Journal
SENSORS
Volume 16, Issue 1, Pages -Publisher
MDPI
DOI: 10.3390/s16010098
Keywords
node self-deployment; uneven clustering; radius adjusting; network reliability
Funding
- National Natural Science Foundation of China [NSFC61273072]
- Environmental Protection Plan of Zhejiang Province [2013A034]
- National Natural Science Major Foundation of Research Instrumentation of China [61427808]
- Key Foundation of China [61333009]
- National Key Basic Research Program of China [2012CB821204]
Ask authors/readers for more resources
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.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available