Age of Information (AoI) is a critical metric in status update systems as these systems require the fresh updates. This letter investigates the uplink of an Internet-of-Thing (IoT) network where L nodes transmit their information packets to a base station. The effects of the arrival rate of packets at the nodes, the number of nodes in the system, and queue length of each node have been studied by devising a discrete time Markov chain (MC) model. This model helps in predicting the values of AoI and probability of packet drops in such systems. The notion of first-in first-out is used for queuing, which transmits the oldest packet first, resulting in decreasing the overall AoI of the system. The results show that AoI increases with the increase in queue length, number of nodes and arrival rate and we quantify the aforementioned metrics using the MC model. The results found using the MC model are also validated using extensive simulations. © 2012 IEEE.
Age of Information (AoI) has been introduced to characterize the newness of data which is observed in real time. In other words, it is the measure of time elapsed since the generation of last received update about a process and is a vital metric in networks such as Internet of things (IoTs), especially when the application demands fresh updates. Most of the applications require fresh data e.g., applications related to environmental monitoring, smart agriculture, body area networks etc. On the other hand backscatter communication promises to resolve one of the most challenging issues of IoT devices, i.e., making them capable for communication without the batteries. The importance of AoI in backscatter communication is paramount to gauge performance of backscatter IoT networks. This chapter addresses the significance of AoI in backscatter communication and suggests some techniques to design a communication system with minimum AoI, maximum energy efficiency, and minimum outage. © 2021, Springer Nature Switzerland AG.
The accelerated move towards the adoption of the industrial Internet of Things (IIoT) paradigm has resulted in numerous shortcomings as far as security is concerned. One of the IIoT affecting critical security threats is what is termed as the ” False Data Injection” (FDI) attack. The FDI attacks aim to mislead the industrial platforms by falsifying their sensor measurements. FDI attacks have successfully overcome the classical threat detection approaches. In this study, we present a novel method of FDI attack detection using Autoencoders (AEs). We exploit the sensor data correlation in time and space, which in turn can help identify the falsified data. Moreover, the falsified data are cleaned using the denoising AEs. Performance evaluation proves the success of our technique in detecting FDI attacks. It also significantly outperforms a support vector machine (SVM) based approach used for the same purpose. The denoising AE data cleaning algorithm is also shown to be very effective in recovering clean data from corrupted (attacked) data.
Recently, the Internet has been utilized by many applications to convey time-sensitive messages. The persistently expanding Internet coverage and its easy accessibility have offered to ascend to a problem which was once regarded as not essential to contemplate. Nowadays, the Internet has been utilized by many applications to convey time-sensitive messages. Wireless access points have widely been used but these access points have limitations regarding area coverage. So for covering a wider space, various access points need to be introduced. Therefore, when the user moves to some other place, the devices expected to switch between access points. Packet loss amid the handovers is a trivial issue. MediaSense is an Internet of Things distributed architecture enabling the development of the IoT application faster. It deals with this trivial handover issue by utilizing a protocol called Distributed Context eXchange Protocol. However, this protocol is centralized in nature and also suffers in a scenario when both sender and receiver address change simultaneously. This paper presents a mechanism to deal with this scenario and presents a distributed solution to deal with this issue within the MediaSense platform. The proposed protocol improves dissemination using retransmission mechanism to diminish packet loss. The proposed protocol has been delineated with a proof of concept chat application and the outcomes have indicated a significant improvement in terms of packet loss.
Due to the ability to handle a large number of users, low latency, and high data rates, NON-orthogonal multiple access (NOMA) is considered a promising access technology for next-generation communication systems. However, as the number of users increases, each user experiences a greater number of successive interference cancellations (SIC), causing the system’s performance to decline. With the increase in the number of users, the fraction of power allocated to each user becomes smaller. Cooperative communication in downlink NOMA is considered as a potential approach to enhance the reliability, capacity, and performance over wireless channels. Space-time block code (STBC)-aided cooperative NOMA (CNOMA) offers an opportunity to improve the weak users’ signal-to-interference-plus-noise (SINR) through strong user cooperation. In this paper, we study the symbol error probability (SEP) performance of the STBC-NOMA and derive the asymptotic expression for SEP when the network is impaired with imperfect SIC (ipSIC) and timing offsets. The simulation results show that the performance of STBC-NOMA was degraded significantly with an increase in the imperfection of SIC and timing errors and that traditional orthogonal access schemes, such as orthogonal frequency division multiple access (OFDMA) and time division multiple access (TDMA), should be used after a threshold SIC level. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.
As the number of mobile devices grows exponentially, it is critical to design a robust access scheme that can handle a large number of devices with low latency. Non-orthogonal multiple access (NOMA) is an effective approach to meet such requirements that can provide higher spectral efficiency. As an extended version, cooperative NOMA has been introduced, where the users with higher channel gains forward signals for users with weak channel gains as cooperators. The conventional cooperative NOMA (CCN) technique can provide diversity gains, which can be used to improve reliability. However, in CCN, the overhead caused by successive interference cancellations (SIC) at each user may become significant, when there exist a massive number of users, which eventually degrades the performance of NOMA considering the power and computational resource limitations of mobile devices. As an alternative, the space-time block-coded NOMA (STBC-NOMA) has been proposed to achieve diversity gain with lower SIC overhead compared to CCN. To better evaluate it, in this paper, we investigate the impact of imperfect channel state information (ipCSI), which is more realistic in real-time processing. We dervie the closed-form expression of the outage probability of STBC-NOMA with ipCSI and compare its performance with CCN and conventional NOMA. © 2021 IEEE.
