Mobility-aware hierarchical fog computing framework for Industrial Internet of Things (IIoT)

The Industrial Internet of Things (IIoTs) is an emerging area that forms the collaborative environment for devices to share resources. In IIoT, many sensors, actuators, and other devices are used to improve industrial efficiency. As most of the devices are mobile; therefore, the impact of mobility can be seen in terms of low-device utilization. Thus, most of the time, the available resources are underutilized. Therefore, the inception of the fog computing model in IIoT has reduced the communication delay in executing complex tasks. However, it is not feasible to cover the entire region through fog nodes; therefore, fog node selection and placement is still the challenging task. This paper proposes a multi-level hierarchical fog node deployment model for the industrial environment. Moreover, the scheme utilized the IoT devices as a fog node; however, the selection depends on energy, path/location, network properties, storage, and available computing resources. Therefore, the scheme used the location-aware module before engaging the device for task computation. The framework is evaluated in terms of memory, CPU, scalability, and system efficiency; also compared with the existing approach in terms of task acceptance rate. The scheme is compared with xFogSim framework that is capable to handle workload upto 1000 devices. However, the task acceptance ratio is higher in the proposed framework due to its multi-tier model. The workload acceptance ratio is 85% reported with 3000 devices; whereas, in xFogsim the ratio is reduced to approx. 68%. The primary reason for high workload acceptation is that the proposed solution utilizes the unused resources of the user devices for computations

Cellular, Wide-Area, and Non-Terrestrial IoT: A Survey on 5G Advances and the Road Towards 6G

The next wave of wireless technologies is proliferating in connecting things among themselves as well as to humans. In the era of the Internet of things (IoT), billions of sensors, machines, vehicles, drones, and robots will be connected, making the world around us smarter. The IoT will encompass devices that must wirelessly communicate a diverse set of data gathered from the environment for myriad new applications. The ultimate goal is to extract insights from this data and develop solutions that improve quality of life and generate new revenue. Providing large-scale, long-lasting, reliable, and near real-time connectivity is the major challenge in enabling a smart connected world. This paper provides a comprehensive survey on existing and emerging communication solutions for serving IoT applications in the context of cellular, wide-area, as well as non-terrestrial networks. Specifically, wireless technology enhancements for providing IoT access in fifth-generation (5G) and beyond cellular networks, and communication networks over the unlicensed spectrum are presented. Aligned with the main key performance indicators of 5G and beyond 5G networks, we investigate solutions and standards that enable energy efficiency, reliability, low latency, and scalability (connection density) of current and future IoT networks. The solutions include grant-free access and channel coding for short-packet communications, non-orthogonal multiple access, and on-device intelligence. Further, a vision of new paradigm shifts in communication networks in the 2030s is provided, and the integration of the associated new technologies like artificial intelligence, non-terrestrial networks, and new spectra is elaborated. Finally, future research directions toward beyond 5G IoT networks are pointed out.Comment: Submitted for review to IEEE CS&

Intelligent Circuits and Systems

ICICS-2020 is the third conference initiated by the School of Electronics and Electrical Engineering at Lovely Professional University that explored recent innovations of researchers working for the development of smart and green technologies in the fields of Energy, Electronics, Communications, Computers, and Control. ICICS provides innovators to identify new opportunities for the social and economic benefits of society.　 This conference bridges the gap between academics and R&D institutions, social visionaries, and experts from all strata of society to present their ongoing research activities and foster research relations between them. It provides opportunities for the exchange of new ideas, applications, and experiences in the field of smart technologies and finding global partners for future collaboration. The ICICS-2020 was conducted in two broad categories, Intelligent Circuits & Intelligent Systems and Emerging Technologies in Electrical Engineering

A Survey on Energy-Efficient Strategies in Static Wireless Sensor Networks

A comprehensive analysis on the energy-efficient strategy in static Wireless Sensor Networks (WSNs) that are not equipped with any energy harvesting modules is conducted in this article. First, a novel generic mathematical definition of Energy Efficiency (EE) is proposed, which takes the acquisition rate of valid data, the total energy consumption, and the network lifetime of WSNs into consideration simultaneously. To the best of our knowledge, this is the first time that the EE of WSNs is mathematically defined. The energy consumption characteristics of each individual sensor node and the whole network are expounded at length. Accordingly, the concepts concerning EE, namely the Energy-Efficient Means, the Energy-Efficient Tier, and the Energy-Efficient Perspective, are proposed. Subsequently, the relevant energy-efficient strategies proposed from 2002 to 2019 are tracked and reviewed. Specifically, they respectively are classified into five categories: the Energy-Efficient Media Access Control protocol, the Mobile Node Assistance Scheme, the Energy-Efficient Clustering Scheme, the Energy-Efficient Routing Scheme, and the Compressive Sensing--based Scheme. A detailed elaboration on both of the basic principle and the evolution of them is made. Finally, further analysis on the categories is made and the related conclusion is drawn. To be specific, the interdependence among them, the relationships between each of them, and the Energy-Efficient Means, the Energy-Efficient Tier, and the Energy-Efficient Perspective are analyzed in detail. In addition, the specific applicable scenarios for each of them and the relevant statistical analysis are detailed. The proportion and the number of citations for each category are illustrated by the statistical chart. In addition, the existing opportunities and challenges facing WSNs in the context of the new computing paradigm and the feasible direction concerning EE in the future are pointed out

