2022 IEEE International Conference on Cloud Computing Technology and Science (CloudCom)最新文献_第3页

Quality of Information Matters: Recommending Web Services for Performance and Utility 信息质量问题:推荐Web服务的性能和效用

2022 IEEE International Conference on Cloud Computing Technology and Science (CloudCom) Pub Date : 2022-12-01 DOI: 10.1109/CloudCom55334.2022.00016

Zheng Song, Owen Rowader, Zheng R. Li, Maryam Tello, E. Tilevich

{"title":"Quality of Information Matters: Recommending Web Services for Performance and Utility","authors":"Zheng Song, Owen Rowader, Zheng R. Li, Maryam Tello, E. Tilevich","doi":"10.1109/CloudCom55334.2022.00016","DOIUrl":"https://doi.org/10.1109/CloudCom55334.2022.00016","url":null,"abstract":"Widely used in modern software systems, web services have become a standard means of provisioning remote resources. As the number of available web services increases, multiple services that satisfy the same functional requirement can be used interchangeably. Given a set of interchangeable services, a software developer needs to find a web service that would provide the best performance and utility. However, web services are recommended based only on their system-related performance characteristics (so called QoS, whose properties include latency, reliability, availability, etc.), while their data-related performance characteristics (e.g., data freshness, correctness, coverage, etc.) are often overlooked. As a consequence, a recommended service may end up delivering information that is inaccurate or outdated, but with high performance. To address this problem, this paper introduces Quality of Information (QoI), a quality metric complementary to QoS, that measures to which degree a web service satisfies data-related non-functional requirements. To minimize the manual effort required to evaluate the results of invoking individual services, we introduce a comparative testing methodology based on the new concept of Objects of Interest (OI). By using OI, developers can normalize the relevant information obtained from dissimilar services, so it can be automatically compared. To concretely realize our ideas, we create QiSR, a system that recommends web services based on their QoI metrics. QiSR helps developers in determining how to match services’ input and output with application data requirements and how to measure the information quality of services. To evaluate the effectiveness of QiSR, we test it on representative manually selected web services. Our evaluation shows that services recommended based on both QoI and QoS exhibit better combined performance and utility than services recommend on QoS alone.","PeriodicalId":282963,"journal":{"name":"2022 IEEE International Conference on Cloud Computing Technology and Science (CloudCom)","volume":"12 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":"115503500","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

Scalable Containerized Pipeline for Real-time Big Data Analytics 用于实时大数据分析的可扩展容器化管道

2022 IEEE International Conference on Cloud Computing Technology and Science (CloudCom) Pub Date : 2022-12-01 DOI: 10.1109/CloudCom55334.2022.00014

Rana Aurangzaib, Waheed Iqbal, Muhammad Abdullah, Faisal Bukhari, Faheem Ullah, A. Erradi

引用次数: 1

Supporting Confidential Workloads in SPIRE 在SPIRE中支持机密工作负载

2022 IEEE International Conference on Cloud Computing Technology and Science (CloudCom) Pub Date : 2022-12-01 DOI: 10.1109/CloudCom55334.2022.00035

E. Falcão, M. Silva, A. Luz, Andrey Brito

{"title":"Supporting Confidential Workloads in SPIRE","authors":"E. Falcão, M. Silva, A. Luz, Andrey Brito","doi":"10.1109/CloudCom55334.2022.00035","DOIUrl":"https://doi.org/10.1109/CloudCom55334.2022.00035","url":null,"abstract":"The migration of traditional deployment to clouds has driven the need for a more robust security model, the Zero-Trust model. The application of zero-trust principles addresses known security issues such as lateral movement attacks but adds extra identity management complexity. In addition, to cover a broader range of attacks, one must think of strategies to protect data, code, and credentials in such applications. Confidential computing aims to fulfill this goal. Nevertheless, confidential computing is even more complex to implement than Zero-Trust. In this work, we combine the Zero-Trust model with confidential computing by leveraging the SPIFFE standard through its reference implementation (SPIRE), and Intel SGX through the SCONE framework, to seamlessly supply software identities to confidential microservices. Furthermore, we also protected the whole identity-provisioning stack with Intel SGX and assessed the performance overhead. We believe this combination not only improves the security of SPIFFE deployments but also leverages SPIFFE to facilitate the integration between confidential computing components and native applications.","PeriodicalId":282963,"journal":{"name":"2022 IEEE International Conference on Cloud Computing Technology and Science (CloudCom)","volume":"26 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":"127260992","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

