首页 > 最新文献

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

英文 中文
The Learning Algorithm of Real-Time Automata 实时自动机的学习算法
Pub Date : 2020-12-11 DOI: 10.1109/ICCC51575.2020.9345101
Junri Mi, Jin Xu
Traditional machine learning algorithms heavily depend on training data. In order to reduce the amount of training data, active learning is proposed to find out the critical data, which place more important roles against other data. The active learning algorithm is also used to learn real-time automaton(RTA). However, a huge number of membership queries and equivalence queries are generated in the learning process. In this paper, We design a new data structure to store the information obtained by membership queries. This data structure is a kind of tree structure, and improve the efficiency of the active learning for real-time RTA because this structure can process counter-examples effectively. Some experiments are conducted, and the results show that the algorithm can significantly reduce the number of membership queries without increasing the equivalence queries numbers. From the data point of view, our algorithm reduces the number of membership queries by 50% and the execution time by 80%.
传统的机器学习算法严重依赖于训练数据。为了减少训练数据的数量,主动学习被提出来找出关键数据,这些关键数据相对于其他数据具有更重要的作用。主动学习算法也被用于实时自动机的学习。然而,在学习过程中会产生大量的成员查询和等价查询。在本文中,我们设计了一种新的数据结构来存储通过成员查询获得的信息。这种数据结构是一种树状结构,能够有效地处理反例,提高了实时RTA主动学习的效率。实验结果表明,该算法可以在不增加等价查询数的情况下显著减少隶属查询数。从数据的角度来看,我们的算法将成员查询的数量减少了50%,执行时间减少了80%。
{"title":"The Learning Algorithm of Real-Time Automata","authors":"Junri Mi, Jin Xu","doi":"10.1109/ICCC51575.2020.9345101","DOIUrl":"https://doi.org/10.1109/ICCC51575.2020.9345101","url":null,"abstract":"Traditional machine learning algorithms heavily depend on training data. In order to reduce the amount of training data, active learning is proposed to find out the critical data, which place more important roles against other data. The active learning algorithm is also used to learn real-time automaton(RTA). However, a huge number of membership queries and equivalence queries are generated in the learning process. In this paper, We design a new data structure to store the information obtained by membership queries. This data structure is a kind of tree structure, and improve the efficiency of the active learning for real-time RTA because this structure can process counter-examples effectively. Some experiments are conducted, and the results show that the algorithm can significantly reduce the number of membership queries without increasing the equivalence queries numbers. From the data point of view, our algorithm reduces the number of membership queries by 50% and the execution time by 80%.","PeriodicalId":386048,"journal":{"name":"2020 IEEE 6th International Conference on Computer and Communications (ICCC)","volume":"149 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":"115420462","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
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
Pub Date : 2020-12-11 DOI: 10.1109/ICCC51575.2020.9345166
Le Yang, Meng Li, Yanhua Zhang, Pengbo Si, Zhuwei Wang, Ruizhe Yang
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.
随着各种通信技术的发展,工业物联网应运而生。为了保证海量工业物联网数据的安全性和隐私性,区块链被广泛认为是一种有前途的技术,并被应用于工业物联网。然而,现有的基于区块链的工业物联网仍然存在以下几个问题:1)计算任务的能耗难以承受;2)区块链共识机制的效率不高;3)网络系统的计算开销严重。针对上述问题和挑战,本文将移动边缘计算(MEC)集成到支持区块链的工业物联网系统中,以提升工业物联网设备的计算能力,提高共识流程的效率。同时,还综合考虑了包括能耗和计算开销在内的加权系统成本。此外,我们为支持区块链的工业物联网系统提出了一个优化框架,以减少消耗,并将所提出的问题制定为马尔可夫决策过程(MDP)。可以动态选择和调整主控制器、卸载决策、块大小和计算服务器,优化设备能量分配,降低加权系统成本。因此,由于高动态和大维度的特点,引入深度强化学习(deep reinforcement learning, DRL)来解决公式化问题。仿真结果表明,与现有方案相比,该方案能显著提高系统性能。
{"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
Pub Date : 2020-12-11 DOI: 10.1109/ICCC51575.2020.9344984
H. Gull, Gomathi Krishna, May Aldossary, S. Z. Iqbal
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.
