Abstract
The significance of unmanned aerial vehicle (UAV)-assisted mobile edge computing (MEC)-based applications is increasing exponentially with the prolification of technological advancement. UAV-assisted MEC-based applications need real-time responses during offloading. With the aim to minimize the overall execution time during offloading, the energy issue got compromised. Although, energy issue of UAV-assisted MEC is a very important performance factor. Here, an energy efficient full offloading technique for UAV-assisted mobile edge servers (EEFOUM) is proposed. The design EEFOUM is explored with an renowned evloutionary algorithm, namely as particle swarm optimization (PSO). The PSO-based EEFOUM algorithm computes the overall energy consumption with the deployment of fixed-wing UAVs and rotary-wing UAVs.
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Ghosh, S., Kuila, P., Biswas, T. (2023). An Energy Efficient Offloading Technique for UAV-Assisted MEC Using Nature Inspired Algorithm. In: Bhateja, V., Yang, XS., Chun-Wei Lin, J., Das, R. (eds) Intelligent Data Engineering and Analytics. FICTA 2022. Smart Innovation, Systems and Technologies, vol 327. Springer, Singapore. https://doi.org/10.1007/978-981-19-7524-0_27
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DOI: https://doi.org/10.1007/978-981-19-7524-0_27
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