**6. Conclusions**

In this paper, we investigate the wireless information transmission and energy transfer of a novel SWIPT-MEC enabled WSN-assisted IoT System. We fomulate an optimization problem by jointly optimizing the CPU frequency, transmitted power, offloading weight factor and harvest weight factor to achieve the minimum system energy consumption. In order to render the problem solvable, we propose a novel alternate group iteration optimization (AGIO) algorithm, which decomposes the original problem into three subproblems and alternately optimizes each subproblem using the group interior point iterative optimization algorithm. Finally, numerical simulation of the proposed strategy is carried on to compare with the two other benchmark schemes. The results demonstrate that the proposed design presents the performance advantages both in energy consumption and latency.

**Author Contributions:** Conceptualization, F.C. and J.H.; methodology, F.C. and A.W.; software, F.C. and Y.Z.; validation, Y.Z. and Z.N.; writing—original draft preparation, F.C. and A.W.; writing—review and editing, all co-authors; supervision, J.H; funding acquisition, J.H. and F.C. All authors have read and agreed to the published version of the manuscript.

**Funding:** This work is funded by the National Natural Science Foundation of China (61601409), Zhejiang Natural Science Foundation (LQ21F010008), Zhejiang Province Science and technology Projects (2021C04004), the Scientific Research Project of the Department of Education of Zhejiang Province (Y202044549) and Zhejiang Postdoctoral Funding.

**Data Availability Statement:** The data used to support the findings of this study are available from the corresponding author upon request.

**Conflicts of Interest:** The authors declare that they have no conflict of interest.
