Scheduling in Real-Time Mobile Systems

In a mobile system, mobility refers to a change in position of a mobile object with respect to time and its reference point, whereas isolation means the isolation relationship between mobile objects under some scheduling policies. Inspired by event-based formal models and the ambient calculus, we first propose the two types of special events, entering and exiting an ambient, as movement events to model and analyze mobility. Based on mobility, we then introduce the notion of the isolation of mobile objects for ambients. To ensure the isolation, a priority policy needs to be used to schedule the movement of mobile objects. However, traditional scheduling policies focus on task scheduling and depend on the strong hypothesis: The scheduled tasks are independent—that is, the scheduled tasks do not affect each other. In a practical mobile system, mobile objects and ambients interact with each other. It is difficult to separate a mobile system into independent tasks. We finally present an automatic approach for generating a priority scheduling policy without considering the preceding assumption. The approach can guarantee the isolation of the mobile objects for ambients in a mobile system. Experiments demonstrate these results.

The traditional research on scheduling focuses on task scheduling and schedulability analysis in concurrent reactive systems. In this article, we dedicate ourselves to event-based scheduling. We first formally define an event-based scheduling policy and propose the notion of the correctness of a scheduling policy in terms of weak termination. Then we investigate the correctness of the decomposition of scheduling controls and finally obtain a decentralized scheduling method. The method can automatically decompose the scheduling policies of a concurrent reactive system into atomic scheduling policies. Every atomic scheduling policy corresponds to one subsystem. Each of the subsystems is a completely independent system, which may be developed and deployed independently. An experiment demonstrates these results that may help engineers to design correct and efficient schedule policies for a concurrent reactive system.

The purpose of the research was to improve the quality of information process control in the interaction of mobile object grouping. This proposal is based on developing and implementing new combined models with algorithms for optimal planning and scheduling of information processes during interaction among mobile objects. The proposed approach would guarantee the required level of aircraft maintenance at the airport. The novel aspect of the proposed solution is that it divides the spatially distributed task of selecting a plan and a schedule for information processes in mobile objects into two subtasks, describing the spatial and temporal features of the original task. The spatial component of the original problem is described as a static model. Using this model, the optimal distribution of information operations over the resources of mobile objects is carried out without binding these operations to time. The time component is described as a dynamic model, within which the information operations are tied to time and the corresponding resources. Examples of construction and research of synthesized plans and schedules are given. Abbreviations: DM, Dynamic model; FIFO, First-In First-Out; Gr, Grouping; HSC, Hardware and software complex; ITS, Intelligent Transport System; IP, Information Processes; MO, Mobile object; PC, Programmed control; SM, Static model; SMS, Special mathematic support; LDM, Logical-dynamic models

Aim. Threats of a non-physical nature have a significant effect on the security of intelligent transportation systems (ITS). They may have the form of unlawful interference in the development and implementation of ITS. The creation of a trusted framework for the development and implementation of ITS is examined as in the case of intelligent water transportation systems (IWTS). Problems. By decree of the President of the Russian Federation, ITS, telecommunications and security of information processing are among the priority areas of scientific and technological development. ITS technologies, as well as those involved in the creation of trusted, secure system and application software are among the most important critical high technologies. The operation of ITS involves wide use of computerised systems that implement the latest information and telecommunication technologies, automated and automatic control technologies, artificial intelligence that can pose security threats. ITS are to be developed and operated in a trusted environment. Methods. The paper used the methodology for ensuring the security of IWTS, development of secure hardware and software platforms for secure automated systems, methods of system analysis, dependability theory, information protection, and law. Results. The paper defines the problem of creating a trusted framework for the development and implementation of IWTS, the applicable terminology is developed. The author examined the effect of IWTS on the security of critical information infrastructure (CII) and national security, developed a model of relationships between the IWTS security domains taking into account threats of physical and non-physical origin. Examples of computer incidents within IWTS that caused consequences at the national and international levels are given. The composition of the IWTS facilities attributed to CII is defined, critical processes implemented by standard CII facilities as part of the IWTS are set forth. The author lists conceptual problems of IWTS security, defines the principles of creating a trusted framework for the development and implementation of IWTS. Conclusion. Ensuring the security of IWTS against modern threats requires solving a number of problems associated with the creation of a trusted framework for the development and implementation of IWTS. For the purpose of improving the timeliness and quality of their solution, the paper proposes an intuitive terminology that reflects the subject area and helps finding a common understanding of the security domain by experts from various industries. IWTS facilities have an effect on CII security and national security in general. That is taken into account in the model of relationships between IWTS security domains, demonstrated using cases of computer incidents within IWTS that caused consequences at the national and international level. Given the above, the paper lists IWTS facilities attributed to CII and sets forth examples of critical processes implemented by standard CII facilities as part of the IWTS. The defined list of conceptual IWTS security problems take into account the growing landscape of IWTS security threats that includes insecure software, hardware and software platforms, software and hardware systems and emerging technologies. When developing the principles for the creation of a trusted IWTS development and implementation framework, the author took into account the best practice of implementing the methodology for creating national secure hardware and software platforms of CII facilities that enables the creation of secure automated systems for various applications that are based on domestically-developed solutions. The examined matters are of a systemic nature, which allows using the findings in the development and implementation of ITS in other modes of transportation.