The next generation of wireless communication systems will integrate terrestrial and nonterrestrial networks, targeting the coverage of the undercovered regions, especially those connected to marine activities. Unmanned aerial vehicle (UAV)-based connectivity solutions offer significant advances to support conventional terrestrial networks. However, the use of UAVs for maritime communication is still an unexplored area of research. Therefore, this article highlights different aspects of UAV-based maritime communication, including the basic architecture, various channel characteristics, and use cases. The article afterward discusses several open research problems, such as mobility management, trajectory optimization, interference management, and beam forming.
The use of quaternion orthogonal designs (QODs) to describe point-to-point communication among dual-polarized antennas has the potential to provide higher rate orthogonal and quasi-orthogonal complex designs exploiting polarization diversity among space and time diversities. Furthermore, it is essential to have a space time block code (STBC) which offers a linear and decoupled decoder which quasi-orthogonal designs fail to attain. In this paper, we show how the realm of quaternions unexpectedly offers us a possible solution and codes obtained from quaternion designs mostly achieve both linear and decoupled decoders. This motivated us to perform an indispensable search for QODs such that the code rate is bounded below by 1/2 and does not sharply decrease as the number of transmit antennas increases. It is shown that three famous recursive techniques do not satisfy this criteria and their code rates decrease rather rapidly. Therefore, we propose another method of constructing quaternion designs suitable for any number of transmit antennas and verify that these attain linear and decoupled decoders with the system model based on quaternionic channel. It is shown that such designs outperform others in terms of transmit diversity, code rates and the optimality of the proposed decoder is validated through simulation results. © 2021 by the authors.
Advances in imaging and display engineering have given rise to new and improved image and videoapplications that aim to maximize visual quality under given resource constraints (e.g., power, bandwidth).Because the human visual system is an imperfect sensor, the images/videos can be represented in a mathematicallylossy fashion but with enough fidelity that the losses are visually imperceptible—commonly termed“visually lossless.” Although a great deal of research has focused on gaining a better understanding ofthe limits of human vision when viewing natural images/video, a universally or even largely accepted definitionof visually lossless remains elusive. Differences in testing methodologies, research objectives, and targetapplications have led to multiple ad-hoc definitions that are often difficult to compare to or otherwise employ inother settings. We present a compendium of technical experiments relating to both vision science and visualquality testing that together explore the research and business perspectives of visually lossless image quality,as well as review recent scientific advances. Together, the studies presented in this paper suggest that a singledefinition of visually lossless quality might not be appropriate; rather, a better goal would be to establish varyinglevels of visually lossless quality that can be quantified in terms of the testing paradigm.
The joint and marginal probability densities of multipaths’ angles-of-arrival (AOA) and times-of-arrival (TOA) at the cellular base station are developed in closed form in this paper. Unlike the general simplification assumption in the open literature in which the scatterers are assumed to be located in a circular region for non-uniform spatial densities, the scatterers in this paper are assumed to be located in an elliptical region to properly model the elliptical footprint around the mobile station from the elevated base station with directional antenna. The inverted elliptic–parabolic spatial density was adopted to model the non-uniform distribution of the scatterers around the mobile. The uplink’s AOA–TOA joint distributions, AOA and TOA marginal distributions were analytically derived in closed form. How the eccentricity of the elliptical scatterer region affects the probability density functions is discussed. Furthermore, the derived AOA marginal distribution is compared to that of the elliptic conic and inverted parabolic models. The proposed model is shown to have better least-squares fit to some empirical AOA data compared to the elliptic conic and inverted parabolic models.
The development of the fifth generation (5G) of cellular systems enables the realization of densely connected, seamlessly integrated, and heterogeneous device networks. While 5G systems were developed to support the Internet of Everything (IoE) paradigm of communication, their mass-scale implementations have excessive capital deployment costs and severely detrimental environmental impacts. Hence, these systems are not feasibly scalable for the envisioned real-time, high-rate, high-reliability, and low-latency requirements of connected consumer, commercial, industrial, healthcare, and environmental processes of the IoE network. The IoE vision is expected to support 30 billion devices by 2030, hence, green communication architectures are critical for the development of next-generation wireless systems. In this context, intelligent reflecting surfaces (IRS) have emerged as a promising disruptive technological advancement that can adjust wireless environments in an energy-efficient manner. This work utilizes and analyzes a multi-node distributed IRS-assisted system in variable channel conditions and resource availability. We then employ machine learning and optimization algorithms for efficient resource allocation and system design of a distributed IRS-enabled industrial Internet of Things (IoT) network. The results show that the proposed data-driven solution is a promising optimization architecture for high-rate, next-generation IoE applications.
