2020 IEEE 17th International Conference on Mobile Ad Hoc and Sensor Systems (MASS)最新文献_第2页

Effective Subcarrier Pairing for Hybrid Delivery in Relay Networks 中继网络中混合传输的有效子载波配对

2020 IEEE 17th International Conference on Mobile Ad Hoc and Sensor Systems (MASS) Pub Date : 2020-12-01 DOI: 10.1109/MASS50613.2020.00038

Xiao Zhang, Li Xiao

{"title":"Effective Subcarrier Pairing for Hybrid Delivery in Relay Networks","authors":"Xiao Zhang, Li Xiao","doi":"10.1109/MASS50613.2020.00038","DOIUrl":"https://doi.org/10.1109/MASS50613.2020.00038","url":null,"abstract":"The emerging 5G adopts OFDM modulation and deploys small-cell amplify and forward (AF) relays for in-cell capacity enhancement and energy efficiency. However, hybrid delivery services for multiple users where broadcast and unicast coexist are inefficient and unfair due to their different QoS requirements. Most existing work considering hybrid broadcast and unicast traffic focuses on different scheduling schemes in onehop scenarios. For dual-hop relay networks, subcarrier mapping or pairing has been studied, but none considers hybrid traffic with both broadcast and unicast. In this paper, we propose an effective subcarrier pairing (ESP) protocol, which exploits the performance diversity in subcarrier pairing at relays to improve the overall performance of hybrid broadcast and unicast traffic. ESP exquisitely pairs subcarriers of two hops into two kinds of subcarrier pairs separately. ESP then allocates subcarrier pairs with low outage probability for broadcast and subcarrier pairs with high capacity for unicast. In ESP design, we study several important metrics such as end-to-end outage probability, capacity, and bit-error-rate (BER) in AF assisted OFDM-CDMA relay networks. We conduct Monte Carlo simulations to verify the effectiveness and fairness of our approach in hybrid transmission. Results show that ESP is efficient in hybrid delivery for relay networks and improves the performance of broadcast services significantly without sacrificing unicast services.","PeriodicalId":105795,"journal":{"name":"2020 IEEE 17th International Conference on Mobile Ad Hoc and Sensor Systems (MASS)","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":"130194224","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: 6

Spectrum Sharing in CBRS Using Blockchain 基于区块链的CBRS频谱共享

2020 IEEE 17th International Conference on Mobile Ad Hoc and Sensor Systems (MASS) Pub Date : 2020-12-01 DOI: 10.1109/MASS50613.2020.00082

Pavithra Chidambaram Pappa, Aarushi Sarbhai, Aniqua Z. Baset, S. Kasera, M. Buddhikot

引用次数: 0

NoiseSenseDNN: Modeling DNN for Sensor Data to Mitigate the Effect of Noise in Edge Devices NoiseSenseDNN:对传感器数据进行深度神经网络建模，以减轻边缘设备中噪声的影响

2020 IEEE 17th International Conference on Mobile Ad Hoc and Sensor Systems (MASS) Pub Date : 2020-12-01 DOI: 10.1109/MASS50613.2020.00053

Tanmoy Sen, Haiying Shen, Matthew Normansell

{"title":"NoiseSenseDNN: Modeling DNN for Sensor Data to Mitigate the Effect of Noise in Edge Devices","authors":"Tanmoy Sen, Haiying Shen, Matthew Normansell","doi":"10.1109/MASS50613.2020.00053","DOIUrl":"https://doi.org/10.1109/MASS50613.2020.00053","url":null,"abstract":"Edge computing usage in many applications, such as transportation and healthcare, has been becoming popular nowadays. These applications often use deep learning (DL) prediction, which are highly dependent on time-series data collected by the sensors in the edge devices. However, the presence of noise in the on-device sensors negatively affects the sensing output of the DL models. Recently proposed time-series based DL approaches (e.g., SADeepSense) address this issue with the assumption that in the presence of noise, the correlation of sensor inputs in an edge device changes. In this paper, through real experiments, we notice that this assumption may not hold true in the presence of shot noise. To handle this problem, in order to further improve the prediction accuracy, we propose a DL model, namely NoiseSenseDNN, which more accurately extracts the correlation between different sensor inputs over time in the presence of both shot and white noise due to its unique architecture. We further propose a compressed version of NoiseSenseDNN that minimizes the inference time and consumed energy of the edge device while meeting the accuracy requirement. Our experiments on a workstation and a real edge device and three real traces show that NoiseSenseDNN outperforms SADeepSense in accuracy, and the compressed NoiseSenseDNN significantly reduces inference time and energy consumption while meeting the required accuracy.","PeriodicalId":105795,"journal":{"name":"2020 IEEE 17th International Conference on Mobile Ad Hoc and Sensor Systems (MASS)","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":"132024678","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

