2022 IEEE International Conference on Cloud Computing Technology and Science (CloudCom)最新文献_第4页

Consideration of a Supercomputing System with Cloud Bursting Functionality from an Operational Perspective 从操作角度考虑具有云爆发功能的超级计算系统

2022 IEEE International Conference on Cloud Computing Technology and Science (CloudCom) Pub Date : 2022-12-01 DOI: 10.1109/CloudCom55334.2022.00031

Arata Endo, Shinji Yoshida, S. Gojuki, Hiroaki Kataoka, Yoshihiko Sato, Akihiro Musa, S. Date

{"title":"Consideration of a Supercomputing System with Cloud Bursting Functionality from an Operational Perspective","authors":"Arata Endo, Shinji Yoshida, S. Gojuki, Hiroaki Kataoka, Yoshihiko Sato, Akihiro Musa, S. Date","doi":"10.1109/CloudCom55334.2022.00031","DOIUrl":"https://doi.org/10.1109/CloudCom55334.2022.00031","url":null,"abstract":"Cloud bursting functionality provides the administrators of on-premise supercomputing systems with an on-demand way of dynamically integrating the computing resources on the cloud into them when the computing demands from the users dramatically increase. In the Cybermedia Center at Osaka University, we have deployed a cloud bursting environment between a supercomputing system named SQUID and Microsoft Azure by respecting the transparency in usage rather than performance. Technically, the transparency allows users to execute their jobs on the cloud computing resources without having to be aware of the cloud in terms of usage. However, how we encourage users of our supercomputing system to use the cloud computing resources is a realistic and important problem to be solved from a practical operational perspective. In this paper, we investigate the cloud bursting environment on SQUID in terms of performance, monetary cost, and transparency on usage. Finally, we discuss how we as the administrators of on-premise supercomputing systems can provide a better way to encourage users to execute their jobs on the cloud computing resource instead of on the on-premise computing resource under our service policy.","PeriodicalId":282963,"journal":{"name":"2022 IEEE International Conference on Cloud Computing Technology and Science (CloudCom)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132439261","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

meQ: Selecting MEC Resources by Considering Service Communication Requirements meQ:通过考虑服务通信需求选择MEC资源

2022 IEEE International Conference on Cloud Computing Technology and Science (CloudCom) Pub Date : 2022-12-01 DOI: 10.1109/CloudCom55334.2022.00020

Matthias Frei, Reinhard German, Anatoli Djanatliev

{"title":"meQ: Selecting MEC Resources by Considering Service Communication Requirements","authors":"Matthias Frei, Reinhard German, Anatoli Djanatliev","doi":"10.1109/CloudCom55334.2022.00020","DOIUrl":"https://doi.org/10.1109/CloudCom55334.2022.00020","url":null,"abstract":"The Multi-Access Edge Computing (MEC) paradigm enables services that have strict network requirements like a maximum tolerable latency or a minimum bandwidth requirement. This consequently leads to a tight coupling of networks and computing, since the service can only function correctly if its communication requirements are met. Numerous existing strategies for MEC service deployment or resource selection put the characteristics of computing demands correlated with the free capacity of nodes or inter-service dependencies in their focus. In contrast, our work is a complementary attempt to enable especially the consideration of the strict communication needs of MEC services. It shows how edge features, i.e., knowledge of edge network conditions and service requirements, can be used to support resource selection and orchestration strategies. We consider and discuss how our model meQ can be applied in real communication systems as well as in heterogeneous networks, where clients may have multiple uplink connections. To enable communication-optimized selection strategies, meQ consists of two major components. A sharable, graph-based network representation and online searches to determine resources. The model benefits from existing work and limits the search space with the use of edge features. A performed simulation study demonstrates the benefits of meQ. The results show that it is possible to significantly reduce the search space, leading to lower search efforts also in large network graphs. An additional system-level simulation proves integration and applicability under realistic conditions.","PeriodicalId":282963,"journal":{"name":"2022 IEEE International Conference on Cloud Computing Technology and Science (CloudCom)","volume":"84 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134029072","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

A Survey on Infrastructure-as-Code Solutions for Cloud Development 云开发的基础设施即代码解决方案调查

2022 IEEE International Conference on Cloud Computing Technology and Science (CloudCom) Pub Date : 2022-12-01 DOI: 10.1109/CloudCom55334.2022.00019

Håkon Teppan, L. Flå, M. Jaatun

引用次数: 1

Performance Analysis of HElib on a Privacy Preserving Search for Genome Information with Fully Homomorphic Encryption HElib算法在全同态基因组信息保密搜索中的性能分析

2022 IEEE International Conference on Cloud Computing Technology and Science (CloudCom) Pub Date : 2022-12-01 DOI: 10.1109/CloudCom55334.2022.00028

