| 1. |
- Ahmad, Sabtain, et al.
(författare)
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Sustainable environmental monitoring via energy and information efficient multi-node placement
- 2023
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Ingår i: IEEE Internet of Things Journal. - : IEEE. - 2327-4662. ; 10:24, s. 22065-22079
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Tidskriftsartikel (refereegranskat)abstract
- The Internet of Things is gaining traction for sensing and monitoring outdoor environments such as water bodies, forests, or agricultural lands. Sustainable deployment of sensors for environmental sampling is a challenging task because of the spatial and temporal variation of the environmental attributes to be monitored, the lack of the infrastructure to power the sensors for uninterrupted monitoring, and the large continuous target environment despite the sparse and limited sampling locations. In this paper, we present an environment monitoring framework that deploys a network of sensors and gateways connected through low-power, long-range networking to perform reliable data collection. The three objectives correspond to the optimization of information quality, communication capacity, and sustainability. Therefore, the proposed environment monitoring framework consists of three main components: (i) to maximize the information collected, we propose an optimal sensor placement method based on QR decomposition that deploys sensors at information- and communication-critical locations; (ii) to facilitate the transfer of big streaming data and alleviate the network bottleneck caused by low bandwidth, we develop a gateway configuration method with the aim to reduce the deployment and communication costs; and (iii) to allow sustainable environmental monitoring, an energy-aware optimization component is introduced. We validate our method by presenting a case study for monitoring the water quality of the Ergene River in Turkey. Detailed experiments subject to real-world data show that the proposed method is both accurate and efficient in monitoring a large environment and catching up with dynamic changes.
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| 2. |
- Ahmed, Tauheed, et al.
(författare)
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FIMBISAE : A Multimodal Biometric Secured Data Access Framework for Internet of Medical Things Ecosystem
- 2023
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Ingår i: IEEE Internet of Things Journal. - : IEEE. - 2327-4662. ; 10:7, s. 6259-6270
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Tidskriftsartikel (refereegranskat)abstract
- Information from the Internet of Medical Things (IoMT) domain demands building safeguards against illegitimate access and identification. Existing user identification schemes suffer from challenges in detecting impersonation attacks which leave systems vulnerable and susceptible to misuse. Significant advancement has been achieved in the domain of biometrics and health informatics. This can take a step ahead with the usage of multimodal biometrics for the identification of healthcare system users. With this aim, the proposed work explores the fingerprint and iris modality to develop a multimodal biometric data identification and access control system for the healthcare ecosystem. In the proposed approach, minutiae-based fingerprint features and a combination of local and global iris features are considered for identification. Further, an index space based on the dimension of the feature vector is created, which gives a 1-D embedding of the high-dimensional feature set. Next, to minimize the impact of false rejection, the approach considers the possible deviation in each element of the feature vector and then stores the data in possible locations using the predefined threshold. Besides, to reduce the false acceptance rate, linking of the modalities has been done for every individual data. The modality linking thus helps in carrying out an efficient search of the queried data, thereby minimizing the false acceptance and rejection rate. Experiments on a chimeric iris and fingerprint bimodal database resulted in an average of 95% reduction in the search space at a hit rate of 98%. The results suggest that the proposed indexing scheme has the potential to substantially reduce the response time without compromising the accuracy of identification.
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| 3. |
- Chavhan, Suresh, et al.
(författare)
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Edge-enabled Blockchain-based V2X Scheme for Secure Communication within the Smart City Development
- 2023
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Ingår i: IEEE Internet of Things Journal. - Piscataway, NJ : Institute of Electrical and Electronics Engineers (IEEE). - 2327-4662. ; 10:24, s. 21282-21293
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Tidskriftsartikel (refereegranskat)abstract
- As the high mobility nature of the vehicles results in frequent leaving and joining the transportation network, real-time data must be collected and shared in a timely manner. In such a transportation network, malicious vehicles can disrupt services and create serious issues, such as deadlocks and accidents. The blockchain is a technology that ensures traceability, consistency, and security in transportation networks. In this study, we integrated edge computing and blockchain technology to improve the optimal utilization of resources, especially in terms of computing, communication, security, and storage. We propose a novel, edge-integrated, blockchain-based vehicle platoon security scheme. For the vehicle platoon, we developed the security architecture, implemented smart contracts for practical network scenarios in NS-3, and integrated them with the SUMO TraCI API. We exhaustively simulated all the scenarios and analyzed the communication performance metrics, such as throughput, delay, and jitter, and the security performance metrics, such as mean squared error, communication, and computational cost. The performance results demonstrate that the developed scheme can solve security-related issues more effectively and efficiently in smart cities. © IEEE
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| 4. |
- Ghayvat, Hemant, et al.
