IEEE Transactions on Mobile Computing最新文献_第7页

Bilateral Pricing for Dynamic Association in Federated Edge Learning 联邦边缘学习中动态关联的双边定价

IF 7.7 2区计算机科学

IEEE Transactions on Mobile Computing Pub Date : 2025-01-08 DOI: 10.1109/TMC.2025.3527048

Bangqi Pan;Jianfeng Lu;Shuqin Cao;Jing Liu;Wenlong Tian;Minglu Li

{"title":"Bilateral Pricing for Dynamic Association in Federated Edge Learning","authors":"Bangqi Pan;Jianfeng Lu;Shuqin Cao;Jing Liu;Wenlong Tian;Minglu Li","doi":"10.1109/TMC.2025.3527048","DOIUrl":"https://doi.org/10.1109/TMC.2025.3527048","url":null,"abstract":"Devices and servers in Federated Edge Learning (FEL) are self-interested and resource-constrained, making it critical to design incentives to improve model performance. However, dynamic network conditions raise energy consumption, while data heterogeneity undermines device cooperation. Current research overlooks the interplay between system efficiency and device clustering, resulting in suboptimal updates. To address these challenges, we develop BENCH, a bilateral pricing mechanism consisting of three core rules aimed at incentivizing participation from both devices and servers. Specifically, we first design a reward allocation rule, based on the Rubinstein bargaining model, which dynamically allocates rewards. Theoretically, we derive a closed-form solution for this rule, demonstrating BENCH achieves Nash equilibrium. Secondly, we design a device partitioning rule that leverages modularity to group similar devices, facilitating personalized edge aggregation to accelerate local data adaptation. Thirdly, we design an edge matching rule that employs the Kuhn-Munkres algorithm to balance the load at edge servers, thus minimizing the congestion. Together, these three rules enable hierarchical optimization of pricing and associations, effectively mitigating the impact of dynamic costs and device heterogeneity. Extensive experiments demonstrate BENCH’s effectiveness in increasing device participation by 28.81% and improving model performance by 2.66% compared to state-of-the-art baselines.","PeriodicalId":50389,"journal":{"name":"IEEE Transactions on Mobile Computing","volume":"24 6","pages":"4684-4697"},"PeriodicalIF":7.7,"publicationDate":"2025-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143925305","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

Indirect-Communication Federated Learning via Mobile Transporters 通过移动传输的间接通信联合学习

IF 7.7 2区计算机科学

IEEE Transactions on Mobile Computing Pub Date : 2025-01-08 DOI: 10.1109/TMC.2025.3527405

Jieming Bian;Cong Shen;Mingzhe Chen;Jie Xu

{"title":"Indirect-Communication Federated Learning via Mobile Transporters","authors":"Jieming Bian;Cong Shen;Mingzhe Chen;Jie Xu","doi":"10.1109/TMC.2025.3527405","DOIUrl":"https://doi.org/10.1109/TMC.2025.3527405","url":null,"abstract":"Federated Learning (FL) is a distributed machine learning framework that efficiently reduces communication and preserves privacy. Existing FL algorithms typically rely on the assumption of direct communication between the server and clients for model data exchange. However, this assumption does not apply in many real-world scenarios where appropriate communication infrastructure is lacking, such as in remote smart sensing. To overcome this challenge, we propose a new framework, FedEx (Federated Learning via Model Express Delivery). FedEx employs mobile transporters, such as Unmanned Aerial Vehicles (UAVs), to establish indirect communication channels between the server and clients. We have developed two algorithms under this framework: FedEx-Sync and FedEx-Async, which differ based on whether the transporters operate on a synchronized or asynchronized schedule. Although indirect communication introduces variable delays in global model dissemination and local model collection, we demonstrate the convergence of both FedEx versions. Additionally, we explore the energy consumption of transporters, integrating it with the convergence bounds and proposing a bi-level optimization algorithm for efficient client assignment and route planning. Our experiments, conducted on two public datasets in a simulated environment, further demonstrate the efficacy of FedEx.","PeriodicalId":50389,"journal":{"name":"IEEE Transactions on Mobile Computing","volume":"24 6","pages":"4845-4857"},"PeriodicalIF":7.7,"publicationDate":"2025-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143925286","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

Fairness-Aware Budgeted Edge Server Placement for Connected Autonomous Vehicles 联网自动驾驶汽车的公平感知预算边缘服务器布局

