| 1. |
- Bai, Jianan, et al.
(författare)
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Multiagent Reinforcement Learning Meets Random Access in Massive Cellular Internet of Things
- 2021
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Ingår i: IEEE Internet of Things Journal. - : IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC. - 2327-4662. ; 8:24, s. 17417-17428
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Tidskriftsartikel (refereegranskat)abstract
- Internet of Things (IoT) has attracted considerable attention in recent years due to its potential of interconnecting a large number of heterogeneous wireless devices. However, it is usually challenging to provide reliable and efficient random access control when massive IoT devices are trying to access the network simultaneously. In this article, we investigate methods to introduce intelligent random access management for a massive cellular IoT network to reduce access latency and access failures. Toward this end, we introduce two novel frameworks, namely, local device selection (LDS) and intelligent preamble selection (IPS). LDS enables local communication between neighboring devices to provide cluster-wide cooperative congestion control, which leads to a better distribution of the access intensity under bursty traffics. Taking advantage of the capability of reinforcement learning in developing cooperative multiagent policies, IPS is introduced to enable the optimization of the preamble selection policy in each IoT clusters. To handle the exponentially growing action space in IPS, we design a novel reinforcement learning structure, named branching actor-critic, to ensure that the output size of the underlying neural networks only grows linearly with the number of action dimensions. Simulation results indicate that the introduced mechanism achieves much lower access delays with fewer access failures in various realistic scenarios of interests.
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| 2. |
- Beltramelli, Luca, et al.
(författare)
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Synchronous LoRa Communication by Exploiting Large-Area out-of-band Synchronization
- 2021
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Ingår i: IEEE Internet of Things Journal. - 2327-4662. ; 8:10, s. 7912-7924
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Tidskriftsartikel (refereegranskat)abstract
- Many new narrowband low-power wide-area networks (LPWANs) (e.g., LoRaWAN, Sigfox) have opted to use pure ALOHA-like access for its reduced control overhead and asynchronous transmissions. Although asynchronous access reduces the energy consumption of IoT devices, the network performance suffers from high intra-network interference in dense deployments. Contrarily, adopting synchronous access can improve throughput and fairness, however, it requires time synchronization. Unfortunately, maintaining synchronization over the narrowband LPWANs wastes channel time and transmission opportunities. In this paper, we propose the use of out-of-band time-dissemination to relatively synchronize the LoRa devices and thereby facilitate resource-efficient slotted uplink communication. In this respect, we conceptualize and analyze a co-designed synchronization and random access communication mechanism that can effectively exploit technologies providing limited time accuracy, such as FM radio data system (FM-RDS). While considering the LoRa-specific parameters, we derive the throughput of the proposed mechanism, compare it to a generic synchronous random access using in-band synchronization, and design the communication parameters under time uncertainty. We scrutinize the transmission time uncertainty of a device by introducing a clock error model that accounts for the errors in the synchronization source, local clock, propagation delay, and transceiver’s transmission time uncertainty. We characterize the time uncertainty of FM-RDS with hardware measurements and perform simulations to evaluate the proposed solution. The results, presented in terms of success probability, throughput, and fairness for a single-cell scenario, suggest that FM-RDS, despite its poor absolute synchronization, can be used effectively to realize time-slotted communication in LoRa with performance similar to that of more accurate time-dissemination technologies.
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| 3. |
- Bera, Basudeb, et al.
(författare)
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Designing Blockchain-Based Access Control Protocol in IoT-Enabled Smart-Grid System
- 2021
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Ingår i: IEEE Internet of Things Journal. - : IEEE. - 2327-4662. ; 8:7, s. 5744-5761
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Tidskriftsartikel (refereegranskat)abstract
- We design a new blockchain-based access control protocol in IoT-enabled smart-grid system, called DBACP-IoTSG. Through the proposed DBACP-IoTSG, the data is securely brought to the service providers from their respective smart meters (SMs). The peer-to-peer (P2P) network is formed by the participating service providers, where the peer nodes are responsible for creating the blocks from the gathered data securely from their corresponding SMs and adding them into the blockchain after validation of the blocks using the voting-based consensus algorithm. In our work, the blockchain is considered as private because the data collected from the consumers of the SMs are private and confidential. By the formal security analysis under the random oracle model, nonmathematical security analysis and software-based formal security verification, DBACP-IoTSG is shown to be resistant against various attacks. We carry out the experimental results of various cryptographic primitives that are needed for comparative analysis using the widely used multiprecision integer and rational arithmetic cryptographic library (MIRACL). A detailed comparative study reveals that DBACP-IoTSG supports more functionality features and provides better security apart from its low communication and computation costs as compared to recently proposed relevant schemes. In addition, the blockchain implementation of DBACP-IoTSG has been performed to measure computational time needed for the varied number of blocks addition and also the varied number of transactions per block in the blockchain.
