2022 18th International Conference on Mobility, Sensing and Networking (MSN)最新文献_第9页

CUE: Compound Uniform Encoding for Writer Retrieval

2022 18th International Conference on Mobility, Sensing and Networking (MSN) Pub Date : 2022-12-01 DOI: 10.1109/MSN57253.2022.00125

Jiakai Luo, Hongwei Lu, Xin Nie, Shenghao Liu, Xianjun Deng, Chenlu Zhu

{"title":"CUE: Compound Uniform Encoding for Writer Retrieval","authors":"Jiakai Luo, Hongwei Lu, Xin Nie, Shenghao Liu, Xianjun Deng, Chenlu Zhu","doi":"10.1109/MSN57253.2022.00125","DOIUrl":"https://doi.org/10.1109/MSN57253.2022.00125","url":null,"abstract":"Writer retrieval is crucial in document forensics and historical document analysis. However, due to the difference in syntactic structure between Chinese and other languages, the existing methods may not be directly applied to Chinese writer retrieval. Previous work on Chinese writer retrieval does not overcome the performance degradation problem when the number of samples grows. In this paper, we propose a novel compound uniform encoding algorithm (CUE) for Chinese writer retrieval, which mainly consists of a combined feature extraction module (CFE) and a prototype substitution module (PS). The CFE module combines two complementary features from image filter response and character contour. It counts local symmetries and edge co-occurrence pairs. PS module substitutes the outliers with the class prototypes to alleviate the influence of the outliers. Finally, the weighted Chi-square distance is applied to measure the similarity between writer and text. To verify the superiority of our proposed method, experiments are conducted on four public datasets and our built dataset. The results validate that CUE outperforms the state-of-the-art algorithms on mAP metric.","PeriodicalId":114459,"journal":{"name":"2022 18th International Conference on Mobility, Sensing and Networking (MSN)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124937634","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Federated Learning for Heterogeneous Mobile Edge Device: A Client Selection Game 面向异构移动边缘设备的联邦学习:一个客户端选择博弈

2022 18th International Conference on Mobility, Sensing and Networking (MSN) Pub Date : 2022-12-01 DOI: 10.1109/MSN57253.2022.00145

Tongfei Liu, Hongya Wang, M. Ma

{"title":"Federated Learning for Heterogeneous Mobile Edge Device: A Client Selection Game","authors":"Tongfei Liu, Hongya Wang, M. Ma","doi":"10.1109/MSN57253.2022.00145","DOIUrl":"https://doi.org/10.1109/MSN57253.2022.00145","url":null,"abstract":"In the federated learning (FL) paradigm, edge devices use local datasets to participate in machine learning model training, and servers are responsible for aggregating and maintaining public models. FL cannot only solve the bandwidth limitation problem of centralized training, but also protect data privacy. However, it is difficult for heterogeneous edge devices to obtain optimal learning performance due to limited computing and communication resources. Specifically, in each round of the global aggregation process by the FL, clients in a ‘strong group’ have a greater chance to contribute their own local training results, while those clients in a ‘weak group’ have a low opportunity to participate, resulting in a negative impact on the final training result. In this paper, we consider a federated learning multi-client selection (FL-MCS) problem, which is an NP-hard problem. To find the optimal solution, we model the FL global aggregation process for clients participation as a potential game. In this game, each client will selfishly decide whether to participate in the FL global aggregation process based on its efforts and rewards. By the potential game, we prove that the competition among clients eventually reaches a stationary state, i.e. the Nash equilibrium point. We also design a distributed heuristic FL multi-client selection algorithm to achieve the maximum reward for the client in a finite number of iterations. Extensive numerical experiments prove the effectiveness of the algorithm.","PeriodicalId":114459,"journal":{"name":"2022 18th International Conference on Mobility, Sensing and Networking (MSN)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128363891","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Traffic Event Augmentation via Vehicular Edge Computing: A Vehicle ReID based Solution 基于车辆边缘计算的交通事件增强:基于车辆ReID的解决方案

2022 18th International Conference on Mobility, Sensing and Networking (MSN) Pub Date : 2022-12-01 DOI: 10.1109/MSN57253.2022.00105

