Nodes performance improvement uasn by using biological inspired algorithm /

dc.campusChennai
dc.contributor.authorSivasami, K.
dc.contributor.authorThangalakshmi, S.
dc.date.accessioned2025-03-05T09:01:35Z
dc.date.accessioned2025-04-01T08:01:00Z
dc.date.available2025-03-05T09:01:35Z
dc.date.issued2023-06-01
dc.description.abstractUnderwater Acoustic Sensor Network (UASN) routing is difficult for several reasons. First, the UASN's energy consumption rises because the distance between nodes changes as it moves with the water current. The gathered scientific data packets are sent from the acoustic network to a receiving station on land. Second, there are difficulties with the underwater acoustic network, such as longer propagation delays and lower capacity because of danger. The biggest hurdle is inefficient data packet transfer between the UASN node and the onshore sink node. Finding a method that uses less energy is just the first step in reaching maximum efficiency. The underwater routing protocol has to be resilient in the face of connection failure brought on by extreme weather or power outages. The Modified Buffalo Optimization Algorithm is a novel optimization technique inspired by nature. The issues listed above may be avoided by using the Modified Buffalo optimization Algorithm that has been presented in this study. It was implemented in the NS2 simulator to evaluate the program's effectiveness and through its paces against the Chimp optimization method. In terms of throughput, packet delivery ratio, and power efficiency, the simulated results shows that the MBOA algorithm out performs COA Algorithm.
dc.identifier.urihttps://doi.org/10.1109/icpcsn58827.2023.00285
dc.identifier.urihttps://dspacenew8-imu.refread.com/handle/123456789/2737
dc.language.isoen
dc.publisherIEEE
dc.schoolSchool of Marine Engineering and Technology
dc.subjectUnderwater acoustic sensor network
dc.subjectModified buffalo optimization algorithm
dc.subjectChimp optimization algorithm
dc.subjectNodes failure
dc.subjectPacket delivery ratio
dc.titleNodes performance improvement uasn by using biological inspired algorithm /
dc.typeArticle

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