2018 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC)最新文献

筛选
英文 中文
Research on Joint Mode Selection and Resource Allocation Scheme in D2D Networks D2D网络中联合模式选择与资源分配方案研究
Jiale Zhao, Shuangzhi Li, Daniel C. F. Ma, X. Mu
{"title":"Research on Joint Mode Selection and Resource Allocation Scheme in D2D Networks","authors":"Jiale Zhao, Shuangzhi Li, Daniel C. F. Ma, X. Mu","doi":"10.1109/CYBERC.2018.00083","DOIUrl":"https://doi.org/10.1109/CYBERC.2018.00083","url":null,"abstract":"In this paper, we consider a single-cell spectrum sharing system, in which there exist multiple cognitive device-to-device (D2D) pairs and cellular users (CUs). For such a system, in order to improve the overall spectral efficiency, we propose a joint mode selection and resource allocation scheme. In detail, a mode selection criterion is firstly built by utilizing the knowledge of channel gain ratio; then, for different modes of D2D users, a resource allocation strategy based on greedy algorithm is derived. Finally, by exploiting the genetic algorithm, dichotomy and Lagrange multiplier method jointly, we further optimize the power allocation scheme. Simulation results demonstrate that the proposed scheme is able to enhance the spectral efficiency of the considered system.","PeriodicalId":282903,"journal":{"name":"2018 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121426144","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
Multi-UAV Task Allocation Based on Improved Algorithm of Multi-objective Particle Swarm Optimization 基于改进多目标粒子群优化算法的多无人机任务分配
Yang Gao, Yingzhou Zhang, Shurong Zhu, Yi Sun
{"title":"Multi-UAV Task Allocation Based on Improved Algorithm of Multi-objective Particle Swarm Optimization","authors":"Yang Gao, Yingzhou Zhang, Shurong Zhu, Yi Sun","doi":"10.1109/CYBERC.2018.00086","DOIUrl":"https://doi.org/10.1109/CYBERC.2018.00086","url":null,"abstract":"With the development of the technology of unmanned aerial vehicle (UAV), the multi-UAV task allocation has become a hot topic in recent years. Recently, many classical intelligent optimization algorithms have been applied to this problem, because the multi-UAV task allocation problem can be formalized as a NP-hard issue. However, most research treat this problem as a single objective optimization problem. In view of this situation, we use an improved algorithm of multi-objective particle swarm optimization (MOPSO) to solve the task allocation problem of multiple UAVs. We will take two stages of SMC resampling to improve the disadvantages in the MOPSO algorithm. In the first stage, resampling is used to improve the slow convergence of the particle swarm optimization in the middle and late stages. In the second stage, resampling is used to expand the search area of the particle swarm optimization algorithm and to prevent the algorithm from falling into the local optimal solution. The simulation results show that the improved algorithm has a good performance in solving the task allocation problem of multiple UAVs.","PeriodicalId":282903,"journal":{"name":"2018 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125680957","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: 10
Evaluating and Detecting Internal Attacks in a Mobile Robotic Network 移动机器人网络内部攻击评估与检测
E. Basan, A. Basan, O. Makarevich
{"title":"Evaluating and Detecting Internal Attacks in a Mobile Robotic Network","authors":"E. Basan, A. Basan, O. Makarevich","doi":"10.1109/CYBERC.2018.00102","DOIUrl":"https://doi.org/10.1109/CYBERC.2018.00102","url":null,"abstract":"In this paper we consider the problem of the need for deep traffic analysis to detect attacks on a network of mobile robots, as well as to assess their effectiveness. The object of the study is a group of mobile robots. It provide a means to analyze the security of mobile robot networks. It analyzes the anomalous activity of robots in a mobile network, based on analysis of traffic at the network and transport layers. To carry out such an analysis, a mathematical approach based on mathematical statistics and probability theory is used. It allows detecting attacks distributed denial of service and Sibyl attack. In addition, this technique allows us to determine what metrics are affected by this or that attack. In addition, it is possible to assess under what conditions the attack has the greatest impact on the network. In this paper, an experimental study was carried out and statistical data collected, the analysis of which allowed us to confirm theoretical assumptions.","PeriodicalId":282903,"journal":{"name":"2018 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126507784","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: 9
A Hybrid of Deep Sentence Representation and Local Feature Representation Model for Question Answer Selection 基于深度句子表示和局部特征表示的混合问答选择模型
