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2020 2nd International Conference on Computer Communication and the Internet (ICCCI)最新文献

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A Novel Node Design Based on Smart Antenna in Ad-hoc Network Ad-hoc网络中基于智能天线的节点设计
Pub Date : 2020-06-01 DOI: 10.1109/ICCCI49374.2020.9145991
Li-min Peng, Zhenhua Liu
In this paper, a novel node design based on smart antenna is investigated. Normally, the ad-hoc consists of many nodes, in which there are source nodes (SNs), destination nodes (DNs) and relay nodes (RNs). To improve the performance of ad-hoc network, smart antenna is introduced to increase the relay links in transmission. In traditional node design, the nodes would use analog beamforming (ABF)to form multi beams to transmit services. But there are three disadvantages in traditional node design, one is the high cost of beams, second is the limitation in beam number, and third is the high service loss probability. In our proposed novel node design, we use digital beamforming (DBF) method to reduce the beam costs. We combine DBF with overlay/underlay mode and introduce overlay/underlay beams to increase the beam number. Also, we take differentiated treatment to different services and transmit different services in proper overlay/underlay beams. Using this novel node design, the ad-hoc network could get more relay links and have low service loss probability, and that leads to more service capacity of ad-hoc network, while the network cost is low. Simulation results show that our proposed novel node design has a better performance than the traditional node design.
本文研究了一种基于智能天线的节点设计方法。通常情况下,ad-hoc由多个节点组成,其中有源节点(SNs)、目的节点(DNs)和中继节点(RNs)。为了提高自组网的性能,引入了智能天线来增加传输中的中继链路。在传统的节点设计中,节点采用模拟波束形成(ABF)形成多波束来传输业务。但传统节点设计存在三个缺点,一是波束成本高,二是波束数量有限,三是业务损失概率高。在我们提出的新型节点设计中,我们使用数字波束形成(DBF)方法来降低波束成本。我们将DBF与叠加/衬底模式结合,引入叠加/衬底波束来增加波束数。此外,我们对不同的业务采取区别对待,并在适当的覆盖/底层梁中传输不同的业务。采用这种新颖的节点设计,使ad-hoc网络可以获得更多的中继链路,业务损失概率低,从而提高了ad-hoc网络的业务容量,同时降低了网络成本。仿真结果表明,本文提出的节点设计比传统的节点设计具有更好的性能。
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引用次数: 0
Blockchain and DHT Based Lookup System Aiming for Alternative DNS 基于区块链和DHT的查找系统,旨在替代DNS
Pub Date : 2020-06-01 DOI: 10.1109/ICCCI49374.2020.9145989
Kazuma Matsuoka, Tsunehiko Suzuki
We propose a new lookup system using blockchain and Distributed Hash Table (DHT). Blockchain allows this system to communicate from one node to another node directly without a trusted third party. DHT allows nodes participating in this system to store data distributedly and to propagate data efficiently. The maximum capacity of the blockchain of this system does not increase by adopting a mechanism setting an expiration period of data. In this paper, we describe our current system structure and report the result of measuring how the query time required for a lookup to any data changes depending on the network size and the ratio of off-line nodes.
我们提出了一种基于区块链和分布式哈希表(DHT)的查找系统。区块链允许该系统直接从一个节点通信到另一个节点,而不需要受信任的第三方。DHT允许参与该系统的节点分布式存储数据并有效地传播数据。本系统采用数据过期机制,不增加区块链的最大容量。在本文中,我们描述了我们当前的系统结构,并报告了根据网络大小和脱机节点的比例测量查找任何数据所需的查询时间如何变化的结果。
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引用次数: 4
A Revolutionary Interactive Smart Classroom (RISC) with the Use of Emerging Technologies 使用新兴技术的革命性交互式智能教室(RISC)
Pub Date : 2020-06-01 DOI: 10.1109/ICCCI49374.2020.9145987
Vasileios A. Memos, Georgios M. Minopoulos, C. Stergiou, Konstantinos E. Psannis, Y. Ishibashi
Nowadays, the traditional teacher-centered way of teaching seems to be anachronistic. Disabled people, and not only, face difficulties to follow the current educational methods. The evolution of technology can offer significant benefits in these problems. Cutting-edge technologies, such as as Internet of Things (IoT), Cloud Computing (CC), Wireless Sensor Networks (WSN), Big Data Analytics (BDA), Compressed Sensing (CS), Augmented Reality/Virtual Reality (AR/VR) and 5G Networking can contribute in the field of smart education. However, smart education is currently in an embryonic 2D data representational state. In this paper, we propose a new Revolutionary Interactive Smart Classroom (RISC) which will provide a virtual environment for enhanced learning experience, based on 5G Network. This classroom will also make use of 3D virtual services in combination with haptic equipment and sensors, in order to carry out augmented human sensing information and touch into the virtual class. The advantages of such a classroom will be the sustainability in many fields, such as Society, Education, Environment, Economics, Technology and Cultural Tourism.
