Ling Tan, Lei Sun, Boyuan Cao, Jingming Xia, Hai Xu
{"title":"Research on weighted energy consumption and delay optimization algorithm based on dual-queue model","authors":"Ling Tan, Lei Sun, Boyuan Cao, Jingming Xia, Hai Xu","doi":"10.1049/cmu2.12710","DOIUrl":"10.1049/cmu2.12710","url":null,"abstract":"<p>This article investigates a mobile edge computing (MEC) network assisted by multiple unmanned aerial vehicles (UAVs) to address the computational and offloading requirements for mobile intelligent terminals (MITs) within crowded venues. The objective is to tackle intricate task processing and diminish MITs' waiting times. Considering the randomness of task arrival at the MITs and the imbalance between the amount of data and computation for complex tasks, a dual-queue model with data cache queue and computation queue is proposed, with minimizing the weighted system total energy consumption and average delay as the optimization objectives. Lyapunov optimization theory is employed to convert the stochastic optimization problem into a deterministic one, and the initial deployment quantity and hovering position of the UAVs are determined by the density-based spatial clustering of applications with noise (DBSCAN) method with noise. Then PPO algorithm for MIT task, resource allocation, and UAV trajectory optimization. Numerical results display the proposed scheme can efficaciously diminish energy consumption and delay by 10% and 33% respectively, compared with the baseline scheme. This paper proposes a practical and feasible solution for stochastic computing offloading in UAV-assisted MEC, which fills the gap in existing research on regarding the consideration of complex task imbalances.</p>","PeriodicalId":55001,"journal":{"name":"IET Communications","volume":"18 1","pages":"81-95"},"PeriodicalIF":1.6,"publicationDate":"2023-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/cmu2.12710","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139159701","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}
Xin Ma, Kai Yang, Chuanzhen Zhang, Hualing Li, Xin Zheng
{"title":"Physical adversarial attack in artificial intelligence of things","authors":"Xin Ma, Kai Yang, Chuanzhen Zhang, Hualing Li, Xin Zheng","doi":"10.1049/cmu2.12714","DOIUrl":"10.1049/cmu2.12714","url":null,"abstract":"<p>With the continuous development of wireless communication and artificial intelligence technology, Internet of Things (IoT) technology has made great progress. Deep learning methods are currently used in IoT technology, but deep neural networks (DNNs) are notoriously susceptible to adversarial examples, and subtle pixel changes to images can result in incorrect recognition results from DNNs. In the real-world application, the patches generated by the recent physical attack methods are larger or less realistic and easily detectable. To address this problem, a Generative Adversarial Network based on Visual attention model and Style transfer network (GAN-VS) is proposed, which reduces the patch area and makes the patch more natural and less noticeable. A visual attention model combined with generative adversarial network is introduced to detect the critical regions of image recognition, and only generate patches within the critical regions to reduce patch area and improve attack efficiency. For any type of seed patch, an adversarial patch can be generated with a high degree of stylistic and content similarity to the attacked image by generative adversarial network and style transfer network. Experimental evaluation shows that the proposed GAN-VS has good camouflage and outperforms state-of-the-art adversarial patch attack methods.</p>","PeriodicalId":55001,"journal":{"name":"IET Communications","volume":"18 6","pages":"375-385"},"PeriodicalIF":1.6,"publicationDate":"2023-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/cmu2.12714","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139166048","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":"Hybrid traffic scheduling in time-sensitive networking for the support of automotive applications","authors":"Hongrui Nie, Yue Su, Weibo Zhao, Junsheng Mu","doi":"10.1049/cmu2.12713","DOIUrl":"10.1049/cmu2.12713","url":null,"abstract":"<p>Time-sensitive networking (TSN) is considered one of the most promising solutions to address real-time scheduling in in-vehicle network due to its capabilities for providing deterministic service. The TSN working group proposed various traffic shaping mechanisms, while deterministic scheduling of hybrid traffic is still not effectively solved since the traffic requirements are difficult to satisfy by standalone or combined mechanisms with fixed time slot divisions. This article presents a time-aware multi-cyclicqueuing and forwarding scheduling model, that integrates the no-wait enabled time-aware shaper and multi-cyclic queuing and forwarding shaping models. Then, a scheduling solution, dubbed “TSN scheduling optimizer” (TSO) is proposed that combines optimization methods and incremental techniques. TSO aims to balance the load to maximize flow schedulability while guaranteeing the service requirements of hybrid traffic. Simulation evaluations through OMNeT++ provide a performance assessment of this proposed scheduling model, which can satisfy multiple types of traffic transmission requirements. Furthermore, TSO is compared with other baseline scheduling solutions, and TSO shows efficacy regarding execution time and schedulability.