2019 15th International Conference on Mobile Ad-Hoc and Sensor Networks (MSN)最新文献_第2页

ACAC: An Airtime-Aware Centralized Association Control System in 802.11ac WLANs 802.11ac无线局域网中的无线时间感知集中关联控制系统

2019 15th International Conference on Mobile Ad-Hoc and Sensor Networks (MSN) Pub Date : 2019-12-01 DOI: 10.1109/MSN48538.2019.00063

J. Yao, Wenjia Wu, Ming Yang, Junzhou Luo

{"title":"ACAC: An Airtime-Aware Centralized Association Control System in 802.11ac WLANs","authors":"J. Yao, Wenjia Wu, Ming Yang, Junzhou Luo","doi":"10.1109/MSN48538.2019.00063","DOIUrl":"https://doi.org/10.1109/MSN48538.2019.00063","url":null,"abstract":"In recent years, 802.11ac wireless local area networks (WLANs) have been popular in campus and enterprise environments, and a large number of access points (APs) are densely deployed to meet the rapidly increasing clients' demand. In such networks, it is challenging to promote the performance of AP-client association since numerous clients need to find their respective optimal APs under the conditions of multiple capability-limited APs and a small number of available channels. Thus, the conventional association mechanism that only utilizes local information on the client side, such as received signal strength indicator (RSSI), may lead to poor network performance. In this context, we propose and implement an airtime-aware centralized association control system that deals with client requests in a centralized manner and makes AP-client association decisions according to the global information, that is, AP airtime utilization and client requests' RSSI. In particular, we design an AP airtime measurement method to obtain AP airtime utilization from the ath10k driver, and present an airtime-aware AP selection algorithm to implement AP selection policy. Furthermore, we develop an experimental testbed, and conduct the experiments to evaluate the performance of our system. The results demonstrate that our system can significantly improve network throughput and effectively guarantee clients' fairness.","PeriodicalId":368318,"journal":{"name":"2019 15th International Conference on Mobile Ad-Hoc and Sensor Networks (MSN)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124510702","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

WiEnhance: Towards Data Augmentation in Human Activity Recognition Using WiFi Signal WiEnhance:利用WiFi信号实现人体活动识别中的数据增强

2019 15th International Conference on Mobile Ad-Hoc and Sensor Networks (MSN) Pub Date : 2019-12-01 DOI: 10.1109/MSN48538.2019.00065

Jin Zhang, Fuxiang Wu, Wen Hu, Qieshi Zhang, Weitao Xu, Jun Cheng

{"title":"WiEnhance: Towards Data Augmentation in Human Activity Recognition Using WiFi Signal","authors":"Jin Zhang, Fuxiang Wu, Wen Hu, Qieshi Zhang, Weitao Xu, Jun Cheng","doi":"10.1109/MSN48538.2019.00065","DOIUrl":"https://doi.org/10.1109/MSN48538.2019.00065","url":null,"abstract":"Recent research have devoted significant efforts on the utilization of WiFi signals to recognize various human activities. An individual's limb motions in the WiFi spectrum could interfere wireless signal propagation which manifested as unique patterns for activities recognition. Existing approaches though yielding reasonable performance in certain cases, are ignorant of a major challenge. The performed activities of the individual normally have inconsistent speed in different situations and time. Besides that the wireless signal reflected by human bodies normally carry substantial information that is specific to that subject. The activity recognition model trained on a certain individual may not work well when being applied to predict another individual's activities. To address this challenge, we propose WiEnhance, a WiFi based activity recognition system that synthesize variant activities data and mitigate the impact of activity inconsistency and subject-specific issues. We conduct extensive experiments and show an average 15.6% performance improvement on activity recognition.","PeriodicalId":368318,"journal":{"name":"2019 15th International Conference on Mobile Ad-Hoc and Sensor Networks (MSN)","volume":"113 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117288957","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: 13

A Cooperative Indoor Localization Enhancement Framework on Edge Computing Platforms for Safety-Critical Applications 面向安全关键应用的边缘计算平台协同室内定位增强框架

2019 15th International Conference on Mobile Ad-Hoc and Sensor Networks (MSN) Pub Date : 2019-12-01 DOI: 10.1109/MSN48538.2019.00077

