2022 Seventh International Conference on Fog and Mobile Edge Computing (FMEC)最新文献

Benchmarking Container Technologies For IoT Environments 物联网环境容器技术的基准测试

2022 Seventh International Conference on Fog and Mobile Edge Computing (FMEC) Pub Date : 2022-12-12 DOI: 10.1109/FMEC57183.2022.10062773

Yinluo Jing, Zhiyi Qiao, R. Sinnott

引用次数: 2

Optimizing Heterogeneous Task Allocation for Edge Compute Micro Clusters Using PSO Metaheuristic 基于粒子群优化的边缘计算微集群异构任务分配

2022 Seventh International Conference on Fog and Mobile Edge Computing (FMEC) Pub Date : 2022-12-12 DOI: 10.1109/FMEC57183.2022.10062755

Yousef Alhaizaey, Jeremy Singer, A. L. Michala

{"title":"Optimizing Heterogeneous Task Allocation for Edge Compute Micro Clusters Using PSO Metaheuristic","authors":"Yousef Alhaizaey, Jeremy Singer, A. L. Michala","doi":"10.1109/FMEC57183.2022.10062755","DOIUrl":"https://doi.org/10.1109/FMEC57183.2022.10062755","url":null,"abstract":"Optimised task allocation is essential for efficient and effective edge computing; however, task allocation differs in edge systems compared to the powerful centralised cloud data centres, given the limited resource capacities in edge and the strict QoS requirements of many innovative Internet of Things (IoT) applications. This paper aims to optimise heterogeneous task allocation specifically for edge micro-cluster platforms. We extend our previous work on optimising task allocation for micro-clusters by presenting a linear-based model and propose a metaheuristic Particle Swarm Optimisation (PSO) technique to minimise the makespan time and the allocation overhead time of heterogeneous workloads in batch execution. We present a comparative performance evaluation of metaheuristic PSO, mixed-integer programming (MIP) and randomised allocation based on the computation overhead time and the quality of the solutions. Our results show a crossover implying that mixed-integer programming is efficient for small-scale clusters, whereas PSO scales better and provides near-optimal solutions for larger-scale micro-clusters.","PeriodicalId":129184,"journal":{"name":"2022 Seventh International Conference on Fog and Mobile Edge Computing (FMEC)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130086586","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

Faster and more accurate machine learning techniques with less data 使用更少数据的更快、更准确的机器学习技术

2022 Seventh International Conference on Fog and Mobile Edge Computing (FMEC) Pub Date : 2022-12-12 DOI: 10.1109/fmec57183.2022.10062706

T. Kalganova

引用次数: 0

A review of IoT architectures in smart healthcare applications 智能医疗应用中的物联网架构综述

2022 Seventh International Conference on Fog and Mobile Edge Computing (FMEC) Pub Date : 2022-12-12 DOI: 10.1109/FMEC57183.2022.10062841

Meriem Arbaoui, Mohamed-el-Amine Brahmia, Abdellatif Rahmoun

{"title":"A review of IoT architectures in smart healthcare applications","authors":"Meriem Arbaoui, Mohamed-el-Amine Brahmia, Abdellatif Rahmoun","doi":"10.1109/FMEC57183.2022.10062841","DOIUrl":"https://doi.org/10.1109/FMEC57183.2022.10062841","url":null,"abstract":"The Internet of Things (IoT) is revolutionizing numerous industries, including healthcare services, known as the Internet of Medical Things (IoMT). A large amount of generated data in IoMT applications need to be transmitted, analyzed, and stored. Consequently, the cloud-only architecture was proposed as being the best-fit organizational infrastructure. Indeed, cloud capabilities of processing, networking, and storage are overwhelming properties that make it outperform classical solutions for decades when it comes to healthcare applications. Nevertheless, this architecture could not keep up with the ever-growing amount of biomedical data. One of the main drawbacks of cloud architecture is the large latency, which prevents it from delivering real-time alerts to save the patient's life in critical situations. In this context, edge and fog computing become good alternatives to reduce health data management complexity and latency and therefore increase their reliability. This paper proposes a review of the most recent healthcare applications based on edge and fog computing, respectively. The selected research works of this survey are classified into four categories depending on their use case application. Furthermore, a comparison study helps extract relevant insights from several recent papers in the current literature to highlight their methodologies and purposes. The main concern is to emphasize what features and properties are to be considered most when designing a distributed healthcare system in an edge-fog architecture. Finally, we present some challenges to be addressed in healthcare applications along with the uprising of new technologies.","PeriodicalId":129184,"journal":{"name":"2022 Seventh International Conference on Fog and Mobile Edge Computing (FMEC)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133086246","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

