Proceedings of the 14th IEEE/ACM International Conference on Utility and Cloud Computing Companion最新文献_第3页

Knowledge distillation for secondary pulmonary tuberculosis classification ensemble 继发性肺结核分类集成的知识提炼

Proceedings of the 14th IEEE/ACM International Conference on Utility and Cloud Computing Companion Pub Date : 2021-12-06 DOI: 10.1145/3492323.3495570

Qinghua Zhou, Hengde Zhu, Xin Zhang, Yudong Zhang

引用次数: 1

Towards failure correlation for improved cloud application service resilience 改进云应用服务弹性的故障相关性

Proceedings of the 14th IEEE/ACM International Conference on Utility and Cloud Computing Companion Pub Date : 2021-12-06 DOI: 10.1145/3492323.3495586

D. Mathews, Mudit Verma, P. Aggarwal, J. Lakshmi

{"title":"Towards failure correlation for improved cloud application service resilience","authors":"D. Mathews, Mudit Verma, P. Aggarwal, J. Lakshmi","doi":"10.1145/3492323.3495586","DOIUrl":"https://doi.org/10.1145/3492323.3495586","url":null,"abstract":"Autonomously dealing with disruptions is necessary for maintaining the quality of a cloud application service. A fault, error, or failure in any component across the application service stack can potentially disrupt the service delivery. Fault localization and failure prediction are essential techniques in managing service failures. Emerging cloud computing paradigms are pushing application services to be built as loosely coupled distributed components for independent scaling. However, such architectures render existing approaches for fault localization and failure prediction to be limiting. Prevalent works on fault localization and failure prediction focus on a specific cloud service architecture layer or a subset of service components or specific fault types. These approaches restrict the view on the impact of the fault on the application service and obviate more intelligent methods for localizing faults or predicting failures, and thus efficiently dealing with service disruptions in an autonomous way. This paper contemplates the propagation of faults in multi-tiered architectures like clouds and uses a real-world disruption scenario to emphasize the need for correlating the faults across the service layers to acquire insights for end-to-end fault analysis for cloud application services.","PeriodicalId":440884,"journal":{"name":"Proceedings of the 14th IEEE/ACM International Conference on Utility and Cloud Computing Companion","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123922307","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

Run-time adaptation of stream processing spanning the cloud and the edge 跨云和边缘的流处理的运行时适应

Proceedings of the 14th IEEE/ACM International Conference on Utility and Cloud Computing Companion Pub Date : 2021-12-06 DOI: 10.1145/3492323.3495627

Adam Cattermole, Jonathan Dowland, P. Watson

{"title":"Run-time adaptation of stream processing spanning the cloud and the edge","authors":"Adam Cattermole, Jonathan Dowland, P. Watson","doi":"10.1145/3492323.3495627","DOIUrl":"https://doi.org/10.1145/3492323.3495627","url":null,"abstract":"Applications that process streams of events generated by sensors are important in a wide range of domains. It is now common to distribute stream processing across edge devices and the cloud. This exploits processing power near the sensors, reducing the load on the cloud and often the required network bandwidth. In this paper we focus on one challenge in distributed stream processing: automatically adapting the partitioning of the processing between the edge and the cloud without a loss of service. An example is when the event arrival rate increases and the edge processor can no longer meet performance requirements. Re-partitioning without loss of service involves moving computations between the edge and the cloud while events are still being processed. In this paper we describe StrIoT - a stream processing system that supports automatic re-partitioning. It is based on a set of functional stream operators, and the paper describes how the run-time system can automatically adapt applications that use them. A key feature is support for the fission and fusion of operators during adaptations. Performance evaluation shows that StrIoT can move parts of a stream processing application between the cloud and edge with only a low, temporary impact on performance.","PeriodicalId":440884,"journal":{"name":"Proceedings of the 14th IEEE/ACM International Conference on Utility and Cloud Computing Companion","volume":"79 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132371922","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

Medical 3D reconstruction based on deep learning for healthcare 基于深度学习的医疗三维重建

Proceedings of the 14th IEEE/ACM International Conference on Utility and Cloud Computing Companion Pub Date : 2021-12-06 DOI: 10.1145/3492323.3495618

Jia-Ji Wang, Shu-Wen Chen, Jiayuan Shao, Xiao-Wei Gu, Huijie Zhu

引用次数: 1

Memory hot-zone and its application to accelerate the convergence of KSM for VM consolidation 内存热区及其在加速虚拟机整合KSM收敛中的应用

Proceedings of the 14th IEEE/ACM International Conference on Utility and Cloud Computing Companion Pub Date : 2021-12-06 DOI: 10.1145/3492323.3500867

Chun-Yuan Huang, Der-Yu Tsai, Che-Rung Lee

引用次数: 0

Proactive autoscaling for edge computing systems with kubernetes 基于kubernetes的边缘计算系统的主动自动伸缩

Proceedings of the 14th IEEE/ACM International Conference on Utility and Cloud Computing Companion Pub Date : 2021-12-06 DOI: 10.1145/3492323.3495588

Li Ju, Prabhmanmeet Singh, S. Toor

引用次数: 8

Monitoring system architecture for the multi-scale blockchain-based logistic network 基于区块链的多尺度物流网络监控系统架构

Proceedings of the 14th IEEE/ACM International Conference on Utility and Cloud Computing Companion Pub Date : 2021-12-06 DOI: 10.1145/3492323.3495633