(författare)
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STRENUOUS : Edge-Line Computing, AI, and IIoT Enabled GPS Spatiotemporal Data-Based Meta-Transmission Healthcare Ecosystem for Virus Outbreaks Discovery
- 2023
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Ingår i: IEEE Internet of Things Journal. - : IEEE. - 2327-4662 .- 2372-2541. ; 10:4, s. 3285-3294
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Tidskriftsartikel (refereegranskat)abstract
- COVID-19 is not the last virus; there would be many others viruses we may face in the future. We already witnessed the loss of economy and daily life through the lockdown. In addition, vaccine, medication, and treatment strategies take clinical trials, so there is a need to tracking and tracing approach. Suitably, exhibiting and computing social evolution is critical for refining the epidemic, but maybe crippled by location data ineptitude of inaccessibility. It is complex and time consuming to identify and detect the chain of virus spread from one person to another through the terabytes of spatiotemporal GPS data. The proposed research aims a HPE edge line computing and big data analytic supported virus outbreak tracing and tracking approach that consumes terabytes of spatiotemporal data. Proposed STRENUOUS system discovers the prospect of applying an individual’s mobility to label mobility streams and forecast a virus-like COVID-19 epidemic transmission. The method and the mechanical assembly further contained an alert component to demonstrate a suspected case if there was a potential exposure with the confirmed subject. The proposed system tracks location data related to a suspected subject in the confirmed subject route, where the location data expresses one or more geographic locations of each user over a period. It recognizes a subcategory of the suspected subject who is expected to transmit a contagion based on the location data. System measure an exposure level of a carrier to the infection based on contaminated location data and a subset of carriers connected with the second location carrier. They investigated whether the people in the confirmed subject’s cross-path can be infected and suggest quarantine followed by testing. The Proposed STRENUOUS system produces a report specifying that the people have been exposed to the virus.
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| 5. |
- Hazra, Abhishek, et al.
(författare)
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Cooperative Transmission Scheduling and Computation Offloading With Collaboration of Fog and Cloud for Industrial IoT Applications
- 2023
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Ingår i: IEEE Internet of Things Journal. - : Institute of Electrical and Electronics Engineers (IEEE). - 2327-4662 .- 2372-2541. ; 10:5, s. 3944-3953
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Tidskriftsartikel (refereegranskat)abstract
- Energy consumption for large amounts of delay-sensitive applications brings serious challenges with the continuous development and diversity of Industrial Internet of Things (IIoT) applications in fog networks. In addition, conventional cloud technology cannot adhere to the delay requirement of sensitive IIoT applications due to long-distance data travel. To address this bottleneck, we design a novel energy–delay optimization framework called transmission scheduling and computation offloading ( TSCO ), while maintaining energy and delay constraints in the fog environment. To achieve this objective, we first present a heuristic-based transmission scheduling strategy to transfer IIoT-generated tasks based on their importance. Moreover, we also introduce a graph-based task-offloading strategy using constrained-restricted mixed linear programming to handle high traffic in rush-hour scenarios. Extensive simulation results illustrate that the proposed TSCO approach significantly optimizes energy consumption and delay up to 12%–17% during computation and communication over the traditional baseline algorithms.
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| 6. |
- Jiang, Zhihan, et al.
(författare)
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Leveraging Machine Learning for Disease Diagnoses based on Wearable Devices : A Survey
- 2023
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Ingår i: IEEE Internet of Things Journal. - : Institute of Electrical and Electronics Engineers (IEEE). - 2327-4662. ; 10:24, s. 21959-21981
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Tidskriftsartikel (refereegranskat)abstract
- Many countries around the world are facing a shortage of healthcare resources, especially during the post-epidemic era, leading to a dramatic increase in the need for self-detection and self-management of diseases. The popularity of smart wearable devices, such as smartwatches, and the development of machine learning bring new opportunities for the early detection and management of various prevalent diseases, such as cardiovascular diseases, Parkinson’s disease, and diabetes. In this survey, we comprehensively review the articles related to specific diseases or health issues based on small wearable devices and machine learning. More specifically, we first present an overview of the articles selected and classify them according to their targeted diseases. Then, we summarize their objectives, wearable device and sensor data, machine learning techniques, and wearing locations. Based on the literature review, we discuss the challenges and propose future directions from the perspectives of privacy concerns, security concerns, transmission latency and reliability, energy consumption, multi-modality, multi-sensor, multi-devices, evaluation metrics, explainability, generalization and personalization, social influence, and human factors, aiming to inspire researchers in this field.
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| 7. |
- Li, Chao, et al.
