2020 IEEE 6th International Conference on Computer and Communications (ICCC)最新文献

The Learning Algorithm of Real-Time Automata 实时自动机的学习算法

2020 IEEE 6th International Conference on Computer and Communications (ICCC) Pub Date : 2020-12-11 DOI: 10.1109/ICCC51575.2020.9345101

Junri Mi, Jin Xu

引用次数: 1

Resource Management for Energy-Efficient and Blockchain-Enabled Industrial IoT: A DRL Approach 节能和区块链支持的工业物联网资源管理:一种DRL方法

2020 IEEE 6th International Conference on Computer and Communications (ICCC) Pub Date : 2020-12-11 DOI: 10.1109/ICCC51575.2020.9345166

Le Yang, Meng Li, Yanhua Zhang, Pengbo Si, Zhuwei Wang, Ruizhe Yang

{"title":"Resource Management for Energy-Efficient and Blockchain-Enabled Industrial IoT: A DRL Approach","authors":"Le Yang, Meng Li, Yanhua Zhang, Pengbo Si, Zhuwei Wang, Ruizhe Yang","doi":"10.1109/ICCC51575.2020.9345166","DOIUrl":"https://doi.org/10.1109/ICCC51575.2020.9345166","url":null,"abstract":"Industrial Internet of Things (IIoT) has emerged with the developments of various communication technologies. In order to guarantee the security and privacy of massive IIoT data, blockchain is widely considered as a promising technology and applied into IIoT. However, there are still several issues in the existing blockchain-enabled IIoT: 1) unbearable energy consumption for computation tasks, 2) poor efficiency of consensus mechanism in blockchain, and 3) serious computation overhead of network systems. To handle the above issues and challenges, in this paper, we integrate mobile edge computing (MEC) into blockchain-enabled IIoT systems to promote the computation capability of IIoT devices and improve the efficiency of consensus process. Meanwhile, the weighted system cost including the energy consumption and the computation overhead are jointly considered. Moreover, we propose an optimization framework for blockchain-enabled IIoT systems to decrease consumption, and formulate the proposed problem as a Markov decision process (MDP). The master controller, offloading decision, block size and computing server can be dynamically selected and adjusted to optimize the devices energy allocation and reduce the weighted system cost. Accordingly, due to the high-dynamic and large-dimensional characteristics, deep reinforcement learning (DRL) is introduced to solve the formulated problem. Simulation results demonstrate that our proposed scheme can improve system performance significantly compared to other existing schemes.","PeriodicalId":386048,"journal":{"name":"2020 IEEE 6th International Conference on Computer and Communications (ICCC)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116787284","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: 4

Severity Prediction of COVID-19 Patients Using Machine Learning Classification Algorithms: A Case Study of Small City in Pakistan with Minimal Health Facility 使用机器学习分类算法预测COVID-19患者的严重程度:以医疗设施最少的巴基斯坦小城市为例

2020 IEEE 6th International Conference on Computer and Communications (ICCC) Pub Date : 2020-12-11 DOI: 10.1109/ICCC51575.2020.9344984

H. Gull, Gomathi Krishna, May Aldossary, S. Z. Iqbal

{"title":"Severity Prediction of COVID-19 Patients Using Machine Learning Classification Algorithms: A Case Study of Small City in Pakistan with Minimal Health Facility","authors":"H. Gull, Gomathi Krishna, May Aldossary, S. Z. Iqbal","doi":"10.1109/ICCC51575.2020.9344984","DOIUrl":"https://doi.org/10.1109/ICCC51575.2020.9344984","url":null,"abstract":"A bstract-Coronavirus disease has been declared as an infectious pandemic affecting the life and health of millions across the globe. It has caused high number of mortalities giving birth to exceptional state of emergency worldwide. It has not affected the people but also has damaged infrastructure of different countries, especially causing an expectational situation in health care systems globally. Due to unavailability of vaccination and faster human to human transmission of virus, healthcare facilities are at high risk of exceeding their limit and capacity, especially in developing countries like Pakistan. Therefore, it is important to manage resources properly in these countries to control high mortality rate and damage it can cause. In this paper we have taken a case study of small city in Pakistan, where healthcare facilities are not enough to deal with pandemic. Most of the COVID-19 patients have to be refer to big cities based on their severity. We have taken data of COVID-19 positive patients from this small city, developed and applied machine learning classification model to predict the severity of patient, in order to deal with the shortage of resources. Among all seven taken and tested algorithms, we have chosen SVM to predict severity of patients. Model has shown 60% of accuracy and have divided patient's severity into mild, moderate and severe levels.","PeriodicalId":386048,"journal":{"name":"2020 IEEE 6th International Conference on Computer and Communications (ICCC)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120915525","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: 4

