2022 IEEE International Conference on Cloud Engineering (IC2E)最新文献_第3页

Optimum VM Placement for NFV Infrastructures NFV基础设施的最佳虚拟机布局

2022 IEEE International Conference on Cloud Engineering (IC2E) Pub Date : 2022-09-01 DOI: 10.1109/IC2E55432.2022.00029

T. Cucinotta, Luigi Pannocchi, Filippo Galli, S. Fichera, Sourav Lahiri, Antonino Artale

{"title":"Optimum VM Placement for NFV Infrastructures","authors":"T. Cucinotta, Luigi Pannocchi, Filippo Galli, S. Fichera, Sourav Lahiri, Antonino Artale","doi":"10.1109/IC2E55432.2022.00029","DOIUrl":"https://doi.org/10.1109/IC2E55432.2022.00029","url":null,"abstract":"This paper constitutes an industrial experience re-port about the use of data center optimization strategies for softwarized network services within the Vodafone resource man-agement unit for the management of virtualized network infras-tructures. The problem of optimum virtual machine placement as needed in the network operator context is detailed, and different solving strategies are proposed and discussed, including heuristics based on genetic optimization. Also, experimental results are presented that compare these strategies with one another from the standpoint of optimality and execution times, using a data-set made of some of the real problems that had to be solved in the past few years by Vodafone, in order to optimize its capacity planning decisions. The presented experimental results highlight that an optimum solver leads to excessively high computation times for large problems, whereas simple heuristics may exhibit significant loss in optimality at reduced computation times. Genetic optimization, on the other hand, constitutes a very interesting trade-off between these two extremes. The data-set used for the provided results is published under an open data license, for possible reuse in future research works on the topic.","PeriodicalId":415781,"journal":{"name":"2022 IEEE International Conference on Cloud Engineering (IC2E)","volume":"223 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117109054","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

Scalable Collaborative Software Visualization as a Service: Short Industry and Experience Paper 可扩展的协作软件可视化作为一种服务:简短的行业和经验论文

2022 IEEE International Conference on Cloud Engineering (IC2E) Pub Date : 2022-09-01 DOI: 10.1109/IC2E55432.2022.00026

Alexander Krause-Glau, W. Hasselbring

{"title":"Scalable Collaborative Software Visualization as a Service: Short Industry and Experience Paper","authors":"Alexander Krause-Glau, W. Hasselbring","doi":"10.1109/IC2E55432.2022.00026","DOIUrl":"https://doi.org/10.1109/IC2E55432.2022.00026","url":null,"abstract":"Software visualizations are used by software developers, for instance, for program comprehension. In this context, a less researched aspect is the collaborative use of online visual-ization services. This paper presents the conceptual design and a prototype implementation of our approach for a collaborative software visualization service for program comprehension. The central idea is an online available software-as-a-service application that analyzes, persists, and visualizes software applications which users intend to explore and comprehend via software visualization. The resulting implementation is a redevelopment of our live trace visualization tool Explor Viz. In comparison to other approaches, ExplorViz utilizes WebGL and other browser technologies instead of a game engine to render its visualizations. As a result, we achieve a platform-independent interoperability that is crucial for (remote) collaboration. Here, users can explore the same visualization via our collaboratively usable desktop, virtual reality, and also augmented reality modes. Our prototype follows the Twelve-Factor App methodology to build a cloud-native application that comprises multiple scalable microservices. Thanks to horizontal scaling, our implementation is capable to analyze a large amount of visualization data; thus, allowing multiple users to simultaneously use the software visualization service. We conducted a set of preliminary performance exper-iments to benchmark our prototype's scalability. Results show that the evaluated service scales linearly with increasing load.","PeriodicalId":415781,"journal":{"name":"2022 IEEE International Conference on Cloud Engineering (IC2E)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124147195","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

Automated Traces-based Anomaly Detection and Root Cause Analysis in Cloud Platforms 云平台中基于跟踪的自动异常检测和根本原因分析

2022 IEEE International Conference on Cloud Engineering (IC2E) Pub Date : 2022-09-01 DOI: 10.1109/IC2E55432.2022.00034

Mbarka Soualhia, F. Wuhib

引用次数: 2

Novel Abstraction and Offload Mechanisms for High Performance Cloud-native Distributed Object Stores 高性能云原生分布式对象存储的新型抽象和卸载机制

2022 IEEE International Conference on Cloud Engineering (IC2E) Pub Date : 2022-09-01 DOI: 10.1109/IC2E55432.2022.00024

A. Reddy, D. Moghe, Manik Taneja, Roger Liao, Subin Francis

{"title":"Novel Abstraction and Offload Mechanisms for High Performance Cloud-native Distributed Object Stores","authors":"A. Reddy, D. Moghe, Manik Taneja, Roger Liao, Subin Francis","doi":"10.1109/IC2E55432.2022.00024","DOIUrl":"https://doi.org/10.1109/IC2E55432.2022.00024","url":null,"abstract":"Object Storage solutions are typically optimised for capacity and cost but performance has traditionally been a second thought. We make the case for a highly performant distributed object store by a) building an abstraction layer to pass immutability and data affinity hints to the underlying storage while also, b) making the Objects layer aware of the hardware configurations enabling the Object Storage controllers to maximise throughput. With these optimizations we show that object storage performance can approach 95% of the maximum possible performance from the underlying raw storage while ensuring that the abstractions are generic enough to be able to run on any general purpose off the shelf storage systems. We have observed these performance gains across more than 1000 customer environments across diverse hardware. We also extend the above optimizations with generic mecha-nisms to offload compute closer to storage that have significant benefits for a broad class of workloads. Specifically, we evaluate performance gains from a) well known constructs like S3 Select for Analytics workloads and b) generic compute offload like Objects Lambda. This ability to offload compute is critical for modern distributed workloads like AI/ML and Analytics processing with very large distributed data sets.","PeriodicalId":415781,"journal":{"name":"2022 IEEE International Conference on Cloud Engineering (IC2E)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115132955","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

