Node Self-Deployment Algorithm Based on an Uneven Cluster with Radius Adjusting for Underwater Sensor Networks

Abstract

Existing move-restricted node self-deployment algorithms are based on a fixed node communication radius, evaluate the performance based on network coverage or the connectivity rate and do not consider the number of nodes near the sink node and the energy consumption distribution of the network topology, thereby degrading network reliability and the energy consumption balance. Therefore, we propose a distributed underwater node self-deployment algorithm. First, each node begins the uneven clustering based on the distance on the water surface. Each cluster head node selects its next-hop node to synchronously construct a connected path to the sink node. Second, the cluster head node adjusts its depth while maintaining the layout formed by the uneven clustering and then adjusts the positions of in-cluster nodes. The algorithm originally considers the network reliability and energy consumption balance during node deployment and considers the coverage redundancy rate of all positions that a node may reach during the node position adjustment. Simulation results show, compared to the connected dominating set (CDS) based depth computation algorithm, that the proposed algorithm can increase the number of the nodes near the sink node and improve network reliability while guaranteeing the network connectivity rate. Moreover, it can balance energy consumption during network operation, further improve network coverage rate and reduce energy consumption.

Underwater Self Deployment of Wireless Sensors for Maximum Coverage and Connectivity using K-Means Clustering

“…Thus the sensor can adjust its depth in this way. Similarly, an air-bladderlike gadget is prescribed to be utilized as a part of underwater sensors for such reason in [11]. Another method used for the adjustment of depth of the sensors is to use tethers from anchors which are placed at the ocean's bottom.…”

“…For optimize coverage, the overlaps between the parent and child node were reduced within each sub tree. In 2016 jiang et al [11] proposed an uneven clustering with radius adjustment. In this algorithm the nodes initially begin the uneven clustering based on their distance from the surface of water.…”

Deployment Protocol for Underwater Wireless Sensors Network based on Virtual Force

“…Regarding the depth-adjustment deployment [18], [17], Akkaya et al [19] propose an algorithm for adjusting the position of sensor nodes after their initial deployment to reduce coverage overlaps between neighbor nodes based on clustering and Graph Colouring. However, this algorithm create small coverage holes between each two nodes which affect the whole connectivity in the topology.…”

Clustering Analysis in Wireless Sensor Networks: The Ambit of Performance Metrics and Schemes Taxonomy

“…Each CH acquires routing table and retains information of all its neighboring nodes. CHs are a dominating set which is a subset of the set consisting of all the nodes in the network [6]. Considering wireless sensor network in graph , a vertex (node) subset of is a DS if each vertex in either belongs to or is adjacent to at least one vertex in S.…”

“…Clustering technique reduces the number of radio transmissions and increases sensor network lifetime [1,2]. Thus, clustering technique can, efficiently, increase lifetime of various sensor applications, such as robot control, environmental control, offices, smart homes, manufacturing environments, body area networks, and underwater sensor networks [3][4][5][6][7][8].…”