Hao Jiang, Penglin Dai, Kai Liu, Feiyu Jin, Hualing Ren, Songtao Guo

{"title":"Traffic Event Augmentation via Vehicular Edge Computing: A Vehicle ReID based Solution","authors":"Hao Jiang, Penglin Dai, Kai Liu, Feiyu Jin, Hualing Ren, Songtao Guo","doi":"10.1109/MSN57253.2022.00105","DOIUrl":"https://doi.org/10.1109/MSN57253.2022.00105","url":null,"abstract":"Traditional traffic event monitoring and detection solutions mainly rely on roadside surveillance cameras. However, existing solutions cannot be applied for traffic event augmentation due to both restricted monitoring angles and limited camera coverage. Therefore, this paper investigates a novel architecture for traffic event augmentation via vehicular edge computing. In particular, multiple vehicles can collaborate with roadside infrastructures for detecting, re-identification and augmenting certain traffic event via vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communications. To enable such an application, we formulate the problem of multi-view augmentation task offloading (MATO) by considering the heterogeneous capabilities of vehicles and edge servers, which aims at minimizing average request delay. On this basis, we design the offloading scheduling framework and propose an adaptive real-time offloading algorithm (ARTO), which makes online offloading decision of object detection and re-identification, by balancing real-time workload among heterogeneous devices. Finally, we implement the hardware-in-the-loop testbed for performance evaluation. The comprehensive results demonstrate the superiority of the proposed algorithm in various realistic traffic scenarios.","PeriodicalId":114459,"journal":{"name":"2022 18th International Conference on Mobility, Sensing and Networking (MSN)","volume":"79 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127117161","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Compact Unknown Tag Identification for Large-Scale RFID Systems 大型RFID系统的紧凑型未知标签识别

2022 18th International Conference on Mobility, Sensing and Networking (MSN) Pub Date : 2022-12-01 DOI: 10.1109/MSN57253.2022.00114

Kai Lin, Honglong Chen, Na Yan, Zhichen Ni, Zhe Li

{"title":"Compact Unknown Tag Identification for Large-Scale RFID Systems","authors":"Kai Lin, Honglong Chen, Na Yan, Zhichen Ni, Zhe Li","doi":"10.1109/MSN57253.2022.00114","DOIUrl":"https://doi.org/10.1109/MSN57253.2022.00114","url":null,"abstract":"Nowadays, Radio Frequency IDentification (RFID) technology is profoundly affecting all walks of life. Unknown tag identification, as an important service for RFID-enabled applications, aims to exactly collect all EPCs (Electronic Product Code) of unknown tags that are not recorded by the back-end server in the RFID systems. Efficient unknown tag identification is significant to accurately discover the unregistered or newly entering tags in many scenarios, such as warehouse management and retail industry. However, the replies of known tags and the unpredictable behaviors of unknown tags bring serious challenges for accurate and efficient identification of unknown tags. To handle these tough issues, we propose a Compact Unknown Tag identification protocol (CUT) to collect unknown tag EPCs in large-scale RFID systems. Firstly, we introduce a compact indicator vector to simultaneously label unknown tags and deactivate known tags. Then the unknown tags are instructed to reply their EPCs via another compact reply based indicator vector. In each indicator vector, the amount of expected empty and singleton slots is increased to greatly improve the labeling, deactivation and collection efficiency. After that, we validate the effectiveness of proposed CUT protocol by extensive theoretical analyses and simulations. The simulation results demonstrate that CUT protocol outperforms the state-of-the-art one.","PeriodicalId":114459,"journal":{"name":"2022 18th International Conference on Mobility, Sensing and Networking (MSN)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121961593","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

An Adaptive Data Rate-Based Task Offloading Scheme in Vehicular Networks 一种基于数据速率的自适应车载网络任务分流方案

2022 18th International Conference on Mobility, Sensing and Networking (MSN) Pub Date : 2022-12-01 DOI: 10.1109/MSN57253.2022.00142

