Publication Type

Conference Proceeding Article

Version

acceptedVersion

Publication Date

12-2018

Abstract

This paper analyzes a human-centric framework, called SmartABLE, for easy retrieval of the sensor values from pervasively deployed smart objects in a campus-like environment. In this framework, smartphones carried by campus occupants act as data mules, opportunistically retrieving data from nearby BLE (Bluetooth Low Energy) equipped smart object sensors and relaying them to a backend repository. We focus specifically on dynamically varying the transmission power of the deployed BLE beacons, so as to extend their operational lifetime without sacrificing the frequency of sensor data retrieval. We propose a memetic algorithm-based power adaptation strategy that can handle deployments of thousands of beacons and tackles two distinct objectives: (1) maximizing BLE beacon lifetime, and (2) reducing the BLE scanning energy of the mules. Using real-world movement traces on the Singapore Management University campus, we show that the benefit of such mule movement-aware power adaptation: it provides reliably frequent retrieval of BLE sensor data, while achieving a significant (5-fold) increase in the sensor lifetime, compared to a traditional fixed-power approach.

Keywords

BLE beacon, Data muling, Transmission power adaptation

Discipline

Numerical Analysis and Scientific Computing | Software Engineering

Research Areas

Software and Cyber-Physical Systems

Publication

2018 IEEE 24th International Conference on Parallel and Distributed Systems ICPADS: Singapore, December 11-13: Proceedings

First Page

962

Last Page

971

ISBN

9781538673089

Identifier

10.1109/PADSW.2018.8644545

Publisher

IEEE

City or Country

Piscataway, NJ

Copyright Owner and License

Authors

Additional URL

https://doi.org/10.1109/PADSW.2018.8644545

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