V. Kashansky, R. Prodan, Aso Validi, C. Olaverri-Monreal, G. Radchenko

{"title":"Monitoring system architecture for the multi-scale blockchain-based logistic network","authors":"V. Kashansky, R. Prodan, Aso Validi, C. Olaverri-Monreal, G. Radchenko","doi":"10.1145/3492323.3495633","DOIUrl":"https://doi.org/10.1145/3492323.3495633","url":null,"abstract":"Contemporary control processes and methods in multi-scale, cyber-physical systems require precise data collection at various levels, timely transmission, and analysis involving large number of computing and storage elements connected within high-performance permissioned consensus networks. For example, in transport networks, resources tend to form multi-scale dynamical systems with diverse operational requirements, including data exchange policies and consensus protocols. Apart from designing complete topology, chaincodes and consensus logic, effective monitoring of the applications and infrastructure of such complex systems remains a research challenge. In this paper, we discuss important aspects of the data-intensive applications monitoring investigated in the frames of the ADAPT project. We present highlights on the toolsets, architectures and details on possible optimization approaches for monitoring data collection. We introduce a dynamic multi-scale monitoring system architecture with preliminary workflow model. It allows obtaining effective low-latency publish-subscribe matching of the dynamically varying monitoring tasks and executing machines.","PeriodicalId":440884,"journal":{"name":"Proceedings of the 14th IEEE/ACM International Conference on Utility and Cloud Computing Companion","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125604446","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: 2

Blockchain-based cyber-physical systems security autonomous routing scheme 基于区块链的网络物理系统安全自主路由方案

Proceedings of the 14th IEEE/ACM International Conference on Utility and Cloud Computing Companion Pub Date : 2021-12-06 DOI: 10.1145/3492323.3495619

Yasheng Zhang, Chengcheng Li, Chao Wang, Peiying Zhang

{"title":"Blockchain-based cyber-physical systems security autonomous routing scheme","authors":"Yasheng Zhang, Chengcheng Li, Chao Wang, Peiying Zhang","doi":"10.1145/3492323.3495619","DOIUrl":"https://doi.org/10.1145/3492323.3495619","url":null,"abstract":"Improving the quality of service (QoS) and quality of experience (QoE) for users of cyber-physical systems (CPS) is the key to the widespread promotion and deployment of this technology. Network latency is an important factor affecting users' network experience. Due to the limited processing capacity of a single device node of CPS, the communication relationship between equipment is extremely complicated, and multi-hop device nodes may be passed through in the middle, so designing an efficient routing scheme for CPS is a serious challenge. CPS routing also faces a security crisis. System nodes may send viruses or erroneous results to user equipment, and user equipment may also refuse to pay for routing services to system nodes. In order to solve the above problems, this paper proposes a secure routing scheme based on blockchain. Blockchain is used to ensure secure transactions between system nodes and user equipment. At the same time, deep reinforcement learning (DRL) technology is used, and two deep neural networks are used to train intelligent agent to achieve low-latency adaptive traffic scheduling. Experimental results show that the proposed autonomous routing technology can reduce the system communication latency by about 31.7%-45.4%.","PeriodicalId":440884,"journal":{"name":"Proceedings of the 14th IEEE/ACM International Conference on Utility and Cloud Computing Companion","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123307353","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 new pulmonary disease diagnosis system based on EfficientNet and transfer learning: pulmonary disease diagnosis based on EfficientNet and TL 基于高效网络和迁移学习的新型肺部疾病诊断系统:基于高效网络和迁移学习的肺部疾病诊断

Proceedings of the 14th IEEE/ACM International Conference on Utility and Cloud Computing Companion Pub Date : 2021-12-06 DOI: 10.1145/3492323.3495568

Siyuan Lu, Xin Zhang, Yudong Zhang

引用次数: 0

Alcoholism via wavelet energy entropy and support vector machine 基于小波能量熵和支持向量机的酒精中毒分析

Proceedings of the 14th IEEE/ACM International Conference on Utility and Cloud Computing Companion Pub Date : 2021-12-06 DOI: 10.1145/3492323.3495617

Yan Yan, Dimas Lima

{"title":"Alcoholism via wavelet energy entropy and support vector machine","authors":"Yan Yan, Dimas Lima","doi":"10.1145/3492323.3495617","DOIUrl":"https://doi.org/10.1145/3492323.3495617","url":null,"abstract":"Alcohol has become a common drink in social etiquette that people inattention to their alcohol intake, resulting in alcoholism. Clinically, it is difficult for the physician to quickly determine whether a patient is at risk for alcoholism unless the physician has sufficient experience to achieve a rapid diagnosis. However, the non-obvious manifestations and potential harms have not been solved in time, so that patients often miss the optimal adjustment period. Based on the common electroencephalogram (EEG), some studies have attempted to combine imaging with computer-aided diagnosis to assist physicians to complete a more sophisticated diagnosis. Various computer-aided methods emerge endlessly and bring good potential application prospects. In this paper, we propose a new method to extract the energy entropy of brain image after wavelet transformation, which combined with a support vector machine classifier for alcohol intoxication detection. In the experiment, our method obtained 92.34±1.86% sensitivity, 92.72±1.00% specificity and 92.53±0.80% accuracy, showing better application ability compared with the new technique.","PeriodicalId":440884,"journal":{"name":"Proceedings of the 14th IEEE/ACM International Conference on Utility and Cloud Computing Companion","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125200431","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