Proceedings of the 11th ACM International Conference on Distributed and Event-based Systems最新文献

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PopSub: Improving Resource Utilization in Distributed Content-based Publish/Subscribe Systems PopSub:提高基于内容的分布式发布/订阅系统的资源利用率
P. Salehi, Kaiwen Zhang, H. Jacobsen
{"title":"PopSub: Improving Resource Utilization in Distributed Content-based Publish/Subscribe Systems","authors":"P. Salehi, Kaiwen Zhang, H. Jacobsen","doi":"10.1145/3093742.3093915","DOIUrl":"https://doi.org/10.1145/3093742.3093915","url":null,"abstract":"Distributed content-based publish/subscribe systems provide a selective, scalable, and decentralized approach to data dissemination. In a pub/sub overlay network, hop-by-hop routing allows brokers to correctly forward messages without requiring global knowledge. However, this model causes brokers to forward publications without knowing the volume and distance of matching subscribers, which can result in inefficient resource utilization. In order to raise the scalability of pub/sub, we introduce Popularity-Based Publication Routing for Content-based Pub/Sub (PopSub), which is specifically designed to raise the resource utilization efficiency. We define a utilization metric to measure the impact of forwarding a publication on the overall delivery of the system. Furthermore, we propose a new publication routing algorithm that takes into account broker resources and publication popularity among subscribers. Lastly, we propose three approaches to handle unpopular publications. Based on our evaluations, using real-world workloads and traces, PopSub is able to improve resource efficiency of the brokers by up to 62%, and reduce delivery latency by up to 57% under high load.","PeriodicalId":325666,"journal":{"name":"Proceedings of the 11th ACM International Conference on Distributed and Event-based Systems","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133379456","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: 15
Real-Time Football Analysis with StreamTeam: Demo 实时足球分析与StreamTeam:演示
L. Probst, Frederik Brix, H. Schuldt, M. Rumo
{"title":"Real-Time Football Analysis with StreamTeam: Demo","authors":"L. Probst, Frederik Brix, H. Schuldt, M. Rumo","doi":"10.1145/3093742.3095089","DOIUrl":"https://doi.org/10.1145/3093742.3095089","url":null,"abstract":"In the last years, the analysis of data in sports has received considerable attention, especially due to the wide availability of unobtrusive wearable sensors. While most approaches focus on the (post-hoc) monitoring of individuals, a big and still largely unsolved challenge is the monitoring of the tactical behavior and tactical compliance of entire teams in real-time. In this paper, we introduce STREAMTEAM, a novel and extensible workflow-based approach to analyze data streams and to detect complex team events in real-time. We show the application of STREAMTEAM to data sets coming from sensors attached to players of football teams.","PeriodicalId":325666,"journal":{"name":"Proceedings of the 11th ACM International Conference on Distributed and Event-based Systems","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127695698","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: 11
Anomaly Detection of Manufacturing Equipment via High Performance RDF Data Stream Processing: Grand Challenge 基于高性能RDF数据流处理的制造设备异常检测:重大挑战
Nihla Akram, Sachini Siriwardene, Malith Jayasinghe, Miyuru Dayarathna, I. Perera, S. Fernando, S. Perera, Upul Bandara, Sriskandarajah Suhothayan
{"title":"Anomaly Detection of Manufacturing Equipment via High Performance RDF Data Stream Processing: Grand Challenge","authors":"Nihla Akram, Sachini Siriwardene, Malith Jayasinghe, Miyuru Dayarathna, I. Perera, S. Fernando, S. Perera, Upul Bandara, Sriskandarajah Suhothayan","doi":"10.1145/3093742.3095100","DOIUrl":"https://doi.org/10.1145/3093742.3095100","url":null,"abstract":"The ACM DEBS Grand Challenge 2017 focuses on anomaly detection of manufacturing equipment. The goal of the challenge is to detect abnormal behavior of a manufacturing machine based on the observations of the stream of measurements provided. The data produced by each sensor is clustered and the state transitions between the observed clusters are modeled as a Markov chain. In this paper we present how we used WSO2 Data Analytics Server (DAS), an open source, comprehensive enterprise data analytics platform, to solve the problem. On the HOBBIT (Holistic Benchmarking of Big Linked Data) platform our solution processed 35 megabytes/second with an end-to-end mean latency of 7.5 ms at an input rate of 1 ms, while the events spent only 1 ms time on average within our grand challenge solution. The paper describes the solution we propose, the experiments' results and presents how we optimized the performance of our solution.","PeriodicalId":325666,"journal":{"name":"Proceedings of the 11th ACM International Conference on Distributed and Event-based Systems","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121440572","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
An Embedded DSL Framework for Distributed Embedded Systems: Doctoral Symposium 分布式嵌入式系统的嵌入式DSL框架:博士研讨会
A. Mizzi, J. Ellul, Gordon J. Pace
