IEEE Transactions on Mobile Computing最新文献_第10页

EdgeShield: Enabling Collaborative DDoS Mitigation at the Edge EdgeShield：在边缘实现协作式 DDoS 缓解

IF 7.7 2区计算机科学

IEEE Transactions on Mobile Computing Pub Date : 2024-08-14 DOI: 10.1109/TMC.2024.3443260

Xiaoyu Xia;Feifei Chen;Qiang He;Ruikun Luo;Bowen Liu;Caslon Chua;Rajkumar Buyya;Yun Yang

{"title":"EdgeShield: Enabling Collaborative DDoS Mitigation at the Edge","authors":"Xiaoyu Xia;Feifei Chen;Qiang He;Ruikun Luo;Bowen Liu;Caslon Chua;Rajkumar Buyya;Yun Yang","doi":"10.1109/TMC.2024.3443260","DOIUrl":"https://doi.org/10.1109/TMC.2024.3443260","url":null,"abstract":"Edge computing (EC) enables low-latency services by pushing computing resources to the network edge. Due to the geographic distribution and limited capacities of edge servers, EC systems face the challenge of edge distributed denial-of-service (DDoS) attacks. Existing systems designed to fight cloud DDoS attacks cannot mitigate edge DDoS attacks effectively due to new attack characteristics. In addition, those systems are typically activated upon detected attacks, which is not always realistic in EC systems. DDoS mitigation needs to be cohesively integrated with workload migration at the edge to ensure timely responses to edge DDoS attacks. In this paper, we present EdgeShield, a novel DDoS mitigation system that leverages edge servers’ computing resources collectively to defend against edge DDoS attacks without the need for attack detection. Aiming to maximize system throughput over time without causing significant service delays, EdgeShield monitors service delays and migrates workloads across an EC system with adaptive mitigation strategies. The experimental results show that EdgeShield significantly outperforms state-of-the-art solutions in both system throughput and service delays.","PeriodicalId":50389,"journal":{"name":"IEEE Transactions on Mobile Computing","volume":"23 12","pages":"14502-14513"},"PeriodicalIF":7.7,"publicationDate":"2024-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142598609","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}

引用次数: 0

Task Offloading and Trajectory Optimization for Secure Communications in Dynamic User Multi-UAV MEC Systems 动态用户多无人机 MEC 系统中安全通信的任务卸载和轨迹优化

IF 7.7 2区计算机科学

IEEE Transactions on Mobile Computing Pub Date : 2024-08-14 DOI: 10.1109/TMC.2024.3442909

Yuhao Zhang;Zhufang Kuang;Yanyan Feng;Fen Hou

{"title":"Task Offloading and Trajectory Optimization for Secure Communications in Dynamic User Multi-UAV MEC Systems","authors":"Yuhao Zhang;Zhufang Kuang;Yanyan Feng;Fen Hou","doi":"10.1109/TMC.2024.3442909","DOIUrl":"https://doi.org/10.1109/TMC.2024.3442909","url":null,"abstract":"With the advantages of high mobility and flexible deployment, Unmanned Aerial Vehicle (UAV) combines with Mobile Edge Computing (MEC) is a promising technology. When dynamic Terminal Users (TUs) offload tasks to UAVs, eavesdroppers may eavesdrop on the channel information. The offloading decisions, trajectory plannings of UAVs and resource allocation with the objective of high-capacity secure communication is a challenging problem. In this paper, we design a multi-UAVs MEC system, where the original region is divided into several sub-regions and TUs offload tasks to UAVs which provide computing services for these TUs. Meanwhile, A joint optimization problem of offloading decision, resource allocation and trajectory planning is formulated, where TUs move with the Gauss-Markov random model. In addition, the Base Station (BS) emits jamming signals to evade the eavesdropping of offloading information from eavesdroppers. The goal of the optimization problem is to maximize the TUs’ minimum secure calculation capacity, and a Joint Dynamic Programming and Bidding (JDPB) algorithm is proposed to solve it. The Successive Convex Approximation (SCA) and Block Coordinate Descent (BCD) algorithms are used to handle the resource allocation and trajectory planning problems, and the bidding method is used to address the task offloading decision problem. Simulation results show that JDPB has better performance and better robustness under different parameter settings than other schemes.","PeriodicalId":50389,"journal":{"name":"IEEE Transactions on Mobile Computing","volume":"23 12","pages":"14427-14440"},"PeriodicalIF":7.7,"publicationDate":"2024-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142598671","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}

引用次数: 0

Patching in Order: Efficient On-Device Model Fine-Tuning for Multi-DNN Vision Applications 有序修补：针对多 DNN 视觉应用的高效设备上模型微调