Localization has gained great attention in recent years, where different technologies have been utilized to achieve high positioning accuracy. Fingerprinting is a common technique for indoor positioning using short-range radio frequency (RF) technologies such as Bluetooth Low Energy (BLE). In this paper, we investigate the suitability of LoRa (Long Range) technology to implement a positioning system using received signal strength indicator (RSSI) fingerprinting. We test in real line-of-sight (LOS) and non-LOS (NLOS) environments to determine appropriate LoRa packet specifications for an accurate RSSI-to-distance mapping function. To further improve the positioning accuracy, we consider the environmental context. Extensive experiments are conducted to examine the performance of LoRa at different spreading factors. We analyze the path loss exponent and the standard deviation of shadowing in each environment
The exponential growth in global mobile data traffic, especially with regards to the massive deployment of devices envisioned for the fifth generation (5G) mobile networks, has given impetus to exploring new spectrum opportunities to support the new traffic demands. The millimeter wave (mmWave) frequency band is considered as a potential candidate for alleviating the spectrum scarcity. Moreover, the concept of multi-tier networks has gained popularity, especially for dense network environments. In this article, we deviate from the conventional multi-tier networks and employ the concept of control-data separation architecture (CDSA), which comprises of a control base station (CBS) overlaying the data base station (DBS). We assume that the CBS operates on the sub-6 GHz single band, while the DBS possesses a dual-band mmWave capability, i.e., 26 GHz unlicensed band and 60 GHz licensed band. We formulate a multi-objective optimization (MOO) problem, which jointly optimizes conflicting objectives: the spectral efficiency (SE) and the energy efficiency (EE). The unique aspect of this work includes the analysis of a joint radio resource allocation algorithm based on Lagrangian Dual Decomposition (LDD) and we compare the proposed algorithm with the maximal-rate (maxRx), dynamic sub-carrier allocation (DSA) and joint power and rate adaptation (JPRA) algorithms to show the performance gains achieved by the proposed algorithm.
With the growing popularity of Internet-of-Things (IoT)-based smart city applications, various long-range and low-power wireless connectivity solutions are under rigorous research. LoRa is one such solution that works in the sub-GHz unlicensed spectrum and promises to provide long-range communication with minimal energy consumption. However, the conventional LoRa networks are single-hop, with the end devices connected to a central gateway through a direct link, which may be subject to large path loss and hence render low connectivity and coverage. This article motivates the use of multi-hop LoRa topologies to enable energy-efficient connectivity in smart city applications. We present a case study that experimentally evaluates and compares single-hop and multi-hop LoRa topologies in terms of range extension and energy efficiency by evaluating packet reception ratio (PRR) for various source to destination distances, spreading factors (SFs), and transmission powers. The results highlight that a multi-hop LoRa network configuration can save significant energy and enhance coverage. For instance, it is shown that to achieve a 90% PRR, a two-hop network provides 50% energy savings as compared to a single-hop network while increasing 35% coverage at a particular SF. In the end, we discuss open challenges in multi-hop LoRa deployment and optimization.
Although Internet-of-Things (IoT) is revolutionizing the IT sector, it is not mature yet as several technologies are still being offered to be candidates for supporting the backbone of this system. IPv6 Routing Protocol for Low-Power and Lossy Networks (RPL) is one of those promising candidate technologies to be adopted by IoT and Industrial IoT (IIoT). Attacks against RPL have shown to be possible, as the attackers utilize the unauthorized parent selection system of the RLP protocol. In this work, we are proposing a methodology and architecture to detect intrusions against IIoT. Especially, we are targeting to detect attacks against RPL by using genetic programming. Our results indicate that the developed framework can successfully (with high accuracy, along with high true positive and low false positive rates) detect routing attacks in RPL-based Industrial IoT networks.
Three major obstacles to wireless communication are electromagnetic interference, multipath fading and signal attenuation. The former stems mainly from collocated wireless systems operating in the same frequency band, while the latter two originate from physical properties of the environment. Identifying the source of packet corruption and loss is crucial, since the adequate countermeasures for different types of threats are essentially different. This problem is especially pronounced in industrial monitoring and control applications, where IEEE 802.15.4 communication is expected to deliver data within tight deadlines, with minimal packet loss. This work presents the Lightweight Packet Error Discriminator (LPED) that distinguishes between errors caused by multipath fading and attenuation, and those inflicted by IEEE 802.11 interference. LPED uses Forward Error Correction to determine the symbol error positions inside erroneously received packets and calculates the error density, which is then fed to a discriminator for error source classification. The statistical constituents of LPED are obtained from an extensive measurement campaign in two different types of industrial environments. The classifier incurs no overhead and in ≥90% of cases a single packet is sufficient for a correct channel diagnosis. Experiments show that LPED accelerates link diagnostics by at least 190%, compared to the relevant state-of-the-art approaches.