一种抽象的冠状病毒疾病已被宣布为影响全球数百万人生活和健康的传染性大流行。它造成了大量的死亡,在世界范围内产生了非常紧急状态。它没有影响到人民,但也破坏了不同国家的基础设施,特别是在全球卫生保健系统中造成了预期的情况。由于无法获得疫苗接种以及病毒在人与人之间的传播速度加快,卫生保健设施面临着超出其极限和能力的高风险,特别是在巴基斯坦等发展中国家。因此,重要的是在这些国家妥善管理资源,以控制高死亡率及其可能造成的损害。在本文中,我们对巴基斯坦的一个小城市进行了案例研究,那里的医疗设施不足以应对流行病。根据病情的严重程度,大部分患者只能转诊到大城市。我们从这个小城市获取了COVID-19阳性患者的数据,开发并应用了机器学习分类模型来预测患者的严重程度,以应对资源短缺的问题。在所有七个已测试的算法中,我们选择支持向量机来预测患者的严重程度。模型的准确率达到60%,并将患者的严重程度分为轻度、中度和重度。
{"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
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
At present, Chinese traditional physiotherapy is more and more trusted and valued by people, among which moxibustion is a very effective treatment. In order to improve the efficiency of human-computer interaction and help physiotherapists to use robots to replace human power, this paper proposes a visual based robot arm trajectory teaching method. The physiotherapy staff only needs to use an optical marker to demonstrate the therapeutic trajectory on the patient's back, and the robotic arm can pick up the expected trajectory and repeat the same work. We use LK optical flow algorithm to obtain marker's motion trajectory, and then smoothen the trajectory through SG filter, which is more executable for robot arm. Finally, we design an experiment and simulate it on MATLAB to obtain the accuracy of the trajectory and the results is impressive.
目前,中国传统物理疗法越来越受到人们的信任和重视,其中艾灸是一种非常有效的治疗方法。为了提高人机交互的效率,帮助物理治疗师使用机器人代替人力,本文提出了一种基于视觉的机械臂轨迹教学方法。物理治疗人员只需要使用光学标记在患者背部展示治疗轨迹,机械臂就可以拾取预期的轨迹并重复相同的工作。采用LK光流算法获取标记物的运动轨迹,并通过SG滤波对轨迹进行平滑处理,使其更适合机械臂的可执行性。最后,我们设计了一个实验,并在MATLAB上进行了仿真,获得了弹道的精度,结果令人印象深刻。
{"title":"A Visual Based Robot Trajectory Teaching Method for Traditional Chinese Medical Moxibustion Therapy","authors":"Jiaxun Liu, Qujiang Lei, Yukai Qiao, Guangchao Gui, Xiuhao Li, Jintao Jin, Weijun Wang","doi":"10.1109/ICCC51575.2020.9345310","DOIUrl":"https://doi.org/10.1109/ICCC51575.2020.9345310","url":null,"abstract":"At present, Chinese traditional physiotherapy is more and more trusted and valued by people, among which moxibustion is a very effective treatment. In order to improve the efficiency of human-computer interaction and help physiotherapists to use robots to replace human power, this paper proposes a visual based robot arm trajectory teaching method. The physiotherapy staff only needs to use an optical marker to demonstrate the therapeutic trajectory on the patient's back, and the robotic arm can pick up the expected trajectory and repeat the same work. We use LK optical flow algorithm to obtain marker's motion trajectory, and then smoothen the trajectory through SG filter, which is more executable for robot arm. Finally, we design an experiment and simulate it on MATLAB to obtain the accuracy of the trajectory and the results is impressive.","PeriodicalId":386048,"journal":{"name":"2020 IEEE 6th International Conference on Computer and Communications (ICCC)","volume":"11 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":"120943323","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
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
Pub Date : 2020-12-11 DOI: 10.1109/ICCC51575.2020.9345280
Chen Jiayao, Zhang Dalong, Han Gangtao, Li Zhiyuan
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.