{"title":"An Embedded DSL Framework for Distributed Embedded Systems: Doctoral Symposium","authors":"A. Mizzi, J. Ellul, Gordon J. Pace","doi":"10.1145/3093742.3093906","DOIUrl":"https://doi.org/10.1145/3093742.3093906","url":null,"abstract":"Programming distributed embedded systems gives rise to a number of challenges. The distributed nodes are typically resource constrained, requiring expert systems programming skills to manage the limited power, communication bandwidth, and memory and computation constraints. The challenge of raising the level of abstraction of programming such systems without incurring too high of an execution performance penalty is thus an important one, and many approaches have been explored in the literature. The work presented in this paper investigates a framework and domain specific language (DSL) to enable programming of such systems at a global network level. The framework enables the compilation, analysis, transformation and interpretation of high-level descriptions of stream processing applications in which information is received and processed in real-time. The ongoing research aims at investigating the following directions. Firstly, a framework to allow the manipulation and multiple interpretations of a stream processor description to support the heterogeneity aspect of devices. Secondly, a language to hide the low-level detail from the developer, while allowing the developer to add hints to enable more efficient compilations. Thirdly, through transformations, different stream processing applications can be fused together to run on the same distributed network to make best of use of available resources.","PeriodicalId":325666,"journal":{"name":"Proceedings of the 11th ACM International Conference on Distributed and Event-based Systems","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114288336","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
Sliding-Window Aggregation Algorithms: Tutorial 滑动窗口聚合算法:教程
Martin Hirzel, S. Schneider, Kanat Tangwongsan
{"title":"Sliding-Window Aggregation Algorithms: Tutorial","authors":"Martin Hirzel, S. Schneider, Kanat Tangwongsan","doi":"10.1145/3093742.3095107","DOIUrl":"https://doi.org/10.1145/3093742.3095107","url":null,"abstract":"Stream processing is important for analyzing continuous streams of data in real time. Sliding-window aggregation is both needed for many streaming applications and surprisingly hard to do efficiently. Picking the wrong aggregation algorithm causes poor performance, and knowledge of the right algorithms and when to use them is scarce. This paper was written to accompany a tutorial, but can be read as a stand-alone survey that aims to better educate the community about fast sliding-window aggregation algorithms for a variety of common aggregation operations and window types.","PeriodicalId":325666,"journal":{"name":"Proceedings of the 11th ACM International Conference on Distributed and Event-based Systems","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123730205","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: 24
Visualising complex event hierarchies using relevant domain ontologies: Doctoral Symposium 使用相关领域本体可视化复杂事件层次:博士研讨会
Riley Perry, M. Bandara, C. Kutay, F. Rabhi
{"title":"Visualising complex event hierarchies using relevant domain ontologies: Doctoral Symposium","authors":"Riley Perry, M. Bandara, C. Kutay, F. Rabhi","doi":"10.1145/3093742.3093901","DOIUrl":"https://doi.org/10.1145/3093742.3093901","url":null,"abstract":"With the growth of data available for analysis, people in many sectors are looking for tools to assist them in collating and visualising patterns in that data. We have developed an event based visualisation system which provides an interactive interface for experts to filter and analyse data. We show that by thinking in terms of events, event hierarchies, and domain ontologies, that we can provide unique results that display patterns within the data being investigated. The proposed system uses a combination of Complex Event Processing (CEP) concepts and domain knowledge via RDF based ontologies. In this case we combine an event model and domain model based on the Financial Industry Business Ontology (FIBO) and conduct experiments on financial data. Our experiments show that, by thinking in terms of event hierarchies, and pre-existing domain ontologies, that certain new relationships between events are more easily discovered.","PeriodicalId":325666,"journal":{"name":"Proceedings of the 11th ACM International Conference on Distributed and Event-based Systems","volume":"35 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131579663","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
Event Forecasting with Pattern Markov Chains 基于模式马尔可夫链的事件预测
E. Alevizos, A. Artikis, G. Paliouras
{"title":"Event Forecasting with Pattern Markov Chains","authors":"E. Alevizos, A. Artikis, G. Paliouras","doi":"10.1145/3093742.3093920","DOIUrl":"https://doi.org/10.1145/3093742.3093920","url":null,"abstract":"We present a system for online probabilistic event forecasting. We assume that a user is interested in detecting and forecasting event patterns, given in the form of regular expressions. Our system can consume streams of events and forecast when the pattern is expected to be fully matched. As more events are consumed, the system revises its forecasts to reflect possible changes in the state of the pattern. The framework of Pattern Markov Chains is used in order to learn a probabilistic model for the pattern, with which forecasts with guaranteed precision may be produced, in the form of intervals within which a full match is expected. Experimental results from real-world datasets are shown and the quality of the produced forecasts is explored, using both precision scores and two other metrics: spread, which refers to the \"focusing resolution\" of a forecast (interval length), and distance, which captures how early a forecast is reported.","PeriodicalId":325666,"journal":{"name":"Proceedings of the 11th ACM International Conference on Distributed and Event-based Systems","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133448514","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: 33