Secure and Privacy-preserving Traffic Monitoring in VANETs VANETs中安全和保护隐私的流量监控

2020 IEEE 17th International Conference on Mobile Ad Hoc and Sensor Systems (MASS) Pub Date : 2020-12-01 DOI: 10.1109/MASS50613.2020.00075

Ayan Roy, S. Madria

引用次数: 2

Vehicular Edge Computing Based Driver Recommendation System Using Federated Learning 基于联邦学习的车辆边缘计算驾驶员推荐系统

2020 IEEE 17th International Conference on Mobile Ad Hoc and Sensor Systems (MASS) Pub Date : 2020-12-01 DOI: 10.1109/MASS50613.2020.00087

Jayant Vyas, Debasis Das, Sajal K. Das

引用次数: 10

Towards Environment-independent Behavior-based User Authentication Using WiFi 基于环境无关行为的WiFi用户认证

2020 IEEE 17th International Conference on Mobile Ad Hoc and Sensor Systems (MASS) Pub Date : 2020-12-01 DOI: 10.1109/MASS50613.2020.00086

Cong Shi, Jian Liu, N. Borodinov, Bruno P. Leao, Yingying Chen

{"title":"Towards Environment-independent Behavior-based User Authentication Using WiFi","authors":"Cong Shi, Jian Liu, N. Borodinov, Bruno P. Leao, Yingying Chen","doi":"10.1109/MASS50613.2020.00086","DOIUrl":"https://doi.org/10.1109/MASS50613.2020.00086","url":null,"abstract":"With the increasing prevalence of smart mobile and Internet of things (IoT) environments, user authentication has become a critical component for not only preventing unauthorized access to security-sensitive systems but also providing customized services for individual users. Unlike traditional approaches relying on tedious passwords or specialized biometric/wearable sensors, this paper presents a device-free user authentication via daily human behavioral patterns captured by existing WiFi infrastructures. Specifically, our system exploits readily available channel state information (CSI) in WiFi signals to capture unique behavioral biometrics residing in the user’s daily activities, without requiring any dedicated sensors or wearable device attachment. To build such a system, one major challenge is that wireless signals always carry substantial information that is specific to the user’s location and surrounding environment, rendering the trained model less effective when being applied to the data collected in a new location or environment. This issue could lead to significant authentication errors and may quickly ruin the whole system in practice. To disentangle the behavioral biometrics for practical environment-independent user authentication, we propose an end-to-end deep-learning based approach with domain adaptation techniques to remove the environment-and location-specific information contained in the collected WiFi measurements. Extensive experiments in a residential apartment and an office with various scales of user location variations and environmental changes demonstrate the effectiveness and generalizability of the proposed authentication system.","PeriodicalId":105795,"journal":{"name":"2020 IEEE 17th International Conference on Mobile Ad Hoc and Sensor Systems (MASS)","volume":"56 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":"114225239","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: 8

A Dynamic Taxi Ride Sharing System Using Particle Swarm Optimization 基于粒子群优化的动态出租车拼车系统

2020 IEEE 17th International Conference on Mobile Ad Hoc and Sensor Systems (MASS) Pub Date : 2020-12-01 DOI: 10.1109/MASS50613.2020.00024

Shrawani Silwal, V. Raychoudhury, Snehanshu Saha, Md Osman Gani

{"title":"A Dynamic Taxi Ride Sharing System Using Particle Swarm Optimization","authors":"Shrawani Silwal, V. Raychoudhury, Snehanshu Saha, Md Osman Gani","doi":"10.1109/MASS50613.2020.00024","DOIUrl":"https://doi.org/10.1109/MASS50613.2020.00024","url":null,"abstract":"With the rapid growth of on-demand taxi services, like Uber, Lyft, etc., urban public transportation scenario is shifting towards a personalized transportation choice for most commuters. While taxi rides are comfortable and time efficient, they often lead to higher cost and road congestion due to lower overall occupancy than bigger vehicles. One efficient way to improve taxi occupancy is to adopt ride sharing. Existing ride sharing solutions are mostly centralized and proprietary. Moreover, given the wide spatio-temporal variation of incoming ride requests designing a dynamic and distributed shared-ride scheduling system is NP-hard. In this paper, we have proposed a publisher (passengers) and subscriber (taxis) based ride sharing system that provides effective real-time ride scheduling for multiple passengers. A particle swarm based route optimization strategy has been applied to determine the most preferable route for passengers. Empirical analysis using large scale single-user taxi ride records from Chicago Transit Authority, show that, our proposed system, ensures a maximum of 91.74% and 63.29% overall success rates during non-peak and peak hours, respectively.","PeriodicalId":105795,"journal":{"name":"2020 IEEE 17th International Conference on Mobile Ad Hoc and Sensor Systems (MASS)","volume":"24 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":"114772879","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