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| 4. |
- Caso, Giuseppe, et al.
(författare)
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Empirical Models for NB-IoT Path Loss in an Urban Scenario
- 2021
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Ingår i: IEEE Internet of Things Journal. - : Institute of Electrical and Electronics Engineers (IEEE). - 2327-4662. ; 8:17, s. 13774-13788
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Tidskriftsartikel (refereegranskat)abstract
- The lack of publicly available large scale measurements has hindered the derivation of empirical path loss (PL) models for Narrowband Internet of Things (NB-IoT). Therefore, simulation-based investigations currently rely on models conceived for other cellular technologies, which are characterized, however, by different available bandwidth, carrier frequency, and infrastructure deployment, among others. In this paper, we take advantage of data from a large scale measurement campaign in the city of Oslo, Norway, to provide the first empirical characterization of NB-IoT PL in an urban scenario. For the PL average term, we characterize Alpha-Beta-Gamma (ABG) and Close-In (CI) models. By analyzing multiple NBIoT cells, we propose a statistical PL characterization, i.e., the model parameters are not set to a single, constant value across cells, but are randomly extracted from well-known distributions. Similarly, we define the PL shadowing distribution, correlation over distance, and inter-site correlation. Finally, we give initial insights on outdoor-to-indoor propagation, using measurements up to deep indoor scenarios. The proposed models improve PL estimation accuracy compared to the ones currently adopted in NB-IoT investigations, enabling more realistic simulations of urban scenarios similar to the sites covered by our measurements.
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| 5. |
- Caso, Giuseppe, et al.
(författare)
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NB-IoT Random Access : Data-driven Analysis and ML-based Enhancements
- 2021
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Ingår i: IEEE Internet of Things Journal. - : IEEE. - 2327-4662. ; 8:14, s. 11384-11399
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Tidskriftsartikel (refereegranskat)abstract
- In the context of massive Machine Type Communications (mMTC), the Narrowband Internet of Things (NB-IoT) technology is envisioned to efficiently and reliably deal with massive device connectivity. Hence, it relies on a tailored Random Access (RA) procedure, for which theoretical and empirical analyses are needed for a better understanding and further improvements. This paper presents the first data-driven analysis of NB-IoT RA, exploiting a large scale measurement campaign. We show how the RA procedure and performance are affected by network deployment, radio coverage, and operators’ configurations, thus complementing simulation-based investigations, mostly focused on massive connectivity aspects. Comparison with the performance requirements reveals the need for procedure enhancements. Hence, we propose a Machine Learning (ML) approach, and show that RA outcomes are predictable with good accuracy by observing radio conditions. We embed the outcome prediction in a RA enhanced scheme, and show that optimized configurations enable a power consumption reduction of at least 50%. We also make our dataset available for further exploration, toward the discovery of new insights and research perspectives.
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| 6. |
- Chen, Hao, et al.
(författare)
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Coded Stochastic ADMM for Decentralized Consensus Optimization With Edge Computing
- 2021
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Ingår i: IEEE Internet of Things Journal. - : Institute of Electrical and Electronics Engineers (IEEE). - 2327-4662. ; 8:7, s. 5360-5373
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Tidskriftsartikel (refereegranskat)abstract
- Big data, including applications with high security requirements, are often collected and stored on multiple heterogeneous devices, such as mobile devices, drones, and vehicles. Due to the limitations of communication costs and security requirements, it is of paramount importance to analyze information in a decentralized manner instead of aggregating data to a fusion center. To train large-scale machine learning models, edge/fog computing is often leveraged as an alternative to centralized learning. We consider the problem of learning model parameters in a multiagent system with data locally processed via distributed edge nodes. A class of minibatch stochastic alternating direction method of multipliers (ADMMs) algorithms is explored to develop the distributed learning model. To address two main critical challenges in distributed learning systems, i.e., communication bottleneck and straggler nodes (nodes with slow responses), error-control-coding-based stochastic incremental ADMM is investigated. Given an appropriate minibatch size, we show that the minibatch stochastic ADMM-based method converges in a rate of O(1/root k), where k denotes the number of iterations. Through numerical experiments, it is revealed that the proposed algorithm is communication efficient, rapidly responding, and robust in the presence of straggler nodes compared with state-of-the-art algorithms.
