Task offload optimization for digital management in cloud computing environments

With the continuous advancement of technologies such as cloud computing, big data, and artificial intelligence, digital management faces both significant challenges and new opportunities. This paper proposes an optimization framework for task offloading and power allocation, which integrates deep neural networks (DNN) and the whale optimization algorithm (WOA) to minimize overall energy consumption while satisfying delay and power constraints. In this framework, DNN is first employed to make decisions regarding task offloading and power allocation, and these decisions are subsequently refined using WOA. Through extensive simulation experiments, the effectiveness of the proposed approach is evaluated in terms of energy efficiency and task delay. The results show that, compared to traditional static allocation methods and existing task offloading optimization algorithms, the proposed joint optimization strategy, combining DNN and WOA, achieves significant improvements in both energy efficiency and delay reduction, particularly as the system scales to handle larger datasets.