A Survey on Industrial Internet of Things: A Cyber-Physical Systems Perspective <s> F. SUMMARY <s> Cloud computing is changing the way industries and enterprises do their businesses in that dynamically scalable and virtualized resources are provided as a service over the Internet. This model creates a brand new opportunity for enterprises. In this paper, some of the essential features of cloud computing are briefly discussed with regard to the end-users, enterprises that use the cloud as a platform, and cloud providers themselves. Cloud computing is emerging as one of the major enablers for the manufacturing industry; it can transform the traditional manufacturing business model, help it to align product innovation with business strategy, and create intelligent factory networks that encourage effective collaboration. Two types of cloud computing adoptions in the manufacturing sector have been suggested, manufacturing with direct adoption of cloud computing technologies and cloud manufacturing-the manufacturing version of cloud computing. Cloud computing has been in some of key areas of manufacturing such as IT, pay-as-you-go business models, production scaling up and down per demand, and flexibility in deploying and customizing solutions. In cloud manufacturing, distributed resources are encapsulated into cloud services and managed in a centralized way. Clients can use cloud services according to their requirements. Cloud users can request services ranging from product design, manufacturing, testing, management, and all other stages of a product life cycle. <s> BIB001 </s> A Survey on Industrial Internet of Things: A Cyber-Physical Systems Perspective <s> F. SUMMARY <s> Recently, cloud manufacturing (CMfg) as a new service-oriented manufacturing mode has been paid wide attention around the world. However, one of the key technologies for implementing CMfg is how to realize manufacturing resource intelligent perception and access. In order to achieve intelligent perception and access of various manufacturing resources, the applications of IoT technologies in CMfg has been investigated in this paper. The classification of manufacturing resources and services, as well as their relationships, are presented. A five-layered structure (i.e., resource layer, perception layer, network layer, service layer, and application layer) resource intelligent perception and access system based on IoT is designed and presented. The key technologies for intelligent perception and access of various resources (i.e., hard manufacturing resources, computational resources, and intellectual resources) in CMfg are described. A prototype application system is developed to valid the proposed method. <s> BIB002 </s> A Survey on Industrial Internet of Things: A Cyber-Physical Systems Perspective <s> F. SUMMARY <s> Software-Defined Networking (SDN) is a promising approach to build future industrial networks. The disruptive change of network architecture and management opens new possibilities in various application domains. While the approach is already deployed in several domains and was also initially examined to be used in the industrial area, many open questions arise when assessing the risks and improvements to be expected. The following work presents features of a potential future industrial network infrastructure and sets up requirements that are important for future communications. It reviews basics of SDN and correlates existing work to the specified requirements. Finally, it presents open questions and room for future research. <s> BIB003 </s> A Survey on Industrial Internet of Things: A Cyber-Physical Systems Perspective <s> F. SUMMARY <s> With recent adoption of wireless sensor-actuator networks (WSANs) in industrial automation, industrial wireless control systems have emerged as a frontier of cyber-physical systems. Despite their success in industrial monitoring applications, existing WSAN technologies face significant challenges in supporting control systems due to their lack of real-time performance and dynamic wireless conditions in industrial plants. This article reviews a series of recent advances in real-time WSANs for industrial control systems: 1) real-time scheduling algorithms and analyses for WSANs; 2) implementation and experimentation of industrial WSAN protocols; 3) cyber-physical codesign of wireless control systems that integrate wireless and control designs; and 4) a wireless cyber-physical simulator for codesign and evaluation of wireless control systems. This article concludes by highlighting research directions in industrial cyber-physical systems. <s> BIB004 </s> A Survey on Industrial Internet of Things: A Cyber-Physical Systems Perspective <s> F. SUMMARY <s> The Industrial Internet of Things (IIoT) is quite different from