IoT platforms have been actively discussed for deploying various IoT services using a horizontal approach. The IoT Data Exchange Platform (IoT-DEP) is one of these platforms, standardized as ISO/IEC 30161 series in ISO/IEC JTC 1/SC 41. These standardized documents specify the requirements, architecture, and functional blocks of the communication components. However, detailed communication sequences among the communication components are considered an implementation issue. This paper proposes a content-centric network with Network initiative And Traffic control (C-NAT) applied to the IoT-DEP as a promising candidate for communication sequences. Moreover, it proposes the reinforcement of C-NAT for low-latency and reliable industrial services when applied to IoT-DEP. Specifically, although the original C-NAT is intended to provide cyclic communication, this study proposes support for non-cyclic communication in reinforced C-NAT.
{"title":"Overview of C-NAT and Its Reinforcement for IoT Data Exchange Platform","authors":"Atsuko Yokotani;Horoshi Mineno;Masaki Mitsuuchi;Koichi Ishibashi;Tetsuya Yokotani","doi":"10.23919/comex.2024COL0012","DOIUrl":"https://doi.org/10.23919/comex.2024COL0012","url":null,"abstract":"IoT platforms have been actively discussed for deploying various IoT services using a horizontal approach. The IoT Data Exchange Platform (IoT-DEP) is one of these platforms, standardized as ISO/IEC 30161 series in ISO/IEC JTC 1/SC 41. These standardized documents specify the requirements, architecture, and functional blocks of the communication components. However, detailed communication sequences among the communication components are considered an implementation issue. This paper proposes a content-centric network with Network initiative And Traffic control (C-NAT) applied to the IoT-DEP as a promising candidate for communication sequences. Moreover, it proposes the reinforcement of C-NAT for low-latency and reliable industrial services when applied to IoT-DEP. Specifically, although the original C-NAT is intended to provide cyclic communication, this study proposes support for non-cyclic communication in reinforced C-NAT.","PeriodicalId":54101,"journal":{"name":"IEICE Communications Express","volume":"13 12","pages":"492-495"},"PeriodicalIF":0.3,"publicationDate":"2024-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10713855","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142761391","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-10DOI: 10.23919/comex.2024XBL0165
Taisei Kosaka;Steven Wandale;Koichi Ichige
In this paper, we introduce a novel approach called the 2-Step Robust Deep Neural Network (DNN), designed specifically for indoor localization utilizing received signal strength indicator (RSSI) data. This method represents an advancement over the previously proposed 2-Step Extreme Gradient Boosting (XGBoost), aiming to enhance estimation precision by leveraging a single coordinate ( $x$