Tian Chen , Wanming Hao , Wencong Yang , Shouyi Yang , Xuandi Sun , Zhiqing Tang
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To solve this problem, we propose a joint privacy protection algorithm (JPPA), which introduces a novel metric for user location privacy guarantee called belief, this metric combines two key factors: task caching status and the geographical location of edge cloud servers. We formulate the problem as a constrained Markov decision process (CMDP), aiming to minimize the average network traffic subject to constraints on belief levels and energy outage probability. By transforming the CMDP into a linear programming problem, computational feasibility is ensured. Simulation results demonstrate that compared to traditional privacy entropy-constrained methods, JPPA reduces average network traffic overhead more effectively while ensuring user location privacy.</div></div>","PeriodicalId":48707,"journal":{"name":"Physical Communication","volume":"72 ","pages":"Article 102813"},"PeriodicalIF":2.2000,"publicationDate":"2025-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A joint privacy protection algorithm for edge computing task offloading based on Dempster–Shafer evidence theory\",\"authors\":\"Tian Chen , Wanming Hao , Wencong Yang , Shouyi Yang , Xuandi Sun , Zhiqing Tang\",\"doi\":\"10.1016/j.phycom.2025.102813\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Edge computing reduces system latency by offloading tasks from cloud servers to Internet of Things (IoT) devices. This architecture decreases network congestion, improves system efficiency, and enables real-time processing. However, in consideration of resource efficiency, user devices tend to select the nearest cloud servers, which may enable potential malicious eavesdropping devices to infer user location through intercepted communication information. Existing research has used privacy entropy to measure user location privacy, and assigned different privacy entropy values to various types of cloud servers. However, user privacy protection in real-world scenarios depends on multiple factors, not just the classification of edge cloud servers. To solve this problem, we propose a joint privacy protection algorithm (JPPA), which introduces a novel metric for user location privacy guarantee called belief, this metric combines two key factors: task caching status and the geographical location of edge cloud servers. We formulate the problem as a constrained Markov decision process (CMDP), aiming to minimize the average network traffic subject to constraints on belief levels and energy outage probability. By transforming the CMDP into a linear programming problem, computational feasibility is ensured. Simulation results demonstrate that compared to traditional privacy entropy-constrained methods, JPPA reduces average network traffic overhead more effectively while ensuring user location privacy.</div></div>\",\"PeriodicalId\":48707,\"journal\":{\"name\":\"Physical Communication\",\"volume\":\"72 \",\"pages\":\"Article 102813\"},\"PeriodicalIF\":2.2000,\"publicationDate\":\"2025-08-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Physical Communication\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1874490725002162\",\"RegionNum\":4,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ENGINEERING, ELECTRICAL & ELECTRONIC\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Physical Communication","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1874490725002162","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
A joint privacy protection algorithm for edge computing task offloading based on Dempster–Shafer evidence theory
Edge computing reduces system latency by offloading tasks from cloud servers to Internet of Things (IoT) devices. This architecture decreases network congestion, improves system efficiency, and enables real-time processing. However, in consideration of resource efficiency, user devices tend to select the nearest cloud servers, which may enable potential malicious eavesdropping devices to infer user location through intercepted communication information. Existing research has used privacy entropy to measure user location privacy, and assigned different privacy entropy values to various types of cloud servers. However, user privacy protection in real-world scenarios depends on multiple factors, not just the classification of edge cloud servers. To solve this problem, we propose a joint privacy protection algorithm (JPPA), which introduces a novel metric for user location privacy guarantee called belief, this metric combines two key factors: task caching status and the geographical location of edge cloud servers. We formulate the problem as a constrained Markov decision process (CMDP), aiming to minimize the average network traffic subject to constraints on belief levels and energy outage probability. By transforming the CMDP into a linear programming problem, computational feasibility is ensured. Simulation results demonstrate that compared to traditional privacy entropy-constrained methods, JPPA reduces average network traffic overhead more effectively while ensuring user location privacy.
期刊介绍:
PHYCOM: Physical Communication is an international and archival journal providing complete coverage of all topics of interest to those involved in all aspects of physical layer communications. Theoretical research contributions presenting new techniques, concepts or analyses, applied contributions reporting on experiences and experiments, and tutorials are published.
Topics of interest include but are not limited to:
Physical layer issues of Wireless Local Area Networks, WiMAX, Wireless Mesh Networks, Sensor and Ad Hoc Networks, PCS Systems; Radio access protocols and algorithms for the physical layer; Spread Spectrum Communications; Channel Modeling; Detection and Estimation; Modulation and Coding; Multiplexing and Carrier Techniques; Broadband Wireless Communications; Wireless Personal Communications; Multi-user Detection; Signal Separation and Interference rejection: Multimedia Communications over Wireless; DSP Applications to Wireless Systems; Experimental and Prototype Results; Multiple Access Techniques; Space-time Processing; Synchronization Techniques; Error Control Techniques; Cryptography; Software Radios; Tracking; Resource Allocation and Inference Management; Multi-rate and Multi-carrier Communications; Cross layer Design and Optimization; Propagation and Channel Characterization; OFDM Systems; MIMO Systems; Ultra-Wideband Communications; Cognitive Radio System Architectures; Platforms and Hardware Implementations for the Support of Cognitive, Radio Systems; Cognitive Radio Resource Management and Dynamic Spectrum Sharing.