the general IoT in terms of latency, bandwidth, cost, security and connectivity. Most existing IoT platforms are designed for general IoT needs, and thus cannot handle the specificities of IIoT. With the anticipated big data generation in IIoT, an open source platform capable of minimizing the amount of data being sent from the edge and at the same time, that can effectively monitor and communicate the condition of the large-scale engineering system by doing efficient real-time edge analytics is sorely needed. In this work, an industrial machine condition-monitoring open-source software database, equipped with a dictionary and small enough to fit into the memory of edge data-analytic devices is created. The database-dictionary system will prevent excessive industrial and smart grid machine data from being sent to the cloud since only fault report and requisite recommendations, sourced from the edge dictionary and database will be sent. An open source software (Python SQLite) situated on Linux operating system is used to create the edge database and the dictionary so that inter-platform portability will be achieved and most IIoT machines will be able to use the platform. Statistical analysis at the network edge using well known industrial methods such as kurtosis and skewness reveal significant differences between generated machine signal and reference signal. This database-dictionary approach is a new paradigm since it is different from legacy methods in which databases are situated only in the cloud with huge memory and servers. The open source deployment will also help to satisfy the criteria of Industrial IoT Consortium and the Open Fog Architecture. <s> BIB005 </s> A Survey on Industrial Internet of Things: A Cyber-Physical Systems Perspective <s> F. SUMMARY <s> Industrial automation deployments constitute challenging environments where moving IoT machines may produce high-definition video and other heavy sensor data during surveying and inspection operations. Transporting massive contents to the edge network infrastructure and then eventually to the remote human operator requires reliable and high-rate radio links supported by intelligent data caching and delivery mechanisms. In this work, we address the challenges of contents dissemination in characteristic factory automation scenarios by proposing to engage moving industrial machines as device-to-device (D2D) caching helpers. With the goal to improve reliability of high-rate millimeter-wave (mmWave) data connections, we introduce the alternative contents dissemination modes and then construct a novel mobility-aware methodology that helps develop predictive mode selection strategies based on the anticipated radio link conditions. We also conduct a thorough system-level evaluation of representative data dissemination strategies to confirm the benefits of predictive solutions that employ D2D-enabled collaborative caching at the wireless edge to lower contents delivery latency and improve data acquisition reliability. <s> BIB006 </s> A Survey on Industrial Internet of Things: A Cyber-Physical Systems Perspective <s> F. SUMMARY <s> In recent years, smart factory in the context of Industry 4.0 and industrial Internet of Things (IIoT) has become a hot topic for both academia and industry. In IIoT system, there is an increasing requirement for exchange of data with different delay flows among different smart devices. However, there are few studies on this topic. To overcome the limitations of traditional methods and address the problem, we seriously consider the incorporation of global centralized software defined network (SDN) and edge computing (EC) in IIoT with EC. We propose the adaptive transmission architecture with SDN and EC for IIoT. Then, according to data streams with different latency constrains, the requirements can be divided into two groups: 1) ordinary and 2) emergent stream. In the low-deadline situation, a coarse-grained transmission path algorithm provided by finding all paths that meet the time constrains in hierarchical Internet of Things (IoT). After that, by employing the path difference degree (PDD), an optimum routing path is selected considering the aggregation of time deadline, traffic load balances, and energy consumption. In the high-deadline situation, if the coarse-grained strategy is beyond the situation, a fine-grained scheme is adopted to establish an effective transmission path by an adaptive power method for getting low latency. Finally, the performance of proposed strategy is evaluated by simulation. The results demonstrate that the proposed scheme outperforms the related methods in terms of average time delay, goodput, throughput, PDD, and download time. Thus, the proposed method provides better solution for IIoT data transmission. <s> BIB007 </s> A Survey on Industrial Internet of Things: A Cyber-Physical Systems Perspective <s> F. SUMMARY <s> Recent standardization efforts in IEEE 802.15.4-2015 Time Scheduled Channel Hopping (TSCH) and the IETF 6TiSCH Working Group (WG), aim to provide deterministic communications and efficient allocation of resources across constrained Internet of Things (IoT) networks, particularly in Industrial IoT (IIoT) scenarios. Within 6TiSCH, Software Defined Networking (SDN) has been identified as means of providing centralized control in a number of key situations. However, implementing a centralized SDN architecture in a Low Power and Lossy Network (LLN) faces considerable challenges: not only is controller traffic subject to jitter due to unreliable links and network contention, but the overhead generated by SDN can severely affect the performance of other traffic. This paper proposes using 6TiSCH tracks, a Layer-2 slicing mechanism for creating dedicated forwarding paths across TSCH networks, in order to isolate the SDN control overhead. Not only does this prevent control traffic from affecting the performance of other data flows, but the properties of 6TiSCH tracks allows deterministic, low-latency SDN controller communication. Using our own lightweight SDN implementation for Contiki OS, we firstly demonstrate the effect of SDN control traffic on application data flows across a 6TiSCH network. We then show that by slicing the network through the allocation of dedicated resources along a SDN control path, tracks provide an effective means of mitigating the cost of SDN control overhead in IEEE 802.15.4-2015 TSCH networks. <s> BIB008 </s> A Survey on Industrial Internet of Things: A Cyber-Physical Systems Perspective <s> F. SUMMARY <s> To apply cyber-physical system (CPS) technique in industrial internet, a wireless technology that is able to robustly maintain hyperconnectivity between a data center and distributed user entities and/or industrial Internet of Things devices is required. We investigate the feasibility of utilizing massive multiple-input multiple-output (MIMO) as such a wireless technology. We analyze the performance of a massive MIMO base station deployed at a data center to provide massive connectivity to a large number of devices. In addition, we discuss related research challenges for deploying massive MIMO in industrial internet applications of CPS, such as device scheduling and power control, energy efficient design and radio frequency energy transfer/harvesting, signaling techniques for drones and mobile robots, and applications of underwater industrial internet. <s> BIB009 </s> A Survey on Industrial Internet of Things: A Cyber-Physical Systems Perspective <s> F. SUMMARY <s> In industrial automation, the state of process control could be monitored by spatially distributed sensors and 5G machine-type communication (MTC) enabled industrial Internet of things (IIoT). Thus, ultra-reliable MTC and high-accurate state estimation play important roles for ensuing system stabilization. However, it is challenging due to complex industrial wireless environments and limited communication resources. To address this issue, this paper first presents a transmission-estimation codesign framework to lay down the foundation for guaranteeing the prescribed estimation accuracy with limited communication resources. Under this framework, a hierarchical transmission-estimation approach is proposed to improve the transmission reliability and estimation accuracy according to system dynamics. The proposed approach is then optimized by formulating a constrained minimization problem, which is mixed integer nonlinear programming and solved efficiently with a block-coordinate-descent-based decomposition method. Finally, simulation results demonstrate that the proposed approach has superiorities in improving both the estimation accuracy and the energy efficiency. <s> BIB010 </s> A Survey on Industrial Internet of Things: A Cyber-Physical Systems Perspective <s> F. SUMMARY <s> Recently, the industrial Internet of Things (IIoT) has drawn high attention in academia and industry in the context of industry 4.0. In the IIoT, smart IoT devices are adopted to improve production efficiency. But, these devices will generate huge amounts of production data, which need to be processed effectively. To support IIoT services efficiently, cloud computing is usually considered as one of the possible solutions. However, the IIoT services still suffer from the high-latency and unreliable links problem between cloud and IIoT terminals. To combat these issues, fog computing is a promising solution which extends computing and storage to the network edge. In this paper, we are motivated to integrate the fog computing to the cloud-based IIoT to build a