2022
DOI: 10.1109/tits.2021.3107527
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AI Based Energy Efficient Routing Protocol for Intelligent Transportation System

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Cited by 60 publications
(26 citation statements)
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“…This work also proposes new method for energy efficiency by implementation of hybrid approach of DAI and selforganizing Map (SOM). It also save the overall network energy and reduce the computation challenges [62].…”
Section: Discussionmentioning
confidence: 99%
“…This work also proposes new method for energy efficiency by implementation of hybrid approach of DAI and selforganizing Map (SOM). It also save the overall network energy and reduce the computation challenges [62].…”
Section: Discussionmentioning
confidence: 99%
“…In [19], the authors developed an energy-efficient non-cooperative game for distributed CRN over interference channels. For CRNs and IoT, a noncooperative game based on power allocation is proposed in [20], which investigates a mesh adaptive search technique for device to device-assisted CRN; [21] proposes a gradient adaptation optimization for power allocation as well as EE in CRNs. Although gradient techniques are reliable, they can fail to accomplish global optimization.…”
Section: Related Workmentioning
confidence: 99%
“…Recently, much AI-related wireless communication work has been discussed by researchers. To realize the rapid response of node communication and meet the requirements of the bandwidth and response time of network transmission for a large amount of data and applications, Pratik Goswami et al [29] proposed a method for implementing distributed artificial intelligence using neural networks. The method realizes node prediction by considering the number of observations of node power consumption when executing a specific application and finally effectively saves the response time of routing.…”
Section: Related Workmentioning
confidence: 99%