Consensus latency of PoW blockchains PoW区块链的共识延迟

2022 IEEE International Conference on Cloud Computing Technology and Science (CloudCom) Pub Date : 2022-12-01 DOI: 10.1109/CloudCom55334.2022.00029

Ke Wang, Hyong S. Kim

引用次数: 0

Managing Digital Objects with Decentralised Identifiers based on NFT-like schema 基于类nft模式管理具有分散标识符的数字对象

2022 IEEE International Conference on Cloud Computing Technology and Science (CloudCom) Pub Date : 2022-12-01 DOI: 10.1109/CloudCom55334.2022.00042

Chunming Rong, Jiahui Geng, M. Jaatun

引用次数: 0

Internet of Wearables: Fog Extrapolation for Reduced Data Collection and Expanded Capture Volume in Real-Time Motion Capture Edge Devices 可穿戴互联网:实时运动捕捉边缘设备中减少数据收集和扩大捕获量的雾外推

2022 IEEE International Conference on Cloud Computing Technology and Science (CloudCom) Pub Date : 2022-12-01 DOI: 10.1109/CloudCom55334.2022.00030

S. Stevens, Paulo Garcia, Hyong Kim

{"title":"Internet of Wearables: Fog Extrapolation for Reduced Data Collection and Expanded Capture Volume in Real-Time Motion Capture Edge Devices","authors":"S. Stevens, Paulo Garcia, Hyong Kim","doi":"10.1109/CloudCom55334.2022.00030","DOIUrl":"https://doi.org/10.1109/CloudCom55334.2022.00030","url":null,"abstract":"The range of applications that make up the Internet-of-Things ecosystem continues to grow. New opportunities present themselves along with new design challenges concerning the efficiency, portability, and processing capabilities of future Internet-of-Things systems. Thus, improving the operational metrics of individual Internet-of-Things devices, particularly across the edge and fog layers, is of paramount importance.In this manuscript, we present an approach for decreasing data collection at the edge, thus reducing form factor and power consumption of edge devices. This is particularly relevant for our application of interest, wearable motion capture, where human comfort and operational longevity are of prime importance. Our approach extrapolates from reduced edge data by leveraging prior physiological knowledge of the captured entity at the computational stage in the fog. By delegating computation to the fog, we also demonstrate the possibility for expanded capture volumes (operational areas) for future wearable motion capture systems and motion capture systems in general.Our approach, when prototyped on a millimeter wave sensor edge device and two fog node platforms of different processing tiers, shows that prior knowledge can facilitate a reduction in capture data dimensionality (and an associated decrease in power consumption) with little to no accuracy degradation, when compared to a more data-intensive edge system (Microsoft Kinect).","PeriodicalId":282963,"journal":{"name":"2022 IEEE International Conference on Cloud Computing Technology and Science (CloudCom)","volume":"26 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":"128267382","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

How to confirm blocks in PoW blockchains 如何确认PoW区块链中的区块

2022 IEEE International Conference on Cloud Computing Technology and Science (CloudCom) Pub Date : 2022-12-01 DOI: 10.1109/CloudCom55334.2022.00037

Ke Wang, Hyong S. Kim

{"title":"How to confirm blocks in PoW blockchains","authors":"Ke Wang, Hyong S. Kim","doi":"10.1109/CloudCom55334.2022.00037","DOIUrl":"https://doi.org/10.1109/CloudCom55334.2022.00037","url":null,"abstract":"Existing PoW blockchains adopt a simple k-block confirmation rule. A block is confirmed after it is buried sufficiently deep in the blockchain. The selection of the required depth k is largely based on empirical experiences and lacks a theoretical guarantee. We ask a fundamental question in PoW blockchains: when and how should miners confirm a block in PoW blockchains? We say a block is in the consensus state if it is included in every miner’s blockchain. The issue of the current k-block rule is that it does not depend on consensus. A block buried k-block deep may not be in the consensus state. We propose that a block should not be confirmed before the miner believes it to be in the consensus state. We present a consensus-inference protocol for miners to infer whether a block is in the consensus state locally. Based on the inference protocol, we further describe a new consensus-aware confirmation rule. Compared to the existing k-block rule, we show that the new rule achieves lower confirmation reversal probability under the same confirmation latency. The reduction could be orders of magnitude when multiple blocks are mined on average per network delay. Correspondingly, we further show that the new rule could improve the scalability of current blockchains by as much as 90% in common scenarios.","PeriodicalId":282963,"journal":{"name":"2022 IEEE International Conference on Cloud Computing Technology and Science (CloudCom)","volume":"5 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":"121302589","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

