satellite communication and increases the response speed for emergent tasks.Extensive experiments show that the proposed multi-solution integration framework and the distributed coordinating strategies are efficient and effective for onboard scheduling considering emergent tasks.

Broadcast Scheduling Strategy Based on the Priority of Real-Time Data in a Mobile Environment

Data broadcast is an important data dissemination approach in mobile environment. On broadcast channel, scalability and efficiency of data transmission are satisfied. In a mobile environment, there exists a kind of real-time database application in which both the transactions and data can have their timing constraints and priorities of different levels. In order to meet the requirement of real-time data disseminating and retrieving, a broadcast scheduling strategy HPF-ED F (Highest Priority First with Earlier Deadline and Frequency) is proposed under the BoD (Broadcast on Demand) model. Using the strategy, data items are scheduled according to their priority the transaction imposed on them or system set for them. The strategy also considers other characteristics of data items such as deadline and popularity of data. The extensive simulation experiments have been conducted to evaluate the performance of the proposed algorithm. Results show that it can achieve excellent performance compared with existing strategies.

An Adaptive Genetic Algorithm for Multiprocessor Real-time Task Scheduling

Real-time task scheduling is of primary significance in multiprocessor systems.Meeting deadlines and achieving high system utilization are the two main objectives of task scheduling in such systems.In this paper,we represent those two goals as the minimization of the average response time and the average task laxity.To achieve this,we propose a genetic-based algorithm with problem-specific and efficient genetic operators.Adaptive control parameters are also employed in our work to improve the genetic algorithms' efficiency.The simulation results show that our proposed algorithm outperforms its counterpart considerably by up to 36% and 35% in terms of the average response time and the average task laxity,respectively.

Energy-Efficient Deterministic Fault-Tolerant Scheduling for Embedded Real-Time Systems

By combining fault-tolerance with power management, this paper developed a new method for aperiodic task set for the problem of task scheduling and voltage allocation in embedded real-time systems. The scbedulability of the system was analyzed through checkpointing and the energy saving was considered via dynamic voltage and frequency scaling. Simulation results showed that the proposed algorithm had better performance compared with the existing voltage allocation techniques. The proposed technique saves 51.5% energy over FT-Only and 19.9% over FT ＋ EC on average. Therefore, the proposed method was more appropriate for aperiodic tasks in embedded real-time systems.

Packet Scheduling Algorithm for Real-Time Services in Broadband WMAN

Packet scheduling algorithm is the key technology to guarantee Quality of Service (QoS) and balance the fairness between users in broadband Wireless Metropolitan Area Network (WMAN). Based on the research of Proportional Fairness (PF) algorithm and Modified Largest Weighted Delay First (M-LWDF) algorithm, a new packet scheduling algorithm for real-time services in broadband WMAN, called Enhanced M-LWDF (EM-LWDF), was proposed. The algorithm phases in new information to measure the load of service queues and updates the state parameters in real-time way, which remarkably improves system performance.Simulation results show that comparing with M-LWDF algorithm, the proposed algorithm is advantageous in performances of queuing delay and fairness while guaranteeing system throughput.

Modeling and Analysis of Scheduling for Distributed Real-time Embedded Systems

Aimed at the deficiencies of resources based time Petri nets （RBTPN） in doing scheduling analysis for distributed real-time embedded systems, the assemblage condition of complex scheduling sequences is presented to easily compute scheduling length and simplify scheduling analysis. Based on this, a new hierarchical RBTPN model is proposed. The model introduces the definition of transition border set, and represents it as an abstract transition. The abstract transition possesses all resources of the set, and has the highest priority of each resource; the cxecution time of abstract transition is the longest time of all possible scheduling sequences. According to the characteristics and assemblage condition of RBTPN, the refinement conditions of transition border set are given, and the conditions ensure the correction of scheduling analysis. As a result, it is easy for us to understand the scheduling model and perform scheduling analysis.

STUDY ON THE DYNAMIC SCHEDULING IN FMS REAL-TIME PRODUCTION ENVIRONMENT

A dynamic database based dynamic scheduling system is proposed.As the schedule is being preformed, the scheduling task data in the dynamic database is updated timely.Genetic algorithm (GA) is employed for generating optimised production plan quickly and easily in response to changes on the shop floor. The current status of the shop is considered while rescheduling, and new plan is used in conjunction with the existing schedule to improve the effeciency of flexble manufacturing systems. Simulation results demonstrate the effectiveness of the proposed system.

