Wireless Sensor Technology Selection for I4.0 Manufacturing Systems

The term smart manufacturing has surfaced as an industrial revolution in Germany known as Industry 4.0 (I4.0); this revolution aims to help the manufacturers adapt to turbulent market trends. Its main scope is implementing machine communication, both vertically and horizontally across the manufacturing hierarchy through Internet of things (IoT), technologies and servitization concepts. The main objective of this research is to help manufacturers manage the high levels of variety and the extreme turbulence of market trends through developing a selection tool that utilizes Analytic Hierarchy Process (AHP) techniques to recommend a suitable industrial wireless sensor network (IWSN) technology that fits their manufacturing requirements.In this thesis, IWSN technologies and their properties were identified, analyzed and compared to identify their potential suitability for different industrial manufacturing system application areas. The study included the identification and analysis of different industrial system types, their application areas, scenarios and respective communication requirements. The developed tool’s sensitivity is also tested to recommend different IWSN technology options with changing influential factors. Also, a prioritizing protocol is introduced in the case where more than one IWSN technology options are recommended by the AHP tool.A real industrial case study with the collaboration of SPM Automation Inc. is presented, where the industrial systems’ class, communication traffic types, and communication requirements were analyzed to recommend a suitable IWSN technology that fits their requirements and assists their shift towards I4.0 through utilizing AHP techniques. The results of this research will serve as a step forward, in the transformation process of manufacturing towards a more digitalized and better connected cyber-physical systems; thus, enhancing manufacturing attributes such as flexibility, reconfigurability, scalability and easing the shift towards implementing I4.0

Edge Computing for Internet of Things

The Internet-of-Things is becoming an established technology, with devices being deployed in homes, workplaces, and public areas at an increasingly rapid rate. IoT devices are the core technology of smart-homes, smart-cities, intelligent transport systems, and promise to optimise travel, reduce energy usage and improve quality of life. With the IoT prevalence, the problem of how to manage the vast volumes of data, wide variety and type of data generated, and erratic generation patterns is becoming increasingly clear and challenging. This Special Issue focuses on solving this problem through the use of edge computing. Edge computing offers a solution to managing IoT data through the processing of IoT data close to the location where the data is being generated. Edge computing allows computation to be performed locally, thus reducing the volume of data that needs to be transmitted to remote data centres and Cloud storage. It also allows decisions to be made locally without having to wait for Cloud servers to respond

Motion Sensor-based Small Cell Sleep Scheduling for 5G Networks

No abstract available

Fuzzy-TOPSIS based Cluster Head selection in mobile sensor networks

One of the critical parameters of Wireless Sensor Networks (WSNs) is node lifetime. There are various methods to increase WSN node lifetime, the clustering technique is being one of them. In clustering, selection of a desired percentage of Cluster Heads (CHs) is performed among the sensor nodes (SNs). Selected CHs are responsible for collecting data from their member nodes, aggregating the data and finally sending it to the sink. In this paper, we propose a Fuzzy-TOPSIS technique, based on multi criteria decision making, to choose CH efficiently and effectively to maximize the WSN lifetime. We will consider several criteria including: residual energy; node energy consumption rate; number of neighbor nodes; average distance between neighboring nodes; and distance from the sink. A threshold based intra-cluster and inter-cluster multi-hop communication mechanism is used to decrease energy consumption. We have also analyzed the impact of node density and different types of mobility strategies in order to investigate impact over WSN lifetime. In order to maximize the load distribution in the WSN, a predictable mobility with octagonal trajectory is proposed. This results in improvement of overall network lifetime and latency. Results shows that the proposed scheme improves the network lifetime by 60%, conserve energy by 80%, a significant reduction of frequent Cluster Head (CH) per round selection by 25% is achieved as compared to the conventional Fuzzy and LEACH protocols

A framework for cloud-based healthcare services to monitor noncommunicable diseases patient

Monitoring patients who have noncommunicable diseases is a big challenge. These illnesses require a continuous monitoring that leads to high cost for patients\u27 healthcare. Several solutions proposed reducing the impact of these diseases in terms of economic with respect to quality of services. One of the best solutions is mobile healthcare, where patients do not need to be hospitalized under supervision of caregivers. This paper presents a new hybrid framework based on mobile multimedia cloud that is scalable and efficient and provides cost-effective monitoring solution for noncommunicable disease patient. In order to validate the effectiveness of the framework, we also propose a novel evaluation model based on Analytical Hierarchy Process (AHP), which incorporates some criteria from multiple decision makers in the context of healthcare monitoring applications. Using the proposed evaluation model, we analyzed three possible frameworks (proposed hybrid framework, mobile, and multimedia frameworks) in terms of their applicability in the real healthcare environment