(författare)
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Federated Hierarchical Trust-based Interaction Scheme for Cross-domain Industrial IoT
- 2023
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Ingår i: IEEE Internet of Things Journal. - : IEEE. - 2327-4662 .- 2372-2541. ; 10:1, s. 447-457
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Tidskriftsartikel (refereegranskat)abstract
- The Industrial Internet of Things (IIoT) is considered to be one of the most promising revolutionary technologies to increase productivity. With the refined development of manufacturing, the entire manufacturing process is split up into several areas of IoT production. Devices from different domains cooperate to perform the same task, which cause security problems in interacted communication among them. Existing authentication methods cause heavy key management overhead or rely on a trusted third party. It is imperative to protect privacy and ensure the credibility of the device during device interaction. This paper proposes a federated hierarchical trust interaction scheme (FHTI) for the cross-domain industrial IoT. It builds a low-privacy network platform through blockchain and protects the data privacy of the IIoT. A hierarchical trust mechanism based on federated detection is designed to realize the unified trust evaluation of cross-domain devices. A trusted cross-domain method based on device trust value is designed to ensure the security and trustworthiness of cross-domain devices. The simulation results show that the FHTI scheme can improve the speed of identity authentication and the detection accuracy of malicious devices.
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| 8. |
- Ma, Teng, et al.
(författare)
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Spreading CDMA via RIS : Multipath Separation, Estimation, and Combination
- 2023
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Ingår i: IEEE Internet of Things Journal. - : Institute of Electrical and Electronics Engineers (IEEE). - 2327-4662. ; 10:13, s. 11396-11413
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Tidskriftsartikel (refereegranskat)abstract
- As a revolutionary technology for future wireless communications, reconfigurable intelligent surface (RIS), characterized by an efficient way of manipulating wireless signals, has been widely investigated in recent years toward enhancing signal quality, energy efficiency, throughput, and so on. However, in RIS-assisted Internet of Things (IoT), a new issue as multipath separation emerges, especially, when deploying multiple RISs to assist communication, since the devices may have limited signal processing capabilities. For alleviating this problem, we conceive a novel RIS-enabled code-division multiple access (CDMA) structure, where each RIS holds a specified time-varying coefficient to tag the channel. Moreover, multipath extraction is further considered, including a practical channel estimation approach along with theoretical derivations in terms of Cramér-Rao lower bound, mean-square error, as well as ergodic channel capacity. Simulation results corroborate the feasibility of the conceived RIS-CDMA structure and the effectiveness of the proposed multipath extraction approach.
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| 9. |
- Maity, Priyanka, et al.
(författare)
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Hybrid Precoder and Combiner Designs for Decentralized Parameter Estimation in mmWave MIMO Wireless Sensor Networks
- 2023
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Ingår i: IEEE Internet of Things Journal. - : Institute of Electrical and Electronics Engineers (IEEE). - 2327-4662. ; 11:1, s. 1629-1643
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Tidskriftsartikel (refereegranskat)abstract
- Hybrid precoder and combiner designs are conceived for decentralized parameter estimation in millimeter wave (mmWave) multiple-input-multiple-output (MIMO) wireless sensor networks (WSNs). More explicitly, efficient pre- and post-processing of the sensor observations and received signal are proposed for the minimum mean square error (MMSE) estimation of a parameter vector. The proposed techniques exploit the limited scattering nature of the mmWave MIMO channel for formulating the hybrid transceiver design framework as a multiple measurement vectors (MMVs)-based sparse signal recovery problem. This is then solved using the iterative appealingly low-complexity simultaneous orthogonal matching pursuit (SOMP). Tailor-made designs are presented for WSNs operating under both total and per-sensor power constraints, while considering ideal noiseless as well as realistic noisy sensors. Furthermore, both the Bayesian Cramer-Rao lower bound and the centralized MMSE bound are derived for benchmarking the proposed decentralized estimation schemes. Our simulation results demonstrate the efficiency of the designs advocated and verify the analytical findings.
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| 10. |
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| 11. |
- Mishra, Deepak, et al.
(författare)
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Low-Complexity Beamforming Designs and Channel Estimation for Passive-Intelligent-Surface-Assisted MISO Energy Transfer
- 2023
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Ingår i: IEEE Internet of Things Journal. - : IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC. - 2327-4662. ; 10:9, s. 8286-8304
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Tidskriftsartikel (refereegranskat)abstract
- The usage of passive intelligent surface (PIS) is emerging as a low-cost green alternative to massive antenna systems for realizing high-energy beamforming (EB) gains. Considering the limited computational capability and constant-envelope precoding for PIS, we propose three novel low-complexity passive EB designs for optimizing the efficacy of PIS-assisted energy transfer (PET) from a multiantenna power beacon (PB) to a single-antenna energy harvesting (EH) user. The first EB design involves solving a univariate equation, and closed forms expressed are presented for the other two. Further, to maximize the practical utility of PET, we introduce a novel channel estimation (CE) protocol for obtaining least-squares estimators for the channels as required for EB designing. Using them, we also derive closed-form expressions for optimal PIS location and optimal time allocation between CE and PET within each coherence block to maximize the users net harvested energy. Numerical results verify the CE analysis and validate the novel analytical bound derived for received power during PET and proposed PIS designs quality against existing benchmarks. We show that the proposed jointly optimal design for PET can yield a significant improvement of about 15 dB, and a reduced active array size at PB can achieve the desired EB gain with sufficient passive elements at PIS. Finally, we also briefly discuss how the proposed CE and EB designs can be extended to the multiuser settings.