A Visual Based Robot Trajectory Teaching Method for Traditional Chinese Medical Moxibustion Therapy 基于视觉的中医艾灸机器人轨迹教学方法

2020 IEEE 6th International Conference on Computer and Communications (ICCC) Pub Date : 2020-12-11 DOI: 10.1109/ICCC51575.2020.9345310

Jiaxun Liu, Qujiang Lei, Yukai Qiao, Guangchao Gui, Xiuhao Li, Jintao Jin, Weijun Wang

引用次数: 1

A Method for Lever Arm Estimation in INS/GPS Integration Using Direct Unscented Kalman Filter 一种基于直接无嗅卡尔曼滤波的INS/GPS集成中杠杆臂估计方法

2020 IEEE 6th International Conference on Computer and Communications (ICCC) Pub Date : 2020-12-11 DOI: 10.1109/ICCC51575.2020.9345280

Chen Jiayao, Zhang Dalong, Han Gangtao, Li Zhiyuan

{"title":"A Method for Lever Arm Estimation in INS/GPS Integration Using Direct Unscented Kalman Filter","authors":"Chen Jiayao, Zhang Dalong, Han Gangtao, Li Zhiyuan","doi":"10.1109/ICCC51575.2020.9345280","DOIUrl":"https://doi.org/10.1109/ICCC51575.2020.9345280","url":null,"abstract":"In Inertial Navigation System (INS) and Global Positioning System (GPS) integrated system, lever arm effect is an important error source, which makes the integrated system highly nonlinear. In addition to nonlinear problem, the lever arm is difficult to measure in practical applications. To solve the problems, the direct filtering method considering the lever arm effect of Unscented Kalman Filter (UKF) is proposed in this paper. The proposed method adds lever arm to system model of direct Kalman filter and compensates the estimated lever arm, and thus the lever arm is constantly estimated and modified as the filter estimations are updated. Specifically, the system state model and measurement model are established based on the direct filtering method. The navigation parameters of INS and lever arm are taken as system state variable, the velocity and position of GPS are taken as measurement variable. Then the UKF is used for INS/GPS integrated system information fusion. Simulation results show that the proposed direct UKF considering lever arm of integrated navigation system can estimate the lever arm correctly. Furthermore, the accuracy of the proposed method is significantly higher than that of standard indirect KF and standard direct UKF.","PeriodicalId":386048,"journal":{"name":"2020 IEEE 6th International Conference on Computer and Communications (ICCC)","volume":"101 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127160346","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

Research on Load Balancing Algorithm of Multicast Services Based on EON 基于EON的组播业务负载均衡算法研究

2020 IEEE 6th International Conference on Computer and Communications (ICCC) Pub Date : 2020-12-11 DOI: 10.1109/ICCC51575.2020.9345258