如今,传统的以教师为中心的教学方式似乎是不合时宜的。不仅是残疾人,要遵循现行的教育方法也面临困难。技术的发展可以在这些问题上提供显著的好处。物联网(IoT)、云计算(CC)、无线传感器网络(WSN)、大数据分析(BDA)、压缩感知(CS)、增强现实/虚拟现实(AR/VR)和5G网络等尖端技术可以为智慧教育领域做出贡献。然而,智能教育目前还处于二维数据表示的萌芽状态。在本文中,我们提出了一种新的基于5G网络的革命性交互式智能教室(RISC),它将为增强学习体验提供虚拟环境。该教室还将利用3D虚拟服务,结合触觉设备和传感器,在虚拟课堂中进行增强的人类感知信息和触摸。这样一个教室的优势将是在许多领域的可持续性,如社会,教育,环境,经济,技术和文化旅游。
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引用次数: 14
New Field Server Addition Method for Low-Price Rice Cultivation Management System 低价水稻栽培管理系统新增田间服务器的方法
Pub Date : 2020-06-01 DOI: 10.1109/ICCCI49374.2020.9145992
Shogo Ishii, Sota Tatsumi, M. Tanaka, Y. Okumura, Tatsuya Kochi
We are developing a rice cultivation management systems using a field server to reduce the workload of farmers. The feature of our field server is a reasonable price. In order to achieve the reasonable price, the accuracy of time synchronization is sacrificed. At present, it is possible to manage environmental data for crops and fields using sensors. However, there are some points to be improved in the current field server. The first is transmission scheduling in advance is had to set up. The second is that field servers cannot be added during the operation. This paper describes a method to notify all nodes of additional field server information and scheduling to solve the above problem. Simultaneous transmission type flooding method is described in detail. We will also report the experimental results. This protocol is robust for the rice cultivation management systems because the field server is stable. Therefore, it meets farmers' expectation to utilize a reasonable field server.
我们正在开发一个使用田间服务器的水稻种植管理系统,以减少农民的工作量。我们现场服务器的特点是价格合理。为了实现合理的价格,牺牲了时间同步的精度。目前,利用传感器管理作物和田地的环境数据是可能的。但是,当前的字段服务器有一些需要改进的地方。首先是传输调度是必须提前设置的。二是在操作过程中无法添加字段服务器。为了解决上述问题,本文提出了一种将附加的服务器信息和调度通知所有节点的方法。详细介绍了同步传输式驱油方法。我们也将报告实验结果。由于田间服务器是稳定的,该协议对于水稻栽培管理系统具有鲁棒性。因此,合理的使用田间服务器是农民的期望。
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引用次数: 1
Implementation of Secure Web Conferencing 安全Web会议的实现
Pub Date : 2020-06-01 DOI: 10.1109/ICCCI49374.2020.9145972
C. Lin, Huan Zhang, Jain-Shing Liu, Shih-Huang Chen
Currently, the online video conference system usually needs to install this application software. Therefore, the software needs to be developed duplicate version for different operating systems (OS), e.g., Android, Windows and MacOS. However, web-based video conference system is OS independent so as to save development cost. In the paper, we present an implementation of a web-based video conference solution by using WebRTC [1]. It can be used for meeting and chat with a browser. Instead of client-server centralized design, in a cyber-video meeting, each member transmits media stream to each other peer-to-peer. Additionally, the media stream is encrypted, and a management mechanism is developed to manage the entry of conference room personnel and achieve a secure multi-party video conference. We also overcome peer-to-peer (P2P)web NAT traversal of media transmission. Our solution covers four main features: P2P Web NAT traversal, dynamic join and leave, access control, dynamic video resolution adjustment.
