An Uneven Node Self-Deployment Optimization Algorithm for Maximized Coverage and Energy Balance in Underwater Wireless Sensor Networks

Abstract

The underwater wireless sensor networks (UWSNs) have been applied in lots of fields such as environment monitoring, military surveillance, data collection, etc. Deployment of sensor nodes in 3D UWSNs is a crucial issue, however, it is a challenging problem due to the complex underwater environment. This paper proposes a growth ring style uneven node depth-adjustment self-deployment optimization algorithm (GRSUNDSOA) to improve the coverage and reliability of UWSNs, meanwhile, and to solve the problem of energy holes. In detail, a growth ring style-based scheme is proposed for constructing the connective tree structure of sensor nodes and a global optimal depth-adjustment algorithm with the goal of comprehensive optimization of both maximizing coverage utilization and energy balance is proposed. Initially, the nodes are scattered to the water surface to form a connected network on this 2D plane. Then, starting from sink node, a growth ring style increment strategy is presented to organize the common nodes as tree structures and each root of subtree is determined. Meanwhile, with the goal of global maximizing coverage utilization and energy balance, all nodes depths are computed iteratively. Finally, all the nodes dive to the computed position once and a 3D underwater connected network with non-uniform distribution and balanced energy is constructed. A series of simulation experiments are performed. The simulation results show that the coverage and reliability of UWSN are improved greatly under the condition of full connectivity and energy balance, and the issue of energy hole can be avoided effectively. Therefore, GRSUNDSOA can prolong the lifetime of UWSN significantly.

Monitoring Area Coverage Based on Adjusting Node Spacing in Mixed Underwater Mobile Wireless Sensor Networks

“…The deployment of sensor nodes in three-dimensional underwater wireless sensor networks is a key problem, but it is a challenging problem due to the complexity of underwater environment. Yan et al [20] proposed a growth ring nonuniform node depth adjustment self-deployment optimization algorithm to improve the coverage and reliability of UWSNs and solve the problem of energy blind area. A construction scheme of sensor node connection tree structure based on growth ring style is proposed, and a global optimal depth adjustment algorithm aiming at maximizing coverage utilization and comprehensive optimization of energy balance is proposed.…”

“…In formulas (17) to (20), α is the parameter of adjusting the moving distance of the node in the process of node movement, which is related to the network environment and the characteristics of the node [32].…”

PINC: Pickup Non-Critical Node Based k-Connectivity Restoration in Wireless Sensor Networks

“…A relationship was derived among the connectivity, transmission range and the node count. Yan et al designed a deployment approach to tackle the energy holes problem and improve the reliability and coverage of underwater WSNs [ 15 ]. The authors presented a growth ring style-based method to form a connected tree layout.…”

Dynamic topology control algorithm for node deployment in mobile underwater wireless sensor networks

“…So, investigating a distribution procedure for defining the ideal arrangement of a network is vital, by regulating the location of sensor nodes in a particular zone 7 . The deployment approach of UWSN regulates three key aspects, together with the energy depletion of nodes, the communication ability, and the network dependability 8 . Efficient deployment of sensor nodes can efficiently improve the coverage area, contribute more toward effectual data collection, avoid rapid network energy depletion, reduced hardware requirement, and ultimately extend the network life‐time to enhance the observing capability of the system 9 …”

“…7 The deployment approach of UWSN regulates three key aspects, together with the energy depletion of nodes, the communication ability, and the network dependability. 8 Efficient deployment of sensor nodes can efficiently improve the coverage area, contribute more toward effectual data collection, avoid rapid network energy depletion, reduced hardware requirement, and ultimately extend the network life-time to enhance the observing capability of the system. 9 Mobility management in UWSN is a complex issue that must be considered in node deployment approaches to confirm connectivity.…”