在惯性导航系统(INS)与全球定位系统(GPS)集成系统中,杠杆臂效应是一个重要的误差源,使集成系统高度非线性。杠杆臂在实际应用中除了存在非线性问题外,还存在测量困难。为了解决这一问题,本文提出了考虑无气味卡尔曼滤波器杠杆臂效应的直接滤波方法。该方法在直接卡尔曼滤波的系统模型中加入杠杆臂,并对估计的杠杆臂进行补偿,从而随着滤波器估计的更新不断估计和修正杠杆臂。具体而言,基于直接滤波方法建立了系统状态模型和测量模型。以惯导系统和杠杆臂的导航参数为系统状态变量,以GPS的速度和位置为测量变量。然后将UKF用于INS/GPS综合系统信息融合。仿真结果表明,考虑组合导航系统杠杆臂的直接UKF能够正确估计杠杆臂。此外,该方法的精度显著高于标准间接KF和标准直接UKF。
{"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
Pub Date : 2020-12-11 DOI: 10.1109/ICCC51575.2020.9345258
Yajun Liu, Xiaoqun Liu, Jianfang Zhang, Yingying Cao, Xiaodong Liu
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.
传统波分复用(WDM)网络的频谱网格是固定的,存在频谱利用率低、灵活性差的缺点。基于此,弹性光网络(EON)应运而生。与传统的WDM网络相比,EON具有灵活的频谱网格,具有较高的网络灵活性,可以为不同的业务提供不同的频谱。但是EON仍然存在负载平衡的问题。为了进一步优化EON,本文采用最小连接算法来解决EON的负载均衡问题,考虑不同服务器的负载能力对其进行改进。此外,为了进一步提高EON的性能,本文将遗传算法、改进最小连接算法和蚁群算法相结合,提出了一种新的算法LC-GAACO。仿真结果表明,在考虑负载均衡的情况下,LC-GAACO算法会消耗更多的光模块,但在网络负载均衡效果、网络频谱利用率和阻塞率方面都优于传统算法。
{"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
Pub Date : 2020-12-11 DOI: 10.1109/ICCC51575.2020.9344964
Yang Xu, W. Muqing, Yao Guohao
In order to solve the problem of low throughput and poor performance in data center network, this paper proposes a traffic scheduling algorithm exploiting fuzzy logic inference based on Software Defined Networking (SDN). The algorithm uses the characteristics of separation of control and forwarding in SDN architecture to choose paths for data flows by the centralized control of controller. It calculates the candidate path set of accessible paths between the source host and the destination host, then comprehensively considers path hops and bandwidth utilization, evaluates the candidate path using fuzzy logic model, and selects the optimal path. The experimental results show that compared with ECMP, Hedera and FSEM, the proposed algorithm improves the network throughput and load balancing, thus improving the overall network performance of the data center.
为了解决数据中心网络吞吐量低、性能差的问题,提出了一种基于软件定义网络(SDN)的基于模糊逻辑推理的流量调度算法。该算法利用SDN架构中控制与转发分离的特点,通过控制器的集中控制为数据流选择路径。计算源主机和目的主机之间可达路径的候选路径集,综合考虑路径跳数和带宽利用率,利用模糊逻辑模型对候选路径进行评估,选择最优路径。实验结果表明,与ECMP、Hedera和FSEM相比,本文算法提高了网络吞吐量和负载均衡,从而提高了数据中心的整体网络性能。
{"title":"An Effective Routing Mechanism Based on Fuzzy Logic for Software-Defined Data Center Networks","authors":"Yang Xu, W. Muqing, Yao Guohao","doi":"10.1109/ICCC51575.2020.9344964","DOIUrl":"https://doi.org/10.1109/ICCC51575.2020.9344964","url":null,"abstract":"In order to solve the problem of low throughput and poor performance in data center network, this paper proposes a traffic scheduling algorithm exploiting fuzzy logic inference based on Software Defined Networking (SDN). The algorithm uses the characteristics of separation of control and forwarding in SDN architecture to choose paths for data flows by the centralized control of controller. It calculates the candidate path set of accessible paths between the source host and the destination host, then comprehensively considers path hops and bandwidth utilization, evaluates the candidate path using fuzzy logic model, and selects the optimal path. The experimental results show that compared with ECMP, Hedera and FSEM, the proposed algorithm improves the network throughput and load balancing, thus improving the overall network performance of the data center.","PeriodicalId":386048,"journal":{"name":"2020 IEEE 6th International Conference on Computer and Communications (ICCC)","volume":"47 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":"125059203","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
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
Pub Date : 2020-12-11 DOI: 10.1109/ICCC51575.2020.9345154
Wenda Lu, Xiaolong Zhao, Chen Sun, Rongjun Chen, Guang Duan
With the development of large-scale construction of smart grid, the edge terminal equipment of power grid will produce a large number of time series power data with great redundancy, which brings great challenges to the storage of edge side of the equipment. In order to reduce the storage cost of edge side, data mining and weight removal are needed. The traditional data mining technology generally adopts the data mining method based on dynamic time regularity, but the disadvantage is that the mining efficiency is low and the adjacent data with low similarity can not be weighed. Aiming at these problems, this paper proposes an algorithm based on weighted integration dynamic time-regulation and Euclidean distance optimization, which can eliminate data redundancy, achieve data mining and weight removal by calculating the similarity between data. Finally, based on the real sampling data of smart grid, the effect of the proposed data mining technology in edge computing security protection system is analyzed and verified.
