Paper Info
Title
Coverage Problem In Camera-Based Sensor Networks Using The Cuda Platform
Abstract
Closed-circuit televisions serve as prevention against crime, and many studies for closed-circuit television deployment have been conducted. The closed-circuit television deployment in downtown is similar to solving coverage problem in wireless camera-based sensor networks. The difference between the two problems is various environmental factors such as buildings, roads, camera capability, and movements of pedestrians. We use a genetic algorithm to increase the efficiency of closed-circuit television deployment in two-dimensional topography. In addition, a parallel experiment using general-purpose computing on graphics processing units is added to improve computing speed, which is a disadvantage in genetic algorithms. The target region is 500mx500m and consists of 50x50grids. The fitness of the evaluation, which refers to a detection rate, is calculated from the corresponding cell when a pedestrian moves to each cell depending on whether the pedestrian is detected. The proposed experiment was superior to the random deployment experiment by approximately 37.5%. There was no significant difference in the detection rate between the CPU experiment and a NVIDIA GeForce GTX 970 experiment in the 95% confidence interval. The efficiency of a CUDA kernel function using the NVIDIA GeForce GTX 970 graphic card was analyzed.
Year
DOI
Venue
2017
10.1177/1550147717746353
INTERNATIONAL JOURNAL OF DISTRIBUTED SENSOR NETWORKS
Keywords
Field
DocType
Sensor deployments, coverage, genetic algorithm, parallel computing, CUDA
Graphics,Pedestrian,Software deployment,CUDA,Computer science,Downtown,Real-time computing,Wireless camera,Wireless sensor network,Genetic algorithm,Distributed computing
Journal
Volume
Issue
ISSN
13
12
1550-1477
Citations 
PageRank 
References 
0
0.34
7
Authors
3
Name
Order
Citations
PageRank
Jae Hyun Seo1235.91
Yourim Yoon218517.18
Yong-Hyuk Kim335540.27