Proceedings of the 15th ACM International Conference on Distributed and Event-based Systems最新文献

Workload-driven systems optimization: things are getting real! 工作负载驱动的系统优化:事情正在变得真实!

Proceedings of the 15th ACM International Conference on Distributed and Event-based Systems Pub Date : 2021-06-28 DOI: 10.1145/3465480.3466918

C. Curino

引用次数: 0

Towards event-driven decentralized marketplaces on the blockchain 朝着区块链上事件驱动的去中心化市场发展

Proceedings of the 15th ACM International Conference on Distributed and Event-based Systems Pub Date : 2021-06-28 DOI: 10.1145/3465480.3466921

Akash Pateria, Kemafor Anyanwu

{"title":"Towards event-driven decentralized marketplaces on the blockchain","authors":"Akash Pateria, Kemafor Anyanwu","doi":"10.1145/3465480.3466921","DOIUrl":"https://doi.org/10.1145/3465480.3466921","url":null,"abstract":"Blockchains have become a popular technology for lowering the trust-tax burden between transacting parties that cannot necessarily trust each other. They are used as substitutes for the centralized authorities typically incorporated in transactional workflows to perform verification tasks and have the advantage of being objective and incorruptible. For applications such as supply chain marketplaces, auxilliary functionalities beyond the core blockchain roles of recording and validating transactions such as event detection are important for enabling application participants be responsive to business conditions. Unfortunately, existing blockchain event frameworks are immature, syntactic, inflexible and not expressive enough for many application needs. In this paper, we propose an approach that involves an event model which \"semantifies blockchain transactions\" and an implementation architecture that integrates a open-source blockchain database BigChainDB with a semantic engine and publish-subscribe messaging platform. Finally, we model and simulate a use-case inspired from the manufacturing domain and present usability and preliminary performance results that demonstrate the discriminatory ability of semantics-enabled event model.","PeriodicalId":217173,"journal":{"name":"Proceedings of the 15th ACM International Conference on Distributed and Event-based Systems","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129645033","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

Machine learning over static and dynamic relational data 基于静态和动态关系数据的机器学习

Proceedings of the 15th ACM International Conference on Distributed and Event-based Systems Pub Date : 2021-06-28 DOI: 10.1145/3465480.3467843

A. Kara, M. Nikolic, Dan Olteanu, Haozhe Zhang

引用次数: 1

A distributed database system for event-based microservices 基于事件的微服务分布式数据库系统

Proceedings of the 15th ACM International Conference on Distributed and Event-based Systems Pub Date : 2021-06-28 DOI: 10.1145/3465480.3466919

Rodrigo Laigner, Yongluan Zhou, M. V. Salles

引用次数: 5

An event driven framework for smart contract execution 用于智能合约执行的事件驱动框架

Proceedings of the 15th ACM International Conference on Distributed and Event-based Systems Pub Date : 2021-06-28 DOI: 10.1145/3465480.3466924

Mudabbir Kaleem, Keshav Kasichainula, Rabimba Karanjai, Lei Xu, Zhimin Gao, Lin Chen, W. Shi

引用次数: 5

Real-time big data stream analytics and complex event detection: modular visual framework, data science platform, and industry applications 实时大数据流分析与复杂事件检测:模块化可视化框架、数据科学平台、行业应用

Proceedings of the 15th ACM International Conference on Distributed and Event-based Systems Pub Date : 2021-06-28 DOI: 10.1145/3465480.3468676

R. Klinkenberg

{"title":"Real-time big data stream analytics and complex event detection: modular visual framework, data science platform, and industry applications","authors":"R. Klinkenberg","doi":"10.1145/3465480.3468676","DOIUrl":"https://doi.org/10.1145/3465480.3468676","url":null,"abstract":"In many industry applications, larger and larger amounts of data become available, allowing to gain deeper insights, to generate more accurate forecats, to optimize and automate processes, and to thereby create significant value. Often the data is not static, but arrives continuously in large data streams, which ideally are processed and leveraged in real-time. This talk will present a modular and flexible platform for real-time big data stream processing, complex event detection, data science and machine learning with an easy-to-use visual process design user interface, seamlessly integrating the most relevant big data and stream processing frameworks (Hadoop, Spark, Spark Streaming, Kafka, Flink, etc.) within one unifying platform and user interface, based on the widely used data science platform RapidMiner. This talk will also provide an overview of applications of this framework across many industries like machine failure prediction and prevention and predictive maintenance in industrial production in the manufacturing industry, criticial event detection, prediction and prevention in the chemical indutry, product quality prediction and optimization as well as energy consumption and cost reduction in the steel and metal industry, data-driven process optimization in the food and beverage industry, various use cases in the automotive and aviation industry, maritime data analysis to detect complex events like piracy or illegal fishing and to avoid collisions, drug effectiveness prediction for cancer drug development and biomedical research, financial time series analysis and forecasting for the investment industry. The latter three use cases are addresed in the European reseach projects INFORE, which will also be shortly introduced.","PeriodicalId":217173,"journal":{"name":"Proceedings of the 15th ACM International Conference on Distributed and Event-based Systems","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114898120","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

Distributed transactions on serverless stateful functions 无服务器状态函数上的分布式事务

Proceedings of the 15th ACM International Conference on Distributed and Event-based Systems Pub Date : 2021-06-28 DOI: 10.1145/3465480.3466920

