Paper Info
Title
A Nature-Inspired Node Deployment Strategy for Connected Confident Information Coverage in Industrial Internet of Things
Abstract
The ever-growing Industrial Internet of Things (IoT) provides a powerful method to sense a series of critical industrial environments. This paper studies how to deploy the fixed number of IoT nodes so that the network lifetime is maximized in a sensing field with obstacles while guaranteeing the requirements of confident information coverage, network connectivity, energy efficiency, fault tolerance, and reliability. An IoT node deployment scheme based on an improved nature-inspired genetic algorithm is proposed to solve the defined constrained optimization problem. In the proposed IoT node deployment scheme, we utilize a population initialization based on the Delaunay triangulation to generate the better initial population, a chromosome modification operation to achieve both connectivity and coverage for each chromosome and a chromosome mirror-crossover operation to produce the better offsprings. Experimental results show that our deployment schema equips better performance in terms of longer network lifetime and comparable coverage ratio compared with the other four peer algorithms.
Year
DOI
Venue
2019
10.1109/JIOT.2019.2896581
IEEE Internet of Things Journal
Keywords
Field
DocType
Peer-to-peer computing,Biological cells,Fault tolerance,Fault tolerant systems,Genetic algorithms,Internet of Things,Sociology
Information coverage,Population,Software deployment,Computer science,Efficient energy use,Computer network,Initialization,Schema (psychology),Genetic algorithm,Delaunay triangulation,Distributed computing
Journal
Volume
Issue
ISSN
6
6
2327-4662
Citations 
PageRank 
References 
4
0.38
0
Authors
5
Name
Order
Citations
PageRank
Lu Dai141.05
Bang Wang280957.74
Laurence T. Yang36870682.61
Xianjun Deng412715.27
Lingzhi Yi5393.97