Abstract
Underwater wireless sensor network (UWSN) has limited bandwidth, long propagation delays, and unrechargeable batteries, which forces the development of techniques minimizing the energy consumption of UWSNs. One solution is clustering that outperforms in terms of energy optimization and, in addition, can also provide scalability and data reliability. The development of clustering algorithms depends on UWSN architectures. In our case, we have proposed a hybrid UWSN network architecture named ACOP-UWSN (ACoustic OPtical Underwater Wireless Sensor Network), which aims for reliable data transmission at the fastest speed with higher data rates and minimized propagation delays. In ACOP-UWSN, optical sensors sense data, whereas acoustic sensors only relay data towards the surface buoy. Clustering of all these nodes may result in unnecessary wastage of the node’s energy and memory. Therefore, we undergo clustering of only optical sensors, as comparatively, sensing and processing of data consume maximum energy and memory than relaying data. In the proposed clustering algorithm, the criteria for cluster head selection are OSNR (optical signal-to-noise ratio) and residual energy. The mathematical derivation of OSNR for underwater wireless optical communication is a key part of the algorithm. The results achieved using the simulation tool show that our proposed OSNR-based energy efficient clustering algorithm (OECA) is efficient in terms of energy and as well data reliability as compared to state of art. The quantitative analysis of the results showed that the total energy consumed for the existing scheme is 450 J, which is more as compared to 400 J of OECA. Similarly, the residual energy of nodes using OECA is 1% greater than the existing scheme. To our knowledge, research on the clustering of optical sensors in UWSN is least available, and we are among the few to work on an OSNR-based clustering algorithm for underwater optical nodes.
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