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| 12. |
- Mostaani, Arsham, et al.
(författare)
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Task-Effective Compression of Observations for the Centralized Control of a Multi-agent System Over Bit-Budgeted Channels
- 2023
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Ingår i: IEEE Internet of Things Journal. - : Institute of Electrical and Electronics Engineers (IEEE). - 2327-4662. ; , s. 1-
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Tidskriftsartikel (refereegranskat)abstract
- We consider a task-effective quantization problem that arises when multiple agents are controlled via a centralized controller (CC). While agents have to communicate their observations to the CC for decision-making, the bit-budgeted communications of agent-CC links may limit the task-effectiveness of the system which is measured by the system’s average sum of stage costs/rewards. As a result, each agent should compress/quantize its observation such that the average sum of stage costs/rewards of the control task is minimally impacted. We address the problem of maximizing the average sum of stage rewards by proposing two different Action-Based State Aggregation (ABSA) algorithms that carry out the indirect and joint design of control and communication policies in the multi-agent system. While the applicability of ABSA-1 is limited to single-agent systems, it provides an analytical framework that acts as a stepping stone to the design of ABSA-2. ABSA-2 carries out the joint design of control and communication for a multi-agent system. We evaluate the algorithms -with average return as the performance metric -using numerical experiments performed to solve a multi-agent geometric consensus problem. The numerical results are concluded by introducing a new metric that measures the effectiveness of communications in a multi-agent system.
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| 13. |
- Nguyen Dang, Tri, et al.
(författare)
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A Contract-Theory-Based Incentive Mechanism for UAV-Enabled VR-Based Services in 5G and Beyond
- 2023
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Ingår i: IEEE Internet of Things Journal. - : Institute of Electrical and Electronics Engineers (IEEE). - 2327-4662. ; 10:18, s. 16465-16479
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Tidskriftsartikel (refereegranskat)abstract
- The proliferation of novel infotainment services, such as virtual reality (VR)-based services, has fundamentally changed the existing mobile networks. These bandwidth-hungry services expanded at a tremendously rapid pace, thus, generating a burden of data traffic in the mobile networks. To cope with this issue, one can use multiaccess edge computing (MEC) to bring the resource to the edge. By doing so, we can release the burden of the core network by taking the communication, computation, and caching resources nearby the end users (UEs). Nevertheless, due to the vast adoption of VR-enabled devices, MEC resources might be insufficient in peak times or dense settings. To overcome these challenges, we propose a system model where the service provider (SP) might rent unmanned area vehicles (UAVs) from UAV SPs (USPs) to serve as micro-base stations (UBSs) that expand the service area and improve the spectrum efficiency. In which, UAV can precached certain sets of VR-based contents and serve UEs via air-to-ground (A2G) communication. Furthermore, future intelligent devices are capable of 5G and B5G communication interfaces, and thus, they can communicate with UAVs via A2G links. By doing so, we can significantly reduce a considerable amount of data traffic in mobile networks. In order to successfully enable such kinds of services, an attractive incentive mechanism is required. Therefore, we propose a contract theory-based incentive mechanism for UAV-assisted MEC in VR-based infotainment services, in which the MEC offers an amount reward to a UAV for serving as a UBS in a specific location for certain time slots. We then derive an optimal contract-based scheme with individual rationality and incentive compatibility conditions. The numerical findings show that our proposed approach outperforms the linear pricing (LP) technique and is close to the optimal solution in terms of social welfare. Additionally, our proposed scheme significantly enhanced the fairness of utility for UAVs in asymmetric information problems.
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| 14. |
- Nguyen, Loc X., et al.
(författare)
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Dependency Tasks Offloading and Communication Resource Allocation in Collaborative UAV Networks : A Metaheuristic Approach
- 2023
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Ingår i: IEEE Internet of Things Journal. - : Institute of Electrical and Electronics Engineers (IEEE). - 2327-4662. ; 10:10, s. 9062-9076
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Tidskriftsartikel (refereegranskat)abstract
- Nowadays, unmanned aerial vehicles (UAVs)-assisted mobile-edge computing (MEC) systems have been exploited as a promising solution for providing computation services to mobile users outside of terrestrial networks. However, it remains challenging for standalone UAVs to meet the computation requirement of numerous users due to their limited computation capacity and battery lives. Therefore, we propose a collaborative scheme among UAVs to share the workload between them. Furthermore, this work is the first to consider the task topology of offloading in MEC-enabled UAVs networks while restricting their power consumption. We study the task topology, in which a task consists of a set of subtasks, and each subtask has dependencies upon other subtasks. In the real world, subtasks with dependencies must wait for their preceding subtasks to complete before being executed, and this affects the offloading strategy. Next, we formulate an optimization problem to minimize the average latency of users by jointly controlling the offloading decision for dependent tasks and allocating the communication resources of UAVs. The formulated problem is NP-hard and cannot be solved in polynomial time. Therefore, we divide the problem into two subproblems: 1) offloading decision problem and 2) communication resource allocation problem. Then, a metaheuristic method is proposed to find the suboptimal solution to the former problem, while the latter problem is solved by using convex optimization. Finally, we conduct simulation experiments to prove that our proposed offloading technique outperforms several benchmark schemes in minimizing the average latency of users for dependency tasks and achieving higher uplink transmission rates.