M. de Heus, Kyriakos Psarakis, Marios Fragkoulis, Asterios Katsifodimos

{"title":"Distributed transactions on serverless stateful functions","authors":"M. de Heus, Kyriakos Psarakis, Marios Fragkoulis, Asterios Katsifodimos","doi":"10.1145/3465480.3466920","DOIUrl":"https://doi.org/10.1145/3465480.3466920","url":null,"abstract":"Serverless computing is currently the fastest-growing cloud services segment. The most prominent serverless offering is Function-as-a-Service (FaaS), where users write functions and the cloud automates deployment, maintenance, and scalability. Although FaaS is a good fit for executing stateless functions, it does not adequately support stateful constructs like microservices and scalable, low-latency cloud applications, mainly because it lacks proper state management support and the ability to perform function-to-function calls. Most importantly, executing transactions across stateful functions remains an open problem. In this paper, we introduce a programming model and implementation for transaction orchestration of stateful serverless functions. Our programming model supports serializable distributed transactions with two-phase commit, as well as relaxed transactional guarantees with Sagas. We design and implement our programming model on Apache Flink StateFun. We choose to build our solution on top of StateFun in order to leverage Flink's exactly-once processing and state management guarantees. We base our evaluation on the YCSB benchmark, which we extended with transactional operations and adapted for the SFaaS programming model. Our experiments show that our transactional orchestration adds 10% overhead to the original system and that Sagas can achieve up to 34% more transactions per second than two-phase commit transactions at a sub-200ms latency.","PeriodicalId":217173,"journal":{"name":"Proceedings of the 15th ACM International Conference on Distributed and Event-based Systems","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129676598","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: 16

Towards creating a generalized complex event processing operator using FlinkCEP: architecture & benchmark 使用FlinkCEP创建一个通用的复杂事件处理操作符:架构和基准

Proceedings of the 15th ACM International Conference on Distributed and Event-based Systems Pub Date : 2021-06-28 DOI: 10.1145/3465480.3467841

E. Kougioumtzi, Antonios Kontaxakis, Antonios Deligiannakis, Y. Kotidis

引用次数: 3

Fast recovery of correlated failures in distributed stream processing engines 分布式流处理引擎中相关故障的快速恢复

Proceedings of the 15th ACM International Conference on Distributed and Event-based Systems Pub Date : 2021-06-28 DOI: 10.1145/3465480.3466923

Li Su, Yongluan Zhou

{"title":"Fast recovery of correlated failures in distributed stream processing engines","authors":"Li Su, Yongluan Zhou","doi":"10.1145/3465480.3466923","DOIUrl":"https://doi.org/10.1145/3465480.3466923","url":null,"abstract":"In a large-scale cluster, correlated failures usually involve a number of nodes failing simultaneously. Although correlated failures occur infrequently, they have significant effect on systems' availability, especially for streaming applications that require real-time analysis, as repairing the failed nodes or acquiring additional ones would take a significant amount of time. Most state-of-the-art distributed stream processing systems (DSPSs) focus on recovering individual failures and do not consider the optimization for recovering correlated failure. In this work, we propose an incremental and query-centric recovery paradigm where the recovery of failed operator partitions would be carefully scheduled based on the current availability of resources, such that the outputs of queries can be recovered as early as possible. By analyzing the existing recovery techniques, we identify the challenges and propose a fault-tolerance framework that can support incremental recovery with minimum overhead during the system's normal execution. We also formulate the new problem of recovery scheduling under correlated failures and design algorithms to optimize the recovery latency with a performance guarantee. A comprehensive set of experiments are conducted to study the validity of our proposal.","PeriodicalId":217173,"journal":{"name":"Proceedings of the 15th ACM International Conference on Distributed and Event-based Systems","volume":"101 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122900613","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

Building an end-to-end BAD application 构建端到端的BAD应用程序

Proceedings of the 15th ACM International Conference on Distributed and Event-based Systems Pub Date : 2021-06-28 DOI: 10.1145/3465480.3467840

Shahrzad Haji Amin Shirazi, M. Carey, V. Tsotras

{"title":"Building an end-to-end BAD application","authors":"Shahrzad Haji Amin Shirazi, M. Carey, V. Tsotras","doi":"10.1145/3465480.3467840","DOIUrl":"https://doi.org/10.1145/3465480.3467840","url":null,"abstract":"Traditional big data infrastructures are passive in nature, passively answering user requests to process and return data. In many applications however, users not only need to analyze data, but also to subscribe to and actively receive data of interest, based on their subscriptions. Their interest may include the incoming data's content as well as its relationships to other data. Moreover, data delivered to subscribers may need to be enriched with additional relevant and actionable information. To address this Big Active Data (BAD) challenge we have advocated the need for building scalable BAD systems that continuously and reliably capture big data while enabling timely and automatic delivery of relevant and possibly enriched information to a large pool of subscribers. In this demo we showcase how to build an end-to-end active application using a BAD system and a standard email broker for data delivery. This includes enabling users to register their interests with the bad system, ingesting and monitoring data, and producing customized results and delivering them to the appropriate subscribers. Through this example we demonstrate that even complex active data applications can be created easily and scale to many users, considerably limiting the effort of application developers, if a BAD approach is taken.","PeriodicalId":217173,"journal":{"name":"Proceedings of the 15th ACM International Conference on Distributed and Event-based Systems","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130382373","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