cloud-fog integrated IIoT (CF-IIoT) network. To achieve the ultra-low service response latency, we introduce the distributed computing to the CF-IIoT network and propose leveraging the real-coded genetic algorithm for constrained optimization problem(RCGA-CO) algorithm to optimize the load balancing problem of the distributed cloud-fog network. Most importantly, considering the unreliable situation in the CF-IIoT (e.g., fog nodes damage, wireless links outage), we propose a task reallocation and retransmission mechanism to reduce the average service latency of the CF-IIoT network architecture. The performance evaluation results validate that the RCGA-CO-based CF-IIoT and our proposed mechanism can provide ultra-low latency service in IIoT scenario. <s> BIB011 </s> A Survey on Industrial Internet of Things: A Cyber-Physical Systems Perspective <s> F. SUMMARY <s> Industry 4.0 or industrial Internet of things (IIoT) has become one of the most talked-about industrial business concepts in recent years. Thus, to efficiently integrate Internet of things technology into industry, the collected and sensed data from IIoT need to be scheduled in real-time constraints, especially for big factories. To this end, we propose in this paper a hierarchical fog servers’ deployment at the network service layer across different tiers. Using probabilistic analysis models, we prove the efficiency of the proposed hierarchical fog computing compared with the flat architecture. In this paper, IIoT data and requests are divided into both high priority and low priority requests; the high priority requests are urgent/emergency demands that need to be scheduled rapidly. Therefore, we use two-priority queuing model in order to schedule and analyze IIoT data. Finally, we further introduce a workload assignment algorithm to offload peak loads over higher tiers of the fog hierarchy. Using realistic industrial data from Bosch group, the benefits of the proposed architecture compared to the conventional flat design are proved using various performance metrics and through extensive simulations. <s> BIB012 </s> A Survey on Industrial Internet of Things: A Cyber-Physical Systems Perspective <s> F. SUMMARY <s> The emergence of the Industrial Internet of Things (IIoT) has paved the way to real-time big data storage, access, and processing in the cloud environment. In IIoT, the big data generated by various devices such as-smartphones, wireless body sensors, and smart meters will be on the order of zettabytes in the near future. Hence, relaying this huge amount of data to the remote cloud platform for further processing can lead to severe network congestion. This in turn will result in latency issues which affect the overall QoS for various applications in IIoT. To cope with these challenges, a recent paradigm shift in computing, popularly known as edge computing, has emerged. Edge computing can be viewed as a complement to cloud computing rather than as a competition. The cooperation and interplay among cloud and edge devices can help to reduce energy consumption in addition to maintaining the QoS for various applications in the IIoT environment. However, a large number of migrations among edge devices and cloud servers leads to congestion in the underlying networks. Hence, to handle this problem, SDN, a recent programmable and scalable network paradigm, has emerged as a viable solution. Keeping focus on all the aforementioned issues, in this article, an SDN-based edge-cloud interplay is presented to handle streaming big data in IIoT environment, wherein SDN provides an efficient middleware support. In the proposed solution, a multi-objective evolutionary algorithm using Tchebycheff decomposition for flow scheduling and routing in SDN is presented. The proposed scheme is evaluated with respect to two optimization objectives, that is, the trade-off between energy efficiency and latency, and the trade-off between energy efficiency and bandwidth. The results obtained prove the effectiveness of the proposed flow scheduling scheme in the IIoT environment. <s> BIB013 </s> A Survey on Industrial Internet of Things: A Cyber-Physical Systems Perspective <s> F. SUMMARY <s> With the fast development of industrial Internet of things (IIoT), a large amount of data is being generated continuously by different sources. Storing all the raw data in the IIoT devices locally is unwise considering that the end devices’ energy and storage spaces are strictly limited. In addition, the devices are unreliable and vulnerable to many threats because the networks may be deployed in remote and unattended areas. In this paper, we discuss the emerging challenges in the aspects of data processing, secure data storage, efficient data retrieval and dynamic data collection in IIoT. Then, we design a