We are living in a world where massive end devices perform computing everywhere and everyday. However, these devices are constrained by the battery and computational resources. With the increasing ...number of intelligent applications (e.g., augmented reality and face recognition) that require much more computational power, they shift to perform computation offloading to the cloud, known as mobile cloud computing (MCC). Unfortunately, the cloud is usually far away from end devices, leading to a high latency as well as the bad quality of experience (QoE) for latency-sensitive applications. In this context, the emergence of edge computing is no coincidence. Edge computing extends the cloud to the edge of the network, close to end users, bringing ultra-low latency and high bandwidth. Consequently, there is a trend of computation offloading toward edge computing. In this paper, we provide a comprehensive perspective on this trend. First, we give an insight into the architecture refactoring in edge computing. Based on that insight, this paper reviews the state-of-the-art research on computation offloading in terms of application partitioning, task allocation, resource management, and distributed execution, with highlighting features for edge computing. Then, we illustrate some disruptive application scenarios that we envision as critical drivers for the flourish of edge computing, such as real-time video analytics, smart "things" (e.g., smart city and smart home), vehicle applications, and cloud gaming. Finally, we discuss the opportunities and future research directions.
This paper considers the massive connectivity application in which a large number of devices communicate with a base-station (BS) in a sporadic fashion. Device activity detection and channel ...estimation are central problems in such a scenario. Due to the large number of potential devices, the devices need to be assigned non-orthogonal signature sequences. The main objective of this paper is to show that by using random signature sequences and by exploiting sparsity in the user activity pattern, the joint user detection and channel estimation problem can be formulated as a compressed sensing single measurement vector (SMV) or multiple measurement vector (MMV) problem depending on whether the BS has a single antenna or multiple antennas and efficiently solved using an approximate message passing (AMP) algorithm. This paper proposes an AMP algorithm design that exploits the statistics of the wireless channel and provides an analytical characterization of the probabilities of false alarm and missed detection via state evolution. We consider two cases depending on whether or not the large-scale component of the channel fading is known at the BS and design the minimum mean squared error denoiser for AMP according to the channel statistics. Simulation results demonstrate the substantial advantage of exploiting the channel statistics in AMP design; however, knowing the large-scale fading component does not appear to offer tangible benefits. For the multiple-antenna case, we employ two different AMP algorithms, namely the AMP with vector denoiser and the parallel AMP-MMV, and quantify the benefit of deploying multiple antennas.
Internet of Things (IoT) is an ever-expanding ecosystem that integrates software, hardware, physical objects, and computing devices to communicate, collect, and exchange data. The IoT provides a ...seamless platform to facilitate interactions between humans and a variety of physical and virtual things, including personalized healthcare domains. Lack of access to medical resources, growth of the elderly population with chronic diseases and their needs for remote monitoring, an increase in medical costs, and the desire for telemedicine in developing countries, make the IoT an interesting subject in healthcare systems. The IoT has a potential to decrease the strain on sanitary systems besides providing tailored health services to improve the quality of life. Therefore, this paper aims to identify, compare systematically, and classify existing investigations taxonomically in the Healthcare IoT (HIoT) systems by reviewing 146 articles between 2015 and 2020. Additionally, we present a comprehensive taxonomy in the HIoT, analyze the articles technically, and classify them into five categories, including sensor-based, resource-based, communication-based, application-based, and security-based approaches. Furthermore, the benefits and limitations of the selected methods, with a comprehensive comparison in terms of evaluation techniques, evaluation tools, and evaluation metrics, are included. Finally, based on the reviewed studies, power management, trust and privacy, fog computing, and resource management as leading open issues; tactile Internet, social networks, big data analytics, SDN/NFV, Internet of nano things, and blockchain as important future trends; and interoperability, real-testbed implementation, scalability, and mobility as challenges are worth more studying and researching in HIoT systems.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
An individual's health is one of the essential aspects of life, but due to the limited technology at health care centers, many people face various restrictions during their treatment. These days, ...Internet-of-Things (IoT) is the most fascinating topic that provides solutions to these limitations in various ways. The IoT is utilized in various healthcare conducts that include detection, treatment, and monitoring of diseases. Wearable devices are a part of IoT that is proposed for helping patients to get the correct treatment. The conventional communication networks developed for humans-based applications face many issues like stringent latency, restricted computing capability, and short battery life. On the other hand, the onset of 5G has developed a new set of technologies that offer the vital "backbone” for connecting to the billions of devices for the upcoming IoT that would completely modify our professional and private lives. Due to the data capabilities, intelligent management, and superfast connectivity of 5G, this network has enabled new health care opportunities that include treatment, data analytics, diagnostics, and imaging. In the current review, a systematic literature survey of IoT, IoT-based wearable devices, and the role of 5G in IoT for healthcare is described in detail. Furthermore, we have explained the usage of wearable devices in detecting the issue in terms of healthcare, such as curing, monitoring, and detection of disease. Nevertheless, this review article also emphasizes the employment of IoT architecture and its wearable devices in addition to the upcoming research challenges related to this area.