Chun Wang, Juan Luo, Qian He

{"title":"A Cooperative Indoor Localization Enhancement Framework on Edge Computing Platforms for Safety-Critical Applications","authors":"Chun Wang, Juan Luo, Qian He","doi":"10.1109/MSN48538.2019.00077","DOIUrl":"https://doi.org/10.1109/MSN48538.2019.00077","url":null,"abstract":"With the maturity and popularity of the Internet of Things (IoT), wireless communication techniques have been vastly applied in daily lives. However, indoor localization has been remained as a challenge due to the insufficient accuracy. In this paper, a cooperative localization method called \"Reliable And Cooperative Indoor Localization (RACIL)\" framework is proposed to determine a target location under the coverage of multiple WSN schemes like WiFi, Blutooth/BLE, Zigbee, and so on. The calculated \"intermediate result\" of target location from each WSN scheme are further evaluated by a confidence degree mechanism on the edge computing platforms for a \"weighted center\" as the final target location. In such a way, both the accuracy and reliability of localization are improved. In order to evaluate the proposed RACIL framework, Matlab simulation and a real tunnel environment emulating coal mining scenario are set up separately for the analysis of location accuracy and capability. The experimental results show that RACIL improves not only the location accuracy but also the location rate in the coverage area with the presence of unreliable anchor nodes in the network.","PeriodicalId":368318,"journal":{"name":"2019 15th International Conference on Mobile Ad-Hoc and Sensor Networks (MSN)","volume":"536 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120878376","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

RF-Recorder: A Contactless Music Play Recording System Using COTS RFID 射频记录器:使用COTS射频识别的非接触式音乐播放记录系统

2019 15th International Conference on Mobile Ad-Hoc and Sensor Networks (MSN) Pub Date : 2019-12-01 DOI: 10.1109/MSN48538.2019.00021

Yuanhao Feng, Panlong Yang, Ziyang Chen, Gang Huang, Yubo Yan, Xiangyang Li

引用次数: 1

POI Recommendation Based on First-Order Collaborative Filtering Tree 基于一阶协同过滤树的POI推荐

2019 15th International Conference on Mobile Ad-Hoc and Sensor Networks (MSN) Pub Date : 2019-12-01 DOI: 10.1109/MSN48538.2019.00058

Jinghua Zhu, Shengchao Ma, Jinbao Li

{"title":"POI Recommendation Based on First-Order Collaborative Filtering Tree","authors":"Jinghua Zhu, Shengchao Ma, Jinbao Li","doi":"10.1109/MSN48538.2019.00058","DOIUrl":"https://doi.org/10.1109/MSN48538.2019.00058","url":null,"abstract":"Point-Of-Interest (POI) recommendation plays an important role in Location-Based Social Networks(LBSN), which is widely used in popular attraction recommendations and travel route planning applications. The traditional recommendation algorithms fail to make full use of social relationships, user check-in distribution features and geographic information because they only use a simple linear function to model the above features. In order to solve the existing problems, we propose a recommendation framework-NCFT(Neural Collaborative Filtering Tree), which can fuse various side information. In the NCFT model, we propose an unsupervised user check-in distribution feature extractor, namely CD-Ex, which unsupervised learning user checkin distribution features. We also propose to build a user-based collaborative filtering tree and item-based collaborative filtering tree, and use the idea of messaging to learn deep representations of users and items. In these two modules, we use multi-head attention and vanilla attention to learn the representations of users and POIs. As for the user social relationship, we use the user's friends in the user-based collaborative tree to assign weights and aggregate his friends' features. The experimental results show that our model has a significant improvement in AUC and F1 compared to other models.","PeriodicalId":368318,"journal":{"name":"2019 15th International Conference on Mobile Ad-Hoc and Sensor Networks (MSN)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127171732","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

ECAISS 2019 Organizing Committee ECAISS 2019组委会

2019 15th International Conference on Mobile Ad-Hoc and Sensor Networks (MSN) Pub Date : 2019-12-01 DOI: 10.1109/msn48538.2019.00014

Ecaiss, Tian Wang, Haipeng Dai, Weiping Zhu, Xiaoyu Wang

引用次数: 0

[Title page i] [标题页i]

2019 15th International Conference on Mobile Ad-Hoc and Sensor Networks (MSN) Pub Date : 2019-12-01 DOI: 10.1109/msn48538.2019.00001

引用次数: 0

Message from the AI2OT 2019 Workshop Chairs 2019年AI2OT研讨会主席致辞

2019 15th International Conference on Mobile Ad-Hoc and Sensor Networks (MSN) Pub Date : 2019-12-01 DOI: 10.1109/msn48538.2019.00010

引用次数: 0

Themis: A Novel Detection Approach for Detecting Mixed Algorithmically Generated Domains Themis:一种检测混合算法生成域的新方法

2019 15th International Conference on Mobile Ad-Hoc and Sensor Networks (MSN) Pub Date : 2019-12-01 DOI: 10.1109/MSN48538.2019.00057

Chao Zheng, Qian Qiang, Tianning Zang, Wen-Han Chao, Yuan Zhou

引用次数: 1

Message from the MSN 2019 Chairs 来自MSN 2019主席的消息

2019 15th International Conference on Mobile Ad-Hoc and Sensor Networks (MSN) Pub Date : 2019-12-01 DOI: 10.1109/msn48538.2019.00005

引用次数: 0