J. Ubiquitous Syst. Pervasive Networks最新文献_第2页

Context-based Reasoning through Fuzzy Logic for Edge Intelligence 基于模糊逻辑的边缘智能上下文推理

J. Ubiquitous Syst. Pervasive Networks Pub Date : 2021-03-01 DOI: 10.5383/JUSPN.15.01.003

Ramin Firouzi, R. Rahmani, T. Kanter

{"title":"Context-based Reasoning through Fuzzy Logic for Edge Intelligence","authors":"Ramin Firouzi, R. Rahmani, T. Kanter","doi":"10.5383/JUSPN.15.01.003","DOIUrl":"https://doi.org/10.5383/JUSPN.15.01.003","url":null,"abstract":"With the advent of edge computing, the Internet of Things (IoT) environment has the ability to process data locally. The complexity of the context reasoning process can be scattered across several edge nodes that are physically placed at the source of the qualitative information by moving the processing and knowledge inference to the edge of the IoT network. This facilitates the real-time processing of a large range of rich data sources that would be less complex and expensive compare to the traditional centralized cloud system. In this paper, we propose a novel approach to provide low-level intelligence for IoT applications through an IoT edge controller that is leveraging the Fuzzy Logic Controller along with edge computing. This low-level intelligence, together with cloud-based intelligence, forms the distributed IoT intelligence. The proposed controller allows distributed IoT gateway to manage input uncertainties; besides, by interacting with its environment, the learning system can enhance its performance over time, which leads to improving the reliability of the IoT gateway. Therefore, such a controller is able to offer different context-aware reasoning to alleviate the distributed IoT. A simulated smart home scenario has been done to prove the plausibility of the low-level intelligence concerning reducing latency and more accurate prediction through learning experiences at the edge.","PeriodicalId":376249,"journal":{"name":"J. Ubiquitous Syst. Pervasive Networks","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131907865","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

An Enhanced Deep Learning Model to Network Attack Detection, by using Parameter Tuning, Hidden Markov Model and Neural Network 基于参数调优、隐马尔可夫模型和神经网络的网络攻击检测增强深度学习模型

J. Ubiquitous Syst. Pervasive Networks Pub Date : 2021-03-01 DOI: 10.5383/JUSPN.15.01.005

Choukri Djellali, Mehdi Adda

引用次数: 1

Towards Landslides Early Warning System With Fog - Edge Computing And Artificial Intelligence* 基于雾边缘计算和人工智能的滑坡预警系统研究*

J. Ubiquitous Syst. Pervasive Networks Pub Date : 2021-03-01 DOI: 10.5383/JUSPN.15.02.002

Olivier Debauche, M. Elmoulat, S. Mahmoudi, S. Mahmoudi, Adriano Guttadauria, P. Manneback, F. Lebeau

{"title":"Towards Landslides Early Warning System With Fog - Edge Computing And Artificial Intelligence*","authors":"Olivier Debauche, M. Elmoulat, S. Mahmoudi, S. Mahmoudi, Adriano Guttadauria, P. Manneback, F. Lebeau","doi":"10.5383/JUSPN.15.02.002","DOIUrl":"https://doi.org/10.5383/JUSPN.15.02.002","url":null,"abstract":"Landslides are phenomena that cause significant human and economic losses. Researchers have investigated the prediction of high landslides susceptibility with various methodologies based upon statistical and mathematical models, in addition to artificial intelligence tools. These methodologies allow to determine the areas that could present a serious risk of landslides. Monitoring these risky areas is particularly important for developing an Early Warning Systems (EWS). As matter of fact, the variety of landslides’ types make their monitoring a sophisticated task to accomplish. Indeed, each landslide area has its own specificities and potential triggering factors; therefore, there is no single device that can monitor all types of landslides. Consequently, Wireless Sensor Networks (WSN) combined with Internet of Things (IoT) allow to set up large-scale data acquisition systems. In addition, recent advances in Artificial Intelligence (AI) and Federated Learning (FL) allow to develop performant algorithms to analyze this data and predict early landslides events at edge level (on gateways). These algorithms are trained in this case at fog level on specific hardware. The novelty of the work proposed in this paper is the integration of Federated Learning based on Fog-Edge approaches to continuously improve prediction models.","PeriodicalId":376249,"journal":{"name":"J. Ubiquitous Syst. Pervasive Networks","volume":"135 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116882343","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: 3