•The trending Internet of Things (IoT)-based wearable technologies that were used in recent years have been discussed.•An IoT-based wearable devices were indorsed to encourage its forthcoming applications in healthcare.•IoT technologies assumed to be one of the key pillars of the fourth industrial revolution in innovations.•Wearable devices, such as smart watches and fitness bands, have become part of the everyday life.•The impact of 5G on Internet of Medical Things (IoMT), IoT and IoT-based wearable devices have been discussed.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
•Augmented Reality (AR) is a major part of industry 4.0 advancements.•While AR is not ready yet for industrial deployment in some areas, it is already used in others.•Hardware and software still ...require improvements in certain areas of AR.•The context of research concerning AR is getting increasingly broader as its implementation rises.•The future research needs to focus on intelligent manufacturing applications of AR.
Industry increasingly moves towards digitally enabled ‘smart factories’ that utilise the internet of things (IoT) to realise intelligent manufacturing concepts like predictive maintenance or extensive machine to machine communication. A core technology to facilitate human integration in such a system is augmented reality (AR), which provides people with an interface to interact with the digital world of a smart factory. While AR is not ready yet for industrial deployment in some areas, it is already used in others. To provide an overview of research activities concerning AR in certain shop floor operations, a total of 96 relevant papers from 2011 to 2018 are reviewed. This paper presents the state of the art, the current challenges, and future directions of manufacturing related AR research through a systematic literature review and a citation network analysis. The results of this review indicate that the context of research concerning AR gets increasingly broader, especially by addressing challenges when implementing AR solutions.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Internet of Things (IoT) analytics is an essential mean to derive knowledge and support applications for smart homes. Connected appliances and devices inside the smart home produce a significant ...amount of data about consumers and how they go about their daily activities. IoT analytics can aid in personalizing applications that benefit both homeowners and the ever growing industries that need to tap into consumers profiles. This article presents a new platform that enables innovative analytics on IoT captured data from smart homes. We propose the use of fog nodes and cloud system to allow data-driven services and address the challenges of complexities and resource demands for online and offline data processing, storage, and classification analysis. We discuss in this paper the requirements and the design components of the system. To validate the platform and present meaningful results, we present a case study using a dataset acquired from real smart home in Vancouver, Canada. The results of the experiments show clearly the benefit and practicality of the proposed platform.
•Knowledge base solution for IoT Data Analytics Applications in Smart Homes.•A comprehensive framework for data collection, processing and real-time recognition.•Building a distinguished profile for activities based on the chronological order of their sensors.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
With the rapid development of the Internet of Things (IoT), the number of sensors utilized for the IoT is expected to exceed 200 billion by 2025. Thus, sustainable energy supplies without the ...recharging and replacement of the charge storage device have become increasingly important. Among various energy harvesters, the triboelectric nanogenerator (TENG) has attracted considerable attention due to its high instantaneous output power, broad selection of available materials, eco-friendly and inexpensive fabrication process, and various working modes customized for target applications. The TENG harvests electrical energy from wasted mechanical energy in the ambient environment. Three types of operational modes based on contact-separation, sliding, and freestanding are reviewed for two different configurations with a double-electrode and a single-electrode structure in the TENGs. Various charge transfer mechanisms to explain the operational principles of TENGs during triboelectrification are also reviewed for electron, ion, and material transfers. Thereafter, diverse methodologies to enhance the output power considering the energy harvesting efficiency and energy transferring efficiency are surveyed. Moreover, approaches involving not only energy harvesting by a TENG but also energy storage by a charge storage device are also reviewed. Finally, a variety of applications with TENGs are introduced. This review can help to advance TENGs for use in self-powered sensors, energy harvesters, and other systems. It can also contribute to assisting with more comprehensive and rational designs of TENGs for various applications.