目前,在线视频会议系统通常需要安装该应用软件。因此,该软件需要针对不同的操作系统(如Android、Windows和MacOS)开发副本版本。而基于web的视频会议系统是独立于操作系统的,可以节省开发成本。在本文中,我们使用WebRTC实现了基于web的视频会议解决方案[1]。它可以用浏览器开会和聊天。在网络视频会议中,每个成员彼此点对点地传输媒体流,而不是客户端-服务器集中式设计。并对媒体流进行加密,开发管理机制,对会议室人员的出入进行管理,实现安全的多方视频会议。我们还克服了媒体传输的点对点(P2P)网络NAT穿越。我们的解决方案包括四个主要特性:P2P Web NAT穿越、动态加入和离开、访问控制、动态视频分辨率调整。
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引用次数: 4
Data Labeling with Novel Decision Module of Tri-training 基于三训练决策模块的数据标注
Pub Date : 2020-06-01 DOI: 10.1109/ICCCI49374.2020.9145968
Chuan-Mu Tseng, Tzu-Wei Huang, Tzong-Jye Liu
In machine learning, supervised learning methods for classifiers have to need sufficient labeled training data. However, it is quite labor-intensive and expensive to manually label a great number of training data. At the moment, there are two types of research related to data labeling: co-training and tri-training. The former primarily uses the voting system based on two algorithms to obtain the labeled results, and the latter is applied to improving co-training. When the two algorithms produce inconsistent results, they will not be able to label the data correctly. Hence, the method of tri-training makes use of the third algorithm to help judge. Our proposed method, Novel Decision Module of Tri-training (NDMTT), uses the output of their architecture to filter the results with threshold conditions, so the validity of the labeling can be improved. When it is improved, one of the classifications can be relatively increased.
在机器学习中,分类器的监督学习方法必须需要足够的标记训练数据。然而,手工标记大量的训练数据是非常费力和昂贵的。目前,与数据标注相关的研究有两种类型:联合训练和三训练。前者主要使用基于两种算法的投票系统来获得标记结果,后者用于改进协同训练。当两种算法产生不一致的结果时,它们将无法正确标记数据。因此,三训练方法利用第三种算法来帮助判断。我们提出的方法,新颖的三训练决策模块(NDMTT),使用他们的体系结构的输出来过滤带有阈值条件的结果,从而可以提高标记的有效性。当它得到改进时,其中一个分类可以相对增加。
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引用次数: 2
New Effective Differential Evolution Algorithm for the Project Scheduling Problem 项目调度问题的一种新的有效差分进化算法
Pub Date : 2020-06-01 DOI: 10.1109/ICCCI49374.2020.9145982
Huu Dang Quoc, Loc Nguyen The, Cuong Nguyen Doan, Toan Phan Thanh
The Resource-Constrained Project Scheduling Problem (RCPSP) is a classical combinational optimization problem that has many practical applications. In this paper, we consider an extension of the RCPSP which called Multi-Skill Resource-Constrained Project Scheduling Problem (MS-RCPSP). In the past few years, various approaches have been proposed to solve this problem such as Genetic Algorithm and Ant Colony Optimization. However, reducing the likelihood of premature convergence is the challenge facing researchers. In this paper, we present a novel algorithm called DEM in order to solve the MS-RCPSP problem. Besides using the differential evolution metaheuristic, we also develop the Reassignment function to improve the solution quality at the end of each iteration, so that proposed algorithm converges rapidly to global extremum. Moreover, proposed algorithm also avoids getting trapped in a local extremum. The experiments were conducted to evaluate the performance of the proposed algorithm, as well as to compare the DEM with previous algorithms such as GreedyDO, HAntCO, and GA. Experimental results show that the proposed algorithm can effectively enhance searching efficiently.
资源约束项目调度问题(RCPSP)是一个经典的组合优化问题,具有许多实际应用。本文考虑了多技能资源约束项目调度问题的一个扩展,即多技能资源约束项目调度问题。在过去的几年里,人们提出了各种方法来解决这个问题,如遗传算法和蚁群优化。然而,减少过早收敛的可能性是研究人员面临的挑战。本文提出了一种新的DEM算法来解决MS-RCPSP问题。除了使用微分进化元启发式算法外,我们还开发了重新分配函数来提高每次迭代结束时的解质量,使算法快速收敛到全局极值。此外,该算法还避免了陷入局部极值。通过实验来评估所提出算法的性能,并将DEM与之前的算法(如GreedyDO、HAntCO和GA)进行比较。实验结果表明,该算法能有效地提高搜索效率。
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引用次数: 6
A Packet Aggregation Scheme for Communication Networks Consisted of Mainly Low-Latency Required Packets 一种通信网络的分组聚合方案,主要由低时延所需的分组组成
Pub Date : 2020-06-01 DOI: 10.1109/ICCCI49374.2020.9145967
Takaya Furuta, R. Takahashi, Y. Fukazawa
The number of devices connected to the Internet is increasing rapidly in the Internet of Things era. Consequently, many packets with a small data size are created and sent over a network. Due to the small data size, the header data of packets has a big impact on the entire traffic when such packets are sent in the same network. The arrival of many packets wastes communication resources. Packet aggregation is one solution to deal with this problem, but it also causes delays. This study focuses on an acceptable waiting time, which is unique to the application, and a packet aggregation scheme for communication networks mainly consisting of low-latency-required packets is proposed.
