Palm tree structure based data aggregation and routing in underwater wireless acoustic sensor networks: Agent oriented approach

The primary constraints of Underwater Wireless Acoustic Sensor Networks (UWASNs) are limited bandwidth, node energy and latency. The process of data aggregation will ease the constraints of UWASN. In this paper, we propose a scheme for data aggregation and routing in UWASN using static and mobile ag...

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Bibliographic Details
Main Authors: Vani Krishnaswamy, Sunilkumar S. Manvi
Format: Article
Language:English
Published: Elsevier 2022-04-01
Series:Journal of King Saud University: Computer and Information Sciences
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S1319157819302848
Description
Summary:The primary constraints of Underwater Wireless Acoustic Sensor Networks (UWASNs) are limited bandwidth, node energy and latency. The process of data aggregation will ease the constraints of UWASN. In this paper, we propose a scheme for data aggregation and routing in UWASN using static and mobile agents based on palm tree structure. The main components of palm tree structure include leaflets, spines, rachis and petioles. The leaflets and smaller leaflets (fronds) are connected to the petiole through spines. The junction of petioles connects to the sink node. The proposed scheme works as follows.Firstly, fronds and leaflets connected to the petioles are created through spines. Secondly, master center nodes are selected on petiole junction using mobile agent based on the parameters such as residual energy, Euclidean distance, petiole angle and connectivity. Thirdly, local center nodes are identified on either side of leaflet and connected to the master center using a mobile agent. Fourthly, the process of local aggregation at local centers happens by taking into account of nodes along the leaflets and carry to a connected master center. Finally, the process of master aggregation at the junction of petioles and delivering the aggregated data to the sink node using a mobile agent is performed. To assess the efficacy of the scheme, simulation in different UWASN scenarios are carried out. The parameters of performance analyzed are master and local center selection time, aggregation ratio, aggregation energy, energy consumption, number of local and master centers involved in the aggregation process and lifespan of the network. We observed that proposed scheme performs better than the existing aggregation scheme.
ISSN:1319-1578