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The European Telecommunications Standards Institute (ETSI) has introduced the paradigm of Multi-Access Edge Computing (MEC) to enable efficient and fast data processing in mobile networks. Among ...other technological requirements, security and privacy are significant factors in the realization of MEC deployments. In this paper, we analyse the security and privacy of the MEC system. We introduce a thorough investigation of the identification and the analysis of threat vectors in the ETSI standardized MEC architecture. Furthermore, we analyse the vulnerabilities leading to the identified threat vectors and propose potential security solutions to overcome these vulnerabilities. The privacy issues of MEC are also highlighted, and clear objectives for preserving privacy are defined. Finally, we present future directives to enhance the security and privacy of MEC services.
In this paper, we study the problem of user activity detection and large-scale fading coefficient estimation in a random access wireless uplink with a massive MIMO base station with a large number ...<inline-formula> <tex-math notation="LaTeX">M </tex-math></inline-formula> of antennas and a large number of wireless single-antenna devices (users). We consider a block fading channel model where the <inline-formula> <tex-math notation="LaTeX">M </tex-math></inline-formula>-dimensional channel vector of each user remains constant over a coherence block containing <inline-formula> <tex-math notation="LaTeX">L </tex-math></inline-formula> signal dimensions in time-frequency. In the considered setting, the number of potential users <inline-formula> <tex-math notation="LaTeX">K_{\text {tot}} </tex-math></inline-formula> is much larger than <inline-formula> <tex-math notation="LaTeX">L </tex-math></inline-formula> but at each time slot only <inline-formula> <tex-math notation="LaTeX">K_{a} \ll K_{\text {tot}} </tex-math></inline-formula> of them are active. Previous results, based on compressed sensing, require that <inline-formula> <tex-math notation="LaTeX">K_{a}\le L </tex-math></inline-formula>, which is a bottleneck in massive deployment scenarios. In this work, we show that such limitation can be overcome when the number of base station antennas <inline-formula> <tex-math notation="LaTeX">M </tex-math></inline-formula> is sufficiently large. More specifically, we prove that with a coherence block of dimension <inline-formula> <tex-math notation="LaTeX">L </tex-math></inline-formula> and a number of antennas <inline-formula> <tex-math notation="LaTeX">M </tex-math></inline-formula> such that <inline-formula> <tex-math notation="LaTeX">K_{a}/M = o(1) </tex-math></inline-formula>, one can identify <inline-formula> <tex-math notation="LaTeX">K_{a} = O\left({L^{2}/\log ^{2}\left({\frac {K_{\text {tot}}}{K_{a}}}\right)}\right) </tex-math></inline-formula> active users, which is much larger than the previously known bounds. We also provide two algorithms. One is based on Non-Negative Least-Squares, for which the above scaling result can be rigorously proved. The other consists of a low-complexity iterative componentwise minimization of the likelihood function of the underlying problem. While for this algorithm a rigorous proof cannot be given, we analyze a constrained version of the Maximum Likelihood (ML) problem (a combinatorial optimization with exponential complexity) and find the same fundamental scaling law for the number of identifiable users. Therefore, we conjecture that the low-complexity (approximated) ML algorithm also achieves the same scaling law and we demonstrate its performance by simulation. We also compare the discussed methods with the (Bayesian) MMV-AMP algorithm, recently proposed for the same setting, and show superior performance and better numerical stability. Finally, we use the discussed approximated ML algorithm as the inner decoder in a concatenated coding scheme for unsourced random access , a grant-free uncoordinated multiple access scheme where all users make use of the same codebook, and the receiver must produce the list of transmitted messages, irrespectively of the identity of the transmitters. We show that reliable communication is possible at any <inline-formula> <tex-math notation="LaTeX">E_{b}/N_{0} </tex-math></inline-formula> provided that a sufficiently large number of base station antennas is used, and that a sum spectral efficiency in the order of <inline-formula> <tex-math notation="LaTeX">\mathcal {O}(L\log (L)) </tex-math></inline-formula> is achievable.
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