Routing Protocol with Improved Reliability

—In this paper, a trade-off between the energy consumption and network lifetime is considered. This paper proposes an optimal routing protocol called Energy Dynamic Adaptive Routing (EDAR) protocol. The DAR protocol maintains a tradeoff between the reliability or packet delivery ratio (PDR) of sensor nodes and Bit Error Ratio (BER) using optimal dynamic adaptive routing approach. The proposed approach operates on three different phases, namely, initialization, dynamic routing and transmission. During initial phase, all the nodes in the UWSN share location and residual energy information among all the nodes in the network. During dynamic routing phase, an optimal Directed Acyclic Graph (DAG) based route selection is exploited to select the neighbor and successor nodes. This facilitates the successive routing to transmit the packets from one node to another. Here, the cost function with directed acyclic graph is utilized for better transmission of packets. The experimental results show that proposed method encounters the issues raised in conventional protocol and improves the reliability of packets with higher BER.

[1]  Hai-yan Wang,et al.  Efficient convex optimization method for underwater passive source localization based on RSS with WSN , 2012, 2012 IEEE International Conference on Signal Processing, Communication and Computing (ICSPCC 2012).

[2]  Defeng Huang,et al.  A slotted CSMA based reinforcement learning approach for extending the lifetime of underwater acoustic wireless sensor networks , 2013, Comput. Commun..

[3]  Z.A. Khan,et al.  Forwarding Nodes Constraint based DBR (CDBR) and EEDBR (CEEDBR) in Underwater WSNs , 2014, FNC/MobiSPC.

[4]  Nadeem Javaid,et al.  SEDG: Scalable and Efficient Data Gathering Routing Protocol for Underwater WSNs , 2015, ANT/SEIT.

[5]  Guy Pujolle,et al.  2D-UBDA: A novel 2-Dimensional underwater WSN barrier deployment algorithm , 2015, 2015 IFIP Networking Conference (IFIP Networking).

[6]  Nadeem Javaid,et al.  The 6th International Conference on Ambient Systems, Networks and Technologies (ANT 2015) DSM: Dynamic Sink Mobility Equipped DBR for Underwater WSNs , 2015 .

[7]  Nadeem Javaid,et al.  ARCUN: Analytical Approach towards Reliability with Cooperation for Underwater WSNs , 2015, ANT/SEIT.

[8]  Nadeem Javaid,et al.  EEIRA: An Energy Efficient Interference and Route Aware Protocol for Underwater WSNs , 2016, 2016 10th International Conference on Complex, Intelligent, and Software Intensive Systems (CISIS).

[9]  Guy Pujolle,et al.  A novel 3D underwater WSN deployment strategy for full-coverage and connectivity in rivers , 2016, 2016 IEEE International Conference on Communications (ICC).

[10]  Syed Hassan Ahmed,et al.  Energy efficient chain based routing protocol for underwater wireless sensor networks , 2017, J. Netw. Comput. Appl..

[11]  Rui Wang,et al.  Improved reverse localization schemes for underwater wireless sensor networks: poster abstract , 2017, IPSN.

[12]  Nadeem Javaid,et al.  Balanced Energy Consumption Based Adaptive Routing for IoT Enabling Underwater WSNs , 2017, IEEE Access.

[13]  Nadeem Javaid,et al.  Establishing a Cooperation-Based and Void Node Avoiding Energy-Efficient Underwater WSN for a Cloud , 2017, IEEE Access.

[14]  Sabu M. Thampi,et al.  Fault-resilient localization for underwater sensor networks , 2017, Ad Hoc Networks.

[15]  Dajun Sun,et al.  Error control and adjustment method for underwater wireless sensor network localization , 2018 .

[16]  S. Vijayachitra,et al.  DECSA: hybrid dolphin echolocation and crow search optimization for cluster-based energy-aware routing in WSN , 2018, Neural Computing and Applications.

[17]  Shabnam Sharma,et al.  A New Bat Algorithm with Distance Computation Capability and Its Applicability in Routing for WSN , 2019 .

[18]  Yu-Yi Chen,et al.  Secure Routing for WSN-Based Tactical-Level Intelligent Transportation Systems , 2019 .