The knowledge of error nature in wireless channels is an essential constituent of efficient communication protocol design. To this end, this paper is the first comprehensive bit- and symbol-level analysis of IEEE 802.15.4 transmission errors in industrial environments. The intention with this paper is to extract the error properties relevant for future improvements of wireless communication reliability and coexistence of radio systems in these harsh conditions. An extensive set of bit-error traces was collected in a variety of scenarios and industrial environments, showing that error behavior is highly dependent on the cause of packet corruption. It is shown that errors inflicted by multipath fading and attenuation exhibit different properties than those imposed by IEEE 802.11 interference. The statistical behavior of these two patterns is concurrently investigated in terms of differences in bit-error distribution, error burst length, channel memory length, and the scale of packet corruption. With these conclusions at hand, abiding to the computational constraints of embedded sensors and the statistical properties of bit-errors, a Reed-Solomon $(15,k)$ block code is chosen to investigate the implications of bit-error nature on practical aspects of channel coding and interleaving. This paper is concluded by a number of findings of high practical relevance, concerning the optimal type, depth, and meaningfulness of interleaving.
Subjective and objective visual quality assessment in the context of stereoscopic three-dimensional TV (3D-TV) is still in the nascent stage and needs to consider the effect of the added depth dimension. As a matter of fact, quality assessment of 3D-TV cannot be considered as a trivial extension of two-dimensional (2D) cases. Furthermore, it may also introduce negative effects not experienced in 2D, e.g., discomfort or nausea. Based on efforts initiated within the cost action ICT 1003 QUALINET, this chapter discusses current challenges in relation to subjective and objective visual quality assessment for stereo-based 3D-TV. Two case studies are presented to illustrate the current state of the art and some of the remaining challenges. © Springer Science+Business Media New York 2013. All rights are reserved.
The current development of video quality assessment algorithms suffers from the lack of available video sequences for training, verification and validation to determine and enhance the algorithm's application scope. The Joint Effort Group of the Video Quality Experts Group (VQEG-JEG) is currently driving efforts towards the creation of large scale, reproducible, and easy to use databases. These databases will contain bitstreams of recent video encoders (H.264, H.265), packet loss impairment patterns and impaired bitstreams, pre-parsed bitstream information into files in XML syntax, and well-known objective video quality measurement outputs. The database is continuously updated and enlarged using reproducible processing chains. Currently, more than 70,000 sequences are available for statistical analysis of video quality measurement algorithms. New research questions are posed as the database is designed to verify and validate models on a very large scale, testing and validating various scopes of applications, while subjective assessment has to be limited to a comparably small subset of the database. Special focus is given on the principles guiding the database development, and some results are given to illustrate the practical usefulness of such a database with respect to the detailed new research questions.
Reconfigurable intelligent surfaces (RISs), with the potential to realize smart radio environments, have emerged as an energy-efficient and a cost-effective technology to support the services and demands foreseen for coming decades. By leveraging a large number of low-cost passive reflecting elements, RISs introduce a phase-shift in the impinging signal to create a favorable propagation channel between the transmitter and the receiver. In this article, we provide a tutorial overview of RISs for sixth-generation (6G) wireless networks. Specifically, we present a comprehensive discussion on performance gains that can be achieved by integrating RISs with emerging communication technologies. We address the practical implementation of RIS-assisted networks and expose the crucial challenges, including the RIS reconfiguration, deployment and size optimization, and channel estimation. Furthermore, we explore the integration of RIS and non-orthogonal multiple access (NOMA) under imperfect channel state information (CSI). Our numerical results illustrate the importance of better channel estimation in RIS-assisted networks and indicate the various factors that impact the size of RIS. Finally, we present promising future research directions for realizing RIS-assisted networks in 6G communication. IEEE
Backscatter Communication (BackCom), which is based on passive reflection and modulation of an incident radio-frequency (RF) wave, has emerged as a cutting-edge technological paradigm for self-sustainable Internet-of-things (IoT). Nevertheless, contemporary BackCom systems are limited to short-range and low data rate applications only, rendering them insufficient on their own to support pervasive connectivity among the massive number of IoT devices. Meanwhile, wireless networks are rapidly evolving toward the smart radio paradigm. In this regard, reconfigurable intelligent surfaces (RISs) have come to the forefront to transform the wireless propagation environment into a fully controllable and customizable space in a cost-effective and energy-efficient manner. Targeting the sixth-generation (6G) horizon, we anticipate the integration of RISs into BackCom systems as a new frontier for enabling 6G IoT networks. In this article, for the first time in the open literature, we provide a tutorial overview of RIS-assisted BackCom (RIS-BackCom) systems. Specifically, we introduce the three different variants of RIS-Back- Com and identify the potential improvements that can be achieved by incorporating RISs into Back- Com systems. In addition, owing to the unrivaled effectiveness of non-orthogonal multiple access (NOMA), we present a case study on a RIS-assisted NOMA-enhanced BackCom system. Finally, we outline the way forward for translating this disruptive concept into real-world applications.