IF 7.7 2区计算机科学

IEEE Transactions on Mobile Computing Pub Date : 2025-01-08 DOI: 10.1109/TMC.2025.3526873

Jintao Wu;Xiaolong Xu;Guangming Cui;Yiwen Zhang;Lianyong Qi;Wanchun Dou;Zhipeng Cai

{"title":"Fairness-Aware Budgeted Edge Server Placement for Connected Autonomous Vehicles","authors":"Jintao Wu;Xiaolong Xu;Guangming Cui;Yiwen Zhang;Lianyong Qi;Wanchun Dou;Zhipeng Cai","doi":"10.1109/TMC.2025.3526873","DOIUrl":"https://doi.org/10.1109/TMC.2025.3526873","url":null,"abstract":"Mobile edge computing (MEC) considerably enhances the capabilities and performance of connected autonomous vehicles (CAVs) by deploying edge servers (ESs) on roadside units (RSUs) near CAVs, thereby ensuring low-latency services. Given the constrained and costly nature of ES resources (computing, storage, and bandwidth), equitable ES utilization is critical for CAV operations. However, fairness considerations are often overlooked in current budgeted edge server placement (ESP) strategies, potentially worsening resource imbalances and compromising user experience. This paper investigates the fairness-aware budgeted edge server placement (FESP) problem within RSUs, proving its NP-hardness. To address FESP, we first propose FESP-O, an integer programming-based optimal approach for small-scale problems, followed by FESP-APX, an approximation approach for large-scale scenarios that provides near-optimal solutions. We analyze the time complexity and approximation ratio of our proposed algorithms and validate their efficacy through experiments on real-world datasets. Extensive experimental results demonstrate significant performance improvements over baseline and state-of-the-art methods, indicating practical suitability and efficiency.","PeriodicalId":50389,"journal":{"name":"IEEE Transactions on Mobile Computing","volume":"24 6","pages":"4762-4776"},"PeriodicalIF":7.7,"publicationDate":"2025-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143925096","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

Through-Wall Mobile Charging: Theory, Methodology, and Implementation 穿墙式移动充电：理论、方法与实现

IF 7.7 2区计算机科学

IEEE Transactions on Mobile Computing Pub Date : 2025-01-08 DOI: 10.1109/TMC.2025.3527440

Yu Sun;Chi Lin;Wei Yang;Haipeng Dai;Jiankang Ren;Lei Wang;Guowei Wu

{"title":"Through-Wall Mobile Charging: Theory, Methodology, and Implementation","authors":"Yu Sun;Chi Lin;Wei Yang;Haipeng Dai;Jiankang Ren;Lei Wang;Guowei Wu","doi":"10.1109/TMC.2025.3527440","DOIUrl":"https://doi.org/10.1109/TMC.2025.3527440","url":null,"abstract":"Wireless Power Transfer (WPT) has revolutionized the field of Wireless Rechargeable Sensor Networks (WRSNs), enabling sustainable operation of sensor nodes. Traditional mobile charging methods often require sensors to be within line-of-sight or physically accessed by the mobile charger, which may potentially lead to user safety or privacy concerns. Addressing this concern, this work is the first to introduce and validate the feasibility of <italic>Through-Wall charging. We formulate the <underline>Wireless charging thr<underline>Ough <underline>Walls (WOW) problem to simultaneously enhance user safety and maximize charging utility. Our approach leverages fundamental principles of electromagnetics to construct an accurate charging model for Magnetic Resonance Coupling-based WPT systems. Additionally, we thoroughly analyze the impact of wall obstruction and provide a generalized framework for through-wall charging. By employing discretization techniques and approximation algorithms, we derive a near-optimal solution to the WOW problem. Extensive simulations and test-bed experiments demonstrate that our proposed approach reduces the reliance on physical access to devices, simplifies deployment in complex environments, and thereby optimizes the travel paths of mobile chargers and enhances the overall performance and lifetime of WRSNs. Compared to conventional methods, our method benefits from more reasonable scheduling order and path construction, achieving an average energy efficiency improvement of 27.8%.","PeriodicalId":50389,"journal":{"name":"IEEE Transactions on Mobile Computing","volume":"24 6","pages":"4971-4986"},"PeriodicalIF":7.7,"publicationDate":"2025-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143925290","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

Cooperative Path Planning With Asynchronous Multiagent Reinforcement Learning 基于异步多智能体强化学习的协同路径规划