Adaptive Policy Tree Algorithm to Approach Collision-Free Transmissions in Slotted ALOHA 开槽ALOHA中无碰撞传输的自适应策略树算法

2020 IEEE 17th International Conference on Mobile Ad Hoc and Sensor Systems (MASS) Pub Date : 2020-12-01 DOI: 10.1109/MASS50613.2020.00027

Molly Zhang, L. D. Alfaro, M. Mosko, C. Funai, Timothy Upthegrove, B. Thapa, D. Javorsek, J. Garcia-Luna-Aceves

引用次数: 4

Posture Tracking Meets Fitness Coaching: A Two-Phase Optimization Approach with Wearable Devices 姿势跟踪与健身指导:可穿戴设备的两阶段优化方法

2020 IEEE 17th International Conference on Mobile Ad Hoc and Sensor Systems (MASS) Pub Date : 2020-12-01 DOI: 10.1109/MASS50613.2020.00070

Han Zhou, Yi Gao, Wenxin Liu, Yuefang Jiang, Wei Dong

{"title":"Posture Tracking Meets Fitness Coaching: A Two-Phase Optimization Approach with Wearable Devices","authors":"Han Zhou, Yi Gao, Wenxin Liu, Yuefang Jiang, Wei Dong","doi":"10.1109/MASS50613.2020.00070","DOIUrl":"https://doi.org/10.1109/MASS50613.2020.00070","url":null,"abstract":"Fitness training is becoming an increasingly popular way of maintaining overall health and preventing illness. However, in some cases the training could be risky and fitness-related injuries have increased by 48% in the USA. The training itself will not cause hurt, but if it is performed in a crucial-improper form (using the wrong technique), it will injure the exerciser. Research has explored the potential of using wearables to monitor fitness training, but the consideration of proper/improper form is not included. In this paper, we propose WearCoach, a wearable based fitness training assistant, which acquires the user’s fitness form information and generates real-time feedback during training. WearCoach differs from previous work of training assistant in 1) it employs a two-phase tracking algorithm to achieve accurate and real-time tracking of body motion, 2) it analyzes the captured arm posture and generates training guidance based on the user’s form, 3) it uses joint orientation as an exercise classification feature to improve recognition accuracy. We conducted experiments with eight participants and nine exercises. Three kinds of feedback are generated, including injury alert, movement correction and symmetry analysis.","PeriodicalId":105795,"journal":{"name":"2020 IEEE 17th International Conference on Mobile Ad Hoc and Sensor Systems (MASS)","volume":"12 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":"115424322","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: 6

Enabling Secure RESTful Web Services in IoT using OpenStack 通过OpenStack实现物联网安全RESTful Web服务

2020 IEEE 17th International Conference on Mobile Ad Hoc and Sensor Systems (MASS) Pub Date : 2020-12-01 DOI: 10.1109/MASS50613.2020.00057

Zakaria Benomar, F. Longo, Giovanni Merlino, A. Puliafito

{"title":"Enabling Secure RESTful Web Services in IoT using OpenStack","authors":"Zakaria Benomar, F. Longo, Giovanni Merlino, A. Puliafito","doi":"10.1109/MASS50613.2020.00057","DOIUrl":"https://doi.org/10.1109/MASS50613.2020.00057","url":null,"abstract":"Thanks to the impact of the advancement in the hardware field, the network size and usage scope of the Internet are continuously growing. Indeed, new smart devices, e.g., sensors, actuators, home appliances are becoming strong enough to communicate and exchange data over the Internet. Accordingly, this distributed ecosystem with sensing/actuation capabilities is introducing new market opportunities with innovative services including, e.g., environmental monitoring, traffic monitoring, homes/buildings control. To conceive new IoT services, enabling the smart devices to join the Internet and expose their capabilities/data through the Web is fundamental. For this purpose, Web Application Programming Interfaces (APIs) or what we refer to also as RESTful Web Services is a paradigm that can enhance the IoT application scope by making smart things part of the Web. In this paper, based on our Stack4Things (S4T) Cloud middleware, we introduce a new approach for exposing services running on IoT devices to the Web so that they become reachable using globally resolvable Uniform Resource Locators (URLs). We emphasized security issues as well by implementing, on the devices, an automated mechanism capable of managing X.509 certificates issuance to enable secure communications using Hypertext Transfer Protocol Secure (HTTPS).","PeriodicalId":105795,"journal":{"name":"2020 IEEE 17th International Conference on Mobile Ad Hoc and Sensor Systems (MASS)","volume":"91 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":"126177401","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