IET Communications最新文献

{"title":"Lightweight Authentication Scheme for Resource-Constrained Devices in IIoT","authors":"Zhong Cao,&nbsp;Xudong Wen,&nbsp;Shan Ai,&nbsp;Haitao Cao,&nbsp;Wenli Shang","doi":"10.1049/cmu2.70039","DOIUrl":"10.1049/cmu2.70039","url":null,"abstract":"<p>The industrial Internet of Things (IIoT) involves interconnected devices and sensors that exchange data in resource-constrained industrial environments. As the number of IIoT devices grows, ensuring secure communication becomes increasingly important. This paper proposes a lightweight authentication scheme leveraging elliptic curve cryptography (ECC) and other lightweight cryptographic techniques to facilitate secure communication among IIoT devices while minimizing computational, communication, and storage overheads. We conduct thorough security evaluations using a stochastic Oracle model and the automated validation of Internet security protocols and applications (AVISPA) tool, as well as informal security analyses based on the Dolev–Yao channel model to validate the correctness of our approach. Simulation results demonstrate that the proposed scheme offers superior security and computational efficiency compared to existing authentication methods in similar contexts.</p>","PeriodicalId":55001,"journal":{"name":"IET Communications","volume":"19 1","pages":""},"PeriodicalIF":1.6,"publicationDate":"2025-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/cmu2.70039","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143846014","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimization mechanism of energy efficiency in coexisting wireless body area networks","authors":"Yuting Qian,&nbsp;Kunqi Guo","doi":"10.1049/cmu2.12712","DOIUrl":"10.1049/cmu2.12712","url":null,"abstract":"<p>This paper studies the optimization of energy efficiency in coexisting wireless body area networks (WBANs). A solution based on combining a naive Bayesian classifier with the Hungarian algorithm is proposed to improve link transmission energy efficiency. The solution is implemented in the following three steps: Firstly, the interference from surrounding WBANs is identified based on a naive Bayesian classifier considering the distance among WBANs, the residual energy of the sensor nodes, and the transmission power of the sensor nodes. Secondly, the signal-to-interference plus noise ratio is determined according to the results of the naive Bayesian classifier. Thirdly, the time slots are allocated adaptively by using the Hungarian algorithm to maximize the overall energy efficiency. The simulation results show that the scheme can improve the overall energy efficiency of the WBAN significantly while ensuring quality of service. In comparison with the iterative algorithm and the PONF algorithm, the proposed scheme has obvious advantages in improving energy efficiency.</p>","PeriodicalId":55001,"journal":{"name":"IET Communications","volume":"19 1","pages":""},"PeriodicalIF":1.6,"publicationDate":"2025-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/cmu2.12712","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143846016","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Efficient Positioning Method for Underground Pipe Gallery Inspection Based on UWB Adaptive Fusion","authors":"Haoyue Lin,&nbsp;Zehua Yin,&nbsp;Chunwu Wang,&nbsp;Yifan Lin,&nbsp;Muhammad Suhail Shaikh,&nbsp;Chang Wang,&nbsp;Xiaoqing Dong","doi":"10.1049/cmu2.70037","DOIUrl":"10.1049/cmu2.70037","url":null,"abstract":"<p>To address the challenges of slow positioning speed and inaccurate localisation of underground pipeline corridors in complex environments using ultra-wideband (UWB) absolute positioning, this paper proposes a Hybrid UWB-IMU Adaptive Localisation Algorithm (HUIALA) for precise underground pipeline corridor positioning. The positioning method uses UWB as absolute positioning, IMU and odometer trajectory calculation as relative positioning (predictive positioning), and updates the observation noise by calculating the fuzzy distance to the triangle centroid to adaptively allocate weights. At the same time, dynamically adjust the intervention and exit of predicted positioning based on system operation, and filter out interference such as UWB positioning drift and absolute positioning failure. The proposed method is based on the simulation and experiment of a wheeled inspection vehicle system using UWB and inertial navigation. The experimental result shows that the proposed method maintains better response speed and high positioning accuracy during dynamic testing in simulated interference environments. The positioning speed is improved by 98.9% compared to single UWB positioning, and the positioning accuracy is improved by about 45.84% and 27.96% compared to single UWB positioning and KF fusion positioning, respectively.