ＬＴＥ－Ａを利用したＩｏＴにおけるデータ伝送方式の電力効率化に関する研究

在本财年，我们使用遗传算法为大规模物联网设备设计了一种智能分组方法。与随机分组方法相比，获得的结果节省了大量物联网设备的能耗。此外，该方法还考虑了对服务质量的要求，如每个物联网设备的数据包到达延迟。此外，我们还通过设计一种网络感知的互联网范围端口扫描方法，最大限度地提高了物联网设备的安全性。这项工作的结果发表在一个高影响因子的期刊上，即IEEE物联网。此外，我们还在IEEE VTC-Fall 2020、IEEE Globecom 2020等通信领域的顶级会议上发表了研究成果。此作品亦获VTC日本学会颁发学生论文奖。研究结果也发表在2020年IEICE大会上。

During this fiscal year, we have designed an intelligent grouping approach for massive IoT devices using the genetic algorithm. The obtained results save a significant amount of energy consumption of IoT devices compared to random grouping approaches. Moreover, the proposed approach also considers the requirements for quality of services such as packet arrival delay of each IoT device. Further, we have also maximized the security of IoT devices by designing a network-aware internet-wide port scan approach. The results of this work are published in a high-impact factor journal that is IEEE Internet of Things. Also, we have published the results in the top conferences of communication areas such as IEEE VTC-Fall 2020, and IEEE Globecom 2020. This work also received a student paper award from VTC Japan society. The results are also published in IEICE general conference 2020.