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| 7. |
- Farag, Hossam, et al.
(författare)
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REA-6TiSCH : Reliable Emergency-Aware Communication Scheme for 6TiSCH Networks
- 2021
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Ingår i: IEEE Internet of Things Journal. - 2327-4662. ; 8:3, s. 1871-1882
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Tidskriftsartikel (refereegranskat)abstract
- In the perspective of the emerging Industrial Internet of things (IIoT), the 6TiSCH working group has been created with the main goal to integrate the capabilities of the IEEE 802.15.4e Time-Slotted Channel Hopping (TSCH) with the IPv6 protocol stack. In order to support time-critical applications in IIoT, reliable real-time communication is a key requirement. Specifically, aperiodic critical traffic, such as emergency alarms, must be reliably delivered to the DODAG root within strict deadline bounds to avoid system failure or safety-critical situations. Currently, there is no mechanism defined in the 6TiSCH architecture for timely and reliably handling of such traffic and its prioritization over the non-critical one. In this paper, we introduce REA-6TiSCH, a reliable emergency-aware communication scheme to support real-time communications of emergency alarms in 6TiSCH networks. In REA-6TiSCH, the aperiodic emergency traffic is opportunistically enabled to hijack transmission cells pre-assigned for the regular periodic traffic in the TSCH schedule. Moreover, we introduce a distributed optimization scheme to improve the probability that an emergency flow is delivered successfully within its deadline bound. To the best of our knowledge, this is the first approach to incorporate emergency alarms in 6TiSCH networks. We evaluate the performance of REA-6TiSCH through extensive simulations and the results show the effectiveness of our proposed method in handling emergency traffic compared to Orchestra scheme. Additionally, we discuss the applicability of REA-6TiSCH and provide guidelines for real implementation in 6TiSCH networks.
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| 8. |
- Fontes, Afonso, 1987
(författare)
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Industrial Internet of Things Security enhanced with Deep Learning Approaches for Smart Cities
- 2021
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Ingår i: IEEE Internet of Things Journal. - 2327-4662.
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Tidskriftsartikel (refereegranskat)abstract
- The significant evolution of the Internet of Things (IoT) enabled the development of numerous devices able to improve many aspects in various fields in the industry for smart cities where machines have replaced humans. With the reduction in manual work and the adoption of automation, cities are getting more efficient and smarter. However, this evolution also made data even more sensitive, especially in the industrial segment. The latter has caught the attention of many hackers targeting Industrial IoT (IIoT) devices or networks, hence the number of malicious software, i.e., malware, has increased as well. In this article, we present the IIoT concept and applications for smart cities, besides also presenting the security challenges faced by this emerging area. We survey currently available deep learning techniques for IIoT in smart cities, mainly Deep Reinforcement Learning, Recurrent Neural Networks, and Convolutional Neural Networks, and highlight the advantages and disadvantages of security-related methods. We also present insights, open issues, and future trends applying deep learning techniques to enhance IIoT security.
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| 9. |
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| 10. |
- Khodaei, Mohammad, et al.