IF 7.7 2区计算机科学

IEEE Transactions on Mobile Computing Pub Date : 2024-08-14 DOI: 10.1109/TMC.2024.3443057

Zhiqiang Cao;Yun Cheng;Zimu Zhou;Anqi Lu;Youbing Hu;Jie Liu;Min Zhang;Zhijun Li

{"title":"Patching in Order: Efficient On-Device Model Fine-Tuning for Multi-DNN Vision Applications","authors":"Zhiqiang Cao;Yun Cheng;Zimu Zhou;Anqi Lu;Youbing Hu;Jie Liu;Min Zhang;Zhijun Li","doi":"10.1109/TMC.2024.3443057","DOIUrl":"https://doi.org/10.1109/TMC.2024.3443057","url":null,"abstract":"The increasing deployment of multiple deep neural networks (DNNs) on edge devices is revolutionizing mobile vision applications, spanning autonomous vehicles, augmented reality, and video surveillance. These applications demand adaptation to contextual and environmental drifts, typically through fine-tuning on edge devices without cloud access, due to increasing data privacy concerns and the urgency for timely responses. However, fine-tuning multiple DNNs on edge devices faces significant challenges due to the substantial computational workload. In this paper, we present PatchLine, a novel framework tailored for efficient on-device training in the form of fine-tuning for multi-DNN vision applications. At the core of PatchLine is an innovative lightweight adapter design called patches coupled with a strategic patch updating approach across models. Specifically, PatchLine adopts drift-adaptive incremental patching, correlation-aware warm patching, and entropy-based sample selection, to holistically reduce the number of trainable parameters, training epochs, and training samples. Experiments on four datasets, three vision tasks, four backbones, and two platforms demonstrate that PatchLine reduces the total computational cost by an average of 55% without sacrificing accuracy compared to the state-of-the-art.","PeriodicalId":50389,"journal":{"name":"IEEE Transactions on Mobile Computing","volume":"23 12","pages":"14484-14501"},"PeriodicalIF":7.7,"publicationDate":"2024-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142598669","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}

引用次数: 0

A Two-Stage Deep Reinforcement Learning Framework for MEC-Enabled Adaptive 360-Degree Video Streaming 用于 MEC 自适应 360 度视频流的两阶段深度强化学习框架

IF 7.7 2区计算机科学

IEEE Transactions on Mobile Computing Pub Date : 2024-08-13 DOI: 10.1109/TMC.2024.3443200

Suzhi Bi;Haoguo Chen;Xian Li;Shuoyao Wang;Yuan Wu;Liping Qian

{"title":"A Two-Stage Deep Reinforcement Learning Framework for MEC-Enabled Adaptive 360-Degree Video Streaming","authors":"Suzhi Bi;Haoguo Chen;Xian Li;Shuoyao Wang;Yuan Wu;Liping Qian","doi":"10.1109/TMC.2024.3443200","DOIUrl":"https://doi.org/10.1109/TMC.2024.3443200","url":null,"abstract":"The emerging multi-access edge computing (MEC) technology effectively enhances the wireless streaming performance of 360-degree videos. By connecting a user's head-mounted device (HMD) to a smart MEC platform, the edge server (ES) can efficiently perform adaptive tile-based video streaming to improve the user's viewing experience. Under constrained wireless channel capacity, the ES can predict the user's field of view (FoV) and transmit to the HMD high-resolution video tiles only within the predicted FoV. In practice, the video streaming performance is challenged by the random FoV prediction error and wireless channel fading effects. For this, we propose in this paper a novel two-stage adaptive 360-degree video streaming scheme that maximizes the user's quality of experience (QoE) to attain stable and high-resolution video playback. Specifically, we divide the video file into groups of pictures (GOPs) of fixed playback interval, where each GOP consists of a number of video frames. At the beginning of each GOP (i.e., the inter-GOP stage), the ES predicts the FoV of the next GOP and allocates an encoding bitrate for transmitting (precaching) the video tiles within the predicted FoV. Then, during the real-time video playback of the current GOP (i.e., the intra-GOP stage), the ES observes the user's true FoV of each frame and transmits the missing tiles to compensate for the FoV prediction errors. To maximize the user's QoE under random variations of FoV and wireless channel, we propose a double-agent deep reinforcement learning framework, where the two agents operate in different time scales to decide the bitrates of inter- and intra-GOP stages, respectively. Experiments based on real-world measurements show that the proposed scheme can effectively mitigate FoV prediction errors and maintain stable QoE performance under different scenarios, achieving over 22.1% higher QoE than some representative benchmark methods.","PeriodicalId":50389,"journal":{"name":"IEEE Transactions on Mobile Computing","volume":"23 12","pages":"14313-14329"},"PeriodicalIF":7.7,"publicationDate":"2024-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142598657","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}

