A Dual-Mode Adaptive MAC Protocol for Process Control in Industrial Wireless Sensor Networks

Doktorgradsavhandling ved Fakultet for teknologi og realfag, Universitetet i Agder, 2017Wireless Sensor Networks (WSNs) consist of sensors and actuators operating together to provide monitoring and control services. These services are used in versatile applications ranging from environmental monitoring t oindustrial automation applications. Industrial Wireless Sensor Network (IWSN) is a sub domain of the WSN domain, focussing the industrial monitoring and automation applications. The IWSN domain differs from the generic WSN domains in terms of its requirements. General IWSN requirements include: energy efficiency and quality of service, and strict requirements are imposed on the quality of service expected by IWSN applications. Quality of service in particular relates to reliability, robustness, and predictability. Medium Access Control (MAC) protocols in an IWSN solution are responsible for managing radio communications, the main consumer of power in every IWSN element. With proper measures, MAC protocols can provide energy efficient solutions along with required quality of service for process control applications. The first goal of the thesis was to assess the possibility of creating a MAC protocol exploiting properties of the application domain, the process control domain. This resulted in the creation of the Dual-Mode Adaptive Medium Access Control Protocol (DMAMAC) which constitutes the main contribution of this thesis. The DMAMAC protocol is energy efficient,while preserving real-time requirements, and is robust to packet failure. This has been guaranteed by the thorough evaluation of the protocol via simulation, verification, and implementation with deployment testing. In parallel, we also investigated the possibility of using an alternative development approach for MAC protocols. Specifically, we have proposed a development approach based on MAC protocol model in CPN tools. The development approach consists of automatic code generation for the MiXiM simulation tool and the TinyOS platform. We used the related GinMAC protocol as a running example for the development approach. The generated code for MiXiM simulation platform and the TinyOS implementation platform are evaluated via simulation and deployment respectively. This results in a faster design to implementation time, and closely related protocol artifacts, improving on the traditional approach

Blockchain, parameterisation and automated arbitrage applied to the chemical industry

This thesis considers three scenarios related to chemical industry where the concepts of eco-industrial parks (EIPs), Industry 4.0, parameterisation, blockchain and arbitrage are brought together to explore the issues of simulation speed and accuracy, machine-to-machine (M2M) communication and automated participation in financial markets. In the first scenario, a biodiesel plant flow sheet model is analysed and parameterised. The relations between 11 inputs typical to a biodiesel plant and its energy requirements are approximated using surrogate models, of which accuracy is assessed. Additionally, the effects of dimensionality, domain size and surrogate type on the accuracy are investigated and global sensitivities of the outputs are computed using High Dimensional Model Representation (HDMR). Most surrogate models achieved at least a reasonable fit regardless of the domain size and number of dimensions. It was observed that in all cases only 4 or fewer inputs have significant influence on any of the outputs and that the interaction terms have only minor effect on any one output. In the second scenario, applications of blockchain technology related to Industry 4.0 are explored and an example where blockchain is employed to facilitate M2M interactions and establish a M2M electricity market in the context of the chemical industry is presented. Successful implementation of two electricity producers and one electricity consumer trading with each other over a blockchain-based network is presented. In the third scenario, an automated arbitrage spotter is developed and applied to two cases: conversion of natural gas to methanol and crude palm oil to biodiesel. The spotter is designed to search for opportunities to make additional profit by analysing the futures market prices for both the reagent and the product. It considers cost of storage and conversion (other feedstock, steam, electricity and other utilities) derived from physical simulations of the chemical process. In a profitable scenario up to 345.17 USD per tonne of biodiesel can be earned by buying contracts for delivery of crude palm oil in September 2018 and selling contracts for delivery of biodiesel in December 2018 in a ratio of 4 to 1.Department of Chemical Engineering and Biotechnology in the University of Cambridge and Cambridge CARES Ltd