Crowdsourcing Location Sensitive Data for Dynamic Scenario by Adaptive Role Assignment

Anubhuti Garg, Amiya Nayak

2017

Abstract

The existing technique for performing crowdsourced, location-based sensing activity minimizes energy consumption by eliminating the use of GPS by some devices. For this, server detects a set of participants for the role of broadcaster which must turn-on their GPS to collect location information and broadcast it to neighbouring devices for their position calculation. However, if new devices join the region then they cannot participate in the ongoing sensing task until next localization phase when server reassigns role to all participants. In addition to this, if devices leave the region then their neighbouring devices may require a change of role. The current work does not provide solution to such dynamic scenarios. We provide time and energy efficient approach to allocate role adaptively to participants when they join or leave the region of interest. For this we propose incremental algorithms to assign role for the new participants joining the region and for modifying the roles of existing participants when some devices leave the region. This also eliminates the need for rerunning the role-assignment algorithm over the entire set of participants for every insertion and deletion. The proposed solutions are capable of saving 95-99.9% of the role assignment time without compensating energy needs.

Paper Citation

in Harvard Style

Garg A. and Nayak A. (2017). Crowdsourcing Location Sensitive Data for Dynamic Scenario by Adaptive Role Assignment . In Proceedings of the 14th International Joint Conference on e-Business and Telecommunications - Volume 2: WINSYS, (ICETE 2017) ISBN 978-989-758-261-5, pages 45-54. DOI: 10.5220/0006436000450054

in Bibtex Style

@conference{winsys17,
author={Anubhuti Garg and Amiya Nayak},
title={Crowdsourcing Location Sensitive Data for Dynamic Scenario by Adaptive Role Assignment},
booktitle={Proceedings of the 14th International Joint Conference on e-Business and Telecommunications - Volume 2: WINSYS, (ICETE 2017)},
year={2017},
pages={45-54},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006436000450054},
isbn={978-989-758-261-5},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 14th International Joint Conference on e-Business and Telecommunications - Volume 2: WINSYS, (ICETE 2017)
TI - Crowdsourcing Location Sensitive Data for Dynamic Scenario by Adaptive Role Assignment
SN - 978-989-758-261-5
AU - Garg A.
AU - Nayak A.
PY - 2017
SP - 45
EP - 54
DO - 10.5220/0006436000450054