Fine-Tuned Access Control for Internet of Things 物联网精细访问控制

2022 Seventh International Conference on Fog and Mobile Edge Computing (FMEC) Pub Date : 2022-12-12 DOI: 10.1109/FMEC57183.2022.10062612

Luke Jakielaszek, Xuening Xu, Xiaojiang Du, E. Ratazzi

引用次数: 0

Leveraging the Internet of Things Aware Healthcare Monitoring System for Better Living Standards 利用物联网感知医疗监控系统提高生活水平

2022 Seventh International Conference on Fog and Mobile Edge Computing (FMEC) Pub Date : 2022-12-12 DOI: 10.1109/FMEC57183.2022.10062818

N. Mirza, Rawad Bader, Adnan Ali, M. Ishak

{"title":"Leveraging the Internet of Things Aware Healthcare Monitoring System for Better Living Standards","authors":"N. Mirza, Rawad Bader, Adnan Ali, M. Ishak","doi":"10.1109/FMEC57183.2022.10062818","DOIUrl":"https://doi.org/10.1109/FMEC57183.2022.10062818","url":null,"abstract":"Nowadays, even after many advancements in the field of healthcare facilities, one of the leading causes of death is considered to be heart disease. The numbers are soaring with every passing year due to the complexity involved in treating and diagnosing heart diseases. Most forms of heart disease can be prevented, but numbers are constantly increasing due to the inadequate number of preventive techniques. Various scholars have used machine learning and algorithm related to data mining to develop predictive systems for heart diseases. In this paper, a simple yet effective hybrid model is designed to predict early disease detection in a human being and deliver solutions for healthy living. It's unique compared to other proposed methods, as it combines the utilization of the Internet of Things, 5G, and artificial intelligence all at once. IoT and 5G facilitate real-time data collection related to the daily pattern of the subject, and AI is used for the predictive model. Results collected from the tested and trained data are accurate. Therefore, the proposed approach can be implemented to work as an alert system by publishing daily analyses and predictive reports together for early prevention.","PeriodicalId":129184,"journal":{"name":"2022 Seventh International Conference on Fog and Mobile Edge Computing (FMEC)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123303262","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

EdgeFNF: Toward Real-time Fake News Detection on Mobile Edge Computing 基于移动边缘计算的实时假新闻检测

2022 Seventh International Conference on Fog and Mobile Edge Computing (FMEC) Pub Date : 2022-12-12 DOI: 10.1109/FMEC57183.2022.10062503

Sawsan Al-Zubi, Feras M. Awaysheh

{"title":"EdgeFNF: Toward Real-time Fake News Detection on Mobile Edge Computing","authors":"Sawsan Al-Zubi, Feras M. Awaysheh","doi":"10.1109/FMEC57183.2022.10062503","DOIUrl":"https://doi.org/10.1109/FMEC57183.2022.10062503","url":null,"abstract":"Fake news (FN) spreads faster than ever due to social networks' ease of access, increasing reach, and lower cost. Twitter and Facebook are the most used platforms, allowing users to express news in short, simple lines that can be fake using their smartphones. Hence, real-time prediction and fast response time are vital in spotting FN and opposing its negative impact. However, smartphones have limited computational capabilities besides unreliable network connections. Relying on the amalgamation of the edge, fog, and cloud computing can relieve the previous bottleneck where computation offloads from edge devices to higher network layers on demand. In this paper, we proposed EdgeFNF, an edge fake news finder approach toward a fully Edge-to-Cloud mobile architecture. EdgeFNF collects data from social media platforms, e.g., tweets and posts, preprocess them on the mobile edge node, and uploads the metadata into a cloud server where multiple data processing techniques for text, such as Natural Language Processing (NLP), take place. Henceforth, detect fake news using NLTK and BERT algorithms. We provide the methodology, system architecture, and merits for achieving real-time, accurate detection of fake news.","PeriodicalId":129184,"journal":{"name":"2022 Seventh International Conference on Fog and Mobile Edge Computing (FMEC)","volume":"106 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115608843","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

