Name
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. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/ICDCS.2018.00048 | 2018 IEEE 38th International Conference on Distributed Computing Systems (ICDCS) |
Keywords | Field | DocType |
edge computing,IoT,approximate computing,big data | Edge computing,Approximation algorithm,Data analysis,Computer science,Reservoir sampling,Sampling (statistics),Analytics,Computer engineering,Sampling fraction,Speedup,Distributed computing | Conference |
ISSN | ISBN | Citations |
1063-6927 | 978-1-5386-6872-6 | 5 |
PageRank | References | Authors |
0.42 | 19 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zhenyu Wen | 1 | 95 | 7.51 |
| Le Quoc, D. | 2 | 55 | 8.21 |
| Pramod Bhatotia | 3 | 414 | 28.94 |
| Ruichuan Chen | 4 | 205 | 18.95 |
| Myung-Jin Lee | 5 | 242 | 21.48 |