An Efficient Real-Time Fault-Tolerant Scheduling Algorithm Based on Multiprocessor Systems

In the context of real-time fault-tolerant scheduling in multiprocessor systems, Primary-backup scheme plays an important role. A backup copy is always preferred to be executed as passive backup copy whenever possible because it can take the advantages of backup copy de-allocation technique and overloading technique to improve schedulability. In this paper, we propose a novel efficient fault-tolerant ratemonotonic best-fit algorithm efficient fault-tolerant rate-monotonic best-fit （ERMBF） based on multiprocessors systems to enhance the schedulability. Unlike existing scheduling algorithms that start scheduling tasks with only one processor. ERMBF pre-allocates a certain amount of processors before starting scheduling tasks, which enlarge the searching spaces for tasks. Besides, when a new processor is allocated, we reassign the task copies that have already been assigned to the existing processors in order to find a superior tasks assignment configuration. These two strategies are all aiming at making as many backup copies as possible to be executed as passive status. As a result, ERMBF can use fewer processors to schedule a set of tasks without losing real-time and fault-tolerant capabilities of the system. Simulation results reveal that ERMBF significantly improves the schedulability over existing, comparable algorithms in literature.

A sensor transaction scheduling algorithm for maintaining real-time data temporal validity

A new scheduling algorithm called deferrable scheduling with time slice exchange (DS-EXC) was proposed to maintain the temporal validity of real-time data. In DS-EXC, the time slice exchange method was designed to further defer the release time of transaction instances derived by the deferrable scheduling algorithm (DS-FP). In this way, more CPU time would be left for lower priority transactions and other transactions. In order to minimize the scheduling overhead, an off-line scheme was designed. In particular, the schedule for a transaction set is generated off-line until a repeating pattern is found, and then the pattern is used to construct the schedule on-line. The performance of DS-EXC was evaluated by sets of experiments. The results show that DS-EXC outperforms DS-FP in terms of increasing schedulable ratio. It also provides better performance under mixed workloads.

SET-MRTS:An Empirical Experiment Tool for Real-Time Scheduling and Synchronization

In the real-time scheduling theory,schedulability and synchronization analyses are used to evaluate scheduling algorithms and real-time locking protocols,respectively,and the empirical synthesis experiment is one of the major methods to compare the performance of such analyses.However,since many sophisticated techniques have been adopted to improve the analytical accuracy,the implementation of such analyses and experiments is often time-consuming.This paper proposes a schedulability experiment toolkit for multiprocessor real-time systems(SET-MRTS),which provides a framework with infrastructures to implement the schedulability and synchronization analyses and the deployment of empirical synthesis experiments.Besides,with well-designed peripheral components for the input and output,experiments can be conducted easily and flexibly on SET-MRTS.This demonstration further proves the effectiveness of SET-MRTS in both functionality and availability.

Scheduling transactions in mobile distributed real-time database systems

A DMVOCC-MVDA （distributed multiversion optimistic concurrency control with multiversion dynamic adjustment） protocol was presented to process mobile distributed real-time transaction in mobile broadcast environments. At the mobile hosts, all transactions perform local pre-validation. The local pre-validation process is carried out against the committed transactions at the server in the last broadcast cycle. Transactions that survive in local pre-validation must be submitted to the server for local final validation. The new protocol eliminates conflicts between mobile read-only and mobile update transactions, and resolves data conflicts flexibly by using multiversion dynamic adjustment of serialization order to avoid unnecessary restarts of transactions. Mobile read-only transactions can be committed with no-blocking, and respond time of mobile read-only transactions is greatly shortened. The tolerance of mobile transactions of disconnections from the broadcast channel is increased. In global validation mobile distributed transactions have to do check to ensure distributed serializability in all participants. The simulation results show that the new concurrency control protocol proposed offers better performance than other protocols in terms of miss rate, restart rate, commit rate. Under high work load （think time is ls） the miss rate of DMVOCC-MVDA is only 14.6%, is significantly lower than that of other protocols. The restart rate of DMVOCC-MVDA is only 32.3%, showing that DMVOCC-MVDA can effectively reduce the restart rate of mobile transactions. And the commit rate of DMVOCC-MVDA is up to 61.2%, which is obviously higher than that of other protocols.

An Automatic Testing System of Scheduling Strategies in Real-Time UNIX

This paper proposes a formal model of the automatic testing system for scheduling strategies in real-time UNIX and describes the algorithm of the key part of the system. The model of the system is an important technology of the automatization of software development. According to the model presented in the paper, many different kinds of automatic testing systems can be designed and developed easily. At the end of the paper, the prototype proves the feasibility of the model and design.

Scheduling Non-stationary Bursts of Real-time and Non-real-time Traffic in ATM Networks

The problem of scheduling real time and non real time traffic in an ATM switch multiplexor when bursts of either type of traffic occur is studied. The scheduling algorithms studied are: Queue Length Threshold (QLT) and Minimum Laxity Threshold (MLT). Analytic results based on Markov Chains are used. In addition the results are compared with an optimal (but impractical) scheduling determined via dynamic programming. Dynamic programming is used in this paper to show that MLT gives a near optimal performance trade off between real time and non real time traffic for constant arrival rates. The trade off QLT allows is not close to optimal. For non real time bursts MLT still gives a close to optimal trade off. For real time bursts the trade off MLT allows between real time and non real time traffic is not as close to optimal, but even where the MLT trade off is not near optimal, the QLT trade off is much worse than the MLT trade off.