Emerging Technologies and Applications for Smart Cities 智慧城市的新兴技术与应用

J. Ubiquitous Syst. Pervasive Networks Pub Date : 2021-03-01 DOI: 10.5383/JUSPN.15.02.003

Vishva Patel, Devansh Shah, Nishant Doshi

引用次数: 4

VLC-based Data Transfer and Energy Harvesting Mobile System 基于vlc的数据传输和能量收集移动系统

J. Ubiquitous Syst. Pervasive Networks Pub Date : 2021-03-01 DOI: 10.5383/JUSPN.15.01.001

Yingying Chen, Bo Liu, Hongbo Liu, Yudong Yao

{"title":"VLC-based Data Transfer and Energy Harvesting Mobile System","authors":"Yingying Chen, Bo Liu, Hongbo Liu, Yudong Yao","doi":"10.5383/JUSPN.15.01.001","DOIUrl":"https://doi.org/10.5383/JUSPN.15.01.001","url":null,"abstract":"This paper explores a low-cost portable visible light communication (VLC) system to support the increasing needs of lightweight mobile applications. VLC grows rapidly in the past decade for many applications (e.g., indoor data transmission, human sensing, and visual MIMO) due to its RF interference immunity and inherent high security. However, most existing VLC systems heavily rely on fixed infrastructures with less adaptability to emerging lightweight mobile applications. This work proposes Light Storage, a portable VLC system takes the advantage of commercial smartphone flashlights as the transmitter and a solar panel equipped with both data reception and energy harvesting modules as the receiver. Light Storage can achieve concurrent data transmission and energy harvesting from the visible light signals. It develops multi-level light intensity data modulation to increase data throughput and integrates the noise reduction functionality to allow portability under various lighting conditions. The system supports synchronization together with adaptive error correction to overcome both the linear and non-linear signal offsets caused by the low time-control ability from the commercial smartphones. Finally, the energy harvesting capability in Light Storage provides sufficient energy support for efficient short range communication. Light Storage is validated in both indoor and outdoor environments and can achieve over 98% data decoding accuracy, demonstrating the potential as an important alternative to support low-cost and portable short range communication.","PeriodicalId":376249,"journal":{"name":"J. Ubiquitous Syst. Pervasive Networks","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125133893","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

Contribution to Multi-Energy Flow Management for Building Energy Hub 对建筑能源枢纽多能流管理的贡献

J. Ubiquitous Syst. Pervasive Networks Pub Date : 2021-03-01 DOI: 10.5383/JUSPN.15.01.004

M. E. Khaili, Redouane Marhoum, Chaimaa Fouhad, H. Ouajji

引用次数: 0

Towards smart manufacturing: Implementation and benefits 迈向智能制造:实施与效益

J. Ubiquitous Syst. Pervasive Networks Pub Date : 2021-03-01 DOI: 10.5383/JUSPN.15.02.004

Karim Haricha, Azeddine Khiat, Y. Issaoui, Ayoub Bahnasse, H. Ouajji

引用次数: 7

IOT Analysis and Management System for Improving Work Performance with an IOT Open Software in Smart Buildings 基于物联网开放软件的智能建筑物联网分析与管理系统

J. Ubiquitous Syst. Pervasive Networks Pub Date : 2021-01-01 DOI: 10.5383/juspn.14.01.001

S. Traboulsi, S. Knauth

引用次数: 2

QoS-Aware Placement of Tasks on a Fog Cluster in an Edge Computing Environment 边缘计算环境下雾集群中qos感知的任务放置

J. Ubiquitous Syst. Pervasive Networks Pub Date : 2020-10-01 DOI: 10.5383/juspn.13.01.002

E. Badidi

{"title":"QoS-Aware Placement of Tasks on a Fog Cluster in an Edge Computing Environment","authors":"E. Badidi","doi":"10.5383/juspn.13.01.002","DOIUrl":"https://doi.org/10.5383/juspn.13.01.002","url":null,"abstract":"The advances made in the sensing and communications technologies over the last few years have made the deployment of IoT solutions possible on a massive scale. The wide deployment of IoT sensors and devices has resulted in the development of smart services that were not possible before. These services typically rely on cloud services for processing IoT data streams, given that edge devices have limited computing and storage capabilities. However, time-sensitive IoT applications and services do not tolerate the high latency they can encounter when sending IoT data streams to the cloud. Fog computing-based solutions for these services are increasingly becoming attractive because of the low latency they can guarantee. With increasing deployments of fog nodes and fog clusters, we propose an architecture for the placement of IoT applications tasks on a cluster of fog nodes in the vicinity of the application’s data sources. The Fog Broker component can implement various scheduling policies to help IoT applications meet their quality-of-service (QoS) requirements. Our simulations show that it is possible to maintain low application latency and distribute the load between the fog nodes of the cluster by using simple scheduling strategies.","PeriodicalId":376249,"journal":{"name":"J. Ubiquitous Syst. Pervasive Networks","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133942032","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: 11

Student orientation using machine learning under MapReduce with Hadoop 面向学生，在MapReduce和Hadoop下使用机器学习

J. Ubiquitous Syst. Pervasive Networks Pub Date : 2020-10-01 DOI: 10.5383/juspn.13.01.003

Farouk Ouatik, M. Erritali, M. Jourhmane

引用次数: 7