IF 7.7 2区计算机科学

IEEE Transactions on Mobile Computing Pub Date : 2025-01-08 DOI: 10.1109/TMC.2025.3526979

Jiaming Yin;Weixiong Rao;Yu Xiao;Keshuang Tang

{"title":"Cooperative Path Planning With Asynchronous Multiagent Reinforcement Learning","authors":"Jiaming Yin;Weixiong Rao;Yu Xiao;Keshuang Tang","doi":"10.1109/TMC.2025.3526979","DOIUrl":"https://doi.org/10.1109/TMC.2025.3526979","url":null,"abstract":"As the number of vehicles grows in urban cities, planning vehicle routes to avoid congestion and decrease commuting time is important. In this paper, we study the shortest path problem (SPP) with <italic>multiple <italic>source-<italic>destination pairs, namely MSD-SPP, to minimize the average travel time of all routing paths. The asynchronous setting in MSD-SPP, i.e., vehicles may not simultaneously complete routing actions, makes it challenging for cooperative route planning among multiple agents and leads to ineffective route planning. To tackle this issue, in this paper, we propose a two-stage framework of inter-region and intra-region route planning by dividing an entire road network into multiple sub-graph regions. Next, the proposed asyn-MARL model allows efficient asynchronous multi-agent learning by three key techniques. First, the model adopts a low-dimensional global state to implicitly represent the high-dimensional joint observations and actions of multi-agents. Second, by a novel trajectory collection mechanism, the model can decrease the redundancy in training trajectories. Additionally, with a novel actor network, the model facilitates the cooperation among vehicles towards the same or close destinations, and a reachability graph can prevent infinite loops in routing paths. On both synthetic and real road networks, the evaluation result demonstrates that asyn-MARL outperforms state-of-the-art planning approaches.","PeriodicalId":50389,"journal":{"name":"IEEE Transactions on Mobile Computing","volume":"24 6","pages":"5016-5030"},"PeriodicalIF":7.7,"publicationDate":"2025-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143918552","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

MagicWrite: One-Dimensional Acoustic Tracking-Based Air Writing System MagicWrite：基于一维声学跟踪的空气书写系统

IF 7.7 2区计算机科学

IEEE Transactions on Mobile Computing Pub Date : 2025-01-07 DOI: 10.1109/TMC.2025.3526185

Hao Pan;Yongjian Fu;Ye Qi;Yi-Chao Chen;Ju Ren

{"title":"MagicWrite: One-Dimensional Acoustic Tracking-Based Air Writing System","authors":"Hao Pan;Yongjian Fu;Ye Qi;Yi-Chao Chen;Ju Ren","doi":"10.1109/TMC.2025.3526185","DOIUrl":"https://doi.org/10.1109/TMC.2025.3526185","url":null,"abstract":"Air writing technology enhances text input for IoT, VR, and AR devices, offering a spatially flexible alternative to physical keyboards. Addressing the demand for such innovation, this paper presents MagicWrite, a novel system utilizing acoustic-based 1D tracking, which is suitable for mobile devices with existing speaker and microphone infrastructure. Compared to 2D or 3D tracking of the finger, 1D tracking eliminates the need for multiple microphones and/or speakers and is more universally applicable. However, challenges emerge when using 1D tracking for recognizing handwritten letters due to trajectory loss and inter-user writing variability. To address this, we develop a general conversion technique that transforms image-based text datasets (<italic>e.g., MNIST) into 1D tracking trajectory data, generating artificial datasets of tracking traces (referred to as <italic>TrackMNISTs) to bolster system robustness and scalability. These tracking datasets facilitate the creation of personalized user databases that align with individual writing habits. Combined with a kNN classifier, our proposed MagicWrite ensures high accuracy and robustness in text input recognition while simultaneously reducing computational load and energy consumption. Extensive experiments validate that our proposed MagicWrite achieves exceptional classification accuracy for unseen users and inputs in five languages, marking it as a robust solution for air writing.","PeriodicalId":50389,"journal":{"name":"IEEE Transactions on Mobile Computing","volume":"24 5","pages":"4403-4418"},"PeriodicalIF":7.7,"publicationDate":"2025-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143786334","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

Field Evaluation of a Softwarized Modem From the Perspective of 5G Cell Search 基于5G小区搜索的软件调制解调器现场评价

IF 7.7 2区计算机科学

IEEE Transactions on Mobile Computing Pub Date : 2025-01-07 DOI: 10.1109/TMC.2025.3526753

