2023 International Conference on Information Networking (ICOIN)最新文献_第2页

Deep Learning for 2D-MIMO scheme based on Optical Camera Communication 基于光学相机通信的2D-MIMO方案的深度学习

2023 International Conference on Information Networking (ICOIN) Pub Date : 2023-01-11 DOI: 10.1109/ICOIN56518.2023.10049055

Huy Nguyen, Van Linh Nguyen, Duc Hoang Tran, Y. Jang

引用次数: 0

Traffic reduction for out-of-band network management over LPWA 通过LPWA减少带外网络管理的流量

2023 International Conference on Information Networking (ICOIN) Pub Date : 2023-01-11 DOI: 10.1109/ICOIN56518.2023.10048968

Kodai Tanabe, G. Hasegawa, G. Kitagata

引用次数: 0

A V2X Access Authorization Mechanism based on Decentralized ID (DID) and Verifiable Credentials (VC) 一种基于去中心化ID (DID)和可验证凭据(VC)的V2X访问授权机制

2023 International Conference on Information Networking (ICOIN) Pub Date : 2023-01-11 DOI: 10.1109/ICOIN56518.2023.10048986

J. Lim, Hansu Oh, Kichun Sim, Sunyoung Kim, Ki-Hyung Kim

引用次数: 0

Joint Association and Power Allocation for Data Collection in HAP-LEO-Assisted IoT Networks hap - leo辅助物联网数据采集联合关联与功率分配

2023 International Conference on Information Networking (ICOIN) Pub Date : 2023-01-11 DOI: 10.1109/ICOIN56518.2023.10049035

Nway Nway Ei, P. Aung, Seong-Bae Park, E. Huh, C. Hong

{"title":"Joint Association and Power Allocation for Data Collection in HAP-LEO-Assisted IoT Networks","authors":"Nway Nway Ei, P. Aung, Seong-Bae Park, E. Huh, C. Hong","doi":"10.1109/ICOIN56518.2023.10049035","DOIUrl":"https://doi.org/10.1109/ICOIN56518.2023.10049035","url":null,"abstract":"Low earth orbit (LEO) satellites and high altitude platforms (HAPs) have recently gained popularity due to its seamless connectivity and global coverage. The aerial network comprising high altitude platforms (HAPs) collects the generated data of the ground internet of things (IoT) devices and then transmits the aggregated data to the terrestrial data processing center via the LEO satellites. However, LEO satellites are generally orbiting with high speed and their visibility times are limited according to the elevation angle and orbital height. Moreover, it is challenging for the HAPs to determine the feasible LEO satellite to associate with and decide the optimal transmit power due to their power constraint. Therefore, in this paper, we formulate a joint association and power allocation problem to maximize the data transmitted by the HAPs and minimize the energy consumption by considering the HAP’s power budget and QoS requirements as well as the data storage and visibility time of the LEO satellites. To address the formulated mixed-integer non-convex problem, the two sub-problems are introduced, namely, HAP-LEO satellite association and power allocation problems, which are then alternately solved by using the GUROBI optimizer and whale optimization method, respectively. The evaluation results have demonstrated that the proposed approach achieves the superior performance when compared to the random scheme.","PeriodicalId":285763,"journal":{"name":"2023 International Conference on Information Networking (ICOIN)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114718420","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Deep Reinforcement Learning Driven Aggregate Flow Entries Eviction in Software Defined Networking 软件定义网络中深度强化学习驱动的聚合流项抽取

2023 International Conference on Information Networking (ICOIN) Pub Date : 2023-01-11 DOI: 10.1109/ICOIN56518.2023.10049020

Junhan Zang, S. M. Raza, Hyunseung Choo, Gyurin Byun, Moonseong Kim

{"title":"Deep Reinforcement Learning Driven Aggregate Flow Entries Eviction in Software Defined Networking","authors":"Junhan Zang, S. M. Raza, Hyunseung Choo, Gyurin Byun, Moonseong Kim","doi":"10.1109/ICOIN56518.2023.10049020","DOIUrl":"https://doi.org/10.1109/ICOIN56518.2023.10049020","url":null,"abstract":"Software-Defined Networking (SDN) separates control from network elements and logically centralizes it in SDN controller to provide global view and control of the network. Network elements, such as switches, only forward data using entries in the flow tables that are installed by the controller. The capacity of flow tables is limited and requires continuous management. Several studies have proposed eviction strategies to make space for new entries in the flow tables, but they assume 1:1 mapping between entries and incoming flows. This assumption is a major limitation, as in real networks many incoming flows can be handled by a single Aggregate Flow Entry (AFE). This paper handles this limitation by proposing Deep Reinforcement Learning (DRL) framework for eviction of AFEs. The proposed framework calculates the degree of AFEs (i.e., how many flows it entertains) along with other parameters to select AFE for eviction, where main objective is to minimize flow table overflows. The experiment results show that the proposed framework reduces the number of overflows by 37%, flow reinstallation by 87%, and the control signaling overhead by 45 % compared to the Random and Least Recently Used Algorithm (LRU).","PeriodicalId":285763,"journal":{"name":"2023 International Conference on Information Networking (ICOIN)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116893206","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An Artificial Intelligence Framework for Holographic Beamforming: Coexistence of Holographic MIMO and Intelligent Omni-Surface 全息波束形成的人工智能框架:全息MIMO与智能全曲面的共存