引用次数: 0

A Secure Transmission Strategy for Smart Grid Communication Infrastructure-Assisted Two Tier Network 智能电网通信基础设施辅助双层网络的安全传输策略

IF 7.7 2区计算机科学

IEEE Transactions on Mobile Computing Pub Date : 2024-08-13 DOI: 10.1109/TMC.2024.3443056

Pei Liu;Kai Ma;Jie Yang;Bo Yang;Zhixin Liu

{"title":"A Secure Transmission Strategy for Smart Grid Communication Infrastructure-Assisted Two Tier Network","authors":"Pei Liu;Kai Ma;Jie Yang;Bo Yang;Zhixin Liu","doi":"10.1109/TMC.2024.3443056","DOIUrl":"https://doi.org/10.1109/TMC.2024.3443056","url":null,"abstract":"Owing to the openness and diversification of heterogeneous communication network, communication security becomes a pressing problem. In this paper, we consider a heterogeneous communication network in which spectrum resources are shared by electric power communication network and licensed network. First, we establish the utility companies’ cost model based on Taguchi loss function. Next, we utilize cooperative relay strategy to enhance the transmission quality and achieve high-speed information transmission in smart grids. Under the premise of ensuring high-quality transmission of electric power communication services, we propose a secure transmission strategy for information resource sharing and interference price trading that utilizes smart grid infrastructure and relay to interfere with eavesdroppers to improve the security rate of licensed user (LU), which achieves mutual benefits. Furthermore, the bernstein approximation method and the successive convex approximation are adopted to obtain the open-form expression of the constraint and transform the non-convex problem into the convex problem, respectively. A distributed robust power control algorithm is then proposed to obtain the optimal solutions. Finally, numerical results verify that the proposed secure scheme and algorithm can increase the secrecy rate at LU, reduce the total electricity cost, and improve both the profit of relay and the social welfare.","PeriodicalId":50389,"journal":{"name":"IEEE Transactions on Mobile Computing","volume":"23 12","pages":"13684-13695"},"PeriodicalIF":7.7,"publicationDate":"2024-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142636575","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}

引用次数: 0

VNF Scheduling and Sampling Rate Maximization in Energy Harvesting IoT Networks 能量收集物联网网络中的 VNF 调度和采样率最大化

IF 7.7 2区计算机科学

IEEE Transactions on Mobile Computing Pub Date : 2024-08-13 DOI: 10.1109/TMC.2024.3442809

Longji Zhang;Kwan-Wu Chin

{"title":"VNF Scheduling and Sampling Rate Maximization in Energy Harvesting IoT Networks","authors":"Longji Zhang;Kwan-Wu Chin","doi":"10.1109/TMC.2024.3442809","DOIUrl":"https://doi.org/10.1109/TMC.2024.3442809","url":null,"abstract":"This paper studies virtual network function (VNF) scheduling in energy harvesting virtualized Internet of Things (IoT) networks. Unlike prior works, sensor devices leverage imprecise computation to vary their computational workload to conserve energy at the expense of computation quality. In this respect, an optimization problem of interest is to maximize the minimum VNF computation/execution quality. To this end, this paper presents the first mixed integer linear program (MILP) that optimizes i) the VNFs executed by each sensor device, ii) the computational resources allocated to VNFs, iii) sampling rate or amount of data supplied by sensor devices to VNFs, iv) the routing of samples to VNFs and forwarding of computation results, and v) link scheduling. In addition, this paper also proposes a heuristic, called sampling control and computation scheduling (SCACS), for large-scale networks. The simulation results show that SCACS reaches 81.66% of the optimal quality. In addition, the application completion rate when using SCACS is at most 39% higher than a benchmark that randomly selects nodes to sample targets and execute VNFs.","PeriodicalId":50389,"journal":{"name":"IEEE Transactions on Mobile Computing","volume":"23 12","pages":"14441-14458"},"PeriodicalIF":7.7,"publicationDate":"2024-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142598639","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}

引用次数: 0

RIC-SDA: A Reputation Incentive Committee-Based Secure Conditional Dual Authentication Scheme for VANETs RIC-SDA：基于声誉激励委员会的 VANET 安全条件双重认证方案

IF 7.7 2区计算机科学

IEEE Transactions on Mobile Computing Pub Date : 2024-08-13 DOI: 10.1109/TMC.2024.3442933