Yajun Liu, Xiaoqun Liu, Jianfang Zhang, Yingying Cao, Xiaodong Liu

{"title":"Research on Load Balancing Algorithm of Multicast Services Based on EON","authors":"Yajun Liu, Xiaoqun Liu, Jianfang Zhang, Yingying Cao, Xiaodong Liu","doi":"10.1109/ICCC51575.2020.9345258","DOIUrl":"https://doi.org/10.1109/ICCC51575.2020.9345258","url":null,"abstract":"The spectrum grid of the traditional wavelength division multiplexing (WDM) network is fixed, so it has the shortcomings of low spectrum utilization and poor flexibility. Based on this, elastic optical network (EON) came into being. Compared with the traditional WDM network, the EON has a flexible spectrum grid with high network flexibility and can provide different spectrums for different services. But the EON still has the problem of load balancing. In order to further optimize the EON, this article uses the Least Connections algorithm to solve the EON load balancing problem, taking into account the different server load capacity to improve it. In addition, to further improve the performance of EON, this paper combines genetic algorithm, improved least connections algorithm and ant colony algorithm to propose a new algorithm LC-GAACO. The simulation results show that the LC-GAACO algorithm will consume more optical transceivers while taking into account load balancing, but the network load balancing effect, network spectrum utilization, and blocking rate are better than traditional algorithms.","PeriodicalId":386048,"journal":{"name":"2020 IEEE 6th International Conference on Computer and Communications (ICCC)","volume":"09 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127182131","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: 2

An Effective Routing Mechanism Based on Fuzzy Logic for Software-Defined Data Center Networks 软件定义数据中心网络中一种基于模糊逻辑的有效路由机制

2020 IEEE 6th International Conference on Computer and Communications (ICCC) Pub Date : 2020-12-11 DOI: 10.1109/ICCC51575.2020.9344964

Yang Xu, W. Muqing, Yao Guohao

引用次数: 0

A Novel Weighted Integration Dynamic Time Regularization and Euclidean Distance Optimization Algorithm for Power Data Mining 电力数据挖掘中一种新的加权积分动态时间正则化与欧氏距离优化算法

2020 IEEE 6th International Conference on Computer and Communications (ICCC) Pub Date : 2020-12-11 DOI: 10.1109/ICCC51575.2020.9345154

Wenda Lu, Xiaolong Zhao, Chen Sun, Rongjun Chen, Guang Duan

引用次数: 0

Secure and Transparent Public-key Management System for Vehicular Social Networks 安全透明的车载社交网络公钥管理系统

2020 IEEE 6th International Conference on Computer and Communications (ICCC) Pub Date : 2020-12-11 DOI: 10.1109/ICCC51575.2020.9345086

Abdul Noor, Youxi Wu, Salabat Khan

{"title":"Secure and Transparent Public-key Management System for Vehicular Social Networks","authors":"Abdul Noor, Youxi Wu, Salabat Khan","doi":"10.1109/ICCC51575.2020.9345086","DOIUrl":"https://doi.org/10.1109/ICCC51575.2020.9345086","url":null,"abstract":"Vehicular Social Networks (VSNs) are expected to become a reality soon, where commuters having common interests in the virtual community of vehicles, drivers, passengers can share information, both about road conditions and their surroundings. This will improve transportation efficiency and public safety. However, social networking exposes vehicles to different kinds of cyber-attacks. This concern can be addressed through an efficient and secure key management framework. This study presents a Secure and Transparent Public-key Management (ST-PKMS) based on blockchain and notary system, but it addresses security and privacy challenges specific to VSNs. ST-PKMS significantly enhances the efficiency and trustworthiness of mutual authentication. In ST-PKMS, each vehicle has multiple short-lived anonymous public-keys, which are recorded on the blockchain platform. However, public-keys get activated only when a notary system notarizes it, and clients accept only notarized public-keys during mutual authentication. Compromised vehicles can be effectively removed from the VSNs by blocking notarization of their public-keys; thus, the need to distribute Certificate Revocation List (CRL) is eliminated in the proposed scheme. ST-PKMS ensures transparency, security, privacy, and availability, even in the face of an active adversary. The simulation and evaluation results show that the ST-PKMS meets real-time performance requirements, and it is cost-effective in terms of scalability, delay, and communication overhead.","PeriodicalId":386048,"journal":{"name":"2020 IEEE 6th International Conference on Computer and Communications (ICCC)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125917955","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: 2

A Machine Learning Pipeline Generation Approach for Data Analysis 数据分析的机器学习管道生成方法

2020 IEEE 6th International Conference on Computer and Communications (ICCC) Pub Date : 2020-12-11 DOI: 10.1109/ICCC51575.2020.9345123

Zhao Ru-tao, Wang Jing, Chen Gao-jian, Li Qian-wen, Yuan Yun-jing

引用次数: 0