Chaofan CHEN, Wendi Nie, Yaoxin Duan, V. Lee, Kai Liu, Huamin Li

{"title":"An Adaptive Data Rate-Based Task Offloading Scheme in Vehicular Networks","authors":"Chaofan CHEN, Wendi Nie, Yaoxin Duan, V. Lee, Kai Liu, Huamin Li","doi":"10.1109/MSN57253.2022.00142","DOIUrl":"https://doi.org/10.1109/MSN57253.2022.00142","url":null,"abstract":"As an important application of Internet of Things (IoT), Internet of Vehicles (IoVs) can provide various valuable services which may require computation-intensive tasks under strict time constraints. Most traditional vehicles may not be able to process all these computation-intensive tasks locally because of the limitation of computing resources. Therefore, task offloading has been proposed, which allows vehicles to offload computation-intensive tasks to Mobile Edge Computing (MEC) servers. With the arising and development of intelligent vehicles, the concept of Vehicle as a Resource (VaaR) has been proposed as an important supplement to MEC, which enables intelligent vehicles to share computation resources with nearby vehicles. Most studies in VaaR generally assume that the transmission data rate of offloading tasks from one vehicle to another is fixed. However, in VaaR, due to the high mobility of vehicles, the communication distance between vehicles may change over time, resulting in changing data rate. Therefore, it is challenging to make offloading decisions (i.e., selecting proper vehicles as computation resource providers) while considering adaptive data rate. In this paper, we study task offloading in vehicular networks while considering adaptive data rate. We propose an Adaptive Data Rate-based Offloading algorithm named ADRO, which can not only achieve minimum energy consumption while satisfying time constraints, but also take adaptive data rate into consideration. Comprehensive experiments have been conducted to demonstrate the efficiency of the ADRO algorithm.","PeriodicalId":114459,"journal":{"name":"2022 18th International Conference on Mobility, Sensing and Networking (MSN)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130645710","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Towards Socially Acceptable Food Type Recognition 走向社会可接受的食物类型识别

2022 18th International Conference on Mobility, Sensing and Networking (MSN) Pub Date : 2022-12-01 DOI: 10.1109/MSN57253.2022.00110

Junjie Wang, Jiexiong Guan, Y. A. Hong, Hong Xue, Shuangquan Wang, Zhenming Liu, Bin Ren, Gang Zhou

{"title":"Towards Socially Acceptable Food Type Recognition","authors":"Junjie Wang, Jiexiong Guan, Y. A. Hong, Hong Xue, Shuangquan Wang, Zhenming Liu, Bin Ren, Gang Zhou","doi":"10.1109/MSN57253.2022.00110","DOIUrl":"https://doi.org/10.1109/MSN57253.2022.00110","url":null,"abstract":"Automatic food type recognition is an essential task of dietary monitoring. It helps medical professionals recognize a user's food contents, estimate the amount of energy intake, and design a personalized intervention model to prevent many chronic diseases, such as obesity and heart disease. Various wearable and mobile devices are utilized as platforms for food type recognition. However, none of them has been widely used in our daily lives and, at the same time, socially acceptable enough for continuous wear. In this paper, we propose a food type recognition method that takes advantage of Airpods Pro, a pair of widely used wireless in-ear headphones designed by Apple, to recognize 20 different types of food. As far as we know, we are the first to use this socially acceptable commercial product to recognize food types. Audio and motion sensor data are collected from Airpods Pro. Then 135 representative features are extracted and selected to construct the recognition model using the lightGBM algorithm. A real-world data collection is conducted to comprehensively evaluate the performance of the proposed method for seven human subjects. The results show that the average f1-score reaches 94.4% for the ten-fold cross-validation test and 96.0% for the self-evaluation test.","PeriodicalId":114459,"journal":{"name":"2022 18th International Conference on Mobility, Sensing and Networking (MSN)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130736998","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Technical Program Committee: MSN 2022 技术项目委员会:MSN 2022

2022 18th International Conference on Mobility, Sensing and Networking (MSN) Pub Date : 2022-12-01 DOI: 10.1109/msn57253.2022.00008

引用次数: 0

Towards Event-driven Misbehavior Detection Mechanism in Social Internet of Vehicles 社交车联网中事件驱动的不良行为检测机制研究

2022 18th International Conference on Mobility, Sensing and Networking (MSN) Pub Date : 2022-12-01 DOI: 10.1109/MSN57253.2022.00059

