2020 16th International Conference on Mobility, Sensing and Networking (MSN)最新文献_第4页

Joint Service Caching and Computation Offloading to Maximize System Profits in Mobile Edge-Cloud Computing 移动边缘云计算中联合服务缓存和计算卸载最大化系统利润

2020 16th International Conference on Mobility, Sensing and Networking (MSN) Pub Date : 2020-12-01 DOI: 10.1109/MSN50589.2020.00050

Qingyang Fan, Junyu Lin, Guangsheng Feng, Zihan Gao, Huiqiang Wang, Yafei Li

引用次数: 7

[Invited] LoRaCTP: a LoRa based Content Transfer Protocol for sustainable edge computing [特邀]LoRaCTP:基于LoRa的可持续边缘计算内容传输协议

2020 16th International Conference on Mobility, Sensing and Networking (MSN) Pub Date : 2020-12-01 DOI: 10.1109/MSN50589.2020.00090

Kiyoshy Nakamura, P. Manzoni, M. Zennaro, Juan-Carlos Cano, C. Calafate

引用次数: 1

Dynamic Resource Allocation for Hierarchical Federated Learning 分层联邦学习的动态资源分配

2020 16th International Conference on Mobility, Sensing and Networking (MSN) Pub Date : 2020-12-01 DOI: 10.1109/MSN50589.2020.00038

Wei Yang Bryan Lim, Jer Shyuan Ng, Zehui Xiong, D. Niyato, Song Guo, Cyril Leung, C. Miao

{"title":"Dynamic Resource Allocation for Hierarchical Federated Learning","authors":"Wei Yang Bryan Lim, Jer Shyuan Ng, Zehui Xiong, D. Niyato, Song Guo, Cyril Leung, C. Miao","doi":"10.1109/MSN50589.2020.00038","DOIUrl":"https://doi.org/10.1109/MSN50589.2020.00038","url":null,"abstract":"One of the enabling technologies of Edge Intelligence is the privacy preserving machine learning paradigm called Federated Learning (FL). However, communication inefficiency remains a key bottleneck in FL. To reduce node failures and device dropouts, the Hierarchical Federated Learning (HFL) framework has been proposed whereby cluster heads are designated to support the data owners through intermediate model aggregation. This decentralized learning approach reduces the reliance on a central controller, e.g., the model owner. However, the issues of resource allocation and incentive design are not well-studied in the HFL framework. In this paper, we consider a two-level resource allocation and incentive mechanism design problem. In the lower level, the cluster heads offer rewards in exchange of the data owners’ participation, and the data owners are free to choose among any clusters to join. Specifically, we apply the evolutionary game theory to model the dynamics of the cluster selection process. In the upper level, given that each cluster head can choose to serve a model owner, the model owners have to compete for the services of the cluster head. As such, we propose a deep learning based auction mechanism to derive the valuation of each cluster head’s services. The performance evaluation shows the uniqueness and stability of our proposed evolutionary game, as well as the revenue maximizing property of the deep learning based auction.","PeriodicalId":447605,"journal":{"name":"2020 16th International Conference on Mobility, Sensing and Networking (MSN)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121282750","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: 4

Real-Time Survivor Detection in UAV Thermal Imagery Based on Deep Learning 基于深度学习的无人机热图像实时幸存者检测

2020 16th International Conference on Mobility, Sensing and Networking (MSN) Pub Date : 2020-12-01 DOI: 10.1109/MSN50589.2020.00065

Jiong Dong, K. Ota, M. Dong

引用次数: 3

A Global Brain fuelled by Local intelligence: Optimizing Mobile Services and Networks with AI 由本地智能驱动的全球大脑:用人工智能优化移动服务和网络

2020 16th International Conference on Mobility, Sensing and Networking (MSN) Pub Date : 2020-12-01 DOI: 10.1109/MSN50589.2020.00021

