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Cost optimization strategy for dependent task offloading in vehicular edge computing
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DOI：10.1016/j.asoc.2025.113441.png)
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Abstract
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• Dependent task offloading in multi-server vehicle edge computing environment. • Offloading decision based on recurrent neural network algorithm. • Dynamic resource allocation based on computational resource blocks. • Experiments on real-world datasets demonstrate 4.23–10.99% cost reduction.
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