</p>","PeriodicalId":55001,"journal":{"name":"IET Communications","volume":"19 1","pages":""},"PeriodicalIF":1.6,"publicationDate":"2025-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/cmu2.70037","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143826766","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Pseudo-Label Selection-Based Federated Semi-Supervised Learning Framework for Vehicular Networks","authors":"Jiachen Liu,&nbsp;Haoren Ke,&nbsp;Jianfeng Yang,&nbsp;Tianqi Yu","doi":"10.1049/cmu2.70035","DOIUrl":"10.1049/cmu2.70035","url":null,"abstract":"<p>In vehicular networks, federated learning (FL) has been used for secure and distributed edge intelligence to support deep neural network (DNN) model training. In the FL, the roadside units (RSUs) and vehicles act as the parameter servers and clients, respectively. However, the raw data collected by the vehicles are normally unlabeled, which can hardly meet the requirements of the supervised learning tasks. To resolve the related issues, a federated semi-supervised learning (FSSL) framework is proposed in this paper. By leveraging semi-supervised learning (SSL), the framework can implement the model training with unlabeled data in vehicles and a small set of manually annotated data in the RSU. Furthermore, a pseudo-label selection method is developed for the vehicles to improve the local pseudo-label prediction accuracy and the convergence of global model training. Simulation experiments have been conducted to evaluate the performance of the proposed FSSL framework. The experimental results show that the proposed framework can effectively utilize unlabeled data in vehicular networks and complete the task of DNN model training.</p>","PeriodicalId":55001,"journal":{"name":"IET Communications","volume":"19 1","pages":""},"PeriodicalIF":1.6,"publicationDate":"2025-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/cmu2.70035","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143818411","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"HybridDep: An elastic hybrid resources allocation strategy for I/O-intensive applications","authors":"Pengmiao Li,&nbsp;Yuchao Zhang,&nbsp;Shaoxuan Yun,&nbsp;Fucai Yu,&nbsp;Aizhi Wu","doi":"10.1049/cmu2.70007","DOIUrl":"10.1049/cmu2.70007","url":null,"abstract":"<p>Along with the rapid development of B5G/6G, the number of applications grows rapidly and the data amount explodes exponentially, putting a massive burden on the resource-limited edge servers. To fully utilize the limited resources, virtualization technology is introduced to provide elastic deployment for applications in edge servers. But for I/O-intensive applications, allocating elastic resources is not as easy as for compute-intensive ones, because the amount of required I/O resources is unknown due to the request uncertainty. Many existing researches try to solve this multi-application deployment problem by peaks clipping and valleys filling, to resource utilization. However, in fact, the times of peaks and valleys of most hybrid deployed applications are similar to each other, which invalidates those traditional solutions. To address this challenge, the actual data is analysed and complementary peak and valley periods in time and space dimensions are found. Based on this finding, an elastic hybrid deployment strategy <i>HybridDep</i> is proposed, for multiple I/O-intensive applications. Validated by simulation experiments using real datasets and traces, this algorithm can reduce about 3.2% deployment cost than the compared algorithm.</p>","PeriodicalId":55001,"journal":{"name":"IET Communications","volume":"19 1","pages":""},"PeriodicalIF":1.6,"publicationDate":"2025-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/cmu2.70007","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143801555","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Dynamic Context-Weighted Embeddings: A Novel Approach to Predictive Modelling","authors":"Zhai Yue,&nbsp;Mohd Ridwan Abd Razak,&nbsp;Lufeng Li","doi":"10.1049/cmu2.70036","DOIUrl":"10.1049/cmu2.70036","url":null,"abstract":"<p>Employee satisfaction prediction models often struggle to capture the complex, non-linear relationships between compensation and job satisfaction, particularly in heterogeneous organisational contexts. This paper introduces a novel deep learning framework incorporating multiple technical innovations to address these challenges. The proposed approach employs a dual-pathway neural architecture with compensation-specific processing modules to explicitly model the non-linear interactions between compensation factors and other job attributes across diverse organisational settings. A differentiated embedding strategy transforms raw features into rich, context-aware representations, enabling the capture of subtle patterns in employee satisfaction dynamics. The framework integrates a context-sensitive attention mechanism that automatically identifies