Industry is going through a transformation phase, enabling automation and data exchange in manufacturing technologies and processes, and this transformation is called Industry 4.0. Industrial Internet-of-Things (IIoT) applications require real-time processing, near-by storage, ultra-low latency, reliability and high data rate, all of which can be satisfied by fog computing architecture. With smart devices expected to grow exponentially, the need for an optimized fog computing architecture and protocols is crucial. Therein, efficient, intelligent and decentralized solutions are required to ensure real-time connectivity, reliability and green communication. In this paper, we provide a comprehensive review of methods and techniques in fog computing. Our focus is on fog infrastructure and protocols in the context of IIoT applications. This article has two main research areas: In the first half, we discuss the history of industrial revolution, application areas of IIoT followed by key enabling technologies that act as building blocks for industrial transformation. In the second half, we focus on fog computing, providing solutions to critical challenges and as an enabler for IIoT application domains. Finally, open research challenges are discussed to enlighten fog computing aspects in different fields and technologies.
The Licensed Assisted Access (LAA) is shown asa required technology to avoid overcrowding of the licensedbands by the increasing cellular traffic. Proposed by 3GPP,LAA uses a Listen Before Talk (LBT) and backoff mechanismsimilar to Wi-Fi. While many mathematical models have beenproposed to study the problem of the coexistence of LAAand Wi-Fi systems, few have tackled the problem of QoSprovisioning, and in particular analysed the behaviour of thevarious classes of priority available in Wi-Fi and LAA. Thispaper presents a new mathematical model to investigate theperformance of different priority classes in coexisting Wi-Fi andLAA networks. Using Discrete Time Markov Chains, we modelthe saturation throughput of all eight priority classes used byWi-Fi and LAA. The numerical results show that with the 3GPPproposed parameters, a fair coexistence between Wi-Fi and LAAcannot be achieved. Wi-Fi users in particular suffer a significantdegradation of their performance caused by the collision withLAA transmissions which has a longer duration compared toWi-Fi transmissions.
Machine to Machine (M2M) communication networksare expected to connect a large number of power constrained devices in long range applications with differentquality of service (QoS) requirements. Medium access control with QoS support such as the Enhanced Distributed Channel Access (EDCA) defined by IEEE 802.11e provides traffic differentiation and corresponding priority classes, which guarantees QoSaccording to the needs of applications. In this paper, we employa station grouping mechanism for enhancing the scalability of EDCA to handle the massive number of access attempts expected in large M2M networks. Furthermore, we develop a discrete time Markov chain (DTMC) model to analyze the performance of EDCA with station grouping. Using the developed DTMC model, we calculate throughput for each access category as well as for different combinations of grouping and EDCA parameters. Thenumerical results show that the model can precisely reveal the behavior of EDCA mechanism. Moreover, it is demonstrated that employing the proposed grouping mechanism for EDCA increasesthe normalized throughput significantly for all classes of priority.
As the market for low-power wide-area network (LPWAN) technologies expands and the number of connected devices increases, it is becoming important to investigate the performance of LPWAN candidate technologies in dense deployment scenarios. In dense deployments, where the networks usually exhibit the traits of an interference-limited system, a detailed intra- and inter-cell interference analysis of LPWANs is required. In this paper, we model and analyze the performance of uplink communication of a LoRa link in a multi-cell LoRa system. To such end, we use mathematical tools from stochastic geometry and geometric probability to model the spatial distribution of LoRa devices. The model captures the effects of the density of LoRa cells and the allocation of quasi-orthogonal spreading factors (SF) on the success probability of the LoRa transmissions. To account for practical deployment of LoRa gateways, we model the spatial distribution of the gateways with a Poisson point process (PPP) and Matèrn hard-core point process (MHC). Using our analytical formulation, we find the uplink performance in terms of success probability and potential throughput for each of the available SF in LoRa’s physical layer. Our results show that in dense multi-cell LoRa deployment with uplink traffic, the intercell interference noticeably degrades the system performance.
Although the idea of using wireless links for covering large areas is not new, the advent of Low Power Wide area networks (LPWANs) has recently started changing the game. Simple, robust, narrowband modulation schemes permit the implementation of low-cost radio devices offering high receiver sensitivity, thus improving the overall link budget. The several technologies belonging to the LPWAN family, including the well-known LoRaWAN solution, provide a cost-effective answer to many Internet-of-things (IoT) applications, requiring wireless communication capable of supporting large networks of many devices (e.g., smart metering). Generally, the adopted medium access control (MAC) strategy is based on pure ALOHA, which, among other things, allows to minimize the traffic overhead under constrained duty cycle limitations of the unlicensed bands. Unfortunately, ALOHA suffers from poor scalability, rapidly collapsing in dense networks. This work investigates the design of an improved LoRaWAN MAC scheme based on slotted ALOHA. In particular, the required time dissemination is provided by out-of-band communications leveraging on Radio Data System(FM-RDS) broadcasting, which natively covers wide areas both indoor and outdoor. An experimental setup based on low-cost hardware is used to characterize the obtainable synchronization performance and derive a timing error model. Consequently, improvements in success probability and energy efficiency have been validated by means of simulations in very large networks with up to 10000 nodes. It is shown that the advantage of the proposed scheme over conventional LoRaWAN communication is up to 100% when short update time and large payload are required. Similar results are obtained regarding the energy efficiency improvement, that is close to 100% for relatively short transmission intervals and long message duration; however, due to the additional overhead for listening the time dissemination messages, efficiency gain can be negative for very short duration of message fastly repeating.