Dongge Tang, Wenge Rong, Libin Shi, Haodong Yang, Zhang Xiong
{"title":"A Hybrid of Deep Sentence Representation and Local Feature Representation Model for Question Answer Selection","authors":"Dongge Tang, Wenge Rong, Libin Shi, Haodong Yang, Zhang Xiong","doi":"10.1109/CYBERC.2018.00057","DOIUrl":"https://doi.org/10.1109/CYBERC.2018.00057","url":null,"abstract":"Answer selection is a one of the critical tasks in natural lan-guage processing area and it is helpful in many practical applications. To better tackle this problem, the first challenge is to effectively extract the sentence information. In this research, we propose an advanced Re-Read-CNN model which can learn a deep sentence representation and meanwhile combine the local feature representation. The experiment results on commonly used datasets have shown its effectiveness and potential for answer selection.","PeriodicalId":282903,"journal":{"name":"2018 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117291699","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
Prior-Information Associated Channel Parameter Estimation for Aeronautical Communications 航空通信的先验信息关联信道参数估计
Youyou Zhao, Xingxuan Zuo, Yingbo Shang, X. Mu, Jiankang Zhang
{"title":"Prior-Information Associated Channel Parameter Estimation for Aeronautical Communications","authors":"Youyou Zhao, Xingxuan Zuo, Yingbo Shang, X. Mu, Jiankang Zhang","doi":"10.1109/CYBERC.2018.00078","DOIUrl":"https://doi.org/10.1109/CYBERC.2018.00078","url":null,"abstract":"L-band digital aeronautical communication system (L-DACS) based on orthogonal Frequency Division Multiplexing (OFDM) technology is the best candidate for the future communication infrastructure of the air-to-ground (AG) communication system. How does the receiver can correctly and timely determine the channel change becomes the basis for ensuring the stable transmission of information in the aeronautical communication network. In this paper, we propose a channel parameter estimation algorithm using the statistical multipath delay information of takeoff and landing near the airport as a priori information in the navigation system and fixed aircraft scene. Simulation results have demonstra-ted that the proposed algorithm significantly improves the estimated performance on the basis of reducing the parameters to be estimated.","PeriodicalId":282903,"journal":{"name":"2018 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128873976","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 Field Intensity Based Model for Initiative File Sharing in Mobile Social Networks 移动社交网络中基于场强的主动文件共享模型
Zehong Zhou, Chenxi Zhang, Zhenyu A. Liao, Jian Xu, Jiangfeng Li
{"title":"A Field Intensity Based Model for Initiative File Sharing in Mobile Social Networks","authors":"Zehong Zhou, Chenxi Zhang, Zhenyu A. Liao, Jian Xu, Jiangfeng Li","doi":"10.1109/CYBERC.2018.00048","DOIUrl":"https://doi.org/10.1109/CYBERC.2018.00048","url":null,"abstract":"An intermittently connected mobile social network (ICMSN) is a special kind of delay tolerant network (DTN). Compared with the stable routing path in conventional networks, there is not a stable routing path from source to destination in ICMSNs. In order to deal with the challenging routing issue in ICMSNs, numerous opportunistic routing algorithms have been proposed. However, the existed approaches cannot achieve the optimal performance in file sharing because most of them focus on the general routing but ignore the social characteristic. In addition, the needed resources passively waited until a request has been received by the nodes in the traditional file sharing schemes. In this paper, a field intensity based model is proposed to solve the passive file sharing problem in ICMSNs. This model exploits the field intensity generated from the inherent features of mobile users to decide a better orientation for messages forwarding. Furthermore, a container which be used to store the information of field is designed to reduce overhead. We also propose a field intensity based redundancy control strategy to maintain the number of copies within a reasonable range. Finally, we realize a initiative file sharing system according to the model. The simulation results show that our method has advantages in performance against other methods.","PeriodicalId":282903,"journal":{"name":"2018 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125293112","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
Mesh Generation Technique and Object Identification for Robotic/Artificial Intelligence 机器人/人工智能的网格生成技术和目标识别
Mahesh Singh