随着智能电网大规模建设的发展,电网边缘终端设备将产生大量具有大冗余度的时间序列电力数据,这给设备边缘端的存储带来了很大的挑战。为了降低边缘边的存储成本,需要进行数据挖掘和去权。传统的数据挖掘技术一般采用基于动态时间规则的数据挖掘方法,缺点是挖掘效率低,且无法对相似度较低的相邻数据进行加权。针对这些问题,本文提出了一种基于加权积分动态时间调节和欧氏距离优化的算法,通过计算数据之间的相似度来消除数据冗余,实现数据挖掘和去权。最后,基于智能电网的真实采样数据,分析并验证了所提出的数据挖掘技术在边缘计算安全防护系统中的效果。
{"title":"A Novel Weighted Integration Dynamic Time Regularization and Euclidean Distance Optimization Algorithm for Power Data Mining","authors":"Wenda Lu, Xiaolong Zhao, Chen Sun, Rongjun Chen, Guang Duan","doi":"10.1109/ICCC51575.2020.9345154","DOIUrl":"https://doi.org/10.1109/ICCC51575.2020.9345154","url":null,"abstract":"With the development of large-scale construction of smart grid, the edge terminal equipment of power grid will produce a large number of time series power data with great redundancy, which brings great challenges to the storage of edge side of the equipment. In order to reduce the storage cost of edge side, data mining and weight removal are needed. The traditional data mining technology generally adopts the data mining method based on dynamic time regularity, but the disadvantage is that the mining efficiency is low and the adjacent data with low similarity can not be weighed. Aiming at these problems, this paper proposes an algorithm based on weighted integration dynamic time-regulation and Euclidean distance optimization, which can eliminate data redundancy, achieve data mining and weight removal by calculating the similarity between data. Finally, based on the real sampling data of smart grid, the effect of the proposed data mining technology in edge computing security protection system is analyzed and verified.","PeriodicalId":386048,"journal":{"name":"2020 IEEE 6th International Conference on Computer and Communications (ICCC)","volume":"1 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":"125892919","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
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
Pub Date : 2020-12-11 DOI: 10.1109/ICCC51575.2020.9345086
Abdul Noor, Youxi Wu, Salabat Khan
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.
车辆社交网络(VSNs)有望很快成为现实,通勤者在车辆、司机、乘客的虚拟社区中有共同的兴趣,可以分享有关道路状况和周围环境的信息。这将提高交通效率和公共安全。然而,社交网络使车辆暴露于各种网络攻击之下。这个问题可以通过一个有效和安全的密钥管理框架来解决。本研究提出了一种基于区块链和公证系统的安全透明的公钥管理(ST-PKMS),但它解决了VSNs特有的安全和隐私挑战。ST-PKMS显著提高了相互认证的效率和可信度。在ST-PKMS中,每辆车都有多个短期匿名公钥,这些公钥被记录在区块链平台上。但是,公钥只有在公证系统对其进行公证时才会被激活,并且客户端在相互身份验证期间只接受经过公证的公钥。通过阻止对其公钥进行公证,可以有效地将受损车辆从VSNs中移除;因此,在提议的方案中不需要分发证书撤销列表(CRL)。即使面对活跃的对手,ST-PKMS也能确保透明性、安全性、隐私性和可用性。仿真和评估结果表明,ST-PKMS满足实时性要求,在可扩展性、时延和通信开销方面具有较好的性价比。
{"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
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
Data analysis requires a high level of expertise for domain workers, and AutoML aims to make these decisions in an automated way. But it is still a difficult problem to automatically generate machine learning pipelines with high performance in acceptable time. This paper presents a DFSR (Data Feature and Service Association) approach to automatically generating machine learning pipelines utilizing data features and service associations. The experimental results showed that the performance of the generated pipelines reached the satisfactory level of current AutoML tools, and the time consumption is reduced to the minute level.
