Cloud Control System Architectures,Technologies and Applications on Intelligent and Connected Vehicles:a Review

The electrification of vehicle helps to improve its operation efficiency and safety.Due to fast development of network,sensors,as well as computing technology,it becomes realizable to have vehicles driving autonomously.To achieve autonomous driving,several steps,including environment perception,path-planning,and dynamic control,need to be done.However,vehicles equipped with on-board sensors still have limitations in acquiring necessary environmental data for optimal driving decisions.Intelligent and connected vehicles(ICV)cloud control system(CCS)has been introduced as a new concept as it is a potentially synthetic solution for high level automated driving to improve safety and optimize traffic flow in intelligent transportation.This paper systematically investigated the concept of cloud control system from cloud related applications on ICVs,and cloud control system architecture design,as well as its core technologies development.Based on the analysis,the challenges and suggestions on cloud control system development have been addressed.

Predictive cruise control for heavy trucks based on slope information under cloud control system

With the advantage of fast calculation and map resources on cloud control system(CCS), cloud-based predictive cruise control(CPCC) for heavy trucks has great potential to improve energy efficiency, which is significant to achieve the goal of national carbon neutrality. However, most investigations focus on the on-board predictive cruise control(PCC) system,lack of research on CPCC architecture under CCS. Besides, the current PCC algorithms have the problems of a single control target and high computational complexity, which hinders the improvement of the control effect. In this paper, a layered architecture based on CCS is proposed to effectively address the realtime computing of CPCC system and the deployment of its algorithm on vehicle-cloud. In addition, based on the dynamic programming principle and the proposed road point segmentation method(RPSM), a PCC algorithm is designed to optimize the speed and gear of heavy trucks with slope information. Simulation results show that the CPCC system can adaptively control vehicle driving through the slope prediction, with fuel-saving rate of 6.17% in comparison with the constant cruise control. Also,compared with other similar algorithms, the PCC algorithm can make the engine operate more in the efficient zone by cooperatively optimizing the gear and speed. Moreover, the RPSM algorithm can reconfigure the road in advance, with a 91% roadpoint reduction rate, significantly reducing algorithm complexity.Therefore, this study has essential research significance for the economic driving of heavy trucks and the promotion of the CPCC system.

A semantic-centered cloud control framework for autonomous unmanned system

Rich semantic information in natural language increases team efficiency in human collaboration, reduces dependence on high precision data information, and improves adaptability to dynamic environment. We propose a semantic centered cloud control framework for cooperative multi-unmanned ground vehicle(UGV) system. Firstly, semantic modeling of task and environment is implemented by ontology to build a unified conceptual architecture, and secondly, a scene semantic information extraction method combining deep learning and semantic web rule language(SWRL) rules is used to realize the scene understanding and task-level cloud task cooperation. Finally, simulation results show that the framework is a feasible way to enable autonomous unmanned systems to conduct cooperative tasks.

Design and implementation of data-driven predictive cloud control system

The rapid increase of the scale and the complexity of the controlled plants bring new challenges such as computing power and storage for conventional control systems.Cloud computing is concerned as a powerful solution to handle complex large-scale control missions by using sufficient computing resources.However,the computing ability enables more complex devices and more data to be involved and most of the data have not been fully utilized.Meanwhile,it is even impossible to obtain an accurate model of each device in the complex control systems for the model-based control algorithms.Therefore,motivated by the above reasons,we propose a data-driven predictive cloud control system.To achieve the proposed system,a practical data-driven predictive cloud control testbed is established and together a cloud-edge communication scheme is developed.Finally,the simulations and experiments demonstrate the effectiveness of the proposed system.

Distributed point-to-point routing method for tasks in cloud control systems

With the rapid development of cloud computing and control theory, a new paradigm of networked control systems called cloud control systems is proposed to meet the requirements of large-scale and complex applications. Currently, cloud control systems are mainly built by using a centralized architecture. The centralized system is overly dependent on the central control plane and has huge challenges in large-scale heterogeneous node systems. In this paper, we propose a decentralized approach to establish cloud control systems by proposing a distributed point-to-point task routing method. A considerable number of tasks in the system will not rely on the central plane and will be directly routed to the target devices through the pointto-point routing method, which improves the horizontal scalability of the cloud control system. The point-to-point routing method directly gives a unique address to every task, making inter-task communication more efficient in a complex heterogeneous and busy cloud control systems. Finally, we experimentally demonstrate that the distributed point-to-point task routing approach is compatible against the state-of-the-art central systems in large-scale task situations.