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| 15. |
- Pandya, Sharnil, Researcher, 1984-, et al.
(författare)
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COUNTERSAVIOR : AIoMT and IIoT enabled Adaptive Virus Outbreak Discovery Framework for Healthcare Informatics
- 2023
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Ingår i: IEEE Internet of Things Journal. - : IEEE. - 2327-4662 .- 2372-2541. ; 10:4, s. 4202-4212
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Tidskriftsartikel (refereegranskat)abstract
- In the current Pandemic, global issues have caused health issues as well as economic downturns. At the beginning of every novel virus outbreak, lockdown is the best possible weapon to reduce the virus spread and save human life as the medical diagnosis followed by treatment and clinical approval takes significant time. The proposed COUNTERSAVIOR system aims at an Artificial Intelligence of Medical Things (AIoMT), and an edge line computing enabled and Big data analytics supported tracing and tracking approach that consumes GPS spatiotemporal data. COUNTERSAVIOR will be a better scientific tool to handle any virus outbreak. The proposed research discovers the prospect of applying an individual’s mobility to label mobility streams and forecast a virus such as COVID-19 pandemic transmission. The proposed system is the extension of the previously proposed COUNTERACT system. The proposed system can also identify the alternative saviour path concerning the confirmed subject’s cross-path using GPS data to avoid the possibility of infections. In the undertaken study, dynamic meta direct and indirect transmission, meta behaviour, and meta transmission saviour models are presented. In conducted experiments, the machine learning and deep learning methodologies have been used with the recorded historical location data for forecasting the behaviour patterns of confirmed and suspected individuals and a robust comparative analysis is also presented. The proposed system produces a report specifying people that have been exposed to the virus and notifying users about available pandemic saviour paths. In the end, we have represented 3D tracker movements of individuals, 3D contact analysis of COVID-19 and suspected individuals for 24 hours, forecasting and risk classification of COVID-19, suspected and safe individuals.
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| 16. |
- Rajput, Kunwar Pritiraj, et al.
(författare)
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Robust Linear Hybrid Beamforming Designs Relying on Imperfect CSI in mmWave MIMO IoT Networks
- 2023
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Ingår i: IEEE Internet of Things Journal. - : Institute of Electrical and Electronics Engineers (IEEE). - 2327-4662 .- 2372-2541. ; 10:10, s. 8893-8906
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Tidskriftsartikel (refereegranskat)abstract
- Linear hybrid beamformer designs are conceived for the decentralized estimation of a vector parameter in a millimeter wave (mmWave) multiple-input multiple-output (MIMO) Internet of Things network (IoTNe). The proposed designs incorporate both total IoTNe and individual IoTNo power constraints, while also eliminating the need for a baseband receiver combiner at the fusion center (FC). To circumvent the non-convexity of the hybrid beamformer design problem, the proposed approach initially determines the minimum mean square error (MMSE) digital transmit precoder (TPC) weights followed by a simultaneous orthogonal matching pursuit (SOMP)-based framework for obtaining the analog RF and digital baseband TPCs. Robust hybrid beamformers are also derived for the realistic imperfect channel state information (CSI) scenario, utilizing both the stochastic and norm-ball CSI uncertainty frameworks. The centralized MMSE bound derived in this work serves as a lower bound for the estimation performance of the proposed hybrid TPC designs. Finally, our simulation results quantify the benefits of the various designs developed.
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| 17. |
- Ramadan, Mohammed, et al.
(författare)
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Secure Equality Test Technique using Identity Based Signcryption for Telemedicine Systems
- 2023
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Ingår i: IEEE Internet of Things Journal. - : Institute of Electrical and Electronics Engineers Inc.. - 2327-4662. ; 10:18, s. 16594-
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Tidskriftsartikel (refereegranskat)abstract
- For telemedicine, Wireless Body Area Network (WBAN) offers enormous benefits where a patient can be remotely monitored without compromising the mobility of remote treatments. With the advent of high capacity and reliable wireless networks, WBANs are used in several remote monitoring systems, limiting the COVID-19 spread. The sensitivity of telemedicine applications mandates confidentiality and privacy requirements. In this paper, we propose a secure WBAN-19 telemedicine system to overcome the pervasiveness of contagious deceases utilizing a novel aggregate identity-based signcryption scheme with an equality test feature. We demonstrate a security analysis regarding indistinguishable adaptive chosen-ciphertext attack (IND-CCA2), one-way security against adaptive chosen-ciphertext attack (OW-CCA2), and unforgeability against adaptive chosen-message attack (EUF-CMA) under the random oracle model. The security analysis of the scheme is followed by complexity evaluations where the computation cost and communication overhead are measured. The evaluation demonstrates that the proposed model is efficient and applicable in telemedicine systems with high-performance capacities.