DDOS attacks detection based on attention-deep learning and local outlier factor 基于注意力深度学习和局部离群因子的DDOS攻击检测

2022 Seventh International Conference on Fog and Mobile Edge Computing (FMEC) Pub Date : 2022-12-12 DOI: 10.1109/FMEC57183.2022.10062705

Abdelkader Dairi, Belkacem Khaldi, F. Harrou, Ying Sun

引用次数: 0

Proposal of a Context-aware Task Scheduling Algorithm for the Fog Paradigm 基于上下文感知的雾范式任务调度算法的研究

2022 Seventh International Conference on Fog and Mobile Edge Computing (FMEC) Pub Date : 2022-12-12 DOI: 10.1109/FMEC57183.2022.10062802

Celestino Barros, Vítor Rocio, André Sousa, Hugo Paredes, Olavo Teixeira

{"title":"Proposal of a Context-aware Task Scheduling Algorithm for the Fog Paradigm","authors":"Celestino Barros, Vítor Rocio, André Sousa, Hugo Paredes, Olavo Teixeira","doi":"10.1109/FMEC57183.2022.10062802","DOIUrl":"https://doi.org/10.1109/FMEC57183.2022.10062802","url":null,"abstract":"Application execution requests in cloud architecture and fog paradigm are generally heterogeneous in terms of contexts at the device and application level. The scheduling of requests in these architectures is an optimization problem with multiple constraints. Despite numerous efforts, task scheduling in these architectures and paradigms still presents some enticing challenges that make us question how tasks are routed between different physical devices, fog, and cloud nodes. The fog is defined as an extension of the cloud, which provides processing, storage, and network services near the edge network, and due to the density and heterogeneity of devices, the scheduling is very complex, and, in the literature, we still find few studies. Trying to bring innovative contributions in these areas, in this paper, we propose a solution to the context-aware task-scheduling problem for fog paradigm. In our proposal, different context parameters are normalized through Min-Max normalization, requisition priorities are defined through the application of the Multiple Linear Regression (MLR) technique and scheduling is performed using Multi-Objective Non-Linear Programming Optimization (MONLIP) technique. The results obtained from simulations in the iFogSim toolkit, show that our proposal performs better compared to the non-context-aware proposals.","PeriodicalId":129184,"journal":{"name":"2022 Seventh International Conference on Fog and Mobile Edge Computing (FMEC)","volume":"191 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114683854","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

Keyword Extraction for Fine-Grained IoT Device Identification 细粒度物联网设备识别关键字提取

2022 Seventh International Conference on Fog and Mobile Edge Computing (FMEC) Pub Date : 2022-12-12 DOI: 10.1109/FMEC57183.2022.10062747

Ashley Andrews, G. Oikonomou, Simon Armour, Paul Thomas, T. Cattermole

{"title":"Keyword Extraction for Fine-Grained IoT Device Identification","authors":"Ashley Andrews, G. Oikonomou, Simon Armour, Paul Thomas, T. Cattermole","doi":"10.1109/FMEC57183.2022.10062747","DOIUrl":"https://doi.org/10.1109/FMEC57183.2022.10062747","url":null,"abstract":"Internet of Things (IoT) devices are becoming more widespread in networks and are shown to have security considerations as an afterthought. Identifying IoT devices can help users locate security vulnerabilities in their networks. Previous studies have used machine learning and rule-based methods to try and identify unknown devices from passive network traffic. The first issue with these approaches however is that the device must have been seen on a training dataset beforehand; otherwise it cannot be identified. The second issue is that trying to achieve granularity on device identification down to firmware level from passive network traffic has not been researched before, and is a key factor in identifying vulnerable devices. This paper contains a novel technique to solve those two problems. The technique automatically identifies unknown devices from passive network traffic without using a machine learning approach that finds and weights keywords found in each packet per device. These keywords then allow device identification down to a specific firmware version. The approach in this paper achieved 71% accuracy for identifying firmware versions and 74% and 78% for models and makes respectively, across a test dataset of 44 devices.","PeriodicalId":129184,"journal":{"name":"2022 Seventh International Conference on Fog and Mobile Edge Computing (FMEC)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124863952","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