Dynamic Buffer Sizing for Out-of-order Event Compensation for Time-sensitive Applications

Author:

Weiss Wolfgang1ORCID,Jiménez Víctor J. Expósito2ORCID,Zeiner Herwig1ORCID

Affiliation:

1. JOANNEUM RESEARCH Forschungsgesellschaft mbH, Austria

2. VIRTUAL VEHICLE Research GmbH, Inffeldgasse, Graz, Austria

Abstract

Today’s sensor network implementations often comprise various types of nodes connected with different types of networks. These and various other aspects influence the delay of transmitting data and therefore of out-of-order data occurrences. This turns into a crucial problem in time-sensitive applications where data must be processed promptly and decisions must be reliable. In this article, we research dynamic buffer sizing algorithms for multiple, distributed, and independent sources, which reorder event streams, thus enabling subsequent time-sensitive applications to work correctly. To be able to evaluate such algorithms, we had to record datasets first. Five novel dynamic buffer sizing algorithms were implemented and compared to state-of-the-art approaches in this domain. The evaluation has shown that the use of a dynamic time-out buffering method is preferable over a static buffer. The higher the variation of the network or other influences in the environment, the more necessary it becomes to use an algorithm that dynamically adapts its buffer size. These algorithms are universally applicable, easy to integrate in existing architectures, and particularly interesting for time-sensitive applications. Dynamic time-out buffering is still a trade-off between reaction time and out-of-order event compensation.

Funder

Bundesministerium für Klimaschutz, Umwelt, Energie, Mobilität, Innovation und Technologie

Steirische Wirtschaftsförderungsgesellschaft

Bundesministerium für Digitalisierung und Wirtschaftsstandort

Bundesministerium für Bildung, Wissenschaft und Forschung

Österreichische Forschungsförderungsgesellschaft

Electronic Components and Systems for European Leadership

Publisher

Association for Computing Machinery (ACM)

Subject

Computer Networks and Communications

Reference25 articles.

1. A Declarative Framework for Matching Iterative and Aggregative Patterns against Event Streams

2. Exploiting k-constraints to reduce memory overhead in continuous queries over data streams;Babu Shivnath;ACM Trans. Datab. Syst.,2004

3. High-performance dynamic pattern matching over disordered streams

Cited by 5 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Optimizing Time Series Queries with Versions;Proceedings of the ACM on Management of Data;2024-05-29

2. Determining Exact Quantiles with Randomized Summaries;Proceedings of the ACM on Management of Data;2024-03-12

3. Time-tired compaction: An elastic compaction scheme for LSM-tree based time-series database;Advanced Engineering Informatics;2024-01

4. Separation or Not: On Handing Out-of-Order Time-Series Data in Leveled LSM-Tree;2022 IEEE 38th International Conference on Data Engineering (ICDE);2022-05

5. s2p: Provenance Research for Stream Processing System;Applied Sciences;2021-06-15

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3