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| 18. |
- Ramadan, Mohammed, et al.
(författare)
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Secure Equality Test Technique Using Identity-Based Signcryption for Telemedicine Systems
- 2023
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Ingår i: IEEE Internet of Things Journal. - 2327-4662. ; 10:18, s. 16594-16604
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Tidskriftsartikel (refereegranskat)abstract
- For telemedicine, wireless body area network (WBAN) offers enormous benefits where a patient can be remotely monitored without compromising the mobility of remote treatments. With the advent of high capacity and reliable wireless networks, WBANs are used in several remote monitoring systems, limiting the COVID-19 spread. The sensitivity of telemedicine applications mandates confidentiality and privacy requirements. In this article, we propose a secure WBAN-19 telemedicine system to overcome the pervasiveness of contagious deceases utilizing a novel aggregate identity-based signcryption scheme with an equality test feature. We demonstrate a security analysis regarding indistinguishable adaptive chosen-ciphertext attack (IND-CCA2), one-way security against adaptive chosen-ciphertext attack (OW-CCA2), and unforgeability against adaptive chosen-message attack (EUF-CMA) under the random oracle model. The security analysis of the scheme is followed by complexity evaluations where the computation cost and communication overhead are measured. The evaluation demonstrates that the proposed model is efficient and applicable in telemedicine systems with high-performance capacities.
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| 19. |
- Reddy, Ch Santosh, et al.
(författare)
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Spectral Efficient Modem Design with OTFS Modulation for Vehicular-IoT System
- 2023
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Ingår i: IEEE Internet of Things Journal. - : Institute of Electrical and Electronics Engineers (IEEE). - 2327-4662 .- 2372-2541. ; 10:3, s. 2444-
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Tidskriftsartikel (refereegranskat)abstract
- A 5G network’s use-case in the Internet of Things (IoT) is a breakthrough, offering networks the ability to handle billions of connected devices with the proper blend of speed, latency, and cost. The IoT networks implemented in highspeed scenarios like intra and inter-vehicular communications in autonomous driving vehicles, high-speed vehicles, and trains will experience a Doppler effect. Orthogonal frequency-division multiplexing, popular transmission technology for existing newradio IoT (NR-IoT), is limited in providing reliable connections in high-speed vehicular scenarios. The performance of such system degrades with higher-order antenna configuration due to the lack of channel state information in highly mobile environments. The recently proposed orthogonal time-frequency space (OTFS) modulation is a strong contender that can handle high mobility but requires efficient transceiver design to be deployed in vehicular NR-IoT (V-IoT) systems. To conserve the resources and minimize the air time of the devices, we have proposed an embedded pilot design in the Delay-Doppler domain for the V-IoT systems. In the designed frame structure, the pilot’s position is optimized as per the vehicle speed to maximize the spectral efficiency of the system. The increase in spectral efficiency is at the cost of interference in the channel search region of the received Delay-Doppler domain OTFS signal. So a new joint estimator and low-complex detector is proposed to handle the interference. The proposed efficient transceiver design with the spectral efficient pilot patterns allow us to conserve resources and remove complex encoder-decoders like the low-density parity check in NR-IoT.
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| 20. |
- Sahoo, Shreeya Swagatika, et al.
(författare)
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A three factor based authentication scheme of 5G wireless sensor networks for IoT system
- 2023
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Ingår i: IEEE Internet of Things Journal. - : IEEE. - 2327-4662. ; 10:17, s. 15087-15099
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Tidskriftsartikel (refereegranskat)abstract
- Internet of Things (IoT) is an expanding technology that facilitate physical devices to inter-connect each other over a public channel. Moreover, the security of the next-generation wireless mobile communication technology, namely 5G with IoT, has been a field of much interest among researchers in the last several years. Previously, Sharif et al. had suggested an IoTbased lightweight three-party authentication scheme proclaiming a secured scheme against different threats. However, it was found that the scheme could not achieve user anonymity and guarantee session key security. Additionally, the scheme fails to provide proper authentication in the login phase, and it s unable to update a new password in the password change phase. Thus, we propose an improved three-factor-based data transmission authentication scheme (TDTAS) to address the weaknesses. The formal security analysis has been proved using the Real-or-Random (RoR) model. The informal security analysis demonstrates that the scheme is secure against several known attacks and achieves more security features. In addition, the comparison of the work with other related schemes demonstrates the proposed scheme has less communicational and storage costs.
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| 21. |
- Seo, Sangwon, et al.