Introduction to intelligent transportation systems: need, operation, tools, intelligent transportation system (ITS) emergency vehicle scenario, and convolutional neural network model for intelligent transportation systems are covered in this chapter. In addition, the chapter discusses the need for intelligent transportation systems, how they work, and the critical stages of intelligent transportation systems. Aside from that, the chapter discusses intelligent transportation system patterns. This work discusses critical challenges in implementing an intelligent transportation system. This chapter discusses intelligent user services in an intelligent transportation system, and also discusses required architecture of vehicular networks/ITS. Big data and new technologies that make it easier and cheaper to collect, store, analyze, use, and share data from various sources have made this more accessible and cheaper. Because of the connected environment, new ways to control and manage transportation systems in real time are also emerging. These new methods of controlling and managing transportation systems will aid in the improvement of overall system performance. These systems use real-time data about traffic flow on city roads to assist people in avoiding traffic and maintaining a clean environment. There has been a significant increase in traffic monitoring, putting traditional transportation systems that rely on cloud computing under a lot of strain. In the last few years, the intelligent transportation system (ITS) has seen a lot of changes. Make trips more efficient: Many ITS technologies can assist people in reducing the number of unnecessary trips and increasing the number of trips taken by other modes. They can also help to reduce traffic congestion, reduce the need for foreign oil, and improve air quality.KeywordsIntelligent transportation system (ITS)Connected and autonomous vehicles (C/AV)Industrial Internet of things (IIoT)Machine learning-assisted intelligent traffic monitoring system (ML-ITMS)Machine learning (ML)

Recently, intelligent transportation systems (ITSs) have emerged. These systems can improve traditional transportation systems and provide traffic information to travelers. In the area of transportation, wireless sensor networks (WSNs) can replace the existing wired sensors and expensive traffic monitoring systems to mitigate the time and costs of installing such systems. However, accurate and on-time traffic information delivery is a major challenge, considering the energy constraints of sensor nodes. In this paper, we propose a two-tier architecture that includes a network of mobile objects (vehicles) in the upper layer and a hierarchical WSN in the bottom layer. Using this approach, a portion of loads on the low-power static sensor nodes can be transferred to mobile objects, such as powerful mobile devices. Moreover, to provide accurate and timely traffic information, a QoS-aware link cost function has been proposed and used for data transmission between the static sensor nodes. In addition, due to the mobility of the objects and the probability of losing packets in the mobile object tier, a reliable data forwarding mechanism has been proposed for this tier. In this mechanism, data packets are forwarded to the neighbors, which enhance the probability of the packets’ being received. The performance evaluation results indicate the effectiveness of the proposed architecture and data reporting mechanism for use in ITS applications.

