2020 5th International Conference on Cloud Computing and Artificial Intelligence: Technologies and Applications (CloudTech)最新文献_第2页

Autonomous Provisioning of Preemptive Instances in Google Cloud for Maximum Performance Per Dollar 在Google Cloud中自主配置先发制人的实例，以实现每美元的最大性能

2020 5th International Conference on Cloud Computing and Artificial Intelligence: Technologies and Applications (CloudTech) Pub Date : 2020-11-24 DOI: 10.1109/CloudTech49835.2020.9365879

H. Haugerud, J. Svensson, A. Yazidi

{"title":"Autonomous Provisioning of Preemptive Instances in Google Cloud for Maximum Performance Per Dollar","authors":"H. Haugerud, J. Svensson, A. Yazidi","doi":"10.1109/CloudTech49835.2020.9365879","DOIUrl":"https://doi.org/10.1109/CloudTech49835.2020.9365879","url":null,"abstract":"Cloud computing and its popularity has boomed over the last decade, enabling anyone to rent computing power on demand. Cloud providers such as Amazon and Google rent out surplus computing power for a discounted price according to demand in their data centers, but with the trade off that it is revocable and can only be rented for a short amount of time.This paper investigates the use of surplus computing power in order to reduce the cost of batch computing. We rely on a simple economical principle, the most cost-efficient Virtual Machine (VM) in a public cloud is the one that offers the highest performance per dollar. Therefore by rescheduling the workloads to the most cost-efficient location in terms of performance per dollar our solution dynamically provisions preemptible VMs in Google Cloud while continuously monitoring the performance per dollar of all available resources in every region. The algorithm automatically relocates workloads to a less expensive location if any appears and handles revoked access of the resources. Our algorithm views the cost reduction problem as a linear optimization problem with constraints and solves it using a greedy procedure. In the experiment we spawn Docker containers to mine cryptocurrency. The experimental results show that 67% of the cost is saved compared to renting on-demand VMs. The system can readily be extended to containers processing similar types of workloads and more generally to applications where the performance per dollar is easy to measure.","PeriodicalId":272860,"journal":{"name":"2020 5th International Conference on Cloud Computing and Artificial Intelligence: Technologies and Applications (CloudTech)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122148921","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

CloudTech 2020 Authors Index CloudTech 2020作者索引

2020 5th International Conference on Cloud Computing and Artificial Intelligence: Technologies and Applications (CloudTech) Pub Date : 2020-11-24 DOI: 10.1109/cloudtech49835.2020.9365882

引用次数: 0

Deep Learning and Approach for Tracking People’s Movements in a Video 视频中人物运动的深度学习与跟踪方法

2020 5th International Conference on Cloud Computing and Artificial Intelligence: Technologies and Applications (CloudTech) Pub Date : 2020-11-24 DOI: 10.1109/CloudTech49835.2020.9365886

Jemai Bornia, A. Frihida, Olivier Debauche, S. Mahmoudi, P. Manneback

引用次数: 0

Business Process Modeling Notation Extension for Real Time Handling - Application to Novel Coronavirus (2019-nCoV) management process 实时处理的业务流程建模符号扩展-应用于新型冠状病毒(2019-nCoV)管理流程

2020 5th International Conference on Cloud Computing and Artificial Intelligence: Technologies and Applications (CloudTech) Pub Date : 2020-11-24 DOI: 10.1109/CloudTech49835.2020.9365900

A. Ouarhim, Jihane Lakhrouit, Karim Baïna

引用次数: 1

Block Sizes Control For an Efficient Real Time Record Linkage 块大小控制为一个有效的实时记录链接

2020 5th International Conference on Cloud Computing and Artificial Intelligence: Technologies and Applications (CloudTech) Pub Date : 2020-11-24 DOI: 10.1109/CloudTech49835.2020.9365866

Hamid Naceur Benkhaled, Djamel Berrabah, F. Boufarès

引用次数: 0

A Model Of A Biometric Recognition System Based On The Hough Transform Of Libor Masek and 1-D Log-Gabor Filter 基于Libor mask的Hough变换和一维Log-Gabor滤波器的生物特征识别系统模型

2020 5th International Conference on Cloud Computing and Artificial Intelligence: Technologies and Applications (CloudTech) Pub Date : 2020-11-24 DOI: 10.1109/CloudTech49835.2020.9365917

Hammou Djalal Rafik, S. Mahmoudi, A. Reda, Mechab Boubaker

{"title":"A Model Of A Biometric Recognition System Based On The Hough Transform Of Libor Masek and 1-D Log-Gabor Filter","authors":"Hammou Djalal Rafik, S. Mahmoudi, A. Reda, Mechab Boubaker","doi":"10.1109/CloudTech49835.2020.9365917","DOIUrl":"https://doi.org/10.1109/CloudTech49835.2020.9365917","url":null,"abstract":"Biometric iris recognition is a very advanced technology for the data protection and identification of individuals. This technology is widely used by multi-national society in terms of data protection and security. A biometric iris recognition system requires an adapted architecture and specific because it generally recommends 5 steps. The acquisition step consists of getting a good quality iris image by digital cameras of high resolution. The segmentation can use an algorithm and mathematical methods such as John Daugman’s Interro Differential Operator [3] or Richard Paul Wildes’s Hough Transform [4]. The normalization phase projects to transform the relevant information from the circular iris image into the rectangular shape. The feature extraction step requires the use of specific filters (1-D Log-Gabor). The end step is the matching that allows us to compare the descriptor of the user with that of the database to determine if the person is authentic or not and this is done using Hamming Distance. The objective of this article is the use of our approach to improving results. The experiments were tested on the Casia V1 [16], MMU1 [17] iris biometric database, which gave very good and encouraging results. We found an accuracy rate of 99.9263 % for Casia V1 and 99.4168 % for MMU1.","PeriodicalId":272860,"journal":{"name":"2020 5th International Conference on Cloud Computing and Artificial Intelligence: Technologies and Applications (CloudTech)","volume":"138 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121330558","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