Dawoon Lim;Subin Jeong;Bitna Kim;Yelan Lee;Hye Jin Shin;Juyeop Kim

{"title":"Field Evaluation of a Softwarized Modem From the Perspective of 5G Cell Search","authors":"Dawoon Lim;Subin Jeong;Bitna Kim;Yelan Lee;Hye Jin Shin;Juyeop Kim","doi":"10.1109/TMC.2025.3526753","DOIUrl":"https://doi.org/10.1109/TMC.2025.3526753","url":null,"abstract":"Modem softwarization, where baseband signals are fully processed using software on a general-purpose CPU, is a promising technology in mobile communications due to its simplicity and flexibility in realizing various features. On the other hand, many still question the effectiveness of a softwarized modem in commercial environments concerning performance and complexity. Motivated by this perspective, this paper presents the design and implementation of a softwarized modem with the specific feature of 5G cell search for field evaluation. Based on the baseline algorithms of 5G cell search in Open Air Interface (OAI), we propose a new software architecture which can efficiently manage a 5G cell search procedure and decompose the overall 5G cell search into sub-algorithms. We also design and implement novel sub-algorithms that enhance the detection of Synchronization Signal Blocks (SSBs). Our softwarized modem utilizes dual-rate sampling to significantly reduce computation complexity during timing offset estimation. It also adaptively detects synchronization signals or cell identities based on the presence of inter-cell interference or multi-path fading. The performance evaluation through field experiments concludes that our softwarized modem outperforms the baseline, and the proposed sub-algorithms are effective in enhancing cell search performance. The detection probability and time consumption results for our softwarized modem confirm that it is feasible for commercial uses.","PeriodicalId":50389,"journal":{"name":"IEEE Transactions on Mobile Computing","volume":"24 6","pages":"4987-5002"},"PeriodicalIF":7.7,"publicationDate":"2025-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143918802","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

AgileDART: An Agile and Scalable Edge Stream Processing Engine AgileDART：一个敏捷和可扩展的边缘流处理引擎

IF 7.7 2区计算机科学

IEEE Transactions on Mobile Computing Pub Date : 2025-01-07 DOI: 10.1109/TMC.2025.3526143

Cheng-Wei Ching;Xin Chen;Chaeeun Kim;Tongze Wang;Dong Chen;Dilma Da Silva;Liting Hu

{"title":"AgileDART: An Agile and Scalable Edge Stream Processing Engine","authors":"Cheng-Wei Ching;Xin Chen;Chaeeun Kim;Tongze Wang;Dong Chen;Dilma Da Silva;Liting Hu","doi":"10.1109/TMC.2025.3526143","DOIUrl":"https://doi.org/10.1109/TMC.2025.3526143","url":null,"abstract":"Edge applications generate a large influx of sensor data on massive scales, and these massive data streams must be processed shortly to derive actionable intelligence. However, traditional data processing systems are not well-suited for these edge applications as they often do not scale well with a large number of concurrent stream queries, do not support low-latency processing under limited edge computing resources, and do not adapt to the level of heterogeneity and dynamicity commonly present in edge computing environments. As such, we present AgileDart, an agile and scalable edge stream processing engine that enables fast stream processing of many concurrently running low-latency edge applications’ queries at scale in dynamic, heterogeneous edge environments. The novelty of our work lies in a dynamic dataflow abstraction that leverages distributed hash table-based peer-to-peer overlay networks to autonomously place, chain, and scale stream operators to reduce query latencies, adapt to workload variations, and recover from failures and a bandit-based path planning model that re-plans the data shuffling paths to adapt to unreliable and heterogeneous edge networks. We show that AgileDart outperforms Storm and EdgeWise on query latency and significantly improves scalability and adaptability when processing many real-world edge stream applications’ queries.","PeriodicalId":50389,"journal":{"name":"IEEE Transactions on Mobile Computing","volume":"24 5","pages":"4510-4528"},"PeriodicalIF":7.7,"publicationDate":"2025-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143786344","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

PCSE: Privacy-Preserving Collaborative Searchable Encryption for Group Data Sharing in Cloud Computing 云计算中群体数据共享的隐私保护协同可搜索加密

IF 7.7 2区计算机科学

IEEE Transactions on Mobile Computing Pub Date : 2025-01-07 DOI: 10.1109/TMC.2025.3526232