Improving the Reliability of Optimised Link State Routing Protocol in Smart Grid’s Neighbour Area Network

A reliable and resilient communication infrastructure that can cope with variable application traffic types and delay objectives is one of the prerequisites that differentiates a Smart Grid from the conventional electrical grid. However, the legacy communication infrastructure in the existing electrical grid is insufficient, if not incapable of satisfying the diverse communication requirements of the Smart Grid. The IEEE 802.11 ad hoc Wireless Mesh Network (WMN) is re-emerging as one of the communication networks that can significantly extend the reach of Smart Grid to backend devices through the Advanced Metering Infrastructure (AMI). However, the unique characteristics of AMI application traffic in the Smart Grid poses some interesting challenges to conventional communication networks including the ad hoc WMN. Hence, there is a need to modify the conventional ad hoc WMN, to address the uncertainties that may exist in its applicability in a Smart Grid environment. This research carries out an in-depth study of the communication of Smart Grid application traffic types over ad hoc WMN deployed in the Neighbour Area Network (NAN). It begins by conducting a critical review of the application characteristics and traffic requirements of several Smart Grid applications and highlighting some key challenges. Based on the reviews, and assuming that the application traffic types use the internet protocol (IP) as a transport protocol, a number of Smart Grid application traffic profiles were developed. Through experimental and simulation studies, a performance evaluation of an ad hoc WMN using the Optimised Link State Routing (OLSR) routing protocol was carried out. This highlighted some capacity and reliability issues that routing AMI application traffic may face within a conventional ad hoc WMN in a Smart Grid NAN. Given the fact that conventional routing solutions do not consider the traffic requirements when making routing decisions, another key observation is the inability of link metrics in routing protocols to select good quality links across multiple hops to a destination and also provide Quality of Service (QoS) support for target application traffic. As with most routing protocols, OLSR protocol uses a single routing metric acquired at the network layer, which may not be able to accommodate different QoS requirements for application traffic in Smart Grid. To address these problems, a novel multiple link metrics approach to improve the reliability performance of routing in ad hoc WMN when deployed for Smart Grid is presented. It is based on the OLSR protocol and explores the possibility of applying QoS routing for application traffic types in NAN based ad hoc WMN. Though routing in multiple metrics has been identified as a complex problem, Multi-Criteria Decision Making (MCDM) techniques such as the Analytical Hierarchy Process (AHP) and pruning have been used to perform such routing on wired and wireless multimedia applications. The proposed multiple metrics OLSR with AHP is used to offer the best available route, based on a number of considered metric parameters. To accommodate the variable application traffic requirements, a study that allows application traffic to use the most appropriate routing metric is presented. The multiple metrics development is then evaluated in Network Simulator 2.34; the simulation results demonstrate that it outperforms existing routing methods that are based on single metrics in OLSR. It also shows that it can be used to improve the reliability of application traffic types, thereby overcoming some weaknesses of existing single metric routing across multiple hops in NAN. The IEEE 802.11g was used to compare and analyse the performance of OLSR and the IEEE 802.11b was used to implement the multiple metrics framework which demonstrate a better performance than the single metric. However, the multiple metrics can also be applied for routing on different IEEE wireless standards, as well as other communication technologies such as Power Line Communication (PLC) when deployed in Smart Grid NAN

Sustainable Edge Node Computing Deployments in Distributed Manufacturing Systems

The advancement of mobile internet technology has created opportunities for integrating the Industrial Internet of Things (IIoT) and edge computing in smart manufacturing. These sustainable technologies enable intelligent devices to achieve high-performance computing with minimal latency. This paper introduces a novel approach to deploy edge computing nodes in smart manufacturing environments at a low cost. However, the intricate interactions among network sensors, equipment, service levels, and network topologies in smart manufacturing systems pose challenges to node deployment. To address this, the proposed sustainable game theory method identifies the optimal edge computing node for deployment to attain the desired outcome. Additionally, the standard design of Software Defined Network (SDN) in conjunction with edge computing serves as forwarding switches to enhance overall computing services. Simulations demonstrate the effectiveness of this approach in reducing network delay and deployment costs associated with computing resources. Given the significance of sustainability, cost efficiency plays a critical role in establishing resilient edge networks. Our numerical and simulation results validate that the proposed scheme surpasses existing techniques like shortest estimated latency first (SELF), shortest estimated buffer first (SEBF), and random deployment (RD) in minimizing the total cost of deploying edge nodes, network delay, packet loss, and energy consumption