</p>","PeriodicalId":55001,"journal":{"name":"IET Communications","volume":"18 2","pages":"111-128"},"PeriodicalIF":1.6,"publicationDate":"2023-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/cmu2.12713","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138950620","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":"Machine learning assisted adaptive LDPC coded system design and analysis","authors":"Cong Xie, Mohammed El-Hajjar, Soon Xin Ng","doi":"10.1049/cmu2.12707","DOIUrl":"10.1049/cmu2.12707","url":null,"abstract":"<p>This paper proposes a novel machine learning (ML) assisted low-latency low density parity check (LDPC) coded adaptive modulation (AM) system, where short block-length LDPC codes are used. Conventional adaptive modulation and coding (AMC) system includes fixed look-up table method, which is also called inner loop link adaptation (ILLA) and outer loop link adaptation (OLLA). For ILLA, the adaptive capability is achieved by switching the modulation and coding modes based on a look-up table using signal-to-noise ratio (SNR) thresholds at the target bit error rate (BER), while OLLA builds upon the ILLA method by dynamically adjusting the SNR thresholds to further optimize the system performance. Although both improve the system overall throughput by switching between different transmission modes, there is still a gap to optimal performance as the BER is comparatively far away from the target BER. Machine learning (ML) is a promising solution in solving various classification problems. In this work, the supervised learning based k-nearest neighbours (KNN) algorithm is invoked for choosing the optimum transmission mode based on the training data and the instantaneous SNR. This work focuses on the low-latency communications scenarios, where short block-length LDPC codes are utilized. On the other hand, given the short block-length constraint, we propose to artificially generate the training data to train our ML assisted AMC scheme. The simulation results show that the proposed ML-LDPC-AMC scheme can achieve a higher throughput than the ILLA system while maintaining the target BER. Compared with OLLA, the proposed scheme can maintain the target BER while the OLLA fails to maintain the target BER when the block length is short. In addition, when considering the channel estimation errors, the performance of the proposed ML-LDPC-AMC maintains the target BER, while the ILLA system's BER performance can be higher than the target BER.</p>","PeriodicalId":55001,"journal":{"name":"IET Communications","volume":"18 1","pages":"1-10"},"PeriodicalIF":1.6,"publicationDate":"2023-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/cmu2.12707","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138959001","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":"iScene: An interpretable framework with hierarchical edge services for scene risk identification in 6G internet of vehicles","authors":"Wuchang Zhong, Siming Wang, Rong Yu","doi":"10.1049/cmu2.12704","DOIUrl":"https://doi.org/10.1049/cmu2.12704","url":null,"abstract":"Scene risk identification is essential for the traffic safety of Internet of Vehicles. However, the performance of existing risk identification approaches is heavily limited by the imbalanced historical data and the poor model interpretability. Meanwhile, the large processing delay and the potential privacy leakage threat also restrict their application. In this paper, a novel risk identification model is proposed that leverages the synthetic minority over‐sampling technique nearest neighbor (SMOTEENN) method to balance between high‐risk and low‐risk data. The risk identification model has fine interpretability by using recursive feature elimination cross validation (RFECV) with the Shapley additive explanation (SHAP) to analyze the importance of different features, and further elaborately design the Focal Loss function to tackle the disparity between the difficult and easy sample learning. The proposed interpretability scene risk identification framework, named iScene, is built on the infrastructure of 6G space‐air‐ground integrated networks (SAGINs) with blockchain assistance. The model updata efficiency and privacy preservation are effectively enhanced. An elastic computing offloading algorithm is applied to minimize the system