(författare)
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Situation-Aware Cluster and Quantization Level Selection Algorithm for Fast Federated Learning
- 2023
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Ingår i: IEEE Internet of Things Journal. - : Institute of Electrical and Electronics Engineers (IEEE). - 2327-4662. ; 10:15, s. 13292-13302
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Tidskriftsartikel (refereegranskat)abstract
- In federated learning (FL), which clients and quantization levels are selected for the deep model parameters has a significant impact on learning time as well as learning accuracy. This is not a trivial issue because it is also significantly affected by factors, such as computational power, communication capacity, and data distribution. Considering these factors, we formulate a joint optimization problem for clustering and selecting clusters with quantization levels. Due to the high complexity of the formulated problem, we propose a situation-aware cluster and quantization level selection (SITUA-CQ) algorithm. In this algorithm, the FL server first assembles clients into clusters to mitigate the impact of biased data distributions and determines the most suitable clusters and quantization levels based on their computing power and channel quality. Extensive simulation results show that SITUA-CQ can reduce the round time by up to 80.3% compared to conventional algorithms.
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| 22. |
- Turchet, Luca, et al.
(författare)
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The Internet of Sounds : Convergent Trends, Insights, and Future Directions
- 2023
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Ingår i: IEEE Internet of Things Journal. - : Institute of Electrical and Electronics Engineers (IEEE). - 2327-4662. ; 10:13, s. 11264-11292
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Tidskriftsartikel (refereegranskat)abstract
- Current sound-based practices and systems developed in both academia and industry point to convergent research trends that bring together the field of sound and music Computing with that of the Internet of Things. This article proposes a vision for the emerging field of the Internet of Sounds (IoS), which stems from such disciplines. The IoS relates to the network of Sound Things, i.e., devices capable of sensing, acquiring, processing, actuating, and exchanging data serving the purpose of communicating sound-related information. In the IoS paradigm, which merges under a unique umbrella the emerging fields of the Internet of Musical Things and the Internet of Audio Things, heterogeneous devices dedicated to musical and nonmusical tasks can interact and cooperate with one another and with other things connected to the Internet to facilitate sound-based services and applications that are globally available to the users. We survey the state-of-the-art in this space, discuss the technological and nontechnological challenges ahead of us and propose a comprehensive research agenda for the field.
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| 23. |
- Vattaparambil Sudarsan, Sreelakshmi, 1996-, et al.
(författare)
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Multilevel Subgranting by Power of Attorney and OAuth Authorization Server in Cyber–Physical Systems
- 2023
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Ingår i: IEEE Internet of Things Journal. - : Institute of Electrical and Electronics Engineers (IEEE). - 2327-4662. ; 10:17, s. 15266-15282
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Tidskriftsartikel (refereegranskat)abstract
- Many Cyber-Physical Systems are today semiautonomous and powerful enough to perform advanced tasks on their own. This means they can also act as representatives of people or devices that have given them an order. However, traditional access control policies and delegation models do not meet industrial requirements such as support for letting autonomous CPS devices act on their own with certified credentials under the sub authorization by subcontractors, without the need for a separate account per device. In this paper, we analyze and compare power of attorney, proxy signature by warrant, and OAuth to identify the strengths and challenges of each. Based on the comparison, we propose an OAuth grant type based on the power of attorney and inspired by the concept of proxy signature by warrant. Power of Attorney is a generic and self-contained document that a principal signs and directs to an agent, thereby providing it the power to execute actions on behalf of the principal for a predefined time, even if it is offline. One key advantage of the power of attorney is that it can support effective sub-granting on several levels to support industrial scenarios where resource owners bring in authorized contractors that can in their turn authorize and bring in several devices without incurring management overhead to the resource owner. A proof-of-concept and performance evaluation of the proposed model is presented using an industrial use-case scenario with multi-level authorization.
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| 24. |
- Wang, Hang, et al.
(författare)
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A Survey on the Metaverse : The State-of-the-Art, Technologies, Applications, and Challenges
- 2023
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Ingår i: IEEE Internet of Things Journal. - : Institute of Electrical and Electronics Engineers (IEEE). - 2327-4662. ; 10:16, s. 14671-14688
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Tidskriftsartikel (refereegranskat)abstract
- In recent years, the concept of the Metaverse has attracted considerable attention. This paper provides a comprehensive overview of the Metaverse. First, the development status of the Metaverse is presented. We summarize the policies of various countries, companies, and organizations relevant to the Metaverse, as well as statistics on the number of Metaverse-related publications. Characteristics of the Metaverse are identified: 1) multi-technology convergence; 2) sociality; 3) hyper-spatio-temporality. For the multi-technology convergence of the Metaverse, we divide the technological framework of the Metaverse into five dimensions. For the sociality of the Metaverse, we focus on the Metaverse as a virtual social world. Regarding the characteristic of hyper-spatio-temporality, we introduce the Metaverse as an open, immersive, and interactive 3D virtual world which can break through the constraints of time and space in the real world. The challenges of the Metaverse are also discussed. IEEE
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| 25. |
- Xu, Yuzhe, et al.