Organizing and Program Committee: IC2E 2022 组委会:IC2E 2022

2022 IEEE International Conference on Cloud Engineering (IC2E) Pub Date : 2022-09-01 DOI: 10.1109/ic2e55432.2022.00006

引用次数: 0

Poster Paper: Operating System Support for Applications Performance Analysis 海报纸:应用程序性能分析的操作系统支持

2022 IEEE International Conference on Cloud Engineering (IC2E) Pub Date : 2022-09-01 DOI: 10.1109/IC2E55432.2022.00039

Riley VanDonge, Naser Ezzati-Jivan

引用次数: 0

Adaptive Replication Strategy in Highly Distributed Data Management Systems 高分布数据管理系统中的自适应复制策略

2022 IEEE International Conference on Cloud Engineering (IC2E) Pub Date : 2022-09-01 DOI: 10.1109/IC2E55432.2022.00036

Simone Bottoni, S. Braghin, Alberto Trombetta, S. Venugopal

引用次数: 0

IoTreeplay: Synchronous Distributed Traffic Replay in IoT Environments IoTreeplay:物联网环境下的同步分布式流量回放

2022 IEEE International Conference on Cloud Engineering (IC2E) Pub Date : 2022-08-19 DOI: 10.1109/IC2E55432.2022.00008

Markus Toll, Ilja Behnke, O. Kao

{"title":"IoTreeplay: Synchronous Distributed Traffic Replay in IoT Environments","authors":"Markus Toll, Ilja Behnke, O. Kao","doi":"10.1109/IC2E55432.2022.00008","DOIUrl":"https://doi.org/10.1109/IC2E55432.2022.00008","url":null,"abstract":"Use-cases in the Internet of Things (IoT) typically involve a high number of interconnected, heterogeneous devices. Due to the criticality of many IoT scenarios, systems and applications need to be tested thoroughly before rollout. Existing staging environments and testing frameworks are able to emulate network properties but fail to deliver actual network-wide traffic control to test systems application independently. To extend existing frameworks, we present the distributed traffic replaying tool IoTreeplay. The tool embeds TCPLivePlay into an environment that allows the synchronous replaying of network traffic with multiple endpoints and connections. Replaying takes place in a user-defined network or testbed containing IoT use-cases. Network traffic can be captured and compared to the original trace to evaluate accuracy and reliability. The resulting implementation is able to accurately replay connections within a maximum transmission rate but struggles with deviations from regular TCP connections, like packet loss or connection reset. An evaluation has been performed, measuring individual and aggregated delays between packets, based on the recorded timestamps.","PeriodicalId":415781,"journal":{"name":"2022 IEEE International Conference on Cloud Engineering (IC2E)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115648029","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

Efficient Transmission and Reconstruction of Dependent Data Streams via Edge Sampling 基于边缘采样的相关数据流的高效传输与重构

2022 IEEE International Conference on Cloud Engineering (IC2E) Pub Date : 2022-08-12 DOI: 10.1109/IC2E55432.2022.00013

Joel Wolfrath, A. Chandra

{"title":"Efficient Transmission and Reconstruction of Dependent Data Streams via Edge Sampling","authors":"Joel Wolfrath, A. Chandra","doi":"10.1109/IC2E55432.2022.00013","DOIUrl":"https://doi.org/10.1109/IC2E55432.2022.00013","url":null,"abstract":"Data stream processing is an increasingly important topic due to the prevalence of smart devices and the demand for real-time analytics. Geo-distributed streaming systems, where cloud-based queries utilize data streams from multiple distributed devices, face challenges since wide-area network (WAN) bandwidth is often scarce or expensive. Edge computing allows us to address these bandwidth costs by utilizing resources close to the devices, e.g. to perform sampling over the incoming data streams, which trades downstream query accuracy to reduce the overall transmission cost. In this paper, we leverage the fact that correlations between data streams may exist across devices located in the same geographical region. Using this insight, we develop a hybrid edge-cloud system which systematically trades off between sampling at the edge and estimation of missing values in the cloud to reduce traffic over the WAN. We present an optimization framework which computes sample sizes at the edge and systematically bounds the number of samples we can estimate in the cloud given the strength of the correlation between streams. Our evaluation with three real-world datasets shows that compared to existing sampling techniques, our system could provide comparable error rates over multiple aggregate queries while reducing WAN traffic by 27-42%.","PeriodicalId":415781,"journal":{"name":"2022 IEEE International Conference on Cloud Engineering (IC2E)","volume":"272 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121042597","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

Network Emulation in Large-Scale Virtual Edge Testbeds: A Note of Caution and the Way Forward 大规模虚拟边缘测试平台中的网络仿真:注意事项和前进方向

2022 IEEE International Conference on Cloud Engineering (IC2E) Pub Date : 2022-08-11 DOI: 10.1109/IC2E55432.2022.00007

Soeren Becker, Tobias Pfandzelter, Nils Japke, David Bermbach, O. Kao

引用次数: 3