Federated Domain Generalization: A Survey

Machine learning typically relies on the assumption that training and testing distributions are identical and that data is centrally stored for training and testing. However, in real-world scenarios, distributions may differ significantly and data is often distributed across different devices, organizations, or edge nodes. Consequently, it is imperative to develop models that can effectively generalize to unseen distributions where data is distributed across different domains. In response to this challenge, there has been a surge of interest in federated domain generalization (FDG) in recent years. FDG combines the strengths of federated learning (FL) and domain generalization (DG) techniques to enable multiple source domains to collaboratively learn a model capable of directly generalizing to unseen domains while preserving data privacy. However, generalizing the federated model under domain shifts is a technically challenging problem that has received scant attention in the research area so far. This paper presents the first survey of recent advances in this area. Initially, we discuss the development process from traditional machine learning to domain adaptation and domain generalization, leading to FDG as well as provide the corresponding formal definition. Then, we categorize recent methodologies into four classes: federated domain alignment, data manipulation, learning strategies, and aggregation optimization, and present suitable algorithms in detail for each category. Next, we introduce commonly used datasets, applications, evaluations, and benchmarks. Finally, we conclude this survey by providing some potential research topics for the future

Optimization and Communication in UAV Networks

UAVs are becoming a reality and attract increasing attention. They can be remotely controlled or completely autonomous and be used alone or as a fleet and in a large set of applications. They are constrained by hardware since they cannot be too heavy and rely on batteries. Their use still raises a large set of exciting new challenges in terms of trajectory optimization and positioning when they are used alone or in cooperation, and communication when they evolve in swarm, to name but a few examples. This book presents some new original contributions regarding UAV or UAV swarm optimization and communication aspects

DESIGN AND OPTIMIZATION OF SIMULTANEOUS WIRELESS INFORMATION AND POWER TRANSFER SYSTEMS

The recent trends in the domain of wireless communications indicate severe upcoming challenges, both in terms of infrastructure as well as design of novel techniques. On the other hand, the world population keeps witnessing or hearing about new generations of mobile/wireless technologies within every half to one decade. It is certain the wireless communication systems have enabled the exchange of information without any physical cable(s), however, the dependence of the mobile devices on the power cables still persist. Each passing year unveils several critical challenges related to the increasing capacity and performance needs, power optimization at complex hardware circuitries, mobility of the users, and demand for even better energy efficiency algorithms at the wireless devices. Moreover, an additional issue is raised in the form of continuous battery drainage at these limited-power devices for sufficing their assertive demands. In this regard, optimal performance at any device is heavily constrained by either wired, or an inductive based wireless recharging of the equipment on a continuous basis. This process is very inconvenient and such a problem is foreseen to persist in future, irrespective of the wireless communication method used. Recently, a promising idea for simultaneous wireless radio-frequency (RF) transmission of information and energy came into spotlight during the last decade. This technique does not only guarantee a more flexible recharging alternative, but also ensures its co-existence with any of the existing (RF-based) or alternatively proposed methods of wireless communications, such as visible light communications (VLC) (e.g., Light Fidelity (Li-Fi)), optical communications (e.g., LASER-equipped communication systems), and far-envisioned quantum-based communication systems. In addition, this scheme is expected to cater to the needs of many current and future technologies like wearable devices, sensors used in hazardous areas, 5G and beyond, etc. This Thesis presents a detailed investigation of several interesting scenarios in this direction, specifically concerning design and optimization of such RF-based power transfer systems. The first chapter of this Thesis provides a detailed overview of the considered topic, which serves as the foundation step. The details include the highlights about its main contributions, discussion about the adopted mathematical (optimization) tools, and further refined minutiae about its organization. Following this, a detailed survey on the wireless power transmission (WPT) techniques is provided, which includes the discussion about historical developments of WPT comprising its present forms, consideration of WPT with wireless communications, and its compatibility with the existing techniques. Moreover, a review on various types of RF energy harvesting (EH) modules is incorporated, along with a brief and general overview on the system modeling, the modeling assumptions, and recent industrial considerations. Furthermore, this Thesis work has been divided into three main research topics, as follows. Firstly, the notion of simultaneous wireless information and power transmission (SWIPT) is investigated in conjunction with the cooperative systems framework consisting of single source, multiple relays and multiple users. In this context, several interesting aspects like relay selection, multi-carrier, and resource allocation are considered, along with problem formulations dealing with either maximization of throughput, maximization of harvested energy, or both. Secondly, this Thesis builds up on the idea of transmit precoder design for wireless multigroup multicasting systems in conjunction with SWIPT. Herein, the advantages of adopting separate multicasting and energy precoder designs are illustrated, where we investigate the benefits of multiple antenna transmitters by exploiting the similarities between broadcasting information and wirelessly transferring power. The proposed design does not only facilitates the SWIPT mechanism, but may also serve as a potential candidate to complement the separate waveform designing mechanism with exclusive RF signals meant for information and power transmissions, respectively. Lastly, a novel mechanism is developed to establish a relationship between the SWIPT and cache-enabled cooperative systems. In this direction, benefits of adopting the SWIPT-caching framework are illustrated, with special emphasis on an enhanced rate-energy (R-E) trade-off in contrast to the traditional SWIPT systems. The common notion in the context of SWIPT revolves around the transmission of information, and storage of power. In this vein, the proposed work investigates the system wherein both information and power can be transmitted and stored. The Thesis finally concludes with insights on the future directions and open research challenges associated with the considered framework

