DCR: Depth-Controlled Routing protocol for underwater sensor networks

Coutinho, Rodolfo W. L.; Vieira, Luiz F. M.; Loureiro, Antônio A. F.

doi:10.1109/iscc.2013.6754988

Cited by 64 publications

(50 citation statements)

References 12 publications

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“…Due to the complex underwater environment, considering only residual energy is not enough. The depth-controlled routing (DCR) protocol was proposed in [12]. In DCR, the underwater sensor nodes are equipped with network topology controllers, which are used to adjust their depth when the greedy geographic routing fails.…”

Section: Related Workmentioning

confidence: 99%

A Routing Protocol Based on Received Signal Strength for Underwater Wireless Sensor Networks (UWSNs)

Ke-jun

et al. 2017

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Abstract:Underwater wireless sensor networks (UWSNs) are featured by long propagation delay, limited energy, narrow bandwidth, high BER (Bit Error Rate) and variable topology structure. These features make it very difficult to design a short delay and high energy-efficiency routing protocol for UWSNs. In this paper, a routing protocol independent of location information is proposed based on received signal strength (RSS), which is called RRSS. In RRSS, a sensor node firstly establishes a vector from the node to a sink node; the length of the vector indicates the RSS of the beacon signal (RSSB) from the sink node. A node selects the next-hop along the vector according to RSSB and the RSS of a hello packet (RSSH). The node nearer to the vector has higher priority to be a candidate next-hop. To avoid data packets being delivered to the neighbor nodes in a void area, a void-avoiding algorithm is introduced. In addition, residual energy is considered when selecting the next-hop. Meanwhile, we establish mathematic models to analyze the robustness and energy efficiency of RRSS. Lastly, we conduct extensive simulations, and the simulation results show RRSS can save energy consumption and decrease end-to-end delay.

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Section: Related Workmentioning

confidence: 99%

A Routing Protocol Based on Received Signal Strength for Underwater Wireless Sensor Networks (UWSNs)

Ke-jun

et al. 2017

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“…14 The void recovery paradigm with mechanical devices such as a floating buoy, autonomous underwater vehicles as in QUO VADIS, 15 and Depth Controlled routing 16 are not preferred due to the extra energy cost incurred by it.…”

Section: Protocols For Void Avoidance With Recovery Using the Partialmentioning

confidence: 99%

Energy Efficiency Analysis of Effective Hydrocast for Underwater Communication

Anand¹,

Titus²

2017

IJAV

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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.

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“…Also using mobility controlled, DCR [12] routing protocol organizes the static underwater sensor network topology before the beginning of the sensing phase through the depth adjustment of some nodes to reduce the amount of void and disconnected nodes. Using similar idea, in [13] the authors proposed a centralized and distributed topology control algorithm that moves void nodes to new depths aim to resume the greedy forwarding routing in longterm monitoring underwater sensor networks; and, in [14] the authors proposed the GEDAR routing protocol that uses the depth adjustment capability of the nodes to move void nodes for new depth locations to aim resume greedy forwarding in the scenario of short-term underwater mobile sensor networks.…”

Section: Related Workmentioning

confidence: 99%

“…The main disadvantage of the mobility controlled methodology is the energy cost to move void nodes. Algorithm 3 presents a centralized procedure based on the works [12]- [14].…”

Section: Local Maximum Recovery Algorithmsmentioning

confidence: 99%

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Local Maximum Routing Recovery in Underwater Sensor Networks: Performance and Trade-offs

Coutinho

Boukerche

Vieira

et al. 2014

2014 IEEE 22nd International Symposium on Modelling, Analysis &Amp; Simulation of Computer and Telecommunication Systems

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Local maximum problem, where the node fails in determine the next-hop neighbor to continue forwarding the packet towards the destination, severely degrades the performance of geographic routing protocols. This degradation is more substantial in underwater sensor networks, that intrinsically have harsh environments and high energy consumption due to the underwater acoustic communication characteristics. In this work, we focus on the performance of the most commonly three methodologies used in design of local maximum recovery procedures of geographic routing protocols for underwater sensor networks: power control, bypassing void regions, and mobility controlled. Taking into consideration the underwater acoustic communication characteristics, we further develop a network energy consumption model for representative solutions of local maximum recovery procedure designed from these methodologies and then we evaluate their performance in terms of the improvements on routing task and the energy consumption. Simulation results show that all three methodologies improve the routing even in hard scenarios of lower network density whereas particularities of each methodology impacts on the network energy consumption.

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DCR: Depth-Controlled Routing protocol for underwater sensor networks

Cited by 64 publications

References 12 publications

A Routing Protocol Based on Received Signal Strength for Underwater Wireless Sensor Networks (UWSNs)

A Routing Protocol Based on Received Signal Strength for Underwater Wireless Sensor Networks (UWSNs)

Energy Efficiency Analysis of Effective Hydrocast for Underwater Communication

Local Maximum Routing Recovery in Underwater Sensor Networks: Performance and Trade-offs

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