Performance Improvement for Industrial Internet of Things Systems based on Optimization of Contention Access Period in Superframes
Chapter One
Introduction
1.1 Preface
This chapter intends to introduce the main ideas of the thesis. First, an overview of the Internet of Things (IoT), IIoT structure systems, and their differences between IoT and IIoT will be presented. Next, the communication protocols of IIoT have been discussed. Besides, the research scope presents in detail discussion. The problem statement is introduced, followed by the research objectives. Finally, the methodology, motivation of this thesis, and thesis contributions are described in more detail, concluded by the thesis organization.
1.1.1 Internet of Things
Recently, the Internet of Things (IoT) becomes is an essential technology due to its significant impact on human life [1] . The term IoT has been introduced in 1999 by Kevin Ashton to connect tiny devices to the Internet and persons to devices. Massive amounts of IoT objects will predict to be installed in machines, humans, vehicles, buildings, and environments. These objects include smartphones, tablets, cameras, smart sensors, and actuators [2] , [3] . Wireless Sensor Network (WSN) is one of the most essential parts of the IoT, which is widely studied and applied wirelessly in different environments for compiling and exchanges data through the coordination among source nodes and sink nodes [4] , [5] . The smart sensors are deployed to establish network connectivity to the Internet through internet protocol (IP), which is powered by batteries that make it subject to energy consumption constraints [6] .
IoT definition is still under discussion, but there is a primary role of IoT devices through providing access to information and services over billions of heterogeneous devices (things), ranging from resource-constrained to powerful tools [7] . Theoretically, IoT means interconnect things and objects which are individually addressable and interact with each other using standard communication protocols [3] , [8] . The new definition of IoT is a new way of addressing issues with remarkable social impact, relevant to new ways for educating, new ways of conceiving homes and cities on a human scale, and quickly responsive to the human needs, which are recent ways of addressing energy management issues, it is modern approaches for electronic healthcare. Rather people and objects have interacted with each other as peers. Objects interaction will allow for creating applications with a higher penetration rate and better virtual representation [9] .
IoT is used for enabling monitoring and control of a myriad of interconnected devices. Managing huge heterogeneous resources of the IoT becomes a great challenge, especially in those cases that it operates on a limited battery [10] . IoT devices are more resource-constrained in terms of energy efficiency that requires to development of an appropriate operating system to build upon these devices [11] . The requirements of the operating systems for IoT nodes are to provide energy saving by using techniques just as radio duty cycling and minimizing the number of periodic tasks that need to be executed. Various kinds of IoT include identification, sensing, communication technologies, computation, services, and semantics [12] .
IoT applications in manufacturing systems called the Industrial Internet of Things (IIoT). The IIoT considers as the base of a new level of organization, management of industrial value chains that enables high flexibility, and resource-saving production as well as enhanced individualization for products at the cost of the massive production. The IIoT is a natural development of IoT; IIoT is a large scale of collection heterogeneous of resources, which include smart devices, machines, communication protocols, networks, and end-users. IIoT sensors are being disseminated increasingly in different kinds of industrial environments, for monitoring machines movement in the smart factory, sense and acquisition phenomena from their surrounding world, and the digital representation of products operations in the smart manufacturing. One of the most important parts of IIoT is the cyber-physical systems (CPS), which computes platforms that monitoring and control physical processes. CPS enables condition monitoring, remote diagnosis, and remote control of the production systems in real-time. IIoT is an emerging technology, it can be able to change industrial companies environments into a new term called smart factory [13] , which considered as the main base for CPS, dynamically organizes and optimizes production processes with focuses on the resource-utilization costs, availability, material, and labor based on data generated and collected by an underlying CPS, even across company boundaries. In the context of smart factories, smart products know their own identity, history, specification, documentation, and also control their production process [14] .
The architecture system of the IIoT network consists of three main layers. The first layer is physical, which is composed of several components such as smart sensors and actuators for collecting phenomena from their around environments. The second layer is a network that consists of many smart resources, which are used for data communications between devices ranging from the network layer to the application layer. The third layer is an application layer that utilizes big data analytics to introduce respected services to end-users [15] . IIoT is a promising technology that enables operators to understand how to optimize productivity or detect a failure before it occurs; potentially saving companies billions of dollars per year. The major IIoT applications are extended to motion control, machine-to-machine interactions, predictive maintenance, smart-grid energy management, big data analytics, and interconnected medical systems [8] . Many standard communication protocols have been developed to operate in each layer of the IIoT networking protocol stack [16] , [17] .