Si-Ahmed Naas, Thaha Mohammed, S. Sigg

{"title":"A Global Brain fuelled by Local intelligence: Optimizing Mobile Services and Networks with AI","authors":"Si-Ahmed Naas, Thaha Mohammed, S. Sigg","doi":"10.1109/MSN50589.2020.00021","DOIUrl":"https://doi.org/10.1109/MSN50589.2020.00021","url":null,"abstract":"Artificial intelligence (AI) is among the most influential technologies to improve daily lives and to promote further economic activities. Recently, a distributed intelligence, referred to as a global brain, has been developed to optimize mobile services and their respective delivery networks. Inspired by interconnected neuron clusters in the human nervous system, it is an architecture interconnecting various AI entities. This paper models the global brain architecture and communication among its components based on multi-agent system technology and graph theory. We target two possible scenarios for communication and propose an optimized communication algorithm. Extensive experimental evaluations using the Java Agent Development Framework (JADE), reveal the performance of the global brain based on optimized communication in terms of network complexity, network load, and the number of exchanged messages. We adapt activity recognition as a real-world problem and show the efficiency of the proposed architecture and communication mechanism based on system accuracy and energy consumption as compared to centralized learning, using a real testbed comprised of NVIDIA Jetson Nanos. Finally, we discuss emerging technologies to foster future global brain machinelearning tasks, such as voice recognition, image processing, natural language processing, and big data processing.","PeriodicalId":447605,"journal":{"name":"2020 16th International Conference on Mobility, Sensing and Networking (MSN)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124152040","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: 2

BIA: A Blockchain-based Identity Authorization Mechanism BIA:基于区块链的身份授权机制

2020 16th International Conference on Mobility, Sensing and Networking (MSN) Pub Date : 2020-12-01 DOI: 10.1109/MSN50589.2020.00031

Xiaodong Ren, Feilong Lin, Zhongyu Chen, Changbing Tang, Zhonglong Zheng, Minglu Li

{"title":"BIA: A Blockchain-based Identity Authorization Mechanism","authors":"Xiaodong Ren, Feilong Lin, Zhongyu Chen, Changbing Tang, Zhonglong Zheng, Minglu Li","doi":"10.1109/MSN50589.2020.00031","DOIUrl":"https://doi.org/10.1109/MSN50589.2020.00031","url":null,"abstract":"The abuse of personal identity information is one of the most serious problems worldwide. Most social services or businesses use the identity authorization to confirm their validity and legality and the copies of users’ identity certification are usually recorded by the service providers. It is easy to leak the users’ identity information due to the untrustworthy service provider or single-point security failure, and various social problems are then caused. To deal with such problems, this paper proposes a Blockchain-based Identity Authorization mechanism (BIA). First, an Identity Authorization Module (IAM) is devised, which reads the identity certificate and transform the identity plaintext to ciphertext under the authorization by the user’s identity certificate entity and password. IAM guarantees the security of identity information by keeping its plaintext offline. Second, a Business Contract Module (BCM) is designed, which provides a general smart contract framework for identity authorization that can be adopted by most of social services or businesses. Third, a double-chain blockchain infrastructure is developed, whereby the encrypted identity information and service smart contracts are respectively recorded in the tamper-resistant, non-repudiable, and publicly verifiable way. Finally, a prototype system has been developed to verify the security, feasibility and effectiveness of the proposed BIA.","PeriodicalId":447605,"journal":{"name":"2020 16th International Conference on Mobility, Sensing and Networking (MSN)","volume":"102 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128580803","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

Improving Analysis of Automatic Distribution Changes for Power Grid 电网配电自动变化的改进分析

2020 16th International Conference on Mobility, Sensing and Networking (MSN) Pub Date : 2020-12-01 DOI: 10.1109/MSN50589.2020.00120

Mei Shi, Zhen Wang, Pengfei Yu, Qi Du

引用次数: 1

MobiFit: Contactless Fitness Assistant for Freehand Exercises Using Just One Cellular Signal Receiver MobiFit:仅使用一个蜂窝信号接收器进行徒手练习的非接触式健身助手

2020 16th International Conference on Mobility, Sensing and Networking (MSN) Pub Date : 2020-12-01 DOI: 10.1109/MSN50589.2020.00057

Guanlong Teng, Feng Hong, Yue Xu, Jianbo Qi, Ruobing Jiang, Chao Liu, Zhongwen Guo

