2018
DOI: 10.1504/ijsnet.2018.088364
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CACA-UAN: a context-aware communication approach to efficient and reliable underwater acoustic sensor networks

Abstract: Underwater acoustic sensor networks (UANs) have emerged as a promising technology recently, which can be applied in many areas such as military and civil, where the communication between devices is crucial and challenging owing to the unique characteristics of underwater acoustic-based environment, such as high latency and low bandwidth. In this paper, context awareness is applied to the design of an underwater communication approach, called context-aware communication approach for a UAN (CACA-UAN), which aims… Show more

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Cited by 3 publications
(2 citation statements)
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“…The results showed significant improvements in various metrics such as packet delivery rates, channel utilization, start-to-end delays, overhead, uptime potential, and organizational throughput. To manage FANET scheduling, a variant of the Ant Colony Optimization (ACO) process called AntHocNet (AHN) is proposed [14], with a focus on minimizing energy usage for different organizations. Evaluation results demonstrate that AHN outperforms ACO.…”
Section: Related Workmentioning
confidence: 99%
See 1 more Smart Citation
“…The results showed significant improvements in various metrics such as packet delivery rates, channel utilization, start-to-end delays, overhead, uptime potential, and organizational throughput. To manage FANET scheduling, a variant of the Ant Colony Optimization (ACO) process called AntHocNet (AHN) is proposed [14], with a focus on minimizing energy usage for different organizations. Evaluation results demonstrate that AHN outperforms ACO.…”
Section: Related Workmentioning
confidence: 99%
“…Various authors have published their work on improving FANET from different perspectives [10][11][12]. Numerous challenges in this network require appropriate solutions [13,14]. By envisioning an efficient algorithm, the network can reach its peak performance.…”
Section: Introductionmentioning
confidence: 99%