Multiobjective Optimized Deployment of Edge-Enabled Wireless Visual Sensor Networks for Target Coverage
Document Type
Article
Publication Date
9-1-2023
Abstract
In wireless visual sensor networks, the generation and transmission of huge amounts of image data consume much energy of sensor nodes (SNs), and their routing and processing take quite a long time. It is of great importance to shorten event reporting delay (ERD) and prolong network lifetime, which can be achieved by the appropriate deployment of edge nodes (ENs) that can not only collect but also process data. This work investigates how to jointly optimize SN deployment, EN deployment, data routing, and data offloading to minimize the number of deployed SNs, the number of deployed ENs, and ERD and maximize network lifetime. We formulate this problem as a mixed-integer nonlinear program and propose a multiobjective differential evolution algorithm to solve it. A large number of simulation results demonstrate that it can deliver a more accurate Pareto set than the nondominated sorting genetic algorithm III.
Identifier
85151564130 (Scopus)
Publication Title
IEEE Internet of Things Journal
External Full Text Location
https://doi.org/10.1109/JIOT.2023.3262849
e-ISSN
23274662
First Page
15325
Last Page
15337
Issue
17
Volume
10
Recommended Citation
Zhu, Xiaojian and Zhou, Mengchu, "Multiobjective Optimized Deployment of Edge-Enabled Wireless Visual Sensor Networks for Target Coverage" (2023). Faculty Publications. 1478.
https://digitalcommons.njit.edu/fac_pubs/1478