and weighs relevant features based on organisational characteristics and temporal patterns, alongside a specialised loss function that adaptively emphasises difficult-to-predict cases, improving performance on complex satisfaction patterns. This model demonstrates robust performance across diverse industry settings, handling missing data and class imbalance effectively. Extensive comparative experiments against state-of-the-art methods (LSTM-Attention, GNN-based approaches and traditional ML models) across multiple datasets show significant improvements, with prediction accuracy increasing by 5.2%–8.5%, mean squared error decreasing by 10.3%–15.2% and AUC-ROC metrics improving by 7.8%. Further analysis reveals superior performance in handling temporal dependencies and organisational context variations, with particular strength in predicting satisfaction levels during significant organisational changes.</p>","PeriodicalId":55001,"journal":{"name":"IET Communications","volume":"19 1","pages":""},"PeriodicalIF":1.6,"publicationDate":"2025-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/cmu2.70036","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143801409","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Joint Active User Detection, Timing Offset and Channel Estimation for FBMC-Based Uplink Massive Access Systems","authors":"Yuhao Qi,&nbsp;Jian Dang,&nbsp;Zaichen Zhang,&nbsp;Liang Wu,&nbsp;Bingcheng Zhu","doi":"10.1049/cmu2.70034","DOIUrl":"10.1049/cmu2.70034","url":null,"abstract":"<p>The robustness against timing offsets of filter bank multi-carrier (FBMC) is appealing for grant-free massive access scenarios that mainly adopt asynchronous transmissions. In this work, we propose a compressed sensing based algorithm for joint active user detection as well as timing offset and channel estimation in uplink communication under the combination of FBMC and grant-free massive access systems, which is critical for subsequent decoding or other processes at receiver. The channel estimation part is based on generalized approximate massage passing (GAMP). The active user detection and timing offset estimation are based on loopy belief propagation (LBP) rules, where the expressions of message passing and belief distributions are derived. Besides, since the receiver may have no prior knowledge about some parameters such as noise variance and activity probability, we introduce the expectation maximization (EM) approach into the proposed algorithm. Moreover, we develop a preamble design method to improve the detection and estimation performance. Simulation results show that the proposed EM-LBP-GAMP algorithm can achieve satisfying performance in terms of missed activity detection probability, timing offset estimation error and normalized mean square error of channel estimation.</p>","PeriodicalId":55001,"journal":{"name":"IET Communications","volume":"19 1","pages":""},"PeriodicalIF":1.6,"publicationDate":"2025-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/cmu2.70034","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143801293","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An Efficient Deadline Based Priority Job Scheduling in Mobile Cloud Computing","authors":"Muhammad Makama Mahmudur Rahman Ohee,&nbsp;Fernaz Narin Nur,&nbsp;Asif Karim,&nbsp;Shaheena Sultana,&nbsp;Sami Azam,&nbsp;Nazmun Nessa Moon","doi":"10.1049/cmu2.70031","DOIUrl":"10.1049/cmu2.70031","url":null,"abstract":"<p>Mobile cloud computing (MCC) combines the portability of mobile devices with cloud data centers to provide advanced services. MCC serves us in various ways in our daily lives, including multimedia streaming, mobile gaming, mobile corporate apps, and data-intensive mobile applications such as augmented reality and virtual reality. Among the several challenges involved in achieving the best performance for this service, job scheduling emerges as a particularly critical one. User satisfaction, cloud service provider requirements, user priority, cloud provider's resource limitation, user deadline, cloud provider's energy consumption, etc., are the main constraints while maintaining job scheduling in mobile cloud computing. To improve the quality of service (QoS) and achieve the effectiveness of job scheduling, we have proposed a multi-objective model to balance the situation between user gratification and the cloud service provider's demand. To optimize the cost efficiency of the virtual machine, two types of jobs represent unconstrained and constrained jobs in the cloud data center. The shortest execution first scheduling (SEFS) algorithm is applied for the unconstrained job, and efficient deadline and priority job scheduling (EDPS) algorithm is applied for the constrained job. Our proposed algorithm improves the performance of the existing state-of-the-art algorithms. Reducing the execution time of jobs and minimizing the resource consumption of cloud providers are the improvements of our proposed algorithm.