A Survey on Deployment Algorithms in Underwater Acoustic Sensor Networks

Han, Guangjie; Zhang, Chenyu; Shu, Lei; Sun, Ning; Li, Qingwu

doi:10.1155/2013/314049

Cited by 78 publications

(61 citation statements)

References 36 publications

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“…A variety of approaches exist including various geometric schemes for static underwater sensor deployment [1], [2], as well as a clustering approach to maintain coverage through redundant clustered sensors [3], [4]. In [5], Mukherjee et al solved the sensor placement problem as a multiobjective optimization problem using elements from statistical mechanics to achieve a low-dimensional representation of the sensor distribution.…”

Section: Richarddtatum@navymilmentioning

confidence: 99%

Decentralized placement of heterogeneous nodes

Tatum

Bays

2016

OCEANS 2016 MTS/IEEE Monterey

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I. ABSTRACT We present a node placement algorithm for planning the deployment of a heterogeneous, underwater sensor network. Typical node placement algorithms do not account for heterogeneous node types and consequently, do not always provide accurate estimates for the total probability of success for the overall mission objective. In our approach, we derive an objective function that couples the probability of success for all node types to be used by a mixed-integer linear programming (MILP) solver for optimal placement. To reduce the computational intensity associated with the MILPbased approach, we provide an algorithm that converts the original optimization problem into several smaller optimization problems. We also describe the accompanying MILP framework that we have developed to create and maintain MILP problems.

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Section: Richarddtatum@navymilmentioning

confidence: 99%

Decentralized placement of heterogeneous nodes

Tatum

Bays

2016

OCEANS 2016 MTS/IEEE Monterey

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“…The TTCB protocol can find the optimal path between the first and the second-level cluster heads in Underwater Wireless Sensor Networks and form dynamic routing between clusters [10][11][12][13][14][15] . The TTCB protocol uses the first-level cluster heads as source nodes and each second-level cluster head as destination node of each unit respectively, using the improved ant colony algorithm to find the optimal routing between source node and destination node.…”

Section: The Election Of Routing Between Clustersmentioning

confidence: 99%

A two-tier routing protocol for cluster-based underwater heterogeneous sensor networks

Han

et al. 2014

9th International Conference on Communications and Networking in China

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An architecture of underwater sensor networks and a two-tier routing protocol for cluster-based underwater heterogeneous sensor networks-TTCB protocol have been proposed in this paper. The architecture includes the upper sensor nodes, the lower sensor nodes, sink node on the sea surface and the base stations on the land. All sensor nodes form two heterogeneous clustering structure. According to the initial energy, the remaining energy of the node, the consumption energy of the previous cluster head, the average distance between the cluster heads and other factors, the TTCB protocol elects the first-level and the second-level cluster head nodes, forms a dynamic cluster head chain. The simulation results show that the TTCB protocol can reduce the average energy consumption of nodes effectively and prolong the survival time of the network, and is suitable for a large number of monitoring nodes in underwater environments.

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“…Deployment of UWSN has attracted significant attention recently due to its tangible impact on the other aspect of UWSN. The deployment in UWSN can be classified as static and distributed deployment [3]. In static deployment, nodes are deployed manually in predefined positions and cannot move once they are deployed.…”

Section: Introductionmentioning

confidence: 99%

Deployment Protocol for Underwater Wireless Sensors Network based on Virtual Force

Almutairi¹,

Mahfoudh²

2017

ijacsa

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Abstract-Recently, Underwater Sensor Networks (UWSNs) have attracted researchers' attention due to the challenges and the peculiar characteristics of the underwater environment. The initial random deployment of UWSN where sensors are scattered over the area via planes or ships is inefficient, and it doesn't achieve full coverage nor maintain network connectivity. Moreover, energy efficiency in underwater networks is a crucial issue since nodes utilize battery power as a source of energy and it is difficult and sometimes impossible to change or replenish these batteries. Our contribution in this research is to improve the performance of UWSNs by designing UW-DVFA, an underwater 3-D self-distributed deployment algorithm based on virtual forces. The main target for this work is to stretch the randomly deployed network in the 3-D area in a way that guarantees full area coverage and network connectivity.

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A Survey on Deployment Algorithms in Underwater Acoustic Sensor Networks

Cited by 78 publications

References 36 publications

Decentralized placement of heterogeneous nodes

Decentralized placement of heterogeneous nodes

A two-tier routing protocol for cluster-based underwater heterogeneous sensor networks

Deployment Protocol for Underwater Wireless Sensors Network based on Virtual Force

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