Using Rank Aggregation in Continuously Answering SPARQL Queries on Streaming and Quasi-static Linked Data 用秩聚合连续回答流和准静态关联数据上的SPARQL查询
Shima Zahmatkesh, Emanuele Della Valle, Daniele Dell'Aglio
{"title":"Using Rank Aggregation in Continuously Answering SPARQL Queries on Streaming and Quasi-static Linked Data","authors":"Shima Zahmatkesh, Emanuele Della Valle, Daniele Dell'Aglio","doi":"10.1145/3093742.3093926","DOIUrl":"https://doi.org/10.1145/3093742.3093926","url":null,"abstract":"Web applications that combine dynamic data stream with distributed background data are getting a growing attention in recent years. Answering in a timely fashion, i.e., reactiveness, is one of the most important performance indicators for those applications. The Semantic Web community showed that RDF Stream Processing (RSP) is an adequate framework to develop this type of applications. However, RSP engines may lose their reactiveness due to the time necessary to access the background data when it is distributed over the Web. State-of-the-art RSP engines remain reactive using a local replica of the background data, but it progressively becomes stale if not updated to reflect the changes in the remote background data. For this reason, recently, the RSP community has investigated maintenance policies of the local replica that guarantee reactiveness while maximizing the freshness of the replica. Previous works simplified the problem with several assumptions. In this paper, we investigate how to remove some of those simplification assumptions. In particular, we target a class of queries for which multiple policies may be used simultaneously and we show that rank aggregation can be effectively used to fairly consider their alternative suggestions. We provide extensive empirical evidence that rank aggregation is key to move a step forward to the practical solution of this problem in the RSP context.","PeriodicalId":325666,"journal":{"name":"Proceedings of the 11th ACM International Conference on Distributed and Event-based Systems","volume":"298 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114575542","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
Software-defined Adaptive Resource Management for Cloud-hosted Group Communication Applications: Poster 用于云托管组通信应用程序的软件定义自适应资源管理:海报
Prithviraj Patil, Akram Hakiri, A. Gokhale
{"title":"Software-defined Adaptive Resource Management for Cloud-hosted Group Communication Applications: Poster","authors":"Prithviraj Patil, Akram Hakiri, A. Gokhale","doi":"10.1145/3093742.3095087","DOIUrl":"https://doi.org/10.1145/3093742.3095087","url":null,"abstract":"Many cloud-hosted applications and cloud infrastructure management services with publish/subscribe semantics rely heavily on the use of group communications. Although multicast is useful for efficient group communications, traditional IP multicast has seen very low adoption in cloud data center networks (DCNs) due to issues with its stability and scalability. The introduction of Software-defined Networking (SDN) in DCNs has provided new opportunities for re-engineering and effectively utilizing multicast capabilities that can overcome existing impediments to the adoption of IP multicast. To that end this paper presents an adaptive and flexible middleware solution called SDN-based Multicast (SDMC), which provides group communication capabilities in DCNs in a way that is both network load-aware and switch memory-efficient. Applications using SDMC remain agnostic to the underlying group communication semantics, which SDMC provides efficiently by dynamically adapting between unicast and multicast in accordance with changing network bandwidth and switch memory usage.","PeriodicalId":325666,"journal":{"name":"Proceedings of the 11th ACM International Conference on Distributed and Event-based Systems","volume":"224 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132230962","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
Raphtory: Decentralised Streaming for Temporal Graphs: Poster Raphtory:时间图的去中心化流:海报
Benjamin A. Steer, F. Cuadrado, R. Clegg
{"title":"Raphtory: Decentralised Streaming for Temporal Graphs: Poster","authors":"Benjamin A. Steer, F. Cuadrado, R. Clegg","doi":"10.1145/3093742.3093903","DOIUrl":"https://doi.org/10.1145/3093742.3093903","url":null,"abstract":"Temporal graphs capture the relationships within data as they develop throughout time. Intuition, therefore, suggests that this model would fit naturally within a streaming architecture, where new points of comparison can be inserted directly into the graph as they arrive from the data source. However, the current state of the art has yet to join these two concepts, supporting either temporal analysis on static data or streaming into one-dimensional dynamic graphs. To solve this problem we introduce Raphtory, a temporal graph streaming platform, which maintains a full graph history whilst efficiently inserting new alterations.","PeriodicalId":325666,"journal":{"name":"Proceedings of the 11th ACM International Conference on Distributed and Event-based Systems","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126293884","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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