</p>","PeriodicalId":55001,"journal":{"name":"IET Communications","volume":"19 1","pages":""},"PeriodicalIF":1.6,"publicationDate":"2025-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/cmu2.70031","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143793326","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Parallel Double-Loop Particle Swarm Optimisation for Offloading Strategy in Blockchain Based Cloud-Edge-End Collaborative Computation","authors":"Junjie Cao,&nbsp;Zhiyong Yu,&nbsp;Jian Yang,&nbsp;Jinjin Chai,&nbsp;Zheng Liang,&nbsp;Yuanfeng Yang","doi":"10.1049/cmu2.70033","DOIUrl":"10.1049/cmu2.70033","url":null,"abstract":"<p>Computing offloading strategies have emerged as a pivotal topic in IoT research, serving as a strategic approach to minimising latency and energy consumption in edge computing. Nevertheless, these advancements have also introduced new challenges, especially in the context of computationally intensive tasks and increasing data privacy requirements in IoT applications. Addressing these challenges requires innovative solutions, with blockchain technology emerging as a highly promising tool. Our work explores the integration of blockchain into IoT edge computing, specifically focusing on computing offloading. We have devised a system architecture that seamlessly integrates edge computing with blockchain technologies, aiming to tackle both optimisation and security concerns. By framing the offloading problem as a multi-objective optimisation issue, we developed a Parallel Double-Loop Particle Swarm Optimisation algorithm. This algorithm introduces a dual-loop subpopulation structure based on broadcast feedback, which enhances information exchange between subpopulations and increases population diversity, thereby mitigating the risk of premature convergence to local optima. Moreover, an innovative collaborative mechanism is introduced, allowing multiple generations of updated particles to iterate simultaneously, significantly boosting the search efficiency of the population. Simulation results demonstrate that the PDPSO algorithm not only achieves significantly faster update speeds but also excels at identifying optimal solutions for the objective function. When compared to other existing algorithms, it offers superior overall performance and holds significant potential for addressing multidimensional constraints such as system delay and local energy consumption. Our findings suggest that this approach could be transformative for future IoT edge computing systems, providing a robust framework for efficient and secure task offloading.</p>","PeriodicalId":55001,"journal":{"name":"IET Communications","volume":"19 1","pages":""},"PeriodicalIF":1.6,"publicationDate":"2025-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/cmu2.70033","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143793643","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Separating Noisy TCP/IP Session Flows Based on Natural Redundancy Decoding","authors":"Guoxian Yu,&nbsp;Xiaomin Ran,&nbsp;Hongyi Yu,&nbsp;Zhixiang Shen","doi":"10.1049/cmu2.70027","DOIUrl":"10.1049/cmu2.70027","url":null,"abstract":"<p>Aiming at the technical challenges of low latency and high reliability in the complex communication environment of the intelligent industrial network, and the trend of the current Internet of Things architecture is increasingly IP-based, this paper proposes a fast and accurate IP packet forwarding method applied to the routing node, aiming at dealing with the header control packet error problem under high bit error conditions. This method breaks through the limitations of traditional retransmission mechanism and artificially adding redundant information, and only uses the natural redundant characteristics of the protocol itself to realize the correct separation of the session flow in high error environment. The test results on the public data set show that the proposed method can complete the separation of the session stream with a probability of not less than 99% at the bit error rate of <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <mi>1</mi>\u0000 <msup>\u0000 <mi>0</mi>\u0000 <mtext>-1</mtext>\u0000 </msup>\u0000 </mrow>\u0000 <annotation>$text{1}{{text{0}}^{text{-1}}}$</annotation>\u0000 </semantics></math> by sacrificing part of the complexity, which provides a new idea and technical means for the fault-tolerant receiving processing of the header five-tuple field in complex communication environments.</p>","PeriodicalId":55001,"journal":{"name":"IET Communications","volume":"19 1","pages":""},"PeriodicalIF":1.6,"publicationDate":"2025-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/cmu2.70027","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143770407","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}