The next-generation blockchain ecosystem is expected to integrate both homogeneous and heterogeneous distributed ledgers. These systems require operations across multiple blockchains to enrich advanced functionalities for future applications. However, the development of blockchain interoperability involves much more complexity regarding the variety of underlying architectures. Guaranteeing the properties of ACID (Atomicity, Consistency, Isolation, Durability) across diverse blockchain systems remains challenging. To clear the fog, this article accordingly provides a comprehensive review of the current progress of blockchain interoperability. We explore the general principles and procedures for interoperable blockchain systems to highlight their design commons. Then, we survey practical instances and compare state-of-the-art systems to present their unique features between distinct solutions. Finally, we discuss critical challenges and point out potential research directions. We believe our work can provide an intuitive guideline for newcomers and also promote rapid development in terms of blockchain interoperability.

Process industries cover a wide set of industries, in which the processes are controlled by a combination of distributed control systems (DCSs) and programmable logic controllers (PLCs). These control systems utilize various measurements such as pressure, flow, and temperature to determine the state of the process and then use field devices such as valves and other actuating devices to manipulate the process. Since there are many different types of field devices and since each device is calibrated to its specific installation, when monitoring devices, it is important to be able to transfer not only the device measurement and diagnostics but also characteristics about the device and the process in which it is installed. The current monitoring architecture, however, creates challenges for continuous monitoring and analysis of diagnostic data. In this paper, we present the design of an Industrial Internet-of-Things (IIoT) system for supporting large-scale and continuous device condition monitoring and analysis in process control systems. The system design seamlessly integrates existing infrastructure [e.g., highway addressable remote transducer (HART) and WirelessHART networks, and DeltaV DCS] and newly developed hardware/software components (e.g., one-way data diode and IoT cellular architecture) together for control network data collection and streaming of the collected device diagnostic parameters to a private cloud to perform streaming data analytics designed for fault identification and prediction. A prototype system has been developed and supported by Emerson Automation Solutions and deployed in the field for design validation and long-term performance evaluation. To the best of our knowledge, this is the first ever publicly reported effort on IoT system design for process automation applications. The design can be readily extended for condition monitoring and analysis of many other industrial facilities and processes.

In this paper, we propose a new MAC protocol for multi-beam directional antenna. In the protocol, each beam-sector has its own control channel, thus the communications among different beam-sectors are independent. It uses the Directional Network Allocation Vector (DNAV) to record the establishment processes. After sensing all the sectors of multi-beam antenna, it uses the global assignment strategy to assign the directional communication channels. Extensive simulation results show that our protocol can significantly improve the throughput of entire wireless network at the expense of the slightly increased RTS/DRTS requests during establishment process.