2023 International Conference on Information Networking (ICOIN) Pub Date : 2023-01-11 DOI: 10.1109/ICOIN56518.2023.10048994

Apurba Adhikary, M. S. Munir, Avi Deb Raha, Yu Qiao, S. Hong, E. Huh, C. Hong

{"title":"An Artificial Intelligence Framework for Holographic Beamforming: Coexistence of Holographic MIMO and Intelligent Omni-Surface","authors":"Apurba Adhikary, M. S. Munir, Avi Deb Raha, Yu Qiao, S. Hong, E. Huh, C. Hong","doi":"10.1109/ICOIN56518.2023.10048994","DOIUrl":"https://doi.org/10.1109/ICOIN56518.2023.10048994","url":null,"abstract":"The forth-coming 6G wireless communication systems are required to meet the increasing demand for network connectivity that requires power savings for generating effective beamforming. Therefore, joint sensing and communication framework is proposed with the coexistence between holographic MIMO (HMIMO) and Intelligent Omni-Surface (IOS) which ensures the extension of the coverage area resulting in lower power consumption for beamforming. An optimization problem is formulated maximizing the utility function considering the channel capacity, beampattern gains with zenith and azimuth angles, distances, and losses during the sensing-communication process. An artificial intelligence framework is designed for solving the formulated NP-hard problem. Firstly, long short-term memory (LSTM) based scheme is utilized to determine the zenith and azimuth angles with a view to obtaining the current location of all the users that are served directly by the HMIMO and users that are served with reflective channel and refractive channel from the IOS. Afterward, a reinforcement learning (RL) based method is developed for allocating the communication resources to the intended users for generating the required beamforming based on the results obtained from the LSTM-based scheme. Finally, simulation results illustrate that the proposed artificial intelligence framework achieves a power gain of 1.5% compare to the baseline method to perform holographic beamforming for serving the users.","PeriodicalId":285763,"journal":{"name":"2023 International Conference on Information Networking (ICOIN)","volume":"7 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117336707","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Secrecy Performance of Energy Harvesting Based D2D Communications in Spectrum-Sharing Networks 频谱共享网络中基于能量采集的D2D通信保密性能研究

2023 International Conference on Information Networking (ICOIN) Pub Date : 2023-01-11 DOI: 10.1109/ICOIN56518.2023.10048975

Surjeet Kumar, Shilpa Thakur, Ajay Singh

引用次数: 0

A Research on Low Latency Motion Control System using Real-time Scheduling in Edge Server 基于边缘服务器实时调度的低延迟运动控制系统研究

2023 International Conference on Information Networking (ICOIN) Pub Date : 2023-01-11 DOI: 10.1109/ICOIN56518.2023.10048964

Dongbeom Ko, Jaeho Jeon, Sungjoo Kang

引用次数: 0

A Long Distance Low Bandwidth Firmware Update process for LPWAN - Taking LoRaP2P+ as example LPWAN的长距离低带宽固件更新流程——以LoRaP2P+为例

2023 International Conference on Information Networking (ICOIN) Pub Date : 2023-01-11 DOI: 10.1109/ICOIN56518.2023.10048943

Daniel Ho Teck Khieng, Yu-Zhe Xie, Jia-Cheng Zhang, N. Huang

{"title":"A Long Distance Low Bandwidth Firmware Update process for LPWAN - Taking LoRaP2P+ as example","authors":"Daniel Ho Teck Khieng, Yu-Zhe Xie, Jia-Cheng Zhang, N. Huang","doi":"10.1109/ICOIN56518.2023.10048943","DOIUrl":"https://doi.org/10.1109/ICOIN56518.2023.10048943","url":null,"abstract":"The increment of IoT devices in the world due to the manpower shortage can be commonly seen around the world nowadays. In agriculture, revolutionary technologies which involve automation has been anticipated in order to face this serious issue. With LPWAN technologies, we can achieve automated mass irrigation almost without the need for manpower involvement. For most crops, production and yield are directly related to crop water use, hence resulting in the importance of precise watering. Device firmware updates for the endpoint devices play an important role to maintain the reliability and security of these system. For a system that is using LPWAN, which is commonly deployed in rural areas, the firmware update over the air(FUOTA) feature can provide the possibility of rolling out a system update without the need to have physical contact with the device while also ensuring all the devices are up-to-date.In this article, we designed a FUOTA process for LPWAN. Through FUOTA, the update patches can be deployed to the devices effortlessly and efficiently further reducing the manpower shortage problem while improving the feature and functionality of the system.","PeriodicalId":285763,"journal":{"name":"2023 International Conference on Information Networking (ICOIN)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128565184","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The study on TAVR Medical Twin Method Based on Real World Data(RWD) 基于真实世界数据(RWD)的TAVR医学孪生方法研究

2023 International Conference on Information Networking (ICOIN) Pub Date : 2023-01-11 DOI: 10.1109/ICOIN56518.2023.10049049

Seung-Min Hyun, Kangyoon Lee

引用次数: 0