Open Access
ARTICLE
Provisioning Intelligent Water Wave Optimization Approach for Underwater Acoustic Wireless Sensor Networks
1 Department of Computer Science and Engineering, Vidhyaa Vikas College of Engineering and Technology, Tiruchengode, Namakkal, Tamilnadu, India
2 Department of Computer Science and Engineering, KSR College of Engineering (Autonomous), Tiruchengode, Namakkal, Tamilnadu, India
* Corresponding Author: M. Manikandan. Email:
Computer Systems Science and Engineering 2022, 43(2), 625-641. https://doi.org/10.32604/csse.2022.022662
Received 14 August 2021; Accepted 18 October 2021; Issue published 20 April 2022
Abstract
In the Acoustics channel, it is incredibly challenging to offer data transfer for time-sourced applications in an energy-efficient manner due to higher error rate and propagation delay. Subsequently, conventional re-transmission over any failure generally initiates significantly larger end-to-end delay, and therefore it is not probable for time-based services. Moreover, standard techniques without any re-transmission consume enormous energy. This investigation proposes a novel multi-hop energy-aware transmission-based intelligent water wave optimization strategy. It ensures reduced end-to-end while attaining potential amongst overall energy efficiency end-to-end packet delay. It merges a naturally inspired meta-heuristic approach with multi-hop routing for data packets to reach the destination. The appropriate design of this Meta heuristic-based energy-aware scheme consumes lesser energy than the conventional one-hop transmission strategy without re-transmission. However, there is no hop-by-hop re-transmission facilitated. The proposed model shows only lesser delay than conventional methods with re-transmission. This work facilitates extensive work to carry out the proposed model performance with the MATLAB simulation environment. The results illustrate that the model is exceptionally energy-efficient with lesser packet delays. With 500 nodes, the packet delivery ratio of proposed model is 100%, average delay is reduced by 2%, total energy consumption is 8 J, average packet redundancy is 1.856, and idle energy is 6.9Mwh. The proposed model outperforms existing approaches like OSF, AOR, and DMR respectively.Keywords
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