(författare)
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Cooperative Location Privacy in Vehicular Networks : Why Simple Mix-zones are not Enough
- 2021
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Ingår i: IEEE Internet of Things Journal. - : Institute of Electrical and Electronics Engineers Inc.. - 2327-4662. ; , s. 1-1
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Tidskriftsartikel (refereegranskat)abstract
- Vehicular communications disclose rich information about the vehicles and their whereabouts. Pseudonymous authentication secures communication while enhancing user privacy. To enhance location privacy, cryptographic mix-zones were proposed to facilitate vehicles covertly transition to new ephemeral credentials. The resilience to (syntactic and semantic) pseudonym linking (attacks) highly depends on the geometry of the mix-zones, mobility patterns, vehicle density, and arrival rates. We introduce a tracking algorithm for linking pseudonyms before and after a cryptographically protected mix-zone. Our experimental results show that an eavesdropper, leveraging standardized vehicular communication messages and road layout, could successfully link ≈73% of pseudonyms during non-rush hours and ≈62% of pseudonyms during rush hours after vehicles change their pseudonyms in a mix-zone. To mitigate such inference attacks, we present a novel cooperative mix-zone scheme that enhances user privacy regardless of the vehicle mobility patterns, vehicle density, and arrival rate to the mix-zone. A subset of vehicles, termed relaying vehicles, are selected to be responsible for emulating non-existing vehicles. Such vehicles cooperatively disseminate decoy traffic without affecting safety-critical operations: with 50% of vehicles as relaying vehicles, the probability of linking pseudonyms (for the entire interval) drops from ≈68% to ≈18%. On average, this imposes 28 ms extra computation overhead, per second, on the Road-Side Units (RSUs) and 4.67 ms extra computation overhead, per second, on the (relaying) vehicle side; it also introduces 1.46 KB/sec extra communication overhead by (relaying) vehicles and 45 KB/sec by RSUs for the dissemination of decoy traffic. Thus, user privacy is enhanced at the cost of low computation and communication overhead.
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| 11. |
- Ma, Yulin, et al.
(författare)
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A novel multi-mode hybrid control method for cooperative driving of an automated vehicle platoon
- 2021
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Ingår i: IEEE Internet of Things Journal. - : IEEE. - 2327-4662. ; 8:7, s. 5822-5838
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Tidskriftsartikel (refereegranskat)abstract
- A multi-mode hybrid automaton is proposed for setting vehicle platoon modes with velocity, distance, length, lane position and other state information. Based on a vehicle platoon shift movement under different modes, decisions are made based on key conditional actions such as sudden acceleration changes because of vehicle distance changes, emergency braking to avoid collisions and free-lane changing choices adapted to various traffic conditions, so as to ensure effortless movement and safety in multi-mode shift. With a 3-degree (longitudinal, lateral, and yaw directions) of freedom coupled model, a hybrid vehicle platoon controller is proposed using non-singular terminal sliding mode control to ensure fast and steady tracking on the hybrid automaton outputs during the multi-mode shift process. Convergence of the hybrid controller in finite time is also analyzed with the Lyapunov exponential stability. The analysis result proves that the proposed controller not only ensures the stability of the individual vehicle and the vehicle platoon, but also ensures stability of the multi-mode shift movement system. The proposed cooperative driving strategy for vehicle platoon is evaluated using simulations, where varying traffic conditions and the influence of cutting off are considered in conjunction with demonstration simulations of a vehicle platoon’s cruising, following, lane changing, overtaking and moving in/out of garage functions.
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| 12. |
- Manjakkal, Libu, et al.
(författare)
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Connected Sensors, Innovative Sensor Deployment, and Intelligent Data Analysis for Online Water Quality Monitoring
- 2021
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Ingår i: IEEE Internet of Things Journal. - : Institute of Electrical and Electronics Engineers (IEEE). - 2327-4662. ; 8:18, s. 13805-13824
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Tidskriftsartikel (refereegranskat)abstract
- The sensor technology for water quality monitoring (WQM) has improved during recent years. The cost-effective sensorised tools that can autonomously measure the essential physical-chemical-biological (PCB) variables are now readily available and are being deployed on buoys, boats, and ships. Yet, there is a disconnect between the data quality, data gathering, and data analysis due to the lack of standardized approaches for data collection and processing, spatiotemporal variation of key parameters in water bodies and new contaminants. Such gaps can be bridged with a network of multiparametric sensor systems deployed in water bodies using autonomous vehicles, such as marine robots and aerial vehicles to broaden the data coverage in space and time. Furthermore, intelligent algorithms [e.g., artificial intelligence (AI)] could be employed for standardized data analysis and forecasting. This article presents a comprehensive review of the sensors, deployment, and analysis technologies for WQM. A network of networked water bodies could enhance the global data intercomparability and enable WQM at a global scale to address global challenges related to food (e.g., aqua/agriculture), drinking water, and health (e.g., water-borne diseases).
