Efficient Geospatial Data Collection in IoT Networks for Mobile Edge Computing
The Mobile Edge Computing (MEC) paradigm changes the role of edge devices from data producers and service requesters to data consumers and processors. MEC mitigates the bandwidth constraint between the edge server and the cloud by directly processing the large data created by the sheer volume of IoT devices in the edge locally. An efficient data-gathering scheme is crucial for providing quality of service (QoS) within MEC. In this paper, we proposed an efficient data collection scheme that only gathers the necessary data from IoT devices like wireless sensors along a trajectory for local services based on geospatial constraints. We only use a vector of the minimal distance of hops (DV-Hop) to the anchor nodes selected by the fog server, instead of using GPS data. The proposed scheme includes a lossy compression algorithm that could compress each routing message, thus reducing the response time. In this paper, the experiments are conducted to evaluate the performance of our data collection using the encoded trajectory routing scheme compared with others using a TOSSIM simulator, and also using the powerTOSSIM-Z with real sensor motes. Our scheme performs better in terms of latency, reliability, coverage, and energy usage compared to other state-of-the-art schemes.
X. Cao and S. K. Madria, "Efficient Geospatial Data Collection in IoT Networks for Mobile Edge Computing," Proceedings of the 18th International Symposium on Network Computing and Applications (2019, Cambridge, UK), Institute of Electrical and Electronics Engineers (IEEE), Sep 2019.
The definitive version is available at https://doi.org/10.1109/NCA.2019.8935061
18th IEEE International Symposium on Network Computing and Applications, NCA 2019 (2019: Sep. 26-28, Cambridge, UK)
Center for Research in Energy and Environment (CREE)
Keywords and Phrases
Data acquisition; Data handling; Edge computing; Quality of service; Sensor nodes, Bandwidth constraint; Data collection scheme; Geo-spatial data; Lossy compressions; Minimal distance; Service requesters; State-of-the-art scheme; Wireless sensor, Internet of things
International Standard Book Number (ISBN)
Article - Conference proceedings
© 2019 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.
01 Sep 2019