IEEE Transactions on Mobile Computing最新文献

{"title":"Correction to “PrivGuardInfer: Channel-Level End-Edge Collaborative Inference Strategy Protecting Original Inputs and Sensitive Attributes”","authors":"Yunhao Yao;Zhiqiang Wang;Puhan Luo;Yihang Cheng;Jiahui Hou;Xiang-Yang Li","doi":"10.1109/TMC.2026.3659976","DOIUrl":"https://doi.org/10.1109/TMC.2026.3659976","url":null,"abstract":"In the above article [1], there are several errors. The corrections are listed below: •Equation [page 9, column left]:","PeriodicalId":50389,"journal":{"name":"IEEE Transactions on Mobile Computing","volume":"25 4","pages":"5952-5952"},"PeriodicalIF":9.2,"publicationDate":"2026-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11424258","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147440684","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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 Learning for Cold-Start-Aware Microservice Scheduling in Dynamic Edge Environments","authors":"Jingxi Lu;Wenhao Li;Jianxiong Guo;Xingjian Ding;Zhiqing Tang;Tian Wang;Weijia Jia","doi":"10.1109/TMC.2025.3641936","DOIUrl":"https://doi.org/10.1109/TMC.2025.3641936","url":null,"abstract":"With the rapid growth of IoT devices and their diverse workloads, container-based microservices deployed at edge nodes have emerged as a lightweight, scalable solution. However, existing microservice scheduling algorithms often assume static resource availability, which is unrealistic when multiple containers are assigned to an edge node. Besides, containers suffer from cold-start inefficiencies during early-stage training in currently popular reinforcement learning (RL) algorithms. In this paper, we propose a hybrid learning framework that combines offline imitation learning (IL) with online Soft Actor-Critic (SAC) optimization to enable cold-start-aware microservice scheduling with dynamic resource allocation. We first formulate a delay-and-energy-aware scheduling problem and construct a rule-based expert to generate demonstration data for behavior cloning. Then, a GRU-enhanced policy network is designed within the policy network to extract correlations among multiple decisions by separately encoding slow-evolving node states and fast-changing microservice features, and an action selection mechanism is provided to speed up convergence. Extensive experiments show that our method significantly accelerates convergence and achieves superior final performance. Compared with baselines, our algorithm improves the total objective by 50% and convergence speed by 70%, and demonstrates the highest stability and robustness across various edge configurations.","PeriodicalId":50389,"journal":{"name":"IEEE Transactions on Mobile Computing","volume":"25 5","pages":"7338-7353"},"PeriodicalIF":9.2,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147588221","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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":"CSI-BERT2: A BERT-Inspired Framework for Efficient CSI Prediction and Classification in Wireless Communication and Sensing","authors":"Zijian Zhao;Fanyi Meng;Zhonghao Lyu;Hang Li;Xiaoyang Li;Guangxu Zhu","doi":"10.1109/TMC.2025.3640420","DOIUrl":"https://doi.org/10.1109/TMC.2025.3640420","url":null,"abstract":"Channel state information (CSI) is a fundamental component in both wireless communication and sensing systems, enabling critical functions such as radio resource optimization and environmental perception. In wireless sensing, data scarcity and packet loss hinder efficient model training, while in wireless communication, high-dimensional CSI matrices and short coherent times caused by high mobility present challenges in CSI etimation. To address these issues, we propose a unified framework named CSIBERT2 for CSI prediction and classification tasks, built on our previous work CSIBERT. We introduce a two-stage training method that first uses a mask language model (MLM) to enable the model to learn general feature extraction from scarce datasets in an unsupervised manner, followed by fine-tuning for specific downstream tasks. Specifically, we extend MLM into a mask prediction model (MPM), which efficiently addresses the CSI prediction task. To further enhance the representation capacity of CSI data, we introduce an adaptive re-weighting layer (ARL) to enhance subcarrier representation and a MLP-based temporal embedding module to mitigate temporal information loss problem inherent in the original Transformer. Extensive experiments demonstrate that CSI-BERT2 achieves state-of-the-art performance across all tasks. Our results further show that CSI-BERT2 generalizes effectively across varying sampling rates and robustly handles discontinuous CSI sequences caused by packet loss—challenges