数据分析需要领域工作者具备高水平的专业知识,而AutoML旨在以自动化的方式做出这些决策。但如何在可接受的时间内自动生成高性能的机器学习管道仍然是一个难题。本文提出了一种利用数据特征和服务关联自动生成机器学习管道的DFSR(数据特征和服务关联)方法。实验结果表明,所生成的管道的性能达到了现有AutoML工具的满意水平,并且将耗时降低到分钟级。
{"title":"A Machine Learning Pipeline Generation Approach for Data Analysis","authors":"Zhao Ru-tao, Wang Jing, Chen Gao-jian, Li Qian-wen, Yuan Yun-jing","doi":"10.1109/ICCC51575.2020.9345123","DOIUrl":"https://doi.org/10.1109/ICCC51575.2020.9345123","url":null,"abstract":"Data analysis requires a high level of expertise for domain workers, and AutoML aims to make these decisions in an automated way. But it is still a difficult problem to automatically generate machine learning pipelines with high performance in acceptable time. This paper presents a DFSR (Data Feature and Service Association) approach to automatically generating machine learning pipelines utilizing data features and service associations. The experimental results showed that the performance of the generated pipelines reached the satisfactory level of current AutoML tools, and the time consumption is reduced to the minute level.","PeriodicalId":386048,"journal":{"name":"2020 IEEE 6th International Conference on Computer and Communications (ICCC)","volume":"26 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":"123247647","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
期刊
2020 IEEE 6th International Conference on Computer and Communications (ICCC)
全部 Acc. Chem. Res. ACS Applied Bio Materials ACS Appl. Electron. Mater. ACS Appl. Energy Mater. ACS Appl. Mater. Interfaces ACS Appl. Nano Mater. ACS Appl. Polym. Mater. ACS BIOMATER-SCI ENG ACS Catal. ACS Cent. Sci. ACS Chem. Biol. ACS Chemical Health & Safety ACS Chem. Neurosci. ACS Comb. Sci. ACS Earth Space Chem. ACS Energy Lett. ACS Infect. Dis. ACS Macro Lett. ACS Mater. Lett. ACS Med. Chem. Lett. ACS Nano ACS Omega ACS Photonics ACS Sens. ACS Sustainable Chem. Eng. ACS Synth. Biol. Anal. Chem. BIOCHEMISTRY-US Bioconjugate Chem. BIOMACROMOLECULES Chem. Res. Toxicol. Chem. Rev. Chem. Mater. CRYST GROWTH DES ENERG FUEL Environ. Sci. Technol. Environ. Sci. Technol. Lett. Eur. J. Inorg. Chem. IND ENG CHEM RES Inorg. Chem. J. Agric. Food. Chem. J. Chem. Eng. Data J. Chem. Educ. J. Chem. Inf. Model. J. Chem. Theory Comput. J. Med. Chem. J. Nat. Prod. J PROTEOME RES J. Am. Chem. Soc. LANGMUIR MACROMOLECULES Mol. Pharmaceutics Nano Lett. Org. Lett. ORG PROCESS RES DEV ORGANOMETALLICS J. Org. Chem. J. Phys. Chem. J. Phys. Chem. A J. Phys. Chem. B J. Phys. Chem. C J. Phys. Chem. Lett. Analyst Anal. Methods Biomater. Sci. Catal. Sci. Technol. Chem. Commun. Chem. Soc. Rev. CHEM EDUC RES PRACT CRYSTENGCOMM Dalton Trans. Energy Environ. Sci. ENVIRON SCI-NANO ENVIRON SCI-PROC IMP ENVIRON SCI-WAT RES Faraday Discuss. Food Funct. Green Chem. Inorg. Chem. Front. Integr. Biol. J. Anal. At. Spectrom. J. Mater. Chem. A J. Mater. Chem. B J. Mater. Chem. C Lab Chip Mater. Chem. Front. Mater. Horiz. MEDCHEMCOMM Metallomics Mol. Biosyst. Mol. Syst. Des. Eng. Nanoscale Nanoscale Horiz. Nat. Prod. Rep. New J. Chem. Org. Biomol. Chem. Org. Chem. Front. PHOTOCH PHOTOBIO SCI PCCP Polym. Chem.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1