overhead under the hierarchical edge service architecture. The experimental evaluation is carried out to verify the effectiveness of the proposed risk identification framework. The results indicate that the G‐Mean value is increased by 23.4%, while the task average response delay is reduced by 21.2%, compared to that in the traditional risk identification approaches with local computing services.","PeriodicalId":55001,"journal":{"name":"IET Communications","volume":" 48","pages":""},"PeriodicalIF":1.6,"publicationDate":"2023-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138961719","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Task offloading and resource allocation for blockchain‐enabled mobile edge computing","authors":"Renbin Fang, Peng Lin, Yize Liu, Yan Liu","doi":"10.1049/cmu2.12703","DOIUrl":"https://doi.org/10.1049/cmu2.12703","url":null,"abstract":"Mobile edge computing (MEC) has risen as an effective approach to support ubiquitous and prosperous mobile applications. Due to the strict delay requirements and the increasingly complex application environments, the computation efficiency and security have become the bottleneck that restricts the MEC system. Here, a blockchain‐enabled task offloading scheme is proposed, where the sensitive computation tasks of user terminals (UTs) can be offloaded to a blockchain‐assisted base station (BS). The MEC‐assisted BS helps UTs compute tasks while the blockchain consensus protocol ensures the security of the task offloading and computing process. To manage the allocation of computing resources between task offloading and blockchain consensus, the task offloading and resource allocation are formulated as a joint optimization problem. The aim of the problem is to minimize the energy consumption of UTs while guaranteeing the delay requirement. By transforming the original problem into a Markov decision process, a collective reinforcement learning algorithm is proposed to solve the problem in an online fashion. In the simulations, the convergence and the performance of the proposed scheme are evaluated. The simulation results show the effectiveness of the scheme.","PeriodicalId":55001,"journal":{"name":"IET Communications","volume":" 22","pages":""},"PeriodicalIF":1.6,"publicationDate":"2023-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138962603","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Mohammed S. Elbasheir, Rashid A. Saeed, Salaheldin Edam
{"title":"Electromagnetic field exposure boundary analysis at the near field for multi-technology cellular base station site","authors":"Mohammed S. Elbasheir, Rashid A. Saeed, Salaheldin Edam","doi":"10.1049/cmu2.12711","DOIUrl":"10.1049/cmu2.12711","url":null,"abstract":"<p>Mobile networks are expanding quickly as a result of significant advancements in wireless technologies and solutions, especially with the recent introduction of the Fifth Generation New Radio. The growth in mobile networks requires the installation of massive numbers of base stations that bring concerns about increasing overall electromagnetic field (EMF) radiation exposure levels. The International Commission on Non-Ionizing Radiation Protection (ICNIRP) has published guidelines that have been adopted by many regulators in many countries to control the overall radiation emitted from EMF transmitters. This paper studies the compliance boundary for a single site operating with multiple technologies including from the second generation (2G) to 5G colocated in the same site. The analysis is performed using a typical site configuration setup for the boundary calculations in the form of the Compliance Distance (CD). The calculation uses the power reduction factor and system load for more realistic results, and in situ measurements are conducted to validate the calculation's formula. The study also investigated the CD for four types of sites, macro, micro, small cell, and indoor sites. Additionally, the study analyzed the power densities (PDs) and total exposure ratio (TER) for the general public and occupational workers at each site. The results show that CD has shorter distances when the power factor is considered, and 5G makes the highest contribution to the TER at the CD in the main directions of the antenna.