Arisa Tsuji, M. Oguchi

{"title":"Performance Analysis of HElib on a Privacy Preserving Search for Genome Information with Fully Homomorphic Encryption","authors":"Arisa Tsuji, M. Oguchi","doi":"10.1109/CloudCom55334.2022.00028","DOIUrl":"https://doi.org/10.1109/CloudCom55334.2022.00028","url":null,"abstract":"Recently, numerous studies have been conducted on the practical implementation of fully homomorphic encryption (FHE) for large data analysis. Many systems using FHE are cloud-based and use many DRAMs because the progression of encryption or bootstrapping increases the time and space complexities. However, DRAMs in the cloud cannot be effectively used because they are shared by several systems and cost us inefficiently. Here, we combine Solid State Drive (SSDs) with DRAMs for an application using FHE. They have several different architectural advantages from DRAMs: they cost less per one bit and have high parallelism. Our primary objective is to utilize SSDs instead of DRAMs and reduce the cost on the cloud when using an application of FHE. This study uses the HElib library and an application for a privacy-preserving search for genome information. First, we identified the bottleneck of this application for using SSDs effectively. We analyzed the features of the application using Hyper-Threading technology and found that it consumes considerable CPU power. It is highly parallel, and the processing of load/store instructions from DRAMs to CPUs in sequential is the bottleneck. Second, we revealed the bottleneck in detail by the function in HElib library. The ”rotate” function is found to be the bottleneck in it. It must be implemented many times because of the FHE algorithm which cannot compare a ciphertext to another one. Finally, the compatibility of this application using the HElib library with SSDs is determined.","PeriodicalId":282963,"journal":{"name":"2022 IEEE International Conference on Cloud Computing Technology and Science (CloudCom)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128977685","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

2SFGL: A Simple And Robust Protocol For Graph-Based Fraud Detection

2022 IEEE International Conference on Cloud Computing Technology and Science (CloudCom) Pub Date : 2022-12-01 DOI: 10.1109/CloudCom55334.2022.00036

Zhirui Pan, Guangzhong Wang, Zhaoning Li, Lifeng Chen, Yang Bian, Zhongyuan Lai

{"title":"2SFGL: A Simple And Robust Protocol For Graph-Based Fraud Detection","authors":"Zhirui Pan, Guangzhong Wang, Zhaoning Li, Lifeng Chen, Yang Bian, Zhongyuan Lai","doi":"10.1109/CloudCom55334.2022.00036","DOIUrl":"https://doi.org/10.1109/CloudCom55334.2022.00036","url":null,"abstract":"Financial crime detection using graph learning improves financial safety and efficiency. However, criminals may commit financial crimes across different institutions to avoid detection, which increases the difficulty of detection for financial institutions which use local data for graph learning. As most financial institutions are subject to strict regulations in regards to data privacy protection, the training data is often isolated and conventional learning technology cannot handle the problem. Federated learning (FL) allows multiple institutions to train a model without revealing their datasets to each other, hence ensuring data privacy protection. In this paper, we proposes a novel two-stage approach to federated graph learning (2SFGL): The first stage of 2SFGL involves the virtual fusion of multiparty graphs, and the second involves model training and inference on the virtual graph. We evaluate our framework on a conventional fraud detection task based on the FraudAmazonDataset and FraudYelpDataset. Experimental results show that integrating and applying a GCN (Graph Convolutional Network) with our 2SFGL framework to the same task results in a 17.6%-30.2% increase in performance on several typical metrics compared to the case only using FedAvg, while integrating GraphSAGE with 2SFGL results in a 6%-16.2% increase in performance compared to the case only using FedAvg. We conclude that our proposed framework is a robust and simple protocol which can be simply integrated to pre-existing graph-based fraud detection methods.","PeriodicalId":282963,"journal":{"name":"2022 IEEE International Conference on Cloud Computing Technology and Science (CloudCom)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130826310","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

Yet Another Blockchain-based Privacy-friendly Social Network 又一个基于区块链的隐私友好型社交网络

2022 IEEE International Conference on Cloud Computing Technology and Science (CloudCom) Pub Date : 2022-12-01 DOI: 10.1109/CloudCom55334.2022.00039

Lars Andreassen Jaatun, Anders Ringen, M. Jaatun

引用次数: 1

On Kubernetes-aided Federated Database Systems 在kubernetes辅助的联邦数据库系统上

2022 IEEE International Conference on Cloud Computing Technology and Science (CloudCom) Pub Date : 2022-11-01 DOI: 10.1109/CloudCom55334.2022.00011

Zheng Li, Nicol'as Sald'ias-Vallejos, Michael A. Rodriguez, A. Rainer

{"title":"On Kubernetes-aided Federated Database Systems","authors":"Zheng Li, Nicol'as Sald'ias-Vallejos, Michael A. Rodriguez, A. Rainer","doi":"10.1109/CloudCom55334.2022.00011","DOIUrl":"https://doi.org/10.1109/CloudCom55334.2022.00011","url":null,"abstract":"Cloud computing has made federated database systems (FDBS) significantly more practical to implement than in the past. As part of a recent Web-based Geographic Information System (WebGIS) project, we are employing cloud-native technologies (from the container ecosystem) to develop a federated database (DB) infrastructure, to help manage and utilise the distributed and various geospatial data. Unfortunately, there seem to be inherent challenges and complexity of applying the container and Kubernetes technologies to building and running DB systems. Considering that most of the geospatial and theme data are pre-obtained and fixed in our WebGIS project, we decided to focus on the read-only user queries and still resort to Kubernetes to implement an FDBS instance to use. Unlike the de facto practices (e.g., using the StatefulSets mechanism, extending Kuberentes APIs, or employing KubeFed), our solution for Kubernetes-aided FDBS simplifies the tech stack by investigating the fractal object of federated data management, inclusively containerising DB instances, and using the lightweight Deployment mechanism to handle stateless DB containers. Overall, this research not only reveals an easy-to-implement approach to constructing read-only components in a fully-fledged FDBS, but also proposes and demonstrates a novel methodology for FDBS investigations.","PeriodicalId":282963,"journal":{"name":"2022 IEEE International Conference on Cloud Computing Technology and Science (CloudCom)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133661842","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