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| 13. |
- Nguyen, Tan N., et al.
(författare)
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Throughput Enhancement in FD-and SWIPT-enabled IoT Networks over Non-Identical Rayleigh Fading Channels
- 2021
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Ingår i: IEEE Internet of Things Journal. - : Institute of Electrical and Electronics Engineers (IEEE). - 2327-4662. ; , s. 1-1
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Tidskriftsartikel (refereegranskat)abstract
- Simultaneous wireless information and power transfer (SWIPT) and full-duplex (FD) communications have emerged as prominent technologies in overcoming the limited energy resources in Internet-of-Things (IoT) networks and improving their spectral efficiency (SE). The article investigates the outage and throughput performance for a decode-and-forward (DF) relay SWIPT system, which consists of one source, multiple relays, and one destination. The relay nodes in this system can harvest energy from the source’s signal and operate in FD mode. A suboptimal, low-complexity, yet efficient relay selection scheme is also proposed. Specifically, a single relay is selected to convey information from a source to a destination so that it achieves the best channel from the source to the relays. An analysis of outage probability (OP) and throughput performed on two relaying strategies, termed static power splitting-based relaying (SPSR) and optimal dynamic power splitting-based relaying (ODPSR), is presented. Notably, we considered independent and non-identically distributed (i.n.i.d.) Rayleigh fading channels, which pose new challenges in obtaining analytical expressions. In this context, we derived exact closed-form expressions of the OP and throughput of both SPSR and ODPSR schemes. We also obtained the optimal power splitting ratio of ODPSR for maximizing the achievable capacity at the destination. Finally, we present extensive numerical and simulation results to confirm our analytical findings. Both simulation and analytical results show the superiority of ODPSR over SPSR.
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| 14. |
- Nguyen, V. -D, et al.
(författare)
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Efficient Federated Learning Algorithm for Resource Allocation in Wireless IoT Networks
- 2021
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Ingår i: IEEE Internet of Things Journal. - : Institute of Electrical and Electronics Engineers (IEEE). - 2327-4662. ; 8:5, s. 3394-3409
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Tidskriftsartikel (refereegranskat)abstract
- Federated learning (FL) allows multiple edge computing nodes to jointly build a shared learning model without having to transfer their raw data to a centralized server, thus reducing communication overhead. However, FL still faces a number of challenges such as nonindependent and identically distributed data and heterogeneity of user equipments (UEs). Enabling a large number of UEs to join the training process in every round raises a potential issue of the heavy global communication burden. To address these issues, we generalize the current state-of-the-art federated averaging (FedAvg) by adding a weight-based proximal term to the local loss function. The proposed FL algorithm runs stochastic gradient descent in parallel on a sampled subset of the total UEs with replacement during each global round. We provide a convergence upper bound characterizing the tradeoff between convergence rate and global rounds, showing that a small number of active UEs per round still guarantees convergence. Next, we employ the proposed FL algorithm in wireless Internet-of-Things (IoT) networks to minimize either total energy consumption or completion time of FL, where a simple yet efficient path-following algorithm is developed for its solutions. Finally, numerical results on unbalanced data sets are provided to demonstrate the performance improvement and robustness on the convergence rate of the proposed FL algorithm over FedAvg. They also reveal that the proposed algorithm requires much less training time and energy consumption than the FL algorithm with full user participation. These observations advocate the proposed FL algorithm for a paradigm shift in bandwidth-constrained learning wireless IoT networks.
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| 15. |
- Park, P., et al.
