Proceedings of the Third ACM International Workshop on Edge Systems, Analytics and Networking最新文献

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Edge replication strategies for wide-area distributed processing 广域分布式处理的边缘复制策略
Niklas Semmler, Matthias Rost, Georgios Smaragdakis, A. Feldmann
{"title":"Edge replication strategies for wide-area distributed processing","authors":"Niklas Semmler, Matthias Rost, Georgios Smaragdakis, A. Feldmann","doi":"10.1145/3378679.3394532","DOIUrl":"https://doi.org/10.1145/3378679.3394532","url":null,"abstract":"The rapid digitalization across industries comes with many challenges. One key problem is how the ever-growing and volatile data generated at distributed locations can be efficiently processed to inform decision making and improve products. Unfortunately, wide-area network capacity cannot cope with the growth of the data at the network edges. Thus, it is imperative to decide which data should be processed in-situ at the edge and which should be transferred and analyzed in data centers. In this paper, we study two families of proactive online data replication strategies, namely ski-rental and machine learning algorithms, to decide which data is processed at the edge, close to where it is generated, and which is transferred to a data center. Our analysis using real query traces from a Global 2000 company shows that such online replication strategies can significantly reduce data transfer volume in many cases up to 50% compared to naive approaches and achieve close to optimal performance. After analyzing their shortcomings for ease of use and performance, we propose a hybrid strategy that combines the advantages of both competitive and machine learning algorithms.","PeriodicalId":268360,"journal":{"name":"Proceedings of the Third ACM International Workshop on Edge Systems, Analytics and Networking","volume":"466 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116511396","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
DeepDish DeepDish
Matthew Danish, J. Brazauskas, Rob Bricheno, Ian Lewis, R. Mortier
{"title":"DeepDish","authors":"Matthew Danish, J. Brazauskas, Rob Bricheno, Ian Lewis, R. Mortier","doi":"10.1145/3378679.3394535","DOIUrl":"https://doi.org/10.1145/3378679.3394535","url":null,"abstract":"When looking at a building or urban settings, information about the number of people present and the way they move through the space is useful for helping designers to understand what they have created, fire marshals to identify potential safety hazards, planners to speculate about what is needed in the future, and the public to have real data on which to base opinions about communal choices. We propose a network of edge devices based on Raspberry Pi and TensorFlow, which will ultimately push data via LoRaWAN to a real-time data server. This network is being integrated into a Digital Twin of a local site which includes several dozen buildings spread over approximately 500,000 square metres. We share and discuss issues regarding privacy, accuracy and performance.","PeriodicalId":268360,"journal":{"name":"Proceedings of the Third ACM International Workshop on Edge Systems, Analytics and Networking","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123960243","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
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