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Authors: Anubhuti Garg and Amiya Nayak

Affiliation: University of Ottawa, Canada

Keyword(s): Participatory Sensing, Localization, Collaborative.

Related Ontology Subjects/Areas/Topics: Applications and Uses ; Cooperative Mobile Systems ; Localization and Positioning Schemes ; Mobile Software and Services ; Sensor Networks ; Sensor, Mesh and Ad Hoc Communications and Networks ; Telecommunications ; Ubiquitous Wireless Services and Protocols ; Vehicular Networks ; Wireless and Mobile Technologies ; Wireless Information Networks and Systems

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 ex isting 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. (More)

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Paper citation in several formats:
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 (ICETE 2017) - WINSYS; ISBN 978-989-758-261-5; ISSN 2184-3236, SciTePress, pages 45-54. DOI: 10.5220/0006436000450054

@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 (ICETE 2017) - WINSYS},
year={2017},
pages={45-54},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006436000450054},
isbn={978-989-758-261-5},
issn={2184-3236},
}

TY - CONF

JO - Proceedings of the 14th International Joint Conference on e-Business and Telecommunications (ICETE 2017) - WINSYS
TI - Crowdsourcing Location Sensitive Data for Dynamic Scenario by Adaptive Role Assignment
SN - 978-989-758-261-5
IS - 2184-3236
AU - Garg, A.
AU - Nayak, A.
PY - 2017
SP - 45
EP - 54
DO - 10.5220/0006436000450054
PB - SciTePress