DIEER: Delay-Intolerant Energy-Efficient Routing with Sink Mobility in Underwater Wireless Sensor Networks

• Main Authors: Kamran Latif, Nadeem Javaid, Imdad Ullah, Zeeshan Kaleem, Zafar Abbas, Long D. Nguyen
• Format: Article
• Language: English
• Published: MDPI AG 2020-06-01
• Series: Sensors
• Subjects: delay sensitive; under water WSN routing; energy-efficient routing; wireless sensor networks; sink mobility
• Online Access: https://www.mdpi.com/1424-8220/20/12/3467

Underwater Wireless Sensor Networks (UWSNs) are an enabling technology for many applications in commercial, military, and scientific domains. In some emergency response applications of UWSN, data dissemination is more important, therefore these applications are handled differently as compared to energy-focused approaches, which is only possible when propagation delay is minimized and packet delivery at surface sinks is assured. Packet delivery underwater is a serious concern because of harsh underwater environments and the dense deployment of nodes, which causes collisions and packet loss. Resultantly, re-transmission causes energy loss and increases end-to-end delay (<inline-formula> <math display="inline"> <semantics> <msub> <mi>D</mi> <mrow> <mi>E</mi> <mn>2</mn> <mi>E</mi> </mrow> </msub> </semantics> </math> </inline-formula>). In this work, we devise a framework for the joint optimization of <i>sink mobility</i>, <i>hold and forward mechanisms</i>, <i>adoptive depth threshold</i> (<inline-formula> <math display="inline"> <semantics> <msub> <mi>d</mi> <mrow> <mi>t</mi> <mi>h</mi> </mrow> </msub> </semantics> </math> </inline-formula>) and <i>data aggregation with pattern matching</i> for reducing nodal propagation delay, maximizing throughput, improving network lifetime, and minimizing energy consumption. To evaluate our technique, we simulate the three-dimensional (3-D) underwater network environment with mobile sink and dense deployments of sensor nodes with varying communication radii. We carry out scalability analysis of the proposed framework in terms of network lifetime, throughput, and packet drop. We also compare our framework to existing techniques, i.e., Mobicast and iAMCTD protocols. We note that adapting varying <inline-formula> <math display="inline"> <semantics> <msub> <mi>d</mi> <mrow> <mi>t</mi> <mi>h</mi> </mrow> </msub> </semantics> </math> </inline-formula> based on node density in a range of network deployment scenarios results in a reduced number of re-transmissions, good energy conservation, and enhanced throughput. Furthermore, results from extensive simulations show that our proposed framework achieves better performance over existing approaches for real-time delay-intolerant applications.