[CloudTech 2020 Front cover] 【CloudTech 2020年封面】

2020 5th International Conference on Cloud Computing and Artificial Intelligence: Technologies and Applications (CloudTech) Pub Date : 2020-11-24 DOI: 10.1109/cloudtech49835.2020.9365880

引用次数: 0

Evaluation of NDVI and NDWI parameters in CPU-GPU Heterogeneous Platforms based CUDA 基于CUDA的CPU-GPU异构平台NDVI和NDWI参数评估

2020 5th International Conference on Cloud Computing and Artificial Intelligence: Technologies and Applications (CloudTech) Pub Date : 2020-11-24 DOI: 10.1109/CloudTech49835.2020.9365888

Fatima Zahra Guerrouj, R. Latif, A. Saddik

{"title":"Evaluation of NDVI and NDWI parameters in CPU-GPU Heterogeneous Platforms based CUDA","authors":"Fatima Zahra Guerrouj, R. Latif, A. Saddik","doi":"10.1109/CloudTech49835.2020.9365888","DOIUrl":"https://doi.org/10.1109/CloudTech49835.2020.9365888","url":null,"abstract":"Artificial intelligence is a field in full development, from facial recognition to autonomous vehicles and referral systems for online shopping, passing by smart farming, these new technologies are invading our daily lives.Nowadays, agricultural applications require more and more computer vision technologies for continuous monitoring and analysis of crop health and yield. That is why machine learning has become one of the mechanisms that make farming more efficient by using high-precision algorithms. This article deals with the Normalized Difference Vegetation Index (NDVI) and the Normalized Difference Water Index (NDWI), which are the most widely used indices in precision agriculture. In this work, we adopt GPU-based heterogeneous architecture using parallel programming with the CUDA language. The algorithm is evaluated on several platforms: NVIDIA Jetson TX1, DELL-desktop, and XU4 board. It has been discovered that the execution time of the two NDVI and NDWI indices on the embedded TX1 card is more optimized and improved compared to the execution time on the XU4 card and the Desktop.","PeriodicalId":272860,"journal":{"name":"2020 5th International Conference on Cloud Computing and Artificial Intelligence: Technologies and Applications (CloudTech)","volume":"87 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116010186","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

Big Data Storage and Analysis for Smart Farming 智慧农业大数据存储与分析

2020 5th International Conference on Cloud Computing and Artificial Intelligence: Technologies and Applications (CloudTech) Pub Date : 2020-11-24 DOI: 10.1109/CloudTech49835.2020.9365869

Fabrice Nolack Fote, Saïd Mahmoudi, Amine Roukh, S. Mahmoudi

引用次数: 13

Bloom filter and its variants for the optimization of MapReduce’s algorithms: A review 用于优化MapReduce算法的Bloom过滤器及其变体:综述

2020 5th International Conference on Cloud Computing and Artificial Intelligence: Technologies and Applications (CloudTech) Pub Date : 2020-11-24 DOI: 10.1109/CloudTech49835.2020.9365876

F. Ezzaki, N. Abghour, A. Elomri, K. Moussaid, M. Rida

{"title":"Bloom filter and its variants for the optimization of MapReduce’s algorithms: A review","authors":"F. Ezzaki, N. Abghour, A. Elomri, K. Moussaid, M. Rida","doi":"10.1109/CloudTech49835.2020.9365876","DOIUrl":"https://doi.org/10.1109/CloudTech49835.2020.9365876","url":null,"abstract":"The bloom filter is a probabilistic data model used to test the existence of an element in a set, i.e., for any given item, the bloom filter could test the membership query on this candidate. The bloom filter has many advantages due to its simplicity and efficiency in highly solving the issue of data representation in many fields and to support membership queries, it has been known as space and time-efficient randomized data structure, by filtering out redundant data and optimizing the memory consumption. However, bloom filters are limited to membership tests and don’t support the deletion of elements. They also generate the false positive probability as they are based on a probabilistic model, this error rate is generated when an element that doesn’t belong to a set is considered as a member of this set by the bloom filter. Our goal is to compare a number of well- existed algorithms related to the boom filter for future work on the optimization of the join’s algorithms in MapReduce. This paper provides an overview of the different variants of the bloom filter and analyses the studies that have been interested in this area of research.","PeriodicalId":272860,"journal":{"name":"2020 5th International Conference on Cloud Computing and Artificial Intelligence: Technologies and Applications (CloudTech)","volume":"93 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122065462","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