ApproxSSPS

Overview

• ApproxSSPS ia a system for approximate processing of geo-referenced mobility data, at scale with quality of service guarantees.
• It specifically focuses on stateful aggregations (e.g., means, counts) and top-N queries.
• Also, it features a controller that interactively learns the latency statistics and calculates proper sampling rates to meet latency or/and accuracy targets.
• An overarching trait of ApproxSSPS is its ability to strike a plausible balance between latency and accuracy targets.
• We evaluate ApproxSSPS on Apache Spark Structured Streaming with real mobility data.
• We also compared ApproxSSPS against a state-of-the-art online adaptive processing system.
  • Our extensive experiments prove that ApproxSSPS can fulfill latency and accuracy targets with varying sets of parameter configurations and load intensities (i.e., transient peaks in data loads versus slow ar-riving streams).
  • Moreover, our results show that ApproxSSPS outperforms the baseline counterpart by significant magnitudes.
• In short, ApproxSSPS is a novel spatial data stream processing system that can deliver real accurate results in a timely manner, by dynamically specifying the limits on data samples.

publication: MDPI Sensors 2021 (journal impact factor (indexed in ISI Thomson Reuters): 3.576)