[1]   Lin D., Chen Z., Liu X., Kong L.*, and Guan Y. L. ESWCM: a novel energy-sustainable approach for SWIPT-enabled WSN with constrained MEAP configurations[J]. IEEE Transactions on Mobile Computing, 2024, 23(9): 9012-9028, (IF: 7.900, n=10).

 [2]   Lin D., and Wan J. TSA-EECS: a topology-scale-adaptive and energy-efficient clustering scheme for energy sustainable large-scale SWIPT-enabled WSNs[J]. IEEE Transactions on Mobile Computing, 2024, 23(12): 13172-13188, (IF: 7.900, n=9).

 [3]   D. Lin, Y. Yu, Y. Tang, Y. Zhao, and Y. L. Guan. A delay-precision-balanced approach for license plate recognition based on fog computing paradigm[J]. IEEE Internet of Things Journal, 2025, Accepted, (IF: 10.238, DOI: 10.1109/JIOT.2025.3597433).

 [4]   Lin D., Li S., Zhang Y.*, Xu J., Wei X., and Guan Y. L. S²EWSN: a conceptual paradigm SWIPT-enabled scalable energy-sustainable wireless sensor networks[J]. IEEE Network, 2025, 39(1): 243-250, (IF: 9.300, n=4).

 [5]   Su C., Wei J. Lin D.*, Kong L., and Guan Y. L. Computation offloading and resource allocation for fog computing in NG wireless networks：a federated deep reinforcement learning approach[J]. IEEE Internet of Things Journal, 2024, 11(4): 6802-6816, (IF: 10.238, n=6).

 [6]   Luo H., Wang J., Lin D.*, Kong L., Zhao Y., and Guan Y. L., A novel energy-efficient approach based on clustering using grey prediction in WSNs for IoT infrastructures[J]. Internet of Things Journal, 2024, 11(24): 40448-40463, (IF: 10.238, n=10).

 [7]   Lin D., Min W.*, and Xu J. An energy-saving routing integrated economic theory with compressive sensing to extend the lifespan of WSNs[J]. IEEE Internet of Things Journal, 2020, 7(8): 7636-7647, (IF: 10.238, n=34).

 [8]   Lin D., Yan M., Kong L.*, Quan R., and Guan Y. L. A framework of flexible real-time intelligent transportation system based on hybrid fog-cloud computing[J]. IEEE Communications Magazine, 2024, 62(1): 126-132, (IF: 9.030, n=8).

 [9]   Lin D., Zhao J., Yu F., and Min W. A novel high-precision and low-latency abandoned object detection method under the hybrid cloud-fog computing architecture[J]. IEEE Internet of Things Journal, 2024, 11(24): 40448-40463, (IF: 10.238, n=3).

[10]   Lin D., Wang Q.*, Min W., Xu J., and Zhang Z. A survey of the energy efficient strategies in wireless sensor networks[J]. ACM Transactions on Sensor Networks, 2020, 17(1): 1-48, (IF: 2.507, n=101).

[11]   Lin D., Wang H., Lei X., Min W.*, and Yao C. DSU-GAN: a robust frontal face recognition approach based on generative adversarial network[J]. Computer Vision and Image Understanding, 2024, 249(104128): 1-11, (IF: 4.500, n=3).

[12]   D. Lin, Z. Zhang, Z. Hua, J. Xu, Y. Zhao, and Y. L. Guan. An energy-efficient cross-layer clustering approach based on gini index theory for WSNs[J]. Computers Materials & Continua, 2025, Accepted, (IF: 1.700, DOI: 10.32604/cmc.2025.066283).

[13]   Lin D., Yao C., Min W.* Han Q., He K., Yang Z., Lei X., and Guo B. A novel fall detection framework with age estimation based on cloud-fog computing architecture[J]. IEEE Sensors Journal, 2024, 24(3): 3058-3071, (IF: 4.325, n=7).

[14]   Lin D., Lin Z., Kong L.*, and Guan Y. L. CMSTR: an energy-efficient routing protocol based on constrained minimum spanning tree for the wireless sensor networks[J]. Ad Hoc Networks, 2023 (103160): 1-13, (IF: 4.816, n=13).

[15]   Zhao C., Wu Q., Lin D.*, Zhang Z., Zhang Kong Y. L., and Guan Y. L. An energy-balanced unequal clustering approach for circular wireless sensor networks[J]. Ad Hoc Networks, 2022, 132(102872): 1-9, (IF: 4.816, n=29).

[16]   Lin D., Gao L., and Min W.* A social welfare theory-based energy-efficient cluster head election scheme for WSNs[J]. IEEE Systems Journal, 2021, 15(3): 4492-4502, (IF: 4.802, n=31).

[17]   Wang Q., Lin D.*, Yang P., and Zhang Z. An energy-efficient compressive sensing-based clustering routing protocol for WSNs[J]. IEEE Sensors Journal, 2019, 19(10): 3950-3960, (IF: 4.325, n=174).

[18]   Su C., Wei J., Lin D.*, Kong L., and Guan Y. L. A novel model for fall detection and action recognition combined lightweight 3D-CNN and convolutional LSTM networks[J]. Pattern Analysis and Applications, 2024, 27(1): 1-16, (IF: 2.307, n=11).

[19]   Lin D., and Wang Q*. A game theory based energy efficient clustering routing protocol for WSNs[J]. Wireless Networks, 2017, 23(4): 1101-1111, (IF: 2.701, n=111).

[20]   Lin D., Kong L.*, Zhao C, Gao J., Ouyang H., Yang Z, and Zhang J. An energy-efficiency-adaptive cluster formation approach for the wireless sensor networks[J]. IET Communications, 2022, 16(2): 255-265, (IF: 1.345, n=4).

[21]   Lin D., Min W., Xu J., Yang J., and Zhang J. An energy-efficient routing method in WSNs based on compressive sensing: from the perspective of social welfare[J]. IEEE Embedded Systems Letters, 2021, 13(3): 126-129, (IF: 2.169, n=13).

[22]   Zeng L., He Z., Tan Z., Geng R., Liu M., Xia L., and Lin D.* Analysis and modeling of ibeacon wireless signal propagation in multiple environments[J]. International Journal of Sensor Networks, 2021, 37(4): 254-264, (IF: 1.264, n=2).

[23]   Su C., Wei J., Lin D.*, and Kong L. Using attention LSGB network for facial expression recognition[J]. Pattern Analysis and Applications, 2023, 26(2), pp.543-553, (IF: 2.307, n=8).

[24]   Lin D., Zhou Z., Guo B., Min W.*, and Han Q., YOLO-G Abandoned Object Detection Method Combined with Gaussian Mixture Model and GhostNet[J]. Journal of Computer-Aided Design & Computer Graphics, 2023, 35(1): 99-107, (n=5).