Smart Utilities IoT-Based Data Collection Scheduling

Arabian Journal for Science and Engineering https://doi.org/10.1007/s13369-023-07835-4 RESEARCH ARTICLE-COMPUTER ENGINEERING AND COMPUTER SCIENCE Smart Utilities IoT-Based Data Collection Scheduling Heba Allah Sayed1,2 · Adel Mounir Said1 · Ashraf William Ibrahim1 Received: 14 November 2022 / Accepted: 6 March 2023 © The Author(s) 2023 Abstract The Internet of Things is an ecosystem that connects billions of smart devices, meters, and sensors. These devices and sensors collect and share data for use and evaluation by organizations in different industry sectors. Humans may use the IoT to live and work more intelligently and gain total control over their lives. Consequently, IoT can be used to connect devices and integrate them with new digital technologies for customers. On the other hand, smart utility companies in the electric, gas, and water sectors need to deliver services more efficiently and analyze their operations in a way that can help optimize performance, detect growing problems in real time, and initiate fixes to avoid unplanned service interruptions. Building actual smart metering networks is costly and time-consuming. Therefore, in this paper, a new Smart Utilities Traffic Scheduling Algorithm (SUTSA) is proposed. To minimize the system complexity, the model is based on narrowband power line communication, in which a wired hidden network sends data across power lines. A simulation is performed using OPNET Modeler 14.5 to evaluate the proposed model. The results proved that the proposed model is highly scalable and achieves full network-bandwidth utilization in different situations based on different application requirements. Keywords Internet of Things · Power line communication · Scheduling · Smart meter · Smart utility 1 Introduction 1.1 Background The Internet of Things (IoT) is considered to be the third revolution in information technology. According to researchers, over three million new devices are connected to the Internet every month [1–3]. Information and communication technology is rapidly converging at three levels of technical innovation: cloud, public infrastructure for processing and exploring streams (PIPE), and devices [4–6]. The cloud is an important component of IoT because it delivers essential services for a wide range of applications. B Heba Allah Sayed Adel Mounir Said Ashraf William Ibrahim 1 Switching Department, National Telecommunication Institute (NTI), Cairo, Egypt 2 Electronics and Communication Department, Faculty of Engineering, Ain Shams University, Cairo, Egypt It allows anyone to build content and applications for consumers worldwide, thus providing a global infrastructure to generate new services [7, 8]. Networks connect things globally and maintain their identity online. This worldwide infrastructure can be accessed through mobile devices at any time and location. As a result, there is a global network of objects, users, and consumers with the ability to launch enterprises, contribute content, and create and acquire new services [9]. PIPE is used by both industries and consumers through a variety of interconnected smart devices. It includes traditional telecommunications, cables, and internet data communication networks. The devices represent the physical sensors of the IoT that aim to collect and process information. It includes personal devices, telecommunications premises, and home entertainment boxes. Currently, smart utility companies face several challenges in expanding and deploying the smart grid (SG) to replace the old electrical infrastructure. SG provides two-way digital communication between the electricity plant and the consumer [10]. It is necessary to implement a low-cost real-time network to carry out all communication operations of the various 123 Arabian Journal for Science and Engineering components of the smart grid. The key challenges are grid infrastructure, communications, security, data management, stability concerns, and energy management [11, 12]. This paper focuses on two main concerns: data management and communication issues. Data management issues: SG integrates a massive number of meters, sensors, and controllers into the power network. The data from these devices were utilized to improve the operators’ capabilities. A failure or damage might be prevented before it occurs through precise data analysis. Consequently, an appropriate platform for IoT must be used in data management design in an Internet network, in which the concepts of communication, processes, and storage should be correctly defined, and it should provide flexibility, security, dominance, administration capabilities, and scalability [13]. Communication issues: A wide range of communication technologies for deployment can be used in SG; however, they all have their own limitations, which include bandwidth limitations, distance limitations, and higher packet loss. Technologies such as 3 G, ZigBee, PLC, GPRS, PLCC, GSM, and GPRS can be used. Although wired communication, such as power line communication, goes beyond the drawbacks of wireless communication, it still has to deal with the issue of shared media [14, 15]. 1.2 Literature and Related Work The smart grid is the future of the electrical industry, which uses upgraded power system components to replace the old electrical infrastructure. It provides two-way digital communication between the electricity plant and the consumer. In addition, it can provide multi-directional communications among all partners in electrical energy [16]. Smart meters are the most important part of the smart grid they record energy usage and send the data to the utility suppliers. Currently, these are the most prevalent methods for calculating, regulating, and monitoring electricity, gas, and water usage. A smart meter is a device that provides reliable real-time monitoring, automatic data gathering, user interaction, and power control [17, 18]. Many authors have suggested different scheduling methods trying to manage communication between smart grid components with high data traffic, meet business requirements, and reduce the probability of data packet loss. Each technique is effective in its own particular parameter set. MAC layer scheduling with queue status information based on PLC was proposed in [19]. It satisfies the QoS requirements of real-time (RT) services and then uses the remaining resources for non-real-time (NRT) services; it lists users in decreasing order based on the utility function’s value. Then allocate physical-layer resources for user scheduling based on this. This technique is effective only when large 123 data rates are necessary. Also, it requires an expensive linear amplifier, which may suffer from Inter-carrier Interference between the subcarriers [20]. Therefore, our contribution is based on a narrowband PLC that overcomes this problem, minimizes system complexity, and avoids OFDM problems. An optimal interference-aware TDMA-like data collecti (...truncated)