Ningbin Yang;Chunming Tang;Tianqi Zong;Zhikang Zeng;Zehui Xiong;Debiao He

{"title":"RIC-SDA: A Reputation Incentive Committee-Based Secure Conditional Dual Authentication Scheme for VANETs","authors":"Ningbin Yang;Chunming Tang;Tianqi Zong;Zhikang Zeng;Zehui Xiong;Debiao He","doi":"10.1109/TMC.2024.3442933","DOIUrl":"https://doi.org/10.1109/TMC.2024.3442933","url":null,"abstract":"Vehicular ad hoc networks (VANETs) establish wireless connections among all vehicles, enabling seamless mobile communication. However, existing conditional privacy protection VANETs authentication schemes fail to address the issue of potential key-exposure and do not provide accelerated vehicle authentication. In this paper, we propose a reputation incentive committee-based secure conditional dual authentication scheme for VANETs called RIC-SDA. Our proposed scheme incorporates dual authentication of the consensus committee and vehicle-to-vehicle (V2V) communication. It enables the rapid provision of dynamic vehicle epoch-key from consensus committee authentication for V2V authentication through our designed reputation incentive mechanism. To mitigate the potential key-exposure problem, we introduce a novel concept of secure vehicle epoch communication, which means V2V authentication is valid for only one epoch blockchain unit time. The proposed scheme achieves lightweight computation and incurs minimal communication overheads, with the signature size being just 137 bytes. The RIC-SDA scheme supports fast batch verification. We prove that our proposed scheme is unforgeable security under random oracle and demonstrate its feasibility by implementing it in a test network based on Ethereum Sepolia. The results demonstrate that our RIC-SDA solution outperforms the existing state-of-the-art authentication VANET schemes regarding efficiency and communication costs.","PeriodicalId":50389,"journal":{"name":"IEEE Transactions on Mobile Computing","volume":"23 12","pages":"14361-14376"},"PeriodicalIF":7.7,"publicationDate":"2024-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142598647","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}

引用次数: 0

Efficient, Scalable, and Sustainable DNN Training on SoC-Clustered Edge Servers 在 SoC 集群边缘服务器上进行高效、可扩展和可持续的 DNN 训练

IF 7.7 2区计算机科学

IEEE Transactions on Mobile Computing Pub Date : 2024-08-13 DOI: 10.1109/TMC.2024.3442430

Mengwei Xu;Daliang Xu;Chiheng Lou;Li Zhang;Gang Huang;Xin Jin;Xuanzhe Liu

{"title":"Efficient, Scalable, and Sustainable DNN Training on SoC-Clustered Edge Servers","authors":"Mengwei Xu;Daliang Xu;Chiheng Lou;Li Zhang;Gang Huang;Xin Jin;Xuanzhe Liu","doi":"10.1109/TMC.2024.3442430","DOIUrl":"https://doi.org/10.1109/TMC.2024.3442430","url":null,"abstract":"In the realm of industrial edge computing, a novel server architecture known as SoC-Cluster, characterized by its aggregation of numerous mobile systems-on-chips (SoCs), has emerged as a promising solution owing to its enhanced energy efficiency and seamless integration with prevalent mobile applications. Despite its advantages, the utilization of SoC-Cluster servers remains unsatisfactory, primarily attributed to the tidal patterns of user-initiated workloads. To address such inefficiency, we introduce \u0000<monospace>SoCFlow+</monospace>\u0000, a pioneering framework designed to facilitate the co-location of deep learning training tasks on SoC-Cluster servers, thereby optimizing resource utilization. \u0000<monospace>SoCFlow+</monospace>\u0000 incorporates three novel techniques tailored to mitigate the inherent limitations of commercial SoC-Cluster servers. First, it employs group-wise parallelism complemented by delayed aggregation, a strategy engineered to enhance the training efficiency and scalability of deep learning models, effectively circumventing network bottlenecks. Second, it integrates a data-parallel mixed-precision training algorithm, optimized to exploit the heterogeneous processing capabilities inherent to mobile SoCs fully. Third, \u0000<monospace>SoCFlow+</monospace>\u0000 employs an underclocking-aware workload re-balanacing mechanism to tackle the training performance degradation caused by the thermal control of mobile SoCs. Through rigorous experimental validation, \u0000<monospace>SoCFlow+</monospace>\u0000 achieves a convergence speedup ranging from 1.6× to 740× across 32 SoCs, compared to conventional benchmarks. Furthermore, when juxtaposed with commodity GPU servers (e.g., NVIDIA V100) under identical power constraints, \u0000<monospace>SoCFlow+</monospace>\u0000 not only exhibits comparable training speed but also achieves a remarkable reduction in energy consumption by a factor of 2.31× to 10.23×, all while preserving convergence accuracy.","PeriodicalId":50389,"journal":{"name":"IEEE Transactions on Mobile Computing","volume":"23 12","pages":"14344-14360"},"PeriodicalIF":7.7,"publicationDate":"2024-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142598666","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}