Attribute-Based Access Control Scheme with Efficient Revocation in Cloud Computing

Attribute-based encryption(ABE) supports the fine-grained sharing of encrypted data.In some common designs,attributes are managed by an attribute authority that is supposed to be fully trustworthy.This concept implies that the attribute authority can access all encrypted data,which is known as the key escrow problem.In addition,because all access privileges are defined over a single attribute universe and attributes are shared among multiple data users,the revocation of users is inefficient for the existing ABE scheme.In this paper,we propose a novel scheme that solves the key escrow problem and supports efficient user revocation.First,an access controller is introduced into the existing scheme,and then,secret keys are generated corporately by the attribute authority and access controller.Second,an efficient user revocation mechanism is achieved using a version key that supports forward and backward security.The analysis proves that our scheme is secure and efficient in user authorization and revocation.

A Novel Stateful PCE-Cloud Based Control Architecture of Optical Networks for Cloud Services

The next-generation optical network is a service oriented network,which could be delivered by utilizing the generalized multiprotocol label switching(GMPLS) based control plane to realize lots of intelligent features such as rapid provisioning,automated protection and restoration(P&R),efficient resource allocation,and support for different quality of service(QoS) requirements.In this paper,we propose a novel stateful PCE-cloud(SPC)based architecture of GMPLS optical networks for cloud services.The cloud computing technologies(e.g.virtualization and parallel computing) are applied to the construction of SPC for improving the reliability and maximizing resource utilization.The functions of SPC and GMPLS based control plane are expanded according to the features of cloud services for different QoS requirements.The architecture and detailed description of the components of SPC are provided.Different potential cooperation relationships between public stateful PCE cloud(PSPC) and region stateful PCE cloud(RSPC) are investigated.Moreover,we present the policy-enabled and constraint-based routing scheme base on the cooperation of PSPC and RSPC.Simulation results for verifying the performance of routing and control plane reliability are analyzed.

Stochastic stabilization of Markovian jump cloud control systems based on max-plus algebra

In this paper, stochastic stabilization is investigated by max-plus algebra for a Markovian jump cloud control system with a reference signal. For the Markovian jump cloud control system, there exists framework adjustment whose evolution is satisfied with a Markov chain. Using max-plus algebra, a maxplus stochastic system is used to describe the Markovian jump cloud control system. A causal feedback matrix is obtained by exponential stability analysis for a causal feedback controller of the Markovian jump cloud control system. A sufficient condition is given to ensure existence on the causal feedback matrix of the causal feedback controller. Based on the causal feedback controller, stochastic stabilization in probability is analyzed for the Markovian jump cloud control system with a reference signal.Simulation results are given to show effectiveness of the causal feedback controller for the Markovian jump cloud control system.

Design and Experimental Demonstration of Software Defined Space Optical Network (SDSON) Architecture Based on Cloud Platform

Space information network is used for real time acquiring, transmitting and processing the space information on the space platform, which provides significant communication services for communication, navigation positioning and science exploration. In this paper, the architecture of Software Defined Space Optical Network (SDSON) based on cloud platform is designed by means of Software Defined Optical Network (SDON) and cloud services. The new architecture combining centralized and distributed management-control mechanism is a multi-layer and multi-domain architecture with powerful computing and storage ability. Moreover, reliable service and unreliable service communication models employed in the space information network are proposed considering the characteristic of Disruption/Delay Tolerant Network (DTN). Finally, the functional verification and demonstration are performed on our optical experimental network platform.

A Review and Outlook on Predictive Cruise Control of Vehicles and Typical Applications Under Cloud Control System

With the application of mobile communication technology in the automotive industry,intelligent connected vehicles equipped with communication and sensing devices have been rapidly promoted.The road and traffic information perceived by intelligent vehicles has important potential application value,especially for improving the energy-saving and safe-driving of vehicles as well as the efficient operation of traffic.Therefore,a type of vehicle control technology called predictive cruise control(PCC)has become a hot research topic.It fully taps the perceived or predicted environmental information to carry out predictive cruise control of vehicles and improves the comprehensive performance of the vehicle-road system.Most existing reviews focus on the economical driving of vehicles,but few scholars have conducted a comprehensive survey of PCC from theory to the status quo.In this paper,the methods and advances of PCC technologies are reviewed comprehensively by investigating the global literature,and typical applications under a cloud control system(CCS)are proposed.Firstly,the methodology of PCC is generally introduced.Then according to typical scenarios,the PCC-related research is deeply surveyed,including freeway and urban traffic scenarios involving traditional vehicles,new energy vehicles,intelligent vehicles,and multi-vehicle platoons.Finally,the general architecture and three typical applications of the cloud control system(CCS)on PCC are briefly introduced,and the prospect and future trends of PCC are proposed.