1.1.2 IIoT Communication Protocols
IIoT is a standardization technology that supports a heterogeneous set of communication protocols stack, widely setting up in every layer for establishing network connectivity, these protocols specifically provide services to end-users at an application layer [9] . Constrained Application Protocol (CoAP) is adopted at an application layer; CoAP is a better protocol for transferring streaming data between users and cloud platforms, which operate over Transmission Control Protocol (TCP) and User Datagram Protocol (UDP) [18] . TCP and UDP are expected to be adopted in the transport layer that helps to maintain the sensor data flow [18] , [19] . The Internet Engineering Task Force (IETF) and the Routing for Low Power and Lossy (RPL) Networks protocols have to be adopted [18] to work well at the network layer, which routes and foreword information on an appropriate path [18] . In the Medium Access Control (MAC) sublayer, the IEEE 802.15.4e protocol is developed, which can use a rigid slot structure with centralized and distributed scheduling to achieve high energy efficiency. The MAC sublayer manages collisions and helps in the energy operations of sensor nodes. In the physical layer, the most prominent standard in low-power radio technology is an IEEE 802.15.4-2006, which is expected to be sufficient for meeting the energy efficiency requirements of the machine to machine (M2M) devices [19] . The physical layer is very useful for connecting devices and preparing the radio, channel, modulation, transmission, and reception bits of data on the physical medium.
In the context of IoT sensors used in the IIoT applications; different methods are proposed and analyzed for improving performance based on the MAC sublayer communication protocols. The most popular MAC communication protocols are IEEE 802.15.4 and IEEE 802.15.4e, where the focuses of this study. IEEE 802.15.4 releases officially by the IEEE Working Group in May 2003 to meet the critical requirements of the IoT applications and wireless communication. The main objectives of the IEEE 802.15.4 are to provide variable data rates that reach up to 10 kbps, low-cost devices, low-power consumption, and extended coverage area [20] , [21] .
IEEE 802.15.4e amendment is published in 2012, for increasing the performance of the IEEE 802.15.4-2011 protocol [22] and can be supported by industrial markets [23] . The MAC sublayer protocols are defined as the superframe structure, and the nodes used the carrier sense multiple access with collision avoidance (CSMA/CA) as a channel access mechanism. The (CSMA/CA) is developed based on sensing the signal before transmission. The coordinator wants to transmit packets to the peripheral nodes, it will sense the channel if it is available for use or busy. If the channel is busy by the transmission of another packet, the coordinator waits some periods then tries to send it again [24] . Several studies are introduced a detailed explanation of the superframe structure [25] , [26] , [27] , [28] , [29] , [30] , and [31] . The superframe structure consists of two portions: an Active Period and optional an Inactive Period. In an Inactive Period, the devices enter the sleep state to save energy. The active period is divided into 16 equal-long timeslots, which include three main portions are Beacon portion, the Contention Access Period (CAP) portion, and the Contention Free Period (CFP) portion. The length of each superframe is equal to the numbers of the timeslots of the CAP, and the numbers of the timeslots of the CFP [28] .
However, one of the critical issues that hinder the development of IIoT networks is performance. Many research efforts have been made in this area that aimed to improve the performance-based superframe structure of the IEEE 802.15.4 and the IEEE 802.15.4e. This thesis proposed a CAP reduction MAC protocol to reduce the number of time slots in order to improve performance and it gives an optimal distribution of the devices based on the superframe structure of the IEEE 802.15.4e.
1.2 Thesis Scope
This research is directed toward improving the performance of the IIoT sensors that are deployed in the smart factory. IIoT promotes such goals by fostering research into technologies, methods, concepts, and tools that will improve operational efficiency, flexibility, reduce costs, and improve the quality of human life. Now a day, it becomes a crucial tool for all smart industries. The performance of the IIoT nodes becomes a very critical issue. The thesis will propose technical solutions for the IIoT systems in order to address the performance issue, which is composed of throughput, packets delay, and energy consumption. The scope of the thesis is focused on the MAC sublayer for the IIoT system based on the superframe structure of the IEEE 802.15.4e DSME protocol.