IEEE 802.11ah is a sub-1 GHz standard designed to meet the requirements of future machine-to-machine (M2M) communications. The standard should be able to support use cases for the M2M communications with thousands of stations capable of generating both periodic and aperiodic traffic for a single access point. In some cases, like environmental and agricultural monitoring. the nodes are typically powered by battery or through energy harvesting. For this application it is important for the communication to be energy efficient. IEEE 802.11ah introduces new energy saving mechanisms and a novel channel access mechanism to achieve this objective even for networks with a large nodes number. This work proposes a mathematical model to compute the energy consumption of an IEEE 802.11ah network.
Many applications for machine-to-machine (M2M) communications are characterized by large numbers of devices with sporadic transmissions and subjected to low energy budgets. This work addresses the importance of energy consumption by proposing a new Medium Access Control (MAC) mechanism for improving the energy efficiency of IEEE 802.11ah, a standard targeting M2M communication. We propose to use the features of IEEE 802.11ah MAC to realize a hybrid contention-reservation mechanism for the transmission of uplink traffic. In the proposed mechanism, any device with a buffered packet will first notify the Access Point (AP) during a contention phase before being given a reserved timeslot for the data transmission. We develop a mathematical model to analyse the energy consumption ofthe proposed mechanism and of IEEE 802.11ah. The results show that for a monitoring scenario, the proposed contention reservation mechanism reduces the energy consumption for a successful uplink data transmission by up to 55%.
Since the purchase of Siri by Apple, and its release with the iPhone 4S in 2011, virtualassistants (VAs) have grown in number and popularity. The sophisticated natural language processingand speech recognition employed by VAs enables users to interact with them conversationally, almostas they would with another human. To service user voice requests, VAs transmit large amounts ofdata to their vendors; these data are processed and stored in the Cloud. The potential data securityand privacy issues involved in this process provided the motivation to examine the current state ofthe art in VA research. In this study, we identify peer-reviewed literature that focuses on securityand privacy concerns surrounding these assistants, including current trends in addressing how voiceassistants are vulnerable to malicious attacks and worries that the VA is recording without the user’sknowledge or consent. The findings show that not only are these worries manifold, but there is agap in the current state of the art, and no current literature reviews on the topic exist. This reviewsheds light on future research directions, such as providing solutions to perform voice authenticationwithout an external device, and the compliance of VAs with privacy regulations.
Wireless sensors and actuators networks are an essential element to realize industrial IoT (IIoT) systems, yet their diffusion is hampered by the complexity of ensuring reliable communication in industrial environments.A significant problem with that respect is the unpredictable fluctuation of a radio-link between the line-of-sight (LoS) and the non-line-of-sight (NLoS) state due to time-varying environments.The impact of link-state over reception performance, suggests that link-state variations should be monitored at run-time, enabling dynamic adaptation of the transmission scheme on a link-basis to safeguard QoS.Starting from the assumption that accurate channel-sounding is unsuitable for low-complexity IIoT devices, we investigate the feasibility of channel-state identification for platforms with limited sensing capabilities. In this context, we evaluate the performance of different supervised-learning algorithms with variable complexity for the inference of the radio-link state.Our approach provides fast link-diagnostics by performing online classification based on a single received packet. Furthermore, the method takes into account the effects of limited sampling frequency, bit-depth, and moving average filtering, which are typical to hardware-constrained platforms.The results of an experimental campaign in both industrial and office environments show promising classification accuracy of LoS/NLoS radio links. Additional tests indicate that the proposed method retains good performance even with low-resolution RSSI-samples available in low-cost WSN nodes, which facilitates its adoption in real IIoT networks.
The Internet of Things (IoT) paradigm contaminated industrial world, allowing for innovative services. The wireless communications seem to be particularly attracting, especially when complement indoor and outdoor Real Time Location Systems (RTLS) for geo-referencing smart objects (e.g. for asset tracking). In this paper, the LoRaWAN solution is considered for transmitting RTLS data. LoRaWAN is an example of Low Power Wide Area Network: it tradeoffs throughput with coverage and power consumption. However, performance can be greatly improved with limited changes to the standard specifications. In this work, a scheduling layer is suggested above the regular stack for allocating communication resources in a time slot channel hopping medium access strategy. The main innovation is the time synchronization, which is obtained opportunistically from the ranging devices belonging to the RTLSs. The experimental testbed, based on commercially available solutions, demonstrates the affordability and feasibility of the proposed approach. When low-cost GPS (outdoor) and UWB (indoor) ranging devices are considered, synchronization error of few microseconds can be easily obtained. The experimental results show the that time reference pulses disciplined by GPS have a maximum jitter of 180 ns and a standard deviation of 40 ns whereas, if time reference pulses disciplined by UWB are considered, the maximum jitter is 3.3 μs and the standard deviation is 0.7 μs.
