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，我们使用遗传算法设计了一种针对海量物联网设备的智能分组方法。与随机分组方法相比，所获得的结果节省了物联网设备的大量能源消耗。此外，该方法还考虑了每个物联网设备对服务质量的要求，如分组到达时延。此外，我们还通过设计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份高影响力的期刊上，即IEEE物联网。此外，我们还在IEEE VTC-Fall 2020和IEEE Globecom 2020等通信领域的顶级会议上发布了结果。这部作品还获得了日本职教协会颁发的学生论文奖。研究结果还发表在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.