An improved DVHop localization algorithm using a novel angle based node reduction and optimization technique

Abstract Wireless sensor networks are becoming increasingly popular across a range of applications. One notable use is in seismic exploration and monitoring for oil and gas reservoirs. This application involves deploying numerous sensor nodes across outdoor fields to measure backscattered waves, which are then used to create an image of the subsurface. These sensor nodes remain active in the field for several days and must be accurately localized to ensure efficient reservoir detection. However, the Distance Vector-Hop (DVHop) algorithm, despite its simplicity, is not suitable for accurate node localization in exploration fields due to obstructions. In this paper, we propose a modified DVHop algorithm specifically designed for precise localization in such environments. Proposed algorithm uses angles between intermediate nodes to identify and circumvent nodes affected by obstructions. Distance estimation is performed using this reduced set of nodes. The estimated distances between these nodes are subsequently solved using Velocity Pausing Particle Swarm Optimization to determine the nodes’ locations. When evaluated in environments resembling exploration fields, our algorithm demonstrated an improvement of 25% to 63% in Average Localization Accuracy compared to other hop-based localization algorithms under similar conditions.

Authors

Institutions

Publication Details

Journal
Discover Applied Sciences
Published
2024-08-12
DOI
https://doi.org/10.1007/s42452-024-06144-1
Citations
1
Primary Topic
Indoor and Outdoor Localization Technologies
Type
article
Field-Weighted Citation Impact
0.21
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

An improved DVHop localization algorithm using a novel angle based node reduction and optimization technique

Soumya J. Bhat, Santhosh Krishnan Venkata
1 citations
Discover Applied Sciences
Indoor and Outdoor Localization Technologies
0.21
article

An improved DVHop localization algorithm using a novel angle based node reduction and optimization technique

Soumya J. Bhat, Santhosh Krishnan Venkata
article en
1 citations

Abstract

Abstract Wireless sensor networks are becoming increasingly popular across a range of applications. One notable use is in seismic exploration and monitoring for oil and gas reservoirs. This application involves deploying numerous sensor nodes across outdoor fields to measure backscattered waves, which are then used to create an image of the subsurface. These sensor nodes remain active in the field for several days and must be accurately localized to ensure efficient reservoir detection. However, the Distance Vector-Hop (DVHop) algorithm, despite its simplicity, is not suitable for accurate node localization in exploration fields due to obstructions. In this paper, we propose a modified DVHop algorithm specifically designed for precise localization in such environments. Proposed algorithm uses angles between intermediate nodes to identify and circumvent nodes affected by obstructions. Distance estimation is performed using this reduced set of nodes. The estimated distances between these nodes are subsequently solved using Velocity Pausing Particle Swarm Optimization to determine the nodes’ locations. When evaluated in environments resembling exploration fields, our algorithm demonstrated an improvement of 25% to 63% in Average Localization Accuracy compared to other hop-based localization algorithms under similar conditions.

Discover Applied SciencesVol. 6(8)
Manipal Academy of Higher Education (IN), Institute of Technology Management (IN)
Openalex Percentile: Top 49%
Indoor and Outdoor Localization Technologies
0.21
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.