The assessment of perceived quality based on psychophysiological methods recently gained attraction as it potentially overcomes certain flaws of psychophysical approaches. Although studies report promising results, it is not possible to arrive at decisive and comparable conclusions that recommend the use of one or another method for a specific application or research question. The video quality expert group started a project on psychophysiological quality assessment to study these novel approaches and to develop a test plan that enables more systematic research. This test plan comprises of a specifically designed set of quality annotated video sequences, suggestions for psychophysiological methods to be studied in quality assessment, and recommendations for the documentation and publications of test results. The test plan is presented in this article.
This paper analyzes how an experimenter can balance errors in subjective video quality tests betweenthe statistical power of finding an effect if it is there and not claiming that an effect is there if the effect is not there,i.e., balancing Type I and Type II errors. The risk of committing Type I errors increases with the number ofcomparisons that are performed in statistical tests. We will show that when controlling for this and at thesame time keeping the power of the experiment at a reasonably high level, it is unlikely that the number oftest subjects that are normally used and recommended by the International Telecommunication Union (ITU),i.e., 15 is sufficient but the number used by the Video Quality Experts Group (VQEG), i.e., 24 is more likelyto be sufficient. Examples will also be given for the influence of Type I error on the statistical significance ofcomparing objective metrics by correlation. We also present a comparison between parametric and nonparametricstatistics. The comparison targets the question whether we would reach different conclusions on the statisticaldifference between the video quality ratings of different video clips in a subjective test, based on thecomparison between the student T-test and the Mann–Whitney U-test. We found that there was hardly a differencewhen few comparisons are compensated for, i.e., then almost the same conclusions are reached. Whenthe number of comparisons is increased, then larger and larger differences between the two methods arerevealed. In these cases, the parametric T-test gives clearly more significant cases, than the nonparametrictest, which makes it more important to investigate whether the assumptions are met for performing a certaintest.
For industry, the need to access accurate and reliable objective video metrics has become more pressing with the advent of new video applications and services such as mobile broadcasting, Internet video, and Internet Protocol television (IPTV). Industry-class objective quality- measurement models have a wide range of uses, including equipment testing (e.g., codec evaluation), transmission- planning and network-dimensioning tasks, head-end quality assurance, in- service network monitoring, and client-based quality measurement. The Video Quality Experts Group (VQEG) is the primary forum for validation testing of objective perceptual quality models. The work of VQEG has resulted in International Telecommunication Union (ITU) standardization of objective quality models designed for standard- definition television and for multimedia applications. This article reviews VQEG's work, paying particular attention to the group's approach to validation testing.
This study focused on evaluating the user experience of the viewing-angle-dependent quality of computer and notebook displays. The tests were performed in a test lab using a notebook with a prismatic display and a computer monitor with a conventional LCD. The notebook display was tilted and turned during an image-quality test and tilted during an acuity test. On the computer monitor, the turn and tilt was simulated in the image-quality test, for checking the TCO requirements. The results from the image-quality test show that the parameter used in the TCO requirement, luminance ratio, would be a reasonable predictor of image quality. However, the experiment with the notebook display shows that, in general, this is not the case, especially for larger viewing angles where the physical characteristics do not show a gradual variation in luminance. Therefore, the luminance ratio in TCO requirements shall be used with caution. In addition, the results for the notebook display show that the visual acu ity decreased faster with increasing viewing angle than predicted from the luminance decrease alone. This means that it will be harder to resolve small details and will, therefore, have a negative influence on the visual ergonomics.
Implementation of the Johnson criteria for infrared images is the probabilities of a discrimination technique. The inputs to the model are the size of the target, the range to it, and the temperature difference against the background. The temperature difference is calculated without taking the background structure into consideration, but it may have a strong influence on the visibility of the target. We investigated whether a perceptually based temperature difference should be used as input. Four different models are discussed: 1. a probability of discrimination model largely based on the Johnson criteria for infrared images, 2. a peak signal-to-noise ratio model, 3. a signal-to-clutter ratio model, and 4. two versions of an image discrimination model based on how human vision analyzes spatial information. The models differ as to how much they try to simulate human perception. To test the models, a psychophysical experiment was carried out with ten test persons, measuring contrast threshold detection in five different infrared backgrounds using a method based on a two-alternative forced-choice methodology. Predictions of thresholds in contrast energy were calculated for the different models and compared to the empirical values. Thresholds depend on the background, and these can be predicted well by the image discrimination models, and better than the other models. Future extensions are discussed.
In this study, we investigate a VR simulator of a forestry crane used for loading logs onto a truck, mainly looking at Quality of Experience (QoE) aspects that may be relevant for task completion, but also whether there are any discomfort related symptoms experienced during task execution. A QoE test has been designed to capture both the general subjective experience of using the simulator and to study task performance. Moreover, a specific focus has been to study the effects of latency on the subjective experience, with regards to delays in the crane control interface. A formal subjective study has been performed where we have added controlled delays to the hand controller (joystick) signals. The added delays ranged from 0 ms to 800 ms. We found no significant effects of delays on the task performance on any scales up to 200 ms. A significant negative effect was found for 800 ms added delay. The Symptoms reported in the Simulator Sickness Questionnaire (SSQ) was significantly higher for all the symptom groups, but a majority of the participants reported only slight symptoms. Two out of thirty test persons stopped the test before finishing due to their symptoms.