that conventional methods fail to address.","PeriodicalId":50389,"journal":{"name":"IEEE Transactions on Mobile Computing","volume":"25 5","pages":"7241-7257"},"PeriodicalIF":9.2,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147588227","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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":"A Low Latency Data Transmission Scheme for Buffered IoT Devices in NB-IoT Networks","authors":"Maria V. Iloridou;Foteini-Niovi Pavlidou","doi":"10.1109/TMC.2025.3642233","DOIUrl":"https://doi.org/10.1109/TMC.2025.3642233","url":null,"abstract":"In narrowband Internet of Things (NB-IoT) networks, latency reduction is a significant issue especially regarding IoT applications with strict latency requirements. The signalling overhead constitutes the major factor of latency increase. 3GPP made several attempts to decrease the signalling overhead for massive machine type communications (mMTC) in NB-IoT networks. Among that attempts, early data transmission (EDT) is one of the latest efforts that reduces the signalling overhead by allowing data transmission without a connection establishment. Although EDT can support the transmission of multiple data packets besides one, it cannot deal with the randomness of data packet arrivals at buffered IoT devices. In this paper, a new data transmission scheme is proposed that reduces signalling overhead by employing piggybacking. Specifically, the proposed scheme concerns buffered IoT devices, which transmit the first data packet of the buffer by participating in the contention-based random access (RA) and the following data packets on the reserved data channels without taking part in RA again, according to the proposed scheme. The effectiveness of the proposed scheme is evaluated with simulation experiments versus the number of IoT devices and mean interarrival time of data packets at each IoT device. Simulation results show that the proposed scheme reduces dropped packets, service delay and enhances throughput.","PeriodicalId":50389,"journal":{"name":"IEEE Transactions on Mobile Computing","volume":"25 5","pages":"7408-7421"},"PeriodicalIF":9.2,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147588264","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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":"Approximation Algorithms for Scheduling Crowdsourcing Tasks in Mobile Social Networks","authors":"Chi-Yeh Chen","doi":"10.1109/TMC.2025.3641981","DOIUrl":"https://doi.org/10.1109/TMC.2025.3641981","url":null,"abstract":"This paper addresses the scheduling problem in mobile social networks, an <inline-formula><tex-math>$mathcal {NP}$</tex-math></inline-formula>-hard problem. First, we identified a gap in the approximation analysis of Zhang et al. (IEEE Transactions on Mobile Computing, 2025) and provided a revised bound. Furthermore, when the required service time for a task exceeds the total contact time between the requester and the crowd worker, we demonstrate that the approximation ratio of the Largest-Ratio-First task scheduling algorithm can reach <inline-formula><tex-math>$2 - frac{1}{m}$</tex-math></inline-formula>. Next, we introduce a randomized approximation algorithm to minimize mobile social networks’ total weighted completion time. This algorithm achieves an expected approximation ratio of <inline-formula><tex-math>$1.5 + epsilon$</tex-math></inline-formula> for <inline-formula><tex-math>$epsilon &gt; 0$</tex-math></inline-formula>. Finally, we present a deterministic approximation algorithm that minimizes mobile social networks’ total weighted completion time. This deterministic algorithm achieves an approximation ratio of <inline-formula><tex-math>$max lbrace 2.5,1+epsilon rbrace$</tex-math></inline-formula> for <inline-formula><tex-math>$epsilon &gt; 0$</tex-math></inline-formula>. Additionally, when the task’s required service time or the total contact time between the requester and the crowd worker is sufficiently large, this algorithm can reach an approximation ratio of <inline-formula><tex-math>$1.5+epsilon$</tex-math></inline-formula> for <inline-formula><tex-math>$epsilon &gt; 0$</tex-math></inline-formula>.","PeriodicalId":50389,"journal":{"name":"IEEE Transactions on Mobile Computing","volume":"25 5","pages":"7308-7322"},"PeriodicalIF":9.2,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147588255","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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":"Autonomous Task Offloading of Vehicular Edge Computing With Parallel Computation Queues","authors":"Sungho Cho;Sung Il Choi;Seung Hyun Oh;Ian P. Roberts;Sang Hyun Lee","doi":"10.1109/TMC.2025.3640244","DOIUrl":"https://doi.org/10.1109/TMC.2025.3640244","url":null,"abstract":"This