在物联网时代,连接到互联网的设备数量正在迅速增加。因此,创建并通过网络发送许多具有小数据大小的数据包。由于报文的头数据量较小,当报文在同一网络中发送时,头数据对整个流量的影响较大。大量数据包的到达浪费了通信资源。分组聚合是处理此问题的一种解决方案,但它也会导致延迟。本研究着眼于应用特有的可接受的等待时间,提出了一种以低延迟要求的数据包为主的通信网络分组聚合方案。
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引用次数: 0
PeTIT: Perceiving the Technological Innovation Trends via the Heuristic Model of Community Detection 基于社区检测启发式模型的技术创新趋势感知
Pub Date : 2020-06-01 DOI: 10.1109/ICCCI49374.2020.9145976
Hecan Zhang, Xin Guo, C. Yi, Yue Dou, Dong Chen, Nannan Tong, Jiandong Wang
Patent analysis is widely used in many kinds of research, such as competitive intelligence analysis, technology trends perceiving, industrial distribution planning, macro-economy regulations, and so on. Based on the patent data, this paper proposed a novel algorithm, which named PeTIT, to perceive the technological innovation trends by applying the heuristic community detection model. The PeTIT algorithm included four steps: patent ontology extraction, technological innovation tree construction, technological innovation community detection, and technological innovation trends perceiving. We implemented the PeTIT algorithm on the real dataset of invention patents in the field of artificial intelligence in China, which ranged from Jun 1st, 2000 to May 1st, 2019. The results showed that the innovation situation of artificial intelligent was mainly concentrated in 10 fields. Moreover, the application field of intelligent driving has become one of the fastest-growing industries. Finally, the experimental results demonstrated that the cubic exponential smoothing model had a higher performance by perceiving the technological innovation trends.
专利分析被广泛应用于竞争情报分析、技术趋势感知、产业布局规划、宏观经济调控等研究领域。基于专利数据,本文提出了一种基于启发式社区检测模型的技术创新趋势感知算法PeTIT。PeTIT算法包括专利本体提取、技术创新树构建、技术创新社区检测和技术创新趋势感知四个步骤。我们在2000年6月1日至2019年5月1日的中国人工智能领域发明专利真实数据集上实现了PeTIT算法。结果表明,人工智能的创新情况主要集中在10个领域。此外,智能驾驶应用领域已成为发展最快的产业之一。最后,实验结果表明,三次指数平滑模型在感知技术创新趋势方面具有较高的性能。
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引用次数: 0
Intelligent SDN Traffic Classification Using Deep Learning: Deep-SDN 基于深度学习的智能SDN流量分类:Deep-SDN
Pub Date : 2020-06-01 DOI: 10.1109/ICCCI49374.2020.9145971
Ali Malik, Ruairí de Fréin, Mohammed Al-Zeyadi, Javier Andreu-Perez
Accurate traffic classification is fundamentally important for various network activities such as fine-grained network management and resource utilisation. Port-based approaches, deep packet inspection and machine learning are widely used techniques to classify and analyze network traffic flows. However, over the past several years, the growth of Internet traffic has been explosive due to the greatly increased number of Internet users. Therefore, both port-based and deep packet inspection approaches have become inefficient due to the exponential growth of the Internet applications that incurs high computational cost. The emerging paradigm of software-defined networking has reshaped the network architecture by detaching the control plane from the data plane to result in a centralised network controller that maintains a global view over the whole network on its domain. In this paper, we propose a new deep learning model for software-defined networks that can accurately identify a wide range of traffic applications in a short time, called Deep-SDN. The performance of the proposed model was compared against the state-of-the-art and better results were reported in terms of accuracy, precision, recall, and f-measure. It has been found that 96% as an overall accuracy can be achieved with the proposed model. Based on the obtained results, some further directions are suggested towards achieving further advances in this research area.
准确的流量分类对于各种网络活动(如细粒度网络管理和资源利用)至关重要。基于端口的方法、深度数据包检测和机器学习是广泛用于分类和分析网络流量的技术。然而,在过去的几年里,由于互联网用户数量的大幅增加,互联网流量呈爆炸式增长。因此,由于Internet应用的指数级增长带来了高昂的计算成本,基于端口和深度包检测方法都变得效率低下。新兴的软件定义网络范例重塑了网络架构,将控制平面与数据平面分离,从而形成一个集中的网络控制器,在其域内维护整个网络的全局视图。在本文中,我们提出了一种新的软件定义网络深度学习模型,该模型可以在短时间内准确识别各种流量应用,称为deep - sdn。将所提出的模型的性能与最先进的模型进行比较,并在准确性、精密度、召回率和f-measure方面报告了更好的结果。研究发现,该模型的总体精度可以达到96%。在此基础上,提出了进一步研究的方向。
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引用次数: 18
期刊
2020 2nd International Conference on Computer Communication and the Internet (ICCCI)
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