Yongliang Xu;Hang Cheng;Ximeng Liu;Changsong Jiang;Xinpeng Zhang;Meiqing Wang

{"title":"PCSE: Privacy-Preserving Collaborative Searchable Encryption for Group Data Sharing in Cloud Computing","authors":"Yongliang Xu;Hang Cheng;Ximeng Liu;Changsong Jiang;Xinpeng Zhang;Meiqing Wang","doi":"10.1109/TMC.2025.3526232","DOIUrl":"https://doi.org/10.1109/TMC.2025.3526232","url":null,"abstract":"Collaborative searchable encryption for group data sharing enables a consortium of authorized users to collectively generate trapdoors and decrypt search results. However, existing countermeasures may be vulnerable to a keyword guessing attack (KGA) initiated by malicious insiders, compromising the confidentiality of keywords. Simultaneously, these solutions often fail to guard against hostile manufacturers embedding backdoors, leading to potential information leakage. To address these challenges, we propose a novel privacy-preserving collaborative searchable encryption (PCSE) scheme tailored for group data sharing. This scheme introduces a dedicated keyword server to export server-derived keywords, thereby withstanding KGA attempts. Based on this, PCSE deploys cryptographic reverse firewalls to thwart subversion attacks. To overcome the single point of failure inherent in a single keyword server, the export of server-derived keywords is collaboratively performed by multiple keyword servers. Furthermore, PCSE extends its capabilities to support efficient multi-keyword searches and result verification and incorporates a rate-limiting mechanism to effectively slow down adversaries’ online KGA attempts. Security analysis demonstrates that our scheme can resist KGA and subversion attack. Theoretical analyses and experimental results show that PCSE is significantly more practical for group data sharing systems compared with state-of-the-art works.","PeriodicalId":50389,"journal":{"name":"IEEE Transactions on Mobile Computing","volume":"24 5","pages":"4558-4572"},"PeriodicalIF":7.7,"publicationDate":"2025-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143786352","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 Game-Theoretical Approach for Distributed Computation Offloading in LEO Satellite-Terrestrial Edge Computing Systems 低轨道卫星-地面边缘计算系统分布式计算卸载的博弈论方法

IF 7.7 2区计算机科学

IEEE Transactions on Mobile Computing Pub Date : 2025-01-07 DOI: 10.1109/TMC.2025.3526200

Ying Chen;Yaozong Yang;Jintao Hu;Yuan Wu;Jiwei Huang

{"title":"A Game-Theoretical Approach for Distributed Computation Offloading in LEO Satellite-Terrestrial Edge Computing Systems","authors":"Ying Chen;Yaozong Yang;Jintao Hu;Yuan Wu;Jiwei Huang","doi":"10.1109/TMC.2025.3526200","DOIUrl":"https://doi.org/10.1109/TMC.2025.3526200","url":null,"abstract":"Due to the limitations of computing resources and battery capacity, the computation tasks of ground devices can be offloaded to edge servers for processing. Moreover, with the development of the low earth orbit (LEO) satellite technology, LEO satellite-terrestrial edge computing can realize a global coverage network to provide seamless computing services beyond the regional restrictions compared to the conventional terrestrial edge computing networks. In this paper, we study the computation offloading problem in the LEO satellite-terrestrial edge computing systems. Ground devices can offload their computation tasks to terrestrial base stations (BSs) or LEO satellites deployed on edge servers for remote processing. We formulate the computation offloading problem to minimize the cost of devices while satisfying resource and LEO satellite communication time constraints. Since each ground device competes for transmission and computing resources to reduce its own offloading cost, we reformulate this problem as the LEO satellite-terrestrial computation offloading game (LSTCO-Game). It is derived that there is an upper bound on transmission interference and computing resource competition among devices. Then, we theoretically prove that at least one Nash equilibrium (NE) offloading strategy exists in the LSTCO-Game. We propose the game-theoretical distributed computation offloading (GDCO) algorithm to find the NE offloading strategy. Next, we analyze the cost obtained by GDCO's NE offloading strategy in the worst case. Experiments are conducted by comparing the proposed GDCO algorithm with other computation offloading methods. The results show that the GDCO algorithm can effectively reduce the offloading cost.","PeriodicalId":50389,"journal":{"name":"IEEE Transactions on Mobile Computing","volume":"24 5","pages":"4389-4402"},"PeriodicalIF":7.7,"publicationDate":"2025-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143786386","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