Clustering Combined with Bio Inspired Routing in Underwater Wireless Sensor Networks

Souiki, Sihem; Hadjila, Mourad; Feham, Mohammed

doi:10.1145/2816839.2816888

Cited by 3 publications

(1 citation statement)

References 13 publications

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“…In this work, we used the same energy model as [23], [24], which was proposed for underwater acoustic networks. According to this model, to achieve a power level P0 at a receiver at a distance d, the transmitter power ETX(d) must be:…”

Section: Energy Modelmentioning

confidence: 99%

An energy aware scheme for layered chain in underwater wireless sensor networks using genetic algorithm

Souiki

Irid

Hadjila

2021

IJECE

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Extending the network lifetime is a very challenging problem that needs to be taken into account during routing data in wireless sensor networks in general and particularly in underwater wireless sensor networks (UWSN). For this purpose, the present paper proposes a multilayer chain based on genetic algorithm routing (MCGA) for routing data from nodes to the sink. This algorithm consists to create a limited number of local chains constructed by using genetic algorithm in order to obtain the shortest path between nodes; furthermore, a leader node (LN) is elected in each chain followed by constructing a global chain containing LNs. The selection of the LN in the closest chain to the sink is as follows: Initially, the closest node to sink is elected LN in this latter because all nodes have initially the same energy value; then the future selection of the LN is based on the residual energy of the nodes. LNs in the other chains are selected based on the proximity to the previous LNs. Data transmission is performed in two steps: intra-chain transmission and inter-chain transmission. Furthermore, MCGA is simulated for different scenarios of mobility and density of nodes in the networks. The performance evaluation of the proposed technique shows a considerable reduction in terms of energy consumption and network lifespan.

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Section: Energy Modelmentioning

confidence: 99%