{"title":"Mesh Generation Technique and Object Identification for Robotic/Artificial Intelligence","authors":"Mahesh Singh","doi":"10.1109/CYBERC.2018.00093","DOIUrl":"https://doi.org/10.1109/CYBERC.2018.00093","url":null,"abstract":"This technique of mesh generation is based on advance and researched quad tree approach which makes use of mathematical technique of variance for selecting quad size and further triangulate the quad for final mesh of image and later filtering of vertices is done as per mapping based on robotic model. Object identification based on Bayesian statistical and probability theorem is used to estimate the foreground object for getting selective object within image for mesh generation. This paper explains estimation algorithms for object identification by detecting background and foreground objects in image obtained from raw video frame@30fps supporting sampling format 4:2:0. This algorithm is implemented tested/verified on and written for android based ARM system and x86 for demo and quality propose.Video frame is live captured in .mp4 file format using aac/avc (H264) audio and video codec. Video is decoded and sub sampled and scaled using ffmeg framework to desired frame size and frame format for Video processing using Open source based framework integrated into propriety applications. This algorithm can be applied for various application including application in defense/artificial intelligence and medical imaging","PeriodicalId":282903,"journal":{"name":"2018 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129973611","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
Users Scheduling and Power Allocation Algorithm for MIMO-OFDMA Green Cognitive Radio Systems MIMO-OFDMA绿色认知无线电系统的用户调度与功率分配算法
N. S. A. G. Yari, Varus Mbembo Loundou, Dong Doan Van
{"title":"Users Scheduling and Power Allocation Algorithm for MIMO-OFDMA Green Cognitive Radio Systems","authors":"N. S. A. G. Yari, Varus Mbembo Loundou, Dong Doan Van","doi":"10.1109/CYBERC.2018.00070","DOIUrl":"https://doi.org/10.1109/CYBERC.2018.00070","url":null,"abstract":"With growing of wireless systems integration, the role that plays green communication platforms are becoming more essential for reducing energy consumption. By proposing a based sub-optimal green energy-efficient algorithm to solve issue of low computational, this paper investigates the effect of users scheduling and power allocation scheme for MIMO-OFDMA green cognitive radio network The problem is formulated as a mixed-integer non-convex optimization problem, in which the objective is to maximize the energy efficiency, enabling Green Communication, under the constraints of the per-user power budget and primary system’s QoS requirements. Taking account of the mixed-integer and non-convexity nature of the problem, we propose a sub-optimal energy-efficient algorithm through two successive steps. The first step schedules the subcarriers among the SUs based on IA while the second step iteratively allocates the power based on Dinkelbach’s method. Through numerical result, the proposed algorithm is revealed to achieve significant improvement in the energy efficiency compared to the traditional spectrum-efficient algorithm.","PeriodicalId":282903,"journal":{"name":"2018 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130177607","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
Interpolation Method for Radio Map Establishment Based on RSS Clustering and Propagation Model Optimization 基于RSS聚类和传播模型优化的射电图建立插值方法
Yongliang Sun, Yu He, Yang Yang
{"title":"Interpolation Method for Radio Map Establishment Based on RSS Clustering and Propagation Model Optimization","authors":"Yongliang Sun, Yu He, Yang Yang","doi":"10.1109/CYBERC.2018.00087","DOIUrl":"https://doi.org/10.1109/CYBERC.2018.00087","url":null,"abstract":"In recent years, Location-Based Services (LBS) have been widely applied in people's life with various localization technologies. Because outdoor localization methods are not suitable for indoor environments, various indoor localization methods have been developed. Among the existing indoor localization methods, Wi-Fi fingerprinting localization has attracted great concerns because of its wide applicability, simple deployment, and comparable performance. This paper proposed an interpolation method for radio map establishment based on RSS clustering and propagation model optimization. Fuzzy C-Means (FCM) clustering algorithm is used to cluster the Received Signal Strength (RSS) samples collected at Reference Points (RPs). In each cluster, propagation model parameters are optimized. Then RSS samples are estimated at select locations for radio map establishment. With the radio map after interpolation, more accurate localization results can be computed using K Nearest Neighbors (KNN) fingerprinting algorithm.","PeriodicalId":282903,"journal":{"name":"2018 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116