work considers a parallel task execution strategy in vehicular edge computing (VEC) networks, where edge servers are deployed along the roadside to process offloaded computational tasks of vehicular users. To minimize the overall waiting delay among vehicular users, a novel task offloading solution is implemented based on the network cooperation balancing resource underutilization and load congestion. Dual evaluation through theoretical and numerical ways shows that the developed solution achieves a globally optimal delay reduction performance compared to existing methods, which is also validated by the feasibility test over a real-map virtual environment. The in-depth analysis reveals that predicting the instantaneous processing power of edge servers facilitates the identification of overloaded servers, which is critical for determining network delay. By considering discrete variables of the queue, the proposed technique’s precise estimation can effectively address these combinatorial challenges to achieve optimal performance.","PeriodicalId":50389,"journal":{"name":"IEEE Transactions on Mobile Computing","volume":"25 5","pages":"7166-7181"},"PeriodicalIF":9.2,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147588210","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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":"Widor: Resolving Practical Challenges in WiFi-Based Corridor Localization","authors":"Shuai Yang;Guanzhong Wang;Yan Chen","doi":"10.1109/TMC.2025.3650744","DOIUrl":"https://doi.org/10.1109/TMC.2025.3650744","url":null,"abstract":"WiFi-based indoor localization, a fundamental technology for numerous real-world applications, including indoor navigation and emergency evacuation, has garnered significant attention over the past decade. While existing works have already achieved remarkable performance under various practical scenarios, they simply take corridor as a test scenario, and attribute performance degradation to complex multipath. To further release the functionality of corridor as bridges connecting different physical spaces, in this paper, we propose Widor, the first <u>Wi</u>Fi indoor localization system that designed specifically for corri<u>dor</u>. We first explore the neglected elevation angle dimension information in WiFi positioning and creatively place AP vertically to avoid the large-angle effect, which is caused by the unique slender structure of the corridor. To eliminate the impact of complex multipath introduced by the narrow environment, we make full use of the Toeplitz structure of the covariance matrix to further improve the spatial resolution of existing commercial WiFi AP without increasing the additional hardware cost. Furthermore, we design a tailored multi-APs joint height compensation algorithm to bridge the gap between 2-D and 3-D localization, which iteratively optimize the height difference between the AP and the client through an alternating optimization method. Both the time dimensional information and map constraint can be used to further improve localization accuracy. We evaluate Widor under various complex corridors in an <inline-formula><tex-math>$ 82,text{m} times 65,text{m}$</tex-math></inline-formula> building, and extensive experimental results show that Widor can achieve <inline-formula><tex-math>$5.2^circ$</tex-math></inline-formula> median angle estimation error and 58 cm localization median error. We also highlight that the proposed Widor system has little impact on the communication performance of existing commercial APs, and can be easily extended to any slender building scenarios, such as mines and tunnels, further broadening the application boundaries of WiFi indoor localization.","PeriodicalId":50389,"journal":{"name":"IEEE Transactions on Mobile Computing","volume":"25 5","pages":"7422-7435"},"PeriodicalIF":9.2,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147588212","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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":"Correction to “Uplink Resource Allocation for RSMA-Aided Digital Twin-Assisted User-Centric Cell-Free Massive MIMO Systems”","authors":"Manobendu Sarker;Md. Zoheb Hassan;Georges Kaddoum;Abraham O. Fapojuwo","doi":"10.1109/TMC.2026.3667369","DOIUrl":"https://doi.org/10.1109/TMC.2026.3667369","url":null,"abstract":"Presents corrections to the paper, Correction to Uplink Resource Allocation for RSMA-Aided Digital Twin-Assisted User-Centric Cell-Free Massive MIMO Systems.","PeriodicalId":50389,"journal":{"name":"IEEE Transactions on Mobile Computing","volume":"25 5","pages":"7471-7471"},"PeriodicalIF":9.2,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11471303","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147588217","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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":"MOSAIC: Mobility-Oriented Scheduling and Intelligent Resource Allocation for IoT","authors":"Abolfazl Younesi;Mehrab Toghani;Sepideh Safari;Mohsen Ansari;Thomas Fahringer","doi":"10.1109/TMC.2025.3640765","DOIUrl":"https://doi.org/10.1109/TMC.2025.3640765","url":null,"abstract":"The relentless growth of mobile Internet of Things (IoT) devices has shifted computation toward a distributed computing continuum, spanning edge, fog, and cloud layers, where energy efficiency, low latency, and dynamic node mobility are critical yet often conflicting goals. Existing scheduling frameworks struggle to balance these demands under real-world conditions, especially as device movement and heterogeneous workloads increase system complexity. We present MOSAIC, a mobility-aware scheduling and resource management framework designed to optimize performance in dynamic IoT environments. Our approach introduces three key innovations. First, a refined five-tier architecture extends the traditional edge-fog-cloud hierarchy by adding proximity, local, and regional mobility layers, enabling computation to follow mobile users more effectively and reducing unnecessary network traffic. Second, MOSAIC integrates a preemption-aware dynamic scheduler with an Adaptive-<inline-formula><tex-math>$lambda$</tex-math></inline-formula> reinforcement learning-based resource manager that adapts based on workload changes and mobility patterns, prioritizing energy-efficient edge execution while meeting strict deadlines. Third, the framework utilizes real-world mobility traces, including Levy-Walk, Random-Walk, and Geolife, to drive reconfiguration and improve decision accuracy. We evaluate MOSAIC through a large-scale deployment across three geographically distributed regions of the Grid’5000 testbed, using realistic workflows and mixed periodic/DAG task loads. Our results show that, compared to state-of-the-art schedulers, MOSAIC reduces energy consumption by 35.9% –×1.5, lowers latency by 42.8% –×4.9, and shortens makespan by 22.6% –×7.2, all while maintaining 100% deadline satisfaction across diverse mobility scenarios.","PeriodicalId":50389,"journal":{"name":"IEEE Transactions on Mobile Computing","volume":"25 5","pages":"7291-7307"},"PeriodicalIF":9.2,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11278779","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147588266","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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":"Throughput-Optimized Service Routing for Microservice Flows in LEO Satellite Networks","authors":"Xindi He;Ting Wang;Yuanming Shi;Xin Liu","doi":"10.1109/TMC.2025.3640395","DOIUrl":"https://doi.org/10.1109/TMC.2025.3640395","url":null,"abstract":"Satellite-based microservice systems have emerged as a promising architecture for enabling scalable and flexible service deployment in Low Earth Orbit (LEO) satellite networks, which are increasingly recognized as a key solution to meet the rising demand for global communication and computation, especially in remote and underserved regions. However, routing microservices efficiently in such systems presents major challenges due to the dynamic topology, intermittent connectivity, and unstable link conditions inherent to satellite constellations. These issues become even more severe under high traffic loads. To address these challenges, we propose Service Pressure, a novel routing algorithm specifically designed for satellite-based microservice systems. Service Pressure comprises two key components: first, the construction of an augmented subgraph to model the complex execution and data transmission dependencies of microservices; second, a distributed service routing algorithm that utilizes queue backlogs. This combination enables the algorithm to effectively handle high throughput and adapt to the dynamic network conditions of satellite constellations. By optimizing resource utilization, minimizing latency, and balancing load across satellite nodes, Service Pressure ensures efficient and stable service orchestration even under fluctuating traffic conditions. Extensive simulations demonstrate that our approach significantly outperforms existing routing methods, particularly in terms of throughput, latency, and stability. Service Pressure offers a significant advancement in satellite microservice routing, making it ideal for next-generation space-ground integrated networks.","PeriodicalId":50389,"journal":{"name":"IEEE Transactions on Mobile Computing","volume":"25 5","pages":"7196-7209"},"PeriodicalIF":9.2,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147588229","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}