ApproxIoT: Approximate Analytics for Edge Computing

Zhenyu Wen, Do Le Quoc, Pramod Bhatotia, Ruichuan Chen, Myungjin Lee

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

IoT-enabled devices continue to generate a massive amount of data. Transforming this continuously arriving raw data into timely insights is critical for many modern online services. For such settings, the traditional form of data analytics over the entire dataset would be prohibitively limiting and expensive for supporting real-time stream analytics.
In this work, we make a case for approximate computing for data analytics in IoT settings. Approximate computing aims for efficient execution of workflows where an approximate output is sufficient instead of the exact output. The idea behind approximate computing is to compute over a representative sample instead of the entire input dataset. Thus, approximate computing — based on the chosen sample size — can make a systematic tradeoff between the output accuracy and computation efficiency.
This motivated the design of APPROXIOT— a data analytics system for approximate computing in IoT. To realize this idea, we designed an online hierarchical stratified reservoir sampling algorithm that uses edge computing resources to produce approximate output with rigorous error bounds. To showcase the effectiveness of our algorithm, we implemented APPROXIOT based on Apache Kafka and evaluated its effectiveness using a set of microbenchmarks and real-world case studies. Our results show that APPROXIOT achieves a speedup 1.3×—9.9× with varying sampling fraction of 80% to 10% compared to simple random sampling.
Original languageEnglish
Title of host publication2018 IEEE 38th International Conference on Distributed Computing Systems (ICDCS)
Place of PublicationVienna, Austria
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages411-421
Number of pages11
ISBN (Electronic)978-1-5386-6871-9
ISBN (Print)978-1-5386-6872-6
DOIs
Publication statusPublished - 23 Jul 2018
Event38th IEEE International Conference on Distributed Computing Systems - Vienna, Austria
Duration: 2 Jul 20185 Jul 2018
http://icdcs2018.ocg.at/

Publication series

Name
PublisherIEEE
ISSN (Electronic)2575-8411

Conference

Conference38th IEEE International Conference on Distributed Computing Systems
Abbreviated titleICDCS 2018
Country/TerritoryAustria
CityVienna
Period2/07/185/07/18
Internet address

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