Secure design for cloud control system against distributed denial of service attack

Nowadays, the development of cloud computing has given power to the resource-constrained network control system （NCS） to out-source heavy computations to the cloud server. However, the development of Cloud Computing produced many security challenges regarding the cyber-physical connection between the cloud and control system. The connection between the control system and cloud server can be subjected to distributed denial of service （DDoS） attack by an attacker to destabilize the NCS. In this paper, we will address this issue by building a secure mechanism for such systems. We will design a detection approach and a mitigation approach for better stable performance of NCS. To ensure the stability of NCS at the time of DDoS attack, we will also design a switching mechanism （SM） for cloud control system （CCS） when there are no more real time solutions available from the cloud. Finally, we will apply the proposed mechanism to an unmanned arial vehicle （UAV）. Our simulation results show that the mechanism works well in stability and protection of NCS under DDoS attack.

Privacy Preserving and Delegated Access Control for Cloud Applications

In cloud computing applications, users＇ data and applications are hosted by cloud providers. This paper proposed an access control scheme that uses a combination of discretionary access control and cryptographic techniques to secure users＇ data and applications hosted by cloud providers. Many cloud applications require users to share their data and applications hosted by cloud providers. To facilitate resource sharing, the proposed scheme allows cloud users to delegate their access permissions to other users easily. Using the access control policies that guard the access to resources and the credentials submitted by users, a third party can infer information about the cloud users. The proposed scheme uses cryptographic techniques to obscure the access control policies and users＇ credentials to ensure the privacy of the cloud users. Data encryption is used to guarantee the confidentiality of data. Compared with existing schemes, the proposed scheme is more flexible and easy to use. Experiments showed that the proposed scheme is also efficient.

Analysis of Classical Encryption Techniques in Cloud Computing

Cloud computing has become a significant computing model in the IT industry. In this emerging model,computing resources such as software, hardware, networking, and storage can be accessed anywhere in the world on a pay-per-use basis. However, storing sensitive data on un-trusted servers is a challenging issue for this model. To guarantee confidentiality and proper access control of outsourced sensitive data, classical encryption techniques are used. However, such access control schemes are not feasible in cloud computing because of their lack of flexibility, scalability, and fine-grained access control. Instead, Attribute-Based Encryption（ABE） techniques are used in the cloud. This paper extensively surveys all ABE schemes and creates a comparison table for the key criteria for these schemes in cloud applications.

Recent Progress in Networked Control Systems——A Survey

For the past decades,networked control systems(NCSs),as an interdisciplinary subject,have been one of the main research highlights and many fruitful results from different aspects have been achieved.With these growing research trends,it is significant to consolidate the latest knowledge and information to keep up with the research needs.In this paper,the results of different aspects of NCSs,such as quantization,estimation,fault detection and networked predictive control,are summarized.In addition,with the development of cloud technique,cloud control systems are proposed for the further development of NCSs.

Intelligent Control Method of Power Supply for Tundish Electromagnetic Induction Heating System

An intelligent control method is proposed to improve the performance of power supply for tundish electromagnetic induction heating,which can adequately regulate the tundish temperature.The topology structure of power supply for tundish electromagnetic induction heating is presented,and its working principle is analyzed.The power supply consists of six power units,and each of them consists of a fore-stage threephase rectifier and back-stage single-phase inverter.The feedforward control DC voltage is used by three-phase rectifier to obtain the stable DC voltage supplied to the inverter.The cloud controller based intelligent temperature control algorithm is combined with the power feed-forward algorithm to obtain accurate tracking of the output current and constant temperature control of the tundish steel in the back-stage inverter.The simulation and experiment are performed to verify the accuracy and effectiveness of the proposed method.

The Interaction between Control and Computing Theories:New Approaches

Day by day, networked control system（NCS） methods have been promoted for distributed closed-loop control systems.Interestingly, the integration of control and computing theories enhanced the development of networked control systems through remote control for wide applications employing the internet. Two further directions to networked control technology are LeaderFollower systems and model predictive control systems. Cloud control system is looked at an extension of networked control systems（NCS） using internet of things（IOT） methodologies. In this paper, a comprehensive literature survey of the new technology of control systems application performed on cloud computing is presented.

IoT System for Intelligent Firefighting in the Electric Power Industry

Traditional fire safety management in the electric power industry has significant drawbacks,including a lack of data,difficulty of maintenance,lack of supervision,and lack of interaction.This type of management lags behind current advanced safety management concepts such as“gate advancement”and“full process man-agement”,and it fails to meet the needs of future energy internet construction and development.In response to these problems,an internet of things system for smart firefighting in the electric power industry was constructed in this study.This system defines a centralized information window,trains a power intelligent firefighting brain,establishes a firefighting cloud management and control system,constructs a power firefighting interaction mech-anism,and performs multi-party coordination of firefighting mechanisms to realize concept of“a whole network on one screen and everything in one network”for managing fires.