SMART TSS: Defining transportation system behavior using big data analytics in smart cities

As a safety-critical issue in complex mobile systems, isolation requires two or more mobile objects not to appear in the same place simultaneously. To ensure such isolation, a scheduling policy is needed to control and coordinate the movement of mobile objects. Unfortunately, existing task scheduling theories fails in providing effective solutions, because it is hardly possible to decompose a complex mobile system into multiple independent tasks. To solve this problem, a more fine-grained event scheduling is proposed in this paper to generate scheduling policies which can ensure the isolation of mobile objects. After defining event scheduling based on event-based formal models called dependency structures, a new event scheduling theory for mobile systems is developed accordingly. Then an algorithm for generating an event scheduling policy is proposed to implement the required isolation. Simulation experiments are conducted to prove the result of our theoretical analysis and show the effectiveness and scalability of the approach.

Recent rapid development of intelligent transportation systems (ITS) makes it possible to improve the efficiency and reliability of transportation networks. Several articles have been presented regarding this topic in the Special Issue of Journal of Advanced Transportation. Wang and Khattak indicated that there is spatial heterogeneity in information acquisition and user decisions. Bekhor and colleagues showed that cellular phone technologies could be used to provide travel data for development of national travel demand model. Based on the deployment of automatic vehicle identification (AVI) technology in urban road network in Beijing, China, Feng and co-researchers proposed a particle filter method for vehicle trajectory reconstruction with the use of AVI and traffic count data. Yang and co-researchers proposed two proactive VSL control models for use on recurrently congested freeway segments. The embedded traffic flow relationships are adopted in the first proactive model to predict the evolution of congestion pattern and to optimize the speed limit on freeway segments with VSL. Using multi-source sensor data, Lu and researchers proposed a Kalman filter model for estimation of time-dependent origin?destination (OD) matrix that is a key input to the self-adaptive traffic control systems for real-time traffic management.

The design of intelligent expressway transportation system based on the Internet of Things is studied to improve the safety, travel experience, and operation management of expressway. The characteristics of the Internet of Things and cloud computing technology and its application on the expressway are analyzed, and the system design requirements of expressway intelligent transportation are understood. Besides, the overall architecture of the system is studied and designed. The IaaS layer, PaaS layer, and SaaS layer of the cloud platform are designed and deployed. The intelligent information system can make expressway highly informative. The simulation experiments reveal that the system only needs 120 milliseconds in accident processing time, which is far lower than the intelligent transportation system that only uses edge computing technology (201 milliseconds) and the intelligent transportation system that only uses cloud computing technology (443 milliseconds). Meanwhile, the accident response time is only 12 s, which is also superior to other models. In terms of cost-effectiveness, the monthly cost of the system is 7004 yuan, with a CPU utilization rate of 53%, demonstrating good cost-effectiveness and resource utilization efficiency. In addition, compared with the existing system, the average traffic congestion time has been reduced by 25%, the traffic accident rate has been reduced by 18%, and the accident rate has been reduced by 27%. The intelligent traffic system design of expressway, expressway safety, travel service, and operation management is effectively improved by researching the intelligent traffic system design of expressway.

This paper explores the integration of Artificial Intelligence Generated Content (AIGC), a rapidly evolving branch of generative AI, with Human-Machine intelligence (HMI) to enhance the functionality of Intelligent Transportation Systems (ITS). As transportation systems grow increasingly complex, adaptive decision-making becomes essential for interpreting vast streams of real-time data from vehicles, infrastructure, and users. AIGC plays a transformative role in optimizing traffic flow through dynamic routing and real-time traffic management, while human intelligence ensures these systems remain responsive to evolving real-world conditions. For safety, AIGC is used to simulate complex driving scenarios for autonomous vehicle training and detect traffic anomalies, with human oversight providing contextual decisions in ambiguous situations. For sustainability, AIGC supports data-driven strategies to reduce emissions and energy use, while human expertise ensures alignment with ethical and environmental goals. This synergy enhances real-time decision-making, improving both accuracy and adaptability across ITS scenarios. The paper presents a comprehensive review of core and supporting AIGC technologies and their applications across key ITS domains. Case studies and initiatives from industry leaders demonstrate practical implementations of AIGC-driven HMI collaboration. To guide future deployments, we propose a conceptual five-layer evaluation framework for assessing AIGC-HMI systems, encompassing functional performance, human interaction, explainability, ethical compliance, and robustness. We also address challenges such as legacy system integration, data privacy, model bias, and scalability. The paper concludes by outlining future research directions, emphasizing the need for scalable, interpretable, and ethically aligned AIGC models. This work contributes to the development of intelligent, adaptive, and trustworthy transportation systems.