(författare)
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Wireless Avionics Intra-Communications : A Survey of Benefits, Challenges, and Solutions
- 2021
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Ingår i: IEEE Internet of Things Journal. - : Institute of Electrical and Electronics Engineers Inc.. - 2327-4662. ; 8:10, s. 7745-7767
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Tidskriftsartikel (refereegranskat)abstract
- In the aeronautics industry, wireless avionics intra-communications have a tremendous potential to improve efficiency and flexibility while reducing weight, fuel consumption, and maintenance costs over traditional wired avionics systems. This survey starts with an overview of the major benefits and opportunities in the deployment of wireless technologies for critical applications in an aircraft. The current state-of-art is presented in terms of system classifications based on data rate demands and transceiver installation locations. We then discuss major technical challenges in the design and realization of the envisioned aircraft applications. Although wireless avionics intra-communication has aspects and requirements similar to mission-critical applications of industrial automation, it also has specific issues such as wireless channels, complex structures, operations, and safety of the aircraft that make this area of research self-standing and challenging. Existing wireless techniques are discussed to investigate the applicability of the current solutions for the critical operations of an aircraft. Specifically, IEEE 802.15.4-based and Bluetooth-based solutions are discussed for low data rate applications, whereas IEEE 802.11-based and UWB-based solutions are considered for high data rate applications. We conclude the survey by highlighting major research directions in this emerging area.
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| 16. |
- Scherer, M., et al.
(författare)
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TinyRadarNN : Combining Spatial and Temporal Convolutional Neural Networks for Embedded Gesture Recognition with Short Range Radars
- 2021
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Ingår i: IEEE Internet of Things Journal. - : Institute of Electrical and Electronics Engineers Inc.. - 2327-4662. ; 8:13, s. 10336-10346
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Tidskriftsartikel (refereegranskat)abstract
- This work proposes a low-power high-accuracy embedded hand-gesture recognition algorithm targeting battery-operated wearable devices using low-power short-range RADAR sensors. A 2-D convolutional neural network (CNN) using range-frequency Doppler features is combined with a temporal convolutional neural network (TCN) for time sequence prediction. The final algorithm has a model size of only 46 thousand parameters, yielding a memory footprint of only 92 KB. Two data sets containing 11 challenging hand gestures performed by 26 different people have been recorded containing a total of 20'210 gesture instances. On the 11 hand gesture data set, accuracies of 86.6% (26 users) and 92.4% (single user) have been achieved, which are comparable to the state of the art, which achieves 87% (10 users) and 94% (single user), while using a TCN-based network that is $7500\times $ smaller than the state of the art. Furthermore, the gesture recognition classifier has been implemented on a parallel ultralow power processor, demonstrating that real-time prediction is feasible with only 21 mW of power consumption for the full TCN sequence prediction network, while a system-level power consumption of less than 120 mW is achieved. We provide open-source access to example code and all data collected and used in this work on tinyradar.ethz.ch. © 2014 IEEE.
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| 17. |
- Sha, Chao, et al.
(författare)
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A Periodic and Distributed Energy Supplement Method based on Maximum Recharging Benefit in Sensor Networks
- 2021
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Ingår i: IEEE Internet of Things Journal. - : IEEE. - 2327-4662. ; 8:4, s. 2649-2669
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Tidskriftsartikel (refereegranskat)abstract
- The issue of using vehicles to wirelessly recharge nodes for energy supplement in Wireless Sensor Networks has become a research hotspot in recent works. Unfortunately, most of the researches did not consider the rationality of the recharging request threshold and also overlooked the difference of node’s power consumption, which may lead to premature death of nodes as well as low efficiency of Wireless Charging Vehicles(WCVs). In order to solve the above problems, a Periodic and Distributed Energy Supplement Method based on maximum recharging benefit (PDESM) is proposed in this paper. Firstly, to avoid frequent recharging requests from nodes, we put forward an annuluses based cost-balanced data uploading strategy under deterministic deployment. Then, one WCV in each annulus periodically selects and recharges nodes located in this region which send the energy supplement requests. In addition, the predicted value of power consumption of nodes are calculated out according to the real-time energy consumption rate, and thus the most appropriate recharging request threshold is obtained. Finally, a moving path optimization scheme based on Minimum Spanning Tree is constructed for distributed recharging. Simulation results show that, PDESM performs well on enhancing the proportion of the alive nodes as well as the wireless recharging efficiency compared with NFAOC and FCFS. Moreover, it also has advantage in balancing the energy consumption of WCVs.
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| 18. |
- Sodhro, Ali Hassan, et al.