1.3 Problem Statement
Some important issues of the IIoT networks are performance, reliability, scalability, robustness, network lifetime, latency, throughput, and mobility that need to be addressed. One of the most essential criteria for an IIoT system is to design and develop a reliable network with reasonable timely data transfer between the nodes and the base station node depends on the communications protocols. IEEE 802.15.4e in particularly suffers from performance degradation, which depends on the distribution of the sensors. This study attempts to enhance the performance by an optimal distribution of the sensors to improve system throughput, packets delay, and energy consumption.
1.4 Thesis Significance
IIoT is played a vital role in the areas ranging from agricultural to smart healthcare technology, where smart healthcare becomes one of the most important medical services recently, which utilizes for remote monitoring and tracking patients that help the doctors to give timely advice to the patients as diseases of Cardiology, Cancer, Diabetes diseases, and COVID – 19 patients. Moreover, one of the best-known IIoT deployments that are deployed for measuring the consumption of machine units for aircraft to replace them with new ones, this operation helps for reducing preventive maintenance. The significance of the thesis comes as a result of improving the performance of the IIoT system. Despite the complex applications, which are clarified through this study, the adoption of IIoT is growing rapidly.
1.5 Thesis Objectives
The major objective of this thesis is to develop a new technique for improving the performance of the IIoT network based on the IEEE 802.15.4e protocol. The proposed technique is deployed for computing an optimal value of the Contention Access Period (CAP) to reduce the number of time slots per superframe so as to achieve an acceptable optimal distribution of the sensors.
1.6 Thesis Contributions
The contribution of this thesis is developing a MAC protocol for improving the IIoT network performance based on the IEEE 802.15.4e protocol by reducing the time slots of the CAP period. This reduction depends on the values of the superframe order (SO), the SO value is setting up as a variable value. The proposed protocol improves the performance of
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the IIoT network that is tested under a Cooja simulator, which gives an optimal distribution of the sensors. Accordingly, throughput is maximized, packets delay is minimized and the energy consumption is reduced. Moreover, the overall total costs has been decreased
1.7 Thesis Methodology
The experimental method is used to address the problem formulations of this thesis. Firstly, a literature study is conducted to review different technologies to get an understanding of IIoT systems technology, IEEE 802.15.4e, IIoT architecture, Contiki-OS, and the necessary components of the Cooja simulator. Secondly, the process of setting up a simulation to conduct experiments and gather quantitative data was also conducted. IIoT has complex issues, it is used in high connected heterogeneous nodes, which causes performance degradation in wireless communication, thus throughout is decreased and the packets delay is increased. In order to develop a technical solution to this issue, a new CAP size-reduction MAC protocol is proposed for reducing the time slots per superframe. The proposed protocol can reduce the CAP duration by increasing the superframe order (SO). If SO is increased, the CAP is decreased, and the CFP is increased. When the CAP was reduced, the number of time slots per the CAP duration is minimized. Simultaneously, it maximizes the bandwidth. To evaluate this protocol, several experiments are done by using the Cooja simulator, which is a Linux-based simulation tool used for measuring three main metrics are throughput, packets delay, and energy consumption. Tmote Sky and Zolertia Z1 are smart sensors, which are utilized through all experiments for comparing the performance of the proposed protocol with the classical performance of an original MAC protocol in terms of the throughput, packets delay, and energy consumption.
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1.8 Thesis Organization
This research is organized as follows: –
Chapter 2 provides background and a literature review of IEEE 802.15 .4e MAC modes (DSME, TSCH, D) protocol. Also discuss the superframe structure of the IEEE 802.15.4e.
Chapter 3 describes the basic knowledge of IIoT, Industry 4.0. Cyber-Physical System, Cyber Manufacturing System, IIoT communication technologies, and Smart Factory.
Chapter 4 formally introduces the new CAP size-reduction MAC protocol based on the superframes, design specific technique for decreasing the number of time slots, then decrease the number of the sensors. This chapter also provides an experiment setup and then presents how throughput, execution time, and energy consumption can be measured based on the IEEE 802.15.4e protocol.
Chapter 5 focuses on the results of the experimental measurements, which begins by providing the first comprehensive comparisons of the performance parameters of IIoT sensor nodes based on a particular operating system. In conclusion, Chapter 6 provides a summary of this research and a listing of the significant contributions as well as some suggestions for future research directions that can build upon this work. Appendices are provided that include the Cooja simulator background and source program for throughput, packets delay, and energy consumption.