(författare)
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Distributed Assignment With Load Balancing for DNN Inference at the Edge
- 2023
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Ingår i: IEEE Internet of Things Journal. - : Institute of Electrical and Electronics Engineers (IEEE). - 2327-4662. ; 10:2, s. 1053-1065
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Tidskriftsartikel (refereegranskat)abstract
- Inference carried out on pretrained deep neural networks (DNNs) is particularly effective as it does not require retraining and entails no loss in accuracy. Unfortunately, resource-constrained devices such as those in the Internet of Things may need to offload the related computation to more powerful servers, particularly, at the network edge. However, edge servers have limited resources compared to those in the cloud; therefore, inference offloading generally requires dividing the original DNN into different pieces that are then assigned to multiple edge servers. Related approaches in the state-of-the-art either make strong assumptions on the system model or fail to provide strict performance guarantees. This article specifically addresses these limitations by applying distributed assignment to DNN inference at the edge. In particular, it devises a detailed model of DNN-based inference, suitable for realistic scenarios involving edge computing. Optimal inference offloading with load balancing is also defined as a multiple assignment problem that maximizes proportional fairness. Moreover, a distributed algorithm for DNN inference offloading is introduced to solve such a problem in polynomial time with strong optimality guarantees. Finally, extensive simulations employing different data sets and DNN architectures establish that the proposed solution significantly improves upon the state-of-the-art in terms of inference time (1.14 to 2.62 times faster), load balance (with Jain's fairness index of 0.9), and convergence (one order of magnitude less iterations).
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| 26. |
- Zhang, Cheng, et al.
(författare)
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A Blockchain-based Model Migration Approach for Secure and Sustainable Federated Learning in IoT Systems
- 2023
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Ingår i: IEEE Internet of Things Journal. - : IEEE. - 2327-4662. ; 10:8, s. 6574-6585
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Tidskriftsartikel (refereegranskat)abstract
- Model migration can accelerate model convergence during federated learning on the Internet of Things (IoT) devices and reduce training costs by transferring feature extractors from fast to slow devices, which, in turn, enables sustainable computing. However, malicious or lazy devices may migrate the fake models or resist sharing models for their benefit, reducing the desired efficiency and reliability of a federated learning system. To this end, this work presents a blockchain-based model migration approach for resource-constrained IoT systems. The proposed approach aims to achieve secure model migration and speed up model training while minimizing computation cost. We first develop an incentive mechanism considering the economic benefits of fast devices, which breaks the Nash equilibrium established by lazy devices and encourages capable devices to train and share models. Second, we design a clustering-based algorithm for identifying malicious devices and preventing them from defrauding incentives. Third, we use blockchain to ensure trustworthiness in model migration and incentive processes. Blockchain records the interaction between the central server and IoT devices and runs the incentive algorithm without exposing the devices’ private data. Theoretical analysis and experimental results show that the proposed approach can accelerate federated learning rates, reduce model training computation costs to increase sustainability, and resist malicious attacks.
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| 27. |
- Zou, Luyao, et al.
(författare)
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When Hierarchical Federated Learning Meets Stochastic Game : Toward an Intelligent UAV Charging in Urban Prosumers
- 2023
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Ingår i: IEEE Internet of Things Journal. - : Institute of Electrical and Electronics Engineers (IEEE). - 2327-4662. ; 10:12, s. 10438-10461
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Tidskriftsartikel (refereegranskat)abstract
- Unmanned aerial vehicles (UAVs) nowadays are developing rapidly for various applications such as UAV taxis and delivery drones. However, the limited battery energy restricts the flight distance of the UAVs. Thus, urban prosumers equipped with drone recharge stations are introduced to provide charging services for the UAVs. In this article, first, a day-ahead energy scheduling problem for UAV charging-enabled urban prosumers is studied, where the objective is to maximize the overall energy satisfaction of the prosumers with ensuring the Quality of Service (QoS) of the charged UAVs. Specifically, to deal with the considered problem, we decompose it into two stages: 1) the day-ahead energy requirement data prediction stage and 2) energy scheduling stage per prosumer. Thus, second, a joint method based on hierarchical federated learning (HFL) on long short-term memory (LSTM) architecture (HFL-LSTM) and stochastic game-based multi-agent double deep $Q$ -learning (MADDQN) with community agent-independent approach is proposed. In particular, the HFL-LSTM approach is leveraged to forecast each prosumer's energy requirement data without centralized collecting local prosumers' data such that to protect data privacy. Then, the stochastic game is adopted to analyze the formulated problem, aiming to find the Nash equilibrium (NE) strategy. Afterward, MADDQN with a community agent-independent method is utilized to achieve the best energy scheduling strategy per prosumer. Finally, the experimental results demonstrate the superiority of the proposed joint method that can achieve the lowest mean squared error with the value of 0.0152 and the highest energy satisfaction $(36388)$ achieved by the NE policy compared with the benchmarks.
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