Abstract

Symmetry in nodes operation in underwater wireless sensor networks (WSNs) is crucial so that nodes consume their energy in a balanced fashion. This prevents rapid death of nodes close to water surface and enhances network life span. Symmetry can be achieved by minimizing delay and ensuring reliable packets delivery to sea surface. It is because delay minimization and reliability are very important in underwater WSNs. Particularly, in dense underworks, packets reliability is of serious concern when a large number of nodes advance packets. The packets collide and are lost. This inefficiently consumes energy and introduces extra delay as the lost packets are usually retransmitted. This is further worsened by adaptation of long routes by packets as the network size grows, as this increases the collision probability of packets. To cope with these issues, two routing schemes are designed for dense underwater WSNs in this paper: delay minimization routing (DMR) and cooperative delay minimization routing (CoDMR). In the DMR scheme, the entire network is divided into four equal regions. The minor sink nodes are placed at center of each region, one in each of the four regions. Unlike the conventional approach, the placement of minor sink nodes in the network involves timer based operation and is independent of the geographical knowledge of the position of every minor sink. All nodes having physical distance from sink lower than the communication range are able to broadcast packets directly to the minor sink nodes, otherwise multi-hopping is used. Placement of the minor sinks in the four regions of the network avoids packets delivery to water surface through long distance multi-hopping, which minimizes delay and balances energy utilization. However, DMR is vulnerable to information reliability due to single path routing. For reliability, CoDMR scheme is designed that adds reliability to DMR using cooperative routing. In CoDMR, a node having physical distance from the sink greater than its communication range, sends the information packets by utilizing cooperation with a single relay node. The destination and the relay nodes are chosen by considering the lowest physical distance with respect to the desired minor sink node. The received packets at the destination node are merged by fixed ratio combining as a diversity technique. The physical distance computation is independent of the geographical knowledge of nodes, unlike the geographical routing protocols. This makes the proposed schemes computationally efficient. Simulation shows that DMR and CoDMR algorithms outperform the counterpart algorithms in terms of total energy cost, energy balancing, packet delivery ratio (PDR), latency, energy left in the battery and nodes depleted of battery power.

Highlights

  • Underwater wireless sensor networks (WSNs) has become an interesting discipline for research because of the exclusive applications

  • As a result minimum energy left in the battery of the cooperative delay minimization routing (CoDMR)

  • The energy left in the battery of nodes of the CoDMR is near to 1500 J and the delay minimization routing (DMR) scheme maintains the highest energy of 2000 J

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Summary

Introduction

Underwater WSNs has become an interesting discipline for research because of the exclusive applications. In CoDMR, all nodes that cannot directly forward information bags to minor sinks due to limited range, use the destination and relay nodes. Unlike the conventional approach, placement of minor sink nodes is independent of the geographical position of the sink nodes, as obtaining this knowledge is really challenging in sea environment due to ocean currents and limited resources. These strategies make the DMR and CoDMR schemes easy to operate and time efficient with less complexity as compared to geographical coordinates based protocols

Literature Review
Network Initialization
Neighbour Identification and Path Setup
Best Forwarder Node Selection and Information Transition
Simulation Results and Analysis
Nodes Depleted of Battery Power
Energy Left in the Battery
Packets Delivery Ratio
Total End-to-End Delay
Total Energy Cost
Conclusions

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