Multicore processors deliver a higher throughput at lower power consumption than unicore processors. In the near future, they will thus be widely used in mobile real-time systems. There have been many research on energy-efficient scheduling of real-time tasks using DVS. These approaches must be modified for multicore processors, however, since normally all the cores in a chip must run at the same performance level. Thus, blindly adopting existing DVS algorithms that do not consider the restriction will result in a waste of energy. This article suggests Dynamic Repartitioning algorithm based on existing partitioning approaches of multiprocessor systems. The algorithm dynamically balances the task loads of multiple cores to optimize power consumption during execution. We also suggest Dynamic Core Scaling algorithm, which adjusts the number of active cores to reduce leakage power consumption under low load conditions. Simulation results show that Dynamic Repartitioning can produce energy savings of about 8 percent even with the best energy-efficient partitioning algorithm. The results also show that Dynamic Core Scaling can reduce energy consumption by about 26 percent under low load conditions.

The topic of the article is movement of a group of autonomous mobile objects during their functioning in the environments with stationary obstacles. The task is solved within the framework of the decentralized control systems. Thus the exchange of information between the mobile objects in a group is minimized. During the planning of the movement and control of the mobile objects the obstacles are transformed into repellers by means of synthesizable controls. The method of the potential fields and the method of control of the mobile objects with the use of unstable modes are the closest to the proposed method. The main difference of the developed method from the method of the potential fields is that a mobile object moves to the field of the forces depending not only on the relative positioning of the robot and an obstacle, but also on the additional dynamic variables. The dynamic way of formation of the repellent forces allows one to operate robots within the system of a decentralized control. The main difference of the offered approach from the method of position and trajectory control with the use of the unstable modes is the way of introduction of the unstable states. In the method of position and trajectory control the change of the parameters of the reference equation of a control system is used. In the offered method additional dynamic variables are used. Stable and unstable states of this variable depend on the state variables of a robot and the objects, next to it. In the local control systems of each mobile object the only values used are those of the own coordinates and speeds, and also coordinates and speeds of the neighboring objects. At that, a centralized algorithm of control is absent. Obstacles in the local algorithms are presented as mobile objects, which makes it possible to unify the control systems for the heterogeneous groups. An analysis was carried out, during which the existence and asymptotic stability of the steady movement modes were proved. The carried out numerical modeling confirmed the results of the analysis and synthesis.

Advances in the use of an intelligent transportation system (ITS) have been deployed in most of the world, which presents new opportunities for developing sustainable transportation system. This paper focuses on improving intelligent transportation systems using Big Data tools in predicting road accidents in Nigeria, based on real-time data gotten from Twitter. The work gives a review of common problems associated with the intelligent transportation system, and how this can be improved by utilizing Apache Spark Big Data. The revolution in intelligent transportation systems can be impacted by the availability of large data that can be used to generate new functions and services in intelligent transportation systems. The framework for utilizing Big Data Apache Spark will be discussed. The Big Data Apache Spark applications will be used to collect a large amount of data from various sources in intelligent transportation system; in return, this will help in predicting road accidents before it happens, and also, a feedback system for alerting can be projected. The use of machine learning algorithms is being used to make necessary predictions for the intelligent transportation system. The result obtained shows that for the classified data relating to road accidents, KNN gave a 94% accuracy when compared to other classification algorithms such as the Naïve Bayes, support vector machine, and the decision tree.

With the continuous development of Intelligent Transportation System (ITS), amount of data can be collected, generated and used by ITS, and the application of big data technology in Intelligent Transportation System is also applied in different kinds of fields. This paper first explains the definition of big data and intelligent transportation systems. Second, the framework of big data technology in the Intelligent Transport System (ITS) is introduced, which summarizes the data collection methods in specific scenarios of ITS, the application methods of data analysis in ITS, and the application of big data technology in ITS. Furthermore, this paper introduces several case studies on the application of big data technology in ITS, including public transport service planning, road traffic flow prediction, road traffic accident analysis, personal travel route planning, rail traffic management and control, and data analysis and prediction of bridge safety. Finally, this paper discusses some challenges of using big data technology in ITS.