Modelling Networks as Neighborly Irregular Graphs

Today’s world is filled with numerous computing devices and electronic gadgets connected to the Internet. These devices continuously sense and deliver their desired task autonomously or via owners. Domestic applications like healthcare monitoring systems, smart farming, noise pollution control, etc....

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Bibliographic Details
Published in:Wireless personal communications 2020-11, Vol.115 (1), p.391-400
Main Authors: Muthuchelvam, M., Kowshalya, A. Meena
Format: Article
Language:English
Subjects:
Algorithms
Communications Engineering
Computer Communication Networks
Electronic devices
Engineering
Irrigation systems
Networks
Noise control
Noise monitoring
Noise pollution
Pollution control
Pollution monitoring
Sensors
Signal,Image and Speech Processing
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Summary:Today’s world is filled with numerous computing devices and electronic gadgets connected to the Internet. These devices continuously sense and deliver their desired task autonomously or via owners. Domestic applications like healthcare monitoring systems, smart farming, noise pollution control, etc., involves many sensors and wearables that tirelessly estimate, evaluate and report the desired outcome. There are circumstances where two or more sensors at the same level, sense the same information and rely to the controller/base station. Handling and processing of such duplicate information results in increased overhead messages and reduced lifetime of sensors. This paper proposes a novel idea to model a network as a Neighborly Irregular graph so that optimal placement of sensor nodes can be guaranteed and communication between sensors at the same level is restricted. A simple and novel algorithm to construct Neighborly Irregular graph is proposed which converts the underlying network to a Neighborly Irregular graph if the network is not Neighborly Irregular. The proposed idea is tested with smart irrigation system in real time to prove its effectiveness. Experimental results prove that the message overheads are drastically reduced when the underlying network is Neighborly Irregular.
ISSN:0929-6212
1572-834X
DOI:10.1007/s11277-020-07577-8