flexible and economical framework to solve the problems above by integrating the fog computing and cloud computing. Based on the time latency requirements, the collected data are processed and stored by the edge server or the cloud server. Specifically, all the raw data are first preprocessed by the edge server and then the time-sensitive data (e.g., control information) are used and stored locally. The non-time-sensitive data (e.g., monitored data) are transmitted to the cloud server to support data retrieval and mining in the future. A series of experiments and simulation are conducted to evaluate the performance of our scheme. The results illustrate that the proposed framework can greatly improve the efficiency and security of data storage and retrieval in IIoT. <s> BIB014 </s> A Survey on Industrial Internet of Things: A Cyber-Physical Systems Perspective <s> F. SUMMARY <s> Software-defined networking (SDN) is a key enabling technology of industrial Internet of Things (IIoT) that provides dynamic reconfiguration to improve data network robustness. In the context of smart grid infrastructure, the strong demand of seamless data transmission during critical events (e.g., failures or natural disturbances) seems to be fundamentally shifting energy attitude toward emerging technology. Therefore, SDN will play a vital role on energy revolution to enable flexible interfacing between smart utility domains and facilitate the integration of mix renewable energy resources to deliver efficient power of sustainable grid. In this regard, we propose a new SDN platform based on IIoT technology to support resiliency by reacting immediately whenever a failure occurs to recover smart grid networks using real-time monitoring techniques. We employ SDN controller to achieve multifunctionality control and optimization challenge by providing operators with real-time data monitoring to manage demand, resources, and increasing system reliability. Data processing will be used to manage resources at local network level by employing SDN switch segment, which is connected to SDN controller through IIoT aggregation node. Furthermore, we address different scenarios to control packet flows between switches on hub-to-hub basis using traffic indicators of the infrastructure layer, in addition to any other data from the application layer. Extensive experimental simulation is conducted to demonstrate the validation of the proposed platform model. The experimental results prove the innovative SDN-based IIoT solutions can improve grid reliability for enhancing smart grid resilience. <s> BIB015
We develop the taxonomy to outline the broader research roadmap for networking in Figure 7 , where existing research works can be mapped into individual cubes (i.e., research areas). The examples include <Control, FA, Latency> (e.g., BIB006 , BIB007 ), <Monitoring, FA, Latency> (e.g., BIB006 , BIB003 , BIB007 ), <Control, PA, Latency> (e.g., BIB004 , BIB007 ), <Monitoring, PA, Latency> (e.g., BIB003 , BIB008 , BIB007 ), <Monitoring, FA, Reliability> (e.g., BIB006 , BIB009 , BIB003 ), <Monitoring, PA, Reliability> (e.g., BIB003 , BIB008 , BIB015 ), and <Monitoring, PA, Others> (''Others'' represents energy efficiency) (e.g., BIB010 ). It is worth noting that there are a number of cubes that have not been well explored. The example include <Others, FA, Latency> (e.g., ''Others'' can be reporting data), <Others, PA, Latency>, <Control, FA, Reliability>, <Control, PA, Reliability>, <Control, PA, Others>, <Monitoring, PA, Others> (e.g., ''Others'' can represents energy efficiency, security, etc.). To fill the gap, we outline several research challenges, which need extensive research efforts in Section VI-A2, including network deployment, resource scheduling and security and privacy. We develop the taxonomy to outline the broader research roadmap for computing in Figure 10 , where existing research works can be mapped into individual cubes (i.e., research areas). Examples include <Storage, FA, QoS> (e.g., BIB011 ), <Transmission, FA, QoS> (e.g., BIB012 - BIB013 ), <Analysis, FA, QoS> (e.g., BIB002 , BIB001 ,  ), <Storage, PA, QoS> (e.g., BIB014 ), <Transmission, PA, QoS> (e.g., BIB011 , BIB013 ), <Analysis, PA, QoS> (e.g.,  ), <Storage, FA, Others> (e.g., BIB014 ), <Transmission, FA, Others> (e.g., BIB005 ). Notice that the element ''Others'' can represent resource efficiency, security, and others. There are a number of cubes that have not been well explored. The example include <Analysis, FA, Others>, <Storage, PA, Others>, <Transmission, PA, Others>, <Analysis, PA, Others>, and others. To fill the gap, we outline several research challenges, which need extensive research efforts in Section VI-A3, including deployment, seamless integration and computing resource management.