(författare)
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Toward Convergence of AI and IoT for Energy-Efficient Communication in Smart Homes
- 2021
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Ingår i: IEEE Internet of Things Journal. - : IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC. - 2327-4662. ; 8:12, s. 9664-9671
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Tidskriftsartikel (refereegranskat)abstract
- The convergence of artificial intelligence (AI) and the Internet of Things (IoT) promotes energy-efficient communication in smart homes. Quality-of-Service (QoS) optimization during video streaming through wireless micro medical devices (WMMDs) in smart healthcare homes is the main purpose of this research. This article contributes in four distinct ways. First, to propose a novel lazy video transmission algorithm (LVTA). Second, a novel video transmission rate control algorithm (VTRCA) is proposed. Third, a novel cloud-based video transmission framework is developed. Fourth, the relationship between buffer size and performance indicators, i.e., peak-to-mean ratio (PMR), energy (i.e., encoding and transmission), and standard deviation, is investigated while comparing LVTA, VTRCA, and baseline approaches. The experimental results demonstrate that the reduction in encoding (32% and 35.4%) and transmission (37% and 39%) energy drains, PMR (5 and 4), and standard deviation (3 and 4 dB) for VTRCA and LVTA, respectively, is greater than that obtained by baseline during video streaming through WMMD.
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| 19. |
- Sodhro, Ali Hassan, et al.
(författare)
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Towards 6G Architecture for Energy Efficient Communication in IoT-Enabled Smart Automation Systems
- 2021
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Ingår i: IEEE Internet of Things Journal. - USA : IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC. - 2327-4662. ; 8:7, s. 5141-5148
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Tidskriftsartikel (refereegranskat)abstract
- Energy-efficient communication has become the center of attention from various interdisciplinary fields, such as industrial automation, healthcare, and transportation, among others. Besides, proliferation in the artificial intelligence (AI)-based sixth-generation (6G) technology for achieving the smart automation system has caught the attention of both academia and industry. Most of the intelligent automation systems are formed by IoT-based user terminal (UT) devices for multimedia (i.e., video, audio, image, and text) content delivery with high clarity and efficiency. Customer satisfaction/perception, i.e., Quality of Experience (QoE), is an essential factor to be analyzed because the Quality of Service (QoS) is not a suitable candidate to portray the feelings and expectations of users during multimedia transmission. Therefore, the energy-efficient, entropy-aware communication, and QoE analysis through IoT devices are the dire need. This article focuses on how the energy-efficient communication and user’s QoE level can be captured through the UT device during multimedia transmission. Thus first, QoS-based joint energy and entropy optimization (QJEEO) algorithm is proposed. Second, the 6G-driven multimedia data structure model and framework are developed for modeling and evaluation of QoE with acquisition time. Third, the relationship between subjective test score (i.e., surveyed data) and objective performance metrics with mobility/speed of IoT-based devices for multimedia service is established. Fourth, the correlation model is proposed for integrating QoS parameters with estimated QoE perceptions. The experimental results indicate that QoE is modeled and evaluated with acquisition time and correlated with QoS parameter, i.e., packet loss ratio (PLR), and average transfer delay during energy-efficient multimedia transmission in 6G-based networks to improve the satisfaction level of customers.
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| 20. |
- Srinivas, Jangirala, et al.
(författare)
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Designing Secure User Authentication Protocol for Big Data Collection in IoT-Based Intelligent Transportation System
- 2021
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Ingår i: IEEE Internet of Things Journal. - : IEEE. - 2327-4662. ; 8:9, s. 7727-7744
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Tidskriftsartikel (refereegranskat)abstract
- Secure access of the real-time data from the IoT smart devices (e.g., vehicles) by a legitimate external party (user) is an important security service for Big Data collection in Internet of Things (IoT)-based Intelligent Transportation System (ITS). To deal with this important issue, we design a new three-factor user authentication scheme, called UAP-BCIoT, which relies on Elliptic Curve Cryptography (ECC). The mutual authentication between the user and an IoT device happens via the semi-trusted Cloud-Gateway (CG) node in UAP-BCIoT. UAP-BCIoT supports several functionality features needed for IoT-based ITS environment including IoT smart device credential validation and Big Data analytics. A detailed security analysis is conducted based on the defined threat model to show that UAP-BCIoT is resilient against many known attacks. A thorough comparative study reveals that UAP-BCIoT supports better security, offers various functionality attributes, and also provides similar costs in communication as well computation as compared to other relevant schemes Finally, the practical demonstration of the proposed UAP-BCIoT is also provided to measure its impact on the network performance parameters.