Channel Access in Wireless Networks: Protocol Design of Energy-Aware Schemes for the IoT and Analysis of Existing Technologies

The design of channel access policies has been an object of study since the deployment of the first wireless networks, as the Medium Access Control (MAC) layer is responsible for coordinating transmissions to a shared channel and plays a key role in the network performance. While the original target was the system throughput, over the years the focus switched to communication latency, Quality of Service (QoS) guarantees, energy consumption, spectrum efficiency, and any combination of such goals. The basic mechanisms to use a shared channel, such as ALOHA, TDMA- and FDMA-based policies, have been introduced decades ago. Nonetheless, the continuous evolution of wireless networks and the emergence of new communication paradigms demand the development of new strategies to adapt and optimize the standard approaches so as to satisfy the requirements of applications and devices. This thesis proposes several channel access schemes for novel wireless technologies, in particular Internet of Things (IoT) networks, the Long-Term Evolution (LTE) cellular standard, and mmWave communication with the IEEE802.11ad standard. The first part of the thesis concerns energy-aware channel access policies for IoT networks, which typically include several battery-powered sensors. In scenarios with energy restrictions, traditional protocols that do not consider the energy consumption may lead to the premature death of the network and unreliable performance expectations. The proposed schemes show the importance of accurately characterizing all the sources of energy consumption (and inflow, in the case of energy harvesting), which need to be included in the protocol design. In particular, the schemes presented in this thesis exploit data processing and compression techniques to trade off QoS for lifetime. We investigate contention-free and contention-based chanel access policies for different scenarios and application requirements. While the energy-aware schemes proposed for IoT networks are based on a clean-slate approach that is agnostic of the communication technology used, the second part of the thesis is focused on the LTE and IEEE802.11ad standards. As regards LTE, the study proposed in this thesis shows how to use machine-learning techniques to infer the collision multiplicity in the channel access phase, information that can be used to understand when the network is congested and improve the contention resolution mechanism. This is especially useful for massive access scenarios; in the last years, in fact, the research community has been investigating on the use of LTE for Machine-Type Communication (MTC). As regards the standard IEEE802.11ad, instead, it provides a hybrid MAC layer with contention-based and contention-free scheduled allocations, and a dynamic channel time allocation mechanism built on top of such schedule. Although this hybrid scheme is expected to meet heterogeneous requirements, it is still not clear how to develop a schedule based on the various traffic flows and their demands. A mathematical model is necessary to understand the performance and limits of the possible types of allocations and guide the scheduling process. In this thesis, we propose a model for the contention-based access periods which is aware of the interleaving of the available channel time with contention-free allocations

WOFEX 2021 : 19th annual workshop, Ostrava, 1th September 2021 : proceedings of papers

The workshop WOFEX 2021 (PhD workshop of Faculty of Electrical Engineer-ing and Computer Science) was held on September 1st September 2021 at the VSB – Technical University of Ostrava. The workshop offers an opportunity for students to meet and share their research experiences, to discover commonalities in research and studentship, and to foster a collaborative environment for joint problem solving. PhD students are encouraged to attend in order to ensure a broad, unconfined discussion. In that view, this workshop is intended for students and researchers of this faculty offering opportunities to meet new colleagues.Ostrav