Kea: A Computation Offloading System for Smartphone Sensor Data

Roshan Bharath Das, Nicolae Vladimir Bozdog, Marc X. Makkes, Henri Bal

Research output: Chapter in Book / Report / Conference proceedingConference contributionAcademicpeer-review

Abstract

Nowadays smartphones are equipped with many sensors which applications can continuously invoke to acquire real-time sensor information, such as GPS tracking. Due to the resource-constrained nature of the smartphones, it is often beneficial if the processing of the sensor data is offloaded to a remote resource. However, the decision to offload the computation depends on a multitude of factors such as the hardware capabilities of the phone, the communication energy and latency and the characteristics of the stream computations, e.g., window size, sensor frequency and operational complexity.In this paper we introduce Kea, a profiling-based computation offloading system that automatically decides whether offloading is beneficial for smartphones. The decision making is based on two criteria: the power consumption of the application and the elapsed time for processing the sensor data. Our evaluation results show that unexpected factors such as CPU frequency scaling and the network state also influence the decision-making process. In addition, we show that Kea's profiling overhead is negligible.

Original languageEnglish
Title of host publicationProceedings - 2017 IEEE 9th International Conference on Cloud Computing Technology and Science, CloudCom 2017
PublisherIEEE Computer Society
Pages9-16
Number of pages8
ISBN (Electronic)9781538606926
DOIs
Publication statusPublished - 27 Dec 2017
Event9th IEEE International Conference on Cloud Computing Technology and Science, CloudCom 2017 - Hong Kong, Hong Kong
Duration: 11 Dec 201714 Dec 2017

Publication series

NameProceedings of the International Conference on Cloud Computing Technology and Science, CloudCom
Volume2017-December
ISSN (Print)2330-2194
ISSN (Electronic)2330-2186

Conference

Conference9th IEEE International Conference on Cloud Computing Technology and Science, CloudCom 2017
CountryHong Kong
CityHong Kong
Period11/12/1714/12/17

Keywords

  • Context-aware computing
  • Mobile cloud computing
  • Mobile phone sensing
  • Models computation offloading

Fingerprint Dive into the research topics of 'Kea: A Computation Offloading System for Smartphone Sensor Data'. Together they form a unique fingerprint.

Cite this