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| 21. |
- Tavana, Morteza, et al.
(författare)
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Wireless Power Transfer for Aircraft IoT Applications : System Design and Measurements
- 2021
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Ingår i: IEEE Internet of Things Journal. - : Institute of Electrical and Electronics Engineers (IEEE). - 2327-4662. ; 8:15, s. 11834-11846
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Tidskriftsartikel (refereegranskat)abstract
- Sensors currently deployed on board have wired connectivity, which increases weight and maintenance costs for aircraft. Removing cables for wireless communications of sensors on board alleviates the cost, however, the powering of sensors becomes a challenge inside aircraft. Wireless power transfer (WPT) via radio-frequency (RF) signals is an emerging solution to remotely power sensors for battery-less operation with long-lived capacitors. In this article, we design a WPT system for aircraft IoT-type applications, including low data rate inside (LI) sensors by determining the number, location, and tilt angles of WPT transmitters given constraints based on the cabin geometry and duty cycle of the sensors. We formulate a robust optimization problem to address the WPT system design under channel uncertainties. We also derive an equivalent integer linear programming and solve that for an optimal deployment to satisfy the duty cycle requirements of LI sensors. We perform experiments inside the cabin to validate the wireless avionics intracommunications channel model. Our simulations demonstrate the feasibility of 90% robust design with 14 WPT transmitters for duty cycles less than 0.1% while keeping the human radiation exposure below the recommended reference value of 4.57 W/m(2).
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| 22. |
- Ye, Xiaozhen, et al.
(författare)
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Flow Experience Detection and Analysis for Game Users by Wearable-Devices-Based Physiological Responses Capture
- 2021
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Ingår i: IEEE Internet of Things Journal. - : IEEE. - 2327-4662. ; 8:3, s. 1373-1387
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Tidskriftsartikel (refereegranskat)abstract
- Relevant research has shown the potential to understand the game user experience (GUX) more accurately and reliably by measuring the user’s psychophysiological responses. However, the current studies are still very scarce and limited in scope and depth. Besides, the low-detection accuracy and the common use of the professional physiological signal apparatus make it difficult to be applied in practice. This article analyzes the GUX, particularly flow experience, based on users’ physiological responses, including the galvanic skin response (GSR) and heart rate (HR) signals, captured by low-cost wearable devices. Based on the collected data sets regarding two test games and the mixed data set, several classification models were constructed to detect the flow state automatically. Hereinto, two strategies were proposed and applied to improve classification performance. The results demonstrated that the flow experience of game users could be effectively classified from other experiences. The best accuracies of two-way classification and three-way classification under the support of the proposed strategies were over 90% and 80%, respectively. Specifically, the comparison test with the existing results showed that Strategy1 could significantly reduce the negative interference of individual differences in physiological signals and improve the classification accuracy. In addition, the results of the mixed data set identified the potential of a general classification model of flow experience.
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| 23. |
- Zhou, Sheng, et al.
(författare)
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Special Issue on Age of Information and Data Semantics for Sensing, Communication, and Control Co-Design in IoT
- 2021
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Ingår i: IEEE Internet of Things Journal. - Piscataway : IEEE-Inst Electrical Electronics Engineers Inc. - 2327-4662. ; 8:19, s. 14431-14434
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- A typical Internet-of-Things (IoT) system consists of three major layers: 1) sensing; 2) communication; and 3) application (i.e., actuation and control) layers. The co-design of these layers has been studied for over two decades, dating back to the concept of communication, computing, and control, i.e., 3C, convergence in the 1990s. Nowadays, with the emergence of wireless-networked machine-type applications, such as connected autonomous driving and factory automation, this co-design is more urgently desired than ever to meet the stringent quality-of-service requirements thereof. To realize this goal, the 5G wireless network of today has mainly focused on the communication part and strived to reliably achieve low air-interface communication delay, i.e., ultra-reliable and low-latency communications (uRLLC). However, more and more wireless communications in IoT are based on status updates instead of general content delivery. The current uRLLC design is insufficient to characterize the status update quality, and thus is unable to optimize for timely status update with constrained wireless resources. Therefore, the performance of computing and control in IoT networks that rely highly on wireless communications is suboptimal.
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