Energy Efficiency Analysis of Effective Hydrocast for Underwater Communication

Underwater acoustic communication is difficult due to a low propagation speed, limited bandwidth, and energy consumption. There is a communication void primarily due to oceanic currents, which cause node mobility. Hence, protocol recovery has been focused on two means: Eulerian and Lagrangian. This work provides an analysis using the Eulerian approach with internetworking between sensors, wherein an effective hydrocast is proposed with the concept of triangulation to avoid long detour paths for recovery. The protocol Effective Hydrocast uses normalized advance wherethe cost is calculated with energy consumption, throughput, packet delivery ratio and propagation delay. Simulations with the ns2 simulator using an aquasim patch with the development of an effective hydrocast protocol are done for throughput with two values of bandwidth minimal 3 kHz and maximal 1000 kHz. The results of throughput are compared with depth based routing, energy efficient depth based routing, energy efficient fitness based routing, hydrocast and void aware pressure routing (VAPR) of which effective hydrocast is better. Then, values obtained for energy consumption between an effective hydrocast and VAPR obtained using ns2 simulation is subjected to a time series analysis using a statistical package for social science. An autoregressive integrated moving average is developed and the best fitting model is estimated with the Bayesian information criterion, where an effective hydrocast is found to be better than VAPR.

[1]  Timothy K. Shih,et al.  Survey on underwater delay/disruption tolerant wireless sensor network routing , 2014 .

[2]  Seungjoon Lee,et al.  Efficient geographic routing in multihop wireless networks , 2005, MobiHoc '05.

[3]  Mario Gerla,et al.  Pressure Routing for Underwater Sensor Networks , 2010, 2010 Proceedings IEEE INFOCOM.

[4]  Mohd Murtadha Mohamad,et al.  Greedy Routing in Underwater Acoustic Sensor Networks: A Survey , 2013, Int. J. Distributed Sens. Networks.

[5]  J. V. Anand,et al.  Regression based analysis of effective hydrocast in underwater environment , 2014, TENCON 2014 - 2014 IEEE Region 10 Conference.

[6]  Nadeem Javaid,et al.  iAMCTD: Improved Adaptive Mobility of Courier Nodes in Threshold-Optimized DBR Protocol for Underwater Wireless Sensor Networks , 2014, Int. J. Distributed Sens. Networks.

[7]  Dongkyun Kim,et al.  An Energy Efficient Localization-Free Routing Protocol for Underwater Wireless Sensor Networks , 2012, Int. J. Distributed Sens. Networks.

[8]  Mario Gerla,et al.  VAPR: Void-Aware Pressure Routing for Underwater Sensor Networks , 2013, IEEE Transactions on Mobile Computing.

[9]  Baozhi Chen,et al.  QUO VADIS: QoS-aware underwater optimization framework for inter-vehicle communication using acoustic directional transducers , 2011, 2011 8th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks.

[10]  Peng Xie,et al.  Void Avoidance in Three-Dimensional Mobile Underwater Sensor Networks , 2009, WASA.

[11]  Dario Pompili,et al.  Underwater acoustic sensor networks: research challenges , 2005, Ad Hoc Networks.

[12]  Liu Guangzhong,et al.  Depth-Based Multi-hop Routing protocol for Underwater Sensor Network , 2010, 2010 The 2nd International Conference on Industrial Mechatronics and Automation.

[13]  S. Basagni,et al.  Channel-aware routing for underwater wireless networks , 2012, 2012 Oceans - Yeosu.

[14]  G. Schwarz Estimating the Dimension of a Model , 1978 .

[15]  Guy Melard,et al.  Algorithm AS197: A fast algorithm for the exact likelihood of autoregressive-moving average models , 1984 .

[16]  Jun-Hong Cui,et al.  DBR: Depth-Based Routing for Underwater Sensor Networks , 2008, Networking.

[17]  Md. Manowarul Islam,et al.  Energy Efficient Fitness Based Routing Protocol for Underwater Sensor Network , 2013 .

[18]  Geert Leus,et al.  Ranging in an Underwater Medium with Multiple Isogradient Sound Speed Profile Layers , 2012, Sensors.

[19]  James Preisig,et al.  Acoustic propagation considerations for underwater acoustic communications network development , 2006, Underwater Networks.

[20]  Kuei-Ping Shih,et al.  DARP: A depth adaptive routing protocol for large-scale underwater acoustic sensor networks , 2012, 2012 Oceans - Yeosu.

[21]  Antonio Alfredo Ferreira Loureiro,et al.  DCR: Depth-Controlled Routing protocol for underwater sensor networks , 2013, 2013 IEEE Symposium on Computers and Communications (ISCC).