引用次数: 0

Ubiquitous Indoor Mapping Using Mobile Radio Tomography 利用移动无线电层析成像技术进行无所不在的室内测绘

IF 7.7 2区计算机科学

IEEE Transactions on Mobile Computing Pub Date : 2024-08-13 DOI: 10.1109/TMC.2024.3442439

Amartya Basu;Ayon Chakraborty;Kush Jajal

{"title":"Ubiquitous Indoor Mapping Using Mobile Radio Tomography","authors":"Amartya Basu;Ayon Chakraborty;Kush Jajal","doi":"10.1109/TMC.2024.3442439","DOIUrl":"https://doi.org/10.1109/TMC.2024.3442439","url":null,"abstract":"The demand for real-time and accurate mapping is ubiquitous, particularly in complex indoor settings. While SLAM-based methods are popular, Radio Tomographic Imaging (RTI) offers an essential set of advantages, including mapping inaccessible or enclosed spaces, shorter scanning trajectories, or even identifying material properties of structures on the map. However, existing RTI systems typically depend on pre-deployed, precisely calibrated infrastructure with ample computing power, making it challenging to deploy in a ubiquitous setting. We design \u0000<sc>UbiqMap</small>\u0000, a lightweight RTI-based end-to-end system capable of mapping indoor spaces in real-time, with minimal to zero reliance over pre-deployed infrastructure. We evaluate the performance of \u0000<sc>UbiqMap</small>\u0000 in various scenarios, including two real deployments - a moderately complex residential apartment (800 sq. ft) and a large building foyer area (3000 sq. ft) and a few simulated scenarios. We demonstrate how \u0000<sc>UbiqMap</small>\u0000 can benefit over traditional SLAM-based techniques in specific contexts and advocate the fusion of RTI methods with SLAM to improve future mapping technologies. Overall, \u0000<sc>UbiqMap</small>\u0000 improves the quality of the estimated map by 30%–40% over the state-of-the-art with equivalent resource availability.","PeriodicalId":50389,"journal":{"name":"IEEE Transactions on Mobile Computing","volume":"23 12","pages":"14031-14043"},"PeriodicalIF":7.7,"publicationDate":"2024-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142595921","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}

引用次数: 0

FLuMe: Understanding Differential Spectrum Mobility Features in High Resolution FLuMe：了解高分辨率下的差异频谱移动特征

IF 7.7 2区计算机科学

IEEE Transactions on Mobile Computing Pub Date : 2024-08-13 DOI: 10.1109/TMC.2024.3442151

Rui Zou;Wenye Wang

{"title":"FLuMe: Understanding Differential Spectrum Mobility Features in High Resolution","authors":"Rui Zou;Wenye Wang","doi":"10.1109/TMC.2024.3442151","DOIUrl":"https://doi.org/10.1109/TMC.2024.3442151","url":null,"abstract":"Existing measurements and modeling of radio spectrum usage have shown that exclusive access leads to low efficiency. Thus, the next generation of wireless networks is adopting new paradigms of spectrum sharing and coexistence among heterogeneous networks. However, two significant limitations in current spectrum tenancy models hinder the development of essential functions in nonexclusive spectrum access. First, these models rely on data with much coarser resolutions than those required for wireless scheduling, rendering them ineffective for spectrum prediction or characterizing spectrum access behavior in a wireless coexistence setting. Second, due to a lack of detailed data, current models cannot describe the access dynamics of individual users, leading to unjustified adoption of simplistic traffic models, such as the on/off model and the M/G/1 queue, in spectrum access algorithm research. To address these limitations, we propose the Frame-Level spectrum Model (FLuMe), a data-driven model that characterizes individual spectrum usage based on high-resolution data. This lightweight model tracks the spectrum tenancy movements of individual users using four variables. The proposed model is applied to high-resolution LTE spectrum tenancy data, from which model parameters are extracted. Comprehensive validations demonstrate the goodness-of-fit of the model and its applicability to spectrum prediction.","PeriodicalId":50389,"journal":{"name":"IEEE Transactions on Mobile Computing","volume":"23 12","pages":"14186-14200"},"PeriodicalIF":7.7,"publicationDate":"2024-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142595839","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}

引用次数: 0