{"title":"MobiFit: Contactless Fitness Assistant for Freehand Exercises Using Just One Cellular Signal Receiver","authors":"Guanlong Teng, Feng Hong, Yue Xu, Jianbo Qi, Ruobing Jiang, Chao Liu, Zhongwen Guo","doi":"10.1109/MSN50589.2020.00057","DOIUrl":"https://doi.org/10.1109/MSN50589.2020.00057","url":null,"abstract":"Freehand exercises help improve physical fitness without any requirements on devices, or places (e.g., gyms). Existing fitness assistant systems require wearing smart devices or exercising at specific positions, which compromises the ubiquitous availability of freehand exercises. This work proposes MobiFit, a contactless freehand exercise assistant using just one cellular signal receiver. MobiFit monitors the ubiquitous cellular signals sent by the base station and provides accurate repetition counting, exercise type recognition, and workout quality assessment without any attachments to the human body. To design MobiFit, we first analyze the characteristics of the received cellular signal sequence during freehand exercises through experimental studies. Based on the observation, we construct the analytic model of the received signals. Guided by the analytic model, MobiFit segments out every repetition and rest interval from one exercise session through spectrogram analysis, and extracts low-frequency features from each repetition for type recognition. We have implemented the prototype of MobiFit and collected 22,960 exercise repetitions performed by ten volunteers over six months. The results confirm that MobiFit achieves high counting accuracy of 98.6%, high recognition accuracy of 94.1%, and low repetition duration estimation error within 0.3s. Besides, the experiments show that MobiFit works both indoor and outdoor, and supports multiple users exercising together.","PeriodicalId":447605,"journal":{"name":"2020 16th International Conference on Mobility, Sensing and Networking (MSN)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131064058","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

UEIoT 2020 Workshop UEIoT 2020研讨会

2020 16th International Conference on Mobility, Sensing and Networking (MSN) Pub Date : 2020-12-01 DOI: 10.1109/msn50589.2020.00014

引用次数: 0

Identifying unfamiliar callers’ professions from privacy-preserving mobile phone data 从保护隐私的移动电话数据中识别不熟悉的来电者的职业

2020 16th International Conference on Mobility, Sensing and Networking (MSN) Pub Date : 2020-12-01 DOI: 10.1109/MSN50589.2020.00088

Jiaquan Zhang, Xiaoming Yao, Xiaoming Fu

{"title":"Identifying unfamiliar callers’ professions from privacy-preserving mobile phone data","authors":"Jiaquan Zhang, Xiaoming Yao, Xiaoming Fu","doi":"10.1109/MSN50589.2020.00088","DOIUrl":"https://doi.org/10.1109/MSN50589.2020.00088","url":null,"abstract":"Identifying an unfamiliar caller’s profession is important to protect citizens’ personal safety and property. Due to limited data protection of many popular online services in some countries such as taxi hailing or takeouts ordering, many users encounter an increasing number of phone calls from strangers. This may aggravate the situation that criminals pretend to be delivery staff or taxi drivers, bringing threats to the society. Additionally, many people nowadays suffer from excessive digital marketing and fraud phone calls because of personal information leakage. However, previous works on malicious call detection only focused on binary classification, and do not work for identification of multiple professions. We observed that web service requests issued from users’ mobile phones which may show their Apps preferences, spatial and temporal patterns, and other profession related information. This offers us a hint to identify unfamiliar callers. In fact, some previous works already leveraged raw data from mobile phones (which includes sensitive information) for personality studies. However, accessing users’ mobile phone raw data may violate the more and more strict private data protection policies or regulations (e.g. GDPR 71). Using appropriate statistical methods to eliminate private information and preserve personal characteristics, provides a way to identify mobile phone callers without privacy concern. In this paper, we exploit privacy-preserving mobile data to develop a model which can automatically identify the callers who are divided into four categories of users: normal users (other professions), taxi drivers, delivery and takeouts staffs, telemarketers and fraudsters. The validation results over an anonymized dataset of 1,282 users with a period of 3 months in Shanghai City prove that the proposed model could achieve an accuracy of 75+%.","PeriodicalId":447605,"journal":{"name":"2020 16th International Conference on Mobility, Sensing and Networking (MSN)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126301905","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