FedTeams: Towards Trust-Based and Resource-Aware Federated Learning 迈向基于信任和资源感知的联邦学习

2022 IEEE International Conference on Cloud Computing Technology and Science (CloudCom) Pub Date : 2022-12-01 DOI: 10.1109/CloudCom55334.2022.00027

D. Popovic, Hend K. Gedawy, Khaled A. Harras

{"title":"FedTeams: Towards Trust-Based and Resource-Aware Federated Learning","authors":"D. Popovic, Hend K. Gedawy, Khaled A. Harras","doi":"10.1109/CloudCom55334.2022.00027","DOIUrl":"https://doi.org/10.1109/CloudCom55334.2022.00027","url":null,"abstract":"Federated Learning (FL) has enabled Machine Learning (ML) applications to capture a larger spectrum of data by allowing such data to remain on-device, a desirable privacy guarantee in many applications. However, the highly iterative nature of FL optimization algorithms requires low-latency and high-throughput connections to clients. Unfortunately, realistic FL training scenarios include heterogeneous clients that are restricted by computation and communication, thereby slowing down or even failing FL training. In this paper, we propose FedTeams; a trust-based and resource-aware FL system that minimizes training latency, while improving accuracy. To achieve this, we mitigate the risk of straggling and weakly-connected clients by leveraging social trust and allowing these clients to offload their data to more powerful trusted peers that can train on their behalf. In specific, we formulate and solve an optimization problem that leverages the FedTeam’s trust graph and client resource information to optimize the distribution of training and minimize training latency. We evaluate FedTeams in a simulated environment, demonstrating up to a 81.6% decrease in training latency and 11.2% increase in global model accuracy when compared to existing state-of-the-art solutions.","PeriodicalId":282963,"journal":{"name":"2022 IEEE International Conference on Cloud Computing Technology and Science (CloudCom)","volume":"81 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":"124876974","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 Hybrid Decision-making Approach to Security Metrics Aggregation in Cloud Environments 云环境中安全度量聚合的混合决策方法

2022 IEEE International Conference on Cloud Computing Technology and Science (CloudCom) Pub Date : 2022-12-01 DOI: 10.1109/CloudCom55334.2022.00034

Ming Lei, Lianying Zhao, M. Pourzandi, F. F. Moghaddam

{"title":"A Hybrid Decision-making Approach to Security Metrics Aggregation in Cloud Environments","authors":"Ming Lei, Lianying Zhao, M. Pourzandi, F. F. Moghaddam","doi":"10.1109/CloudCom55334.2022.00034","DOIUrl":"https://doi.org/10.1109/CloudCom55334.2022.00034","url":null,"abstract":"In cybersecurity, being able to quantity the level of security has been a long quest so that decisions can be made toward improving security. Various metrics have been proposed and applied, which can usually be computed from collected measurements. However, only certain aspects of the target system are measured corresponding to the purpose the metrics were designed for, be it software vulnerabilities or configuration errors, thus lacking a concise and clear image of the overall security of a system for the practitioners to act on, especially when it comes to large-scale or complex systems.We argue that overall security metrics are defined by humans based on specific security goals before they can be computed. Therefore, we propose a hybrid approach to the aggregation of well-established individual security metrics by combining machine computation with human decision making. In particular, we modify the Analytic Hierarchy Process (AHP) to reach a group decision of selected “experts”, which can derive the weights of individual metrics for their aggregation. We showcase its feasibility by selecting several common metrics to measure the target systems in our testbed, and conducting an AHP survey with seventeen experts. The resulted overall security score for the target systems shows how our approach enables comparison of the overall security between those systems. By considering cloud-oriented settings, we also showcase how this approach can be applicable to today’s virtualized environments.","PeriodicalId":282963,"journal":{"name":"2022 IEEE International Conference on Cloud Computing Technology and Science (CloudCom)","volume":"33 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":"123666371","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

IEEE CloudCom 2022 Committees IEEE CloudCom 2022委员会

2022 IEEE International Conference on Cloud Computing Technology and Science (CloudCom) Pub Date : 2022-12-01 DOI: 10.1109/cloudcom55334.2022.00009

引用次数: 0