In this article, we have investigated a VR simulator of a forestry crane used for loading logs onto a truck. We have mainly studied the Quality of Experience (QoE) aspects that may be relevant for task completion, and whether there are any discomfort related symptoms experienced during the task execution. QoE experiments were designed to capture the general subjective experience of using the simulator, and to study task performance. The focus was to study the effects of latency on the subjective experience, with regards to delays in the crane control interface. Subjective studies were performed with controlled delays added to the display update and hand controller (joystick) signals. The added delays ranged from 0 to 30 ms for the display update, and from 0 to 800 ms for the hand controller. We found a strong effect on latency in the display update and a significant negative effect for 800 ms added delay on latency in the hand controller (in total approx. 880 ms latency including the system delay). The Simulator Sickness Questionnaire (SSQ) gave significantly higher scores after the experiment compared to before the experiment, but a majority of the participants reported experiencing only minor symptoms. Some test subjects ceased the test before finishing due to their symptoms, particularly due to the added latency in the display update.
It is well-known that active selection of fixation points in humans is highly context and task dependent. It is therefore likely that successful computational processes for fixation in active vision should be so too. We are considering active fixation in the context of recognition of man-made objects characterized by their shapes. In this situation the qualitative shape and type of observed junctions play an important role. The fixations are driven by a grouping strategy, which forms sets of connected junctions separated from the surrounding at depth discontinuities. We have furthermore developed a methodology for rapid active detection and classification of junctions by selection of fixation points. The approach is based on direct computations from image data and allows integration of stereo and accommodation cues with luminance information. This work form a part of an effort to perform active recognition of generic objects, in the spirit of Malik and Biederman, but on real imagery rather than on line-drawings.
Focus-of-attention is extremely important in human visual perception. If computer vision systems are to perform tasks in a complex, dynamic world they will have to be able to control processing in a way that is analogous to visual attention in humans. Problems connected to foveation (examination of selected regions of the world at high resolution) are examined. In particular, the problem of finding and classifying junctions from this aspect is considered. It is shown that foveation as simulated by controlled, active zooming in conjunction with scale-space techniques allows for robust detection and classification of junctions.
The TCO requirements provide well-known and recognized quality labels for displays.For these requirements to remain useful, they must continuously be reviewed and updated when nec-essary. The study described here was performed in response to the market trend of designing flat-paneldisplays and notebooks with glare panels. The purpose of this study was to investigate subjectiveresponses to display screens of different gloss levels for office workers working on different tasks undernormal office-lighting conditions. The study consisted of three parts, one where the users should setan acceptable reflex level, one where the user should rate their disturbance on a category scale, andone where the visual acuity of the users were investigated whether they were affected by glare or not.The results show that increasing gloss and increasing luminance levels had negative effects on theacceptance and the disturbance of reflexes. There were statistically significant differences in theacceptance and the disturbance levels between screens with low gloss and screens with high gloss,which suggests that screens with the highest gloss levels should be avoided. The study did not showan effect on the performance based on acuity testing.
This paper gives an overview of three recent studies by the authors on the topic of 3D video Quality of Experience (QoE). Two of studies [1,2] investigated different psychological dimension that may be needed for describing 3D video QoE and the third the visibility and annoyance of crosstalk[3]. The results shows that the video quality scale could be sufficient for evaluating S3D video experience for coding and spatial resolution reduction distortions. It was also confirmed that with a more complex mixture of degradations more than one scale should be used to capture the QoE in these cases. The study found a linear relationship between the perceived crosstalk and the amount of crosstalk.
Stereoscopic 3D TV viewing puts different visual demands on the viewer compared to 2D TV viewing. Previous research has reported on viewers' fatigue and discomfort and other negative effects. This study is to investigate further how severe and what symptoms may arise from somewhat longish 3D TV viewing.
The MPEG 3DV project is working on the next-generation video encoding standard and in this process, MPEG issued a call for proposal of encoding algorithms. To evaluate these algorithms a large scale subjective test was performed involving Laboratories all over the world[1, 2]. For the participating Labs, it was optional to administer a slightly modified Simulator Sickness Questionnaire (SSQ) before and after the test. One of the SSQ data sets described in this article is coming from this study. The SSQ data from the MPEG test is the largest data set in this study and also contains the longest viewing times. Along with the SSQ data from the MPEG test, we have also collected questionnaire data in three other 3D TV studies. We did two on the same 3D TV (passive film pattern retarder) as in the MPEG test, and one was using a projector system. As comparison SSQ data from a 2D video quality experiment is also presented.
This investigation shows a statistically significant increase in symptoms after viewing 3D TV primarily related to the visual or Oculomotor system. Surprisingly, 3D video viewing using projectors did not show this effect.