</p>","PeriodicalId":55001,"journal":{"name":"IET Communications","volume":"18 1","pages":"11-27"},"PeriodicalIF":1.6,"publicationDate":"2023-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/cmu2.12711","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138965015","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":"CSVRF: A CAM-based popularity-aware egress group-caching scheme for SVRF-based packet forward engines","authors":"Ruisi Wu, Wen-Kang Jia","doi":"10.1049/cmu2.12701","DOIUrl":"10.1049/cmu2.12701","url":null,"abstract":"<p>As a key component of high-performance switches and routers, the packet forwarding engine (PFE) is mainly responsible for selecting the appropriate output port for tens of thousands of packets within an extremely short time frame. However, the performance of PFE is determined by the selected group membership algorithm. This paper puts forth a hybrid strategy–caching scalar-pair and vectors routing and forwarding (CSVRF), consisting of virtual output port bitmap caching (VOPBC) and fractional-<i>N</i> SVRF to address major multicast forwarding issues such as scalability by using content addressable memory. In CSVRF, a virtual output port bitmap cache is introduced, which includes the most popular combinations of output port bitmap and divides the big scalar-pair into <i>N</i> sub-groups to achieve parallel compute and the reusability of less bit-length prime. The results demonstrate that the memory space and the forwarding latency are effectively reduced compared with previous work. In space efficiency, it only required 10% memory space compared with the original SVRF/fractional-<i>N</i> SVRF, decreased 10% memory usage compared with pure VOPBC and nearly improved 1 to 4 orders of magnitude of packet processing time compared with the original SVRF and the fractional-<i>N</i> SVRF respectively.</p>","PeriodicalId":55001,"journal":{"name":"IET Communications","volume":"18 1","pages":"40-54"},"PeriodicalIF":1.6,"publicationDate":"2023-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/cmu2.12701","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138966292","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":"Monte Carlo-based service migration under multiple constraints in mobile edge computing","authors":"Qiang Zhang, Hao Yu","doi":"10.1049/cmu2.12705","DOIUrl":"10.1049/cmu2.12705","url":null,"abstract":"<p>Mobile edge computing as an emerging technique can provide services for mobile terminals, and meanwhile the mobility of users brings new challenges. When a user moves across different areas, the system needs to determine whether to migrate service so as to guarantee quality of experience for the user. However, it is difficult to obtain the optimal migration policy in real time due to the huge state space. Considering delay-sensitive data-intensive applications run by mobile terminals with limited battery power, an efficient service migration policy should be able to make a good tradeoff among service cost, service delay and terminal energy consumption. Here, an online Monte Carlo-based service migration (MCSM) policy is proposed to minimize service cost under constraints of deadline and terminal energy consumption. A penalty mechanism is designed to update reward when partial or all constraints are not meet. State-action value estimation and policy improvement are triggered only on the completion of each episode. Each episode is traversed reversely to calculate the average cumulative reward so as to improve policy. Experimental results show that the proposed approach can improve service success ratio and reduce average service cost compared to the existing service migration policies.</p>","PeriodicalId":55001,"journal":{"name":"IET Communications","volume":"18 1","pages":"28-39"},"PeriodicalIF":1.6,"publicationDate":"2023-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/cmu2.12705","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138966577","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":"Wireless sensor network security defense strategy based on Bayesian reputation evaluation model","authors":"Zhijun Teng, Sian Zhu, Mingzhe Li, Libo Yu, Jinliang Gu, Liwen Guo","doi":"10.1049/cmu2.12700","DOIUrl":"10.1049/cmu2.12700","url":null,"abstract":"<p>In order to solve the security problems caused by malicious nodes in wireless sensor networks, a TS-BRS reputation model based on time series analysis is proposed in this paper. By using the time series analysis method, the matching analysis of two time series is carried out to reduce the interference of channel conflicts on the reputation evaluation model and improve the accuracy of model recognition. In order to improve the adaptability of the evaluation model, the adaptive maintenance function μ is introduced into the update of credit value, which aggravates the influence of node behaviour on credit value at the present stage. The simulation results show that the new reputation evaluation model can effectively improve the detection rate and detection speed of malicious nodes in the network. After the introduction of maintenance function, the reputation value of the captured malicious nodes in the network has a faster convergence speed.</p>","PeriodicalId":55001,"journal":{"name":"IET Communications","volume":"18 1","pages":"55-62"},"PeriodicalIF":1.6,"publicationDate":"2023-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/cmu2.12700","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138972836","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}