Chenchen Lv, Yue Cao, Lexi Xu, Shitao Zou, Yongdong Zhu, Zhili Sun

{"title":"Towards Event-driven Misbehavior Detection Mechanism in Social Internet of Vehicles","authors":"Chenchen Lv, Yue Cao, Lexi Xu, Shitao Zou, Yongdong Zhu, Zhili Sun","doi":"10.1109/MSN57253.2022.00059","DOIUrl":"https://doi.org/10.1109/MSN57253.2022.00059","url":null,"abstract":"Due to inadequate management of Vehicular Ad hoc Networks (VANETs), malicious nodes could participate in communications along with misbehavior, e.g., dropping packets and spreading fake information. Therefore, it is essential to detect misbehavior of internal attackers that will cause network performance degradation (e.g., taking longer time to receive messages or reaching destinations with detours). Apart from the capture of dynamic network topology of VANETs, the social relationship among nodes can also be applied as a relatively stable metric to qualify nodes. This paper proposes a misbehavior detection mechanism based on social relationships, from which nodes determine trust for the receiver or transmitter. Based on the proposed mechanism, road traffic control applications can avoid the interference from malicious nodes. The construction of social relationships depends on the geographic information reflected by the movement of nodes, including contact frequency and trajectory similarity, since the geographic information can accurately indicate the relevance among nodes. In addition to the social relationship, the proposed mechanism also evaluates the data trust from time and spatial factors to reduce the interference of fake data. Finally, the proposed mechanism integrates data trust and social relationships to enable misbehavior detection decisions. Extensive results of simulations show that the proposed mechanism has outstanding malicious nodes detection rates under various proportions of malicious nodes and movement patterns.","PeriodicalId":114459,"journal":{"name":"2022 18th International Conference on Mobility, Sensing and Networking (MSN)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128041652","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Online Service Provisioning and Updating in QoS-aware Mobile Edge Computing qos感知移动边缘计算中的在线服务提供和更新

2022 18th International Conference on Mobility, Sensing and Networking (MSN) Pub Date : 2022-12-01 DOI: 10.1109/MSN57253.2022.00051

Shuaibing Lu, Jie Wu, Pengfan Lu, Jiamei Shi, Ning Wang, Juan Fang

{"title":"Online Service Provisioning and Updating in QoS-aware Mobile Edge Computing","authors":"Shuaibing Lu, Jie Wu, Pengfan Lu, Jiamei Shi, Ning Wang, Juan Fang","doi":"10.1109/MSN57253.2022.00051","DOIUrl":"https://doi.org/10.1109/MSN57253.2022.00051","url":null,"abstract":"The vigorous development of IoT technology has spawned a series of applications that are delay-sensitive or resource-intensive. Mobile edge computing is an emerging paradigm which provides services between end devices and traditional cloud data centers to users. However, with the continuously increasing investment of demands, it is nontrivial to maintain a higher quality-of-service (QoS) under the erratic activities of mobile users. In this paper, we investigate the service provisioning and updating problem under the multiple-users scenario by improving the performance of services with long-term cost constraints. We first decouple the original long-term optimization problem into a per-slot deterministic one by using Lyapunov optimization. Then, we propose two service updating decision strategies by considering the trajectory prediction conditions of users. Based on that, we design an online strategy by utilizing the committed horizon control method looking forward to multiple slots predictions. We prove the performance bound of our online strategy theoretically in terms of the trade-off between delay and cost. Extensive experiments demonstrate the superior performance of the proposed algorithm.","PeriodicalId":114459,"journal":{"name":"2022 18th International Conference on Mobility, Sensing and Networking (MSN)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114171872","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Privacy protection scheme based on certificateless in VSN s environment VSN环境下基于无证书的隐私保护方案

2022 18th International Conference on Mobility, Sensing and Networking (MSN) Pub Date : 2022-12-01 DOI: 10.1109/MSN57253.2022.00153

Yanfei Lu, Suzhen Cao, Yi Guo, Qizhi He, Zixuan Fang, Junjian Yan

{"title":"Privacy protection scheme based on certificateless in VSN s environment","authors":"Yanfei Lu, Suzhen Cao, Yi Guo, Qizhi He, Zixuan Fang, Junjian Yan","doi":"10.1109/MSN57253.2022.00153","DOIUrl":"https://doi.org/10.1109/MSN57253.2022.00153","url":null,"abstract":"In vehicular social networks (VSN s), cloud service providers can provide many convenient services for vehicles to ensure the safety of driving. However, the wireless communication between entities in VSN s is vulnerable to attacks, which can lead to vehicle privacy leakage. To solve this problem, a certificateless searchable encryption scheme with privacy-preserving features that can resist keyword guessing attacks is proposed based on the VSN s application environment. The scheme combines proxy re-encryption technology, which enables vehicle users to obtain accurate request results without disclosing privacy information to cloud service providers, and achieves the privacy of vehicle identity and confidentiality of transmitted data. In addition, the authorization process of the data service provider not only ensures the security of the data but also achieves revocability of user authorization. Based on the computational Diffie-Hellman problem and the discrete logarithm problem, the scheme is proved to be resistant to internal or external keyword guessing attacks under the random oracle model, and the experimental results show that the scheme has better performance in terms of computational and communication efficiency.","PeriodicalId":114459,"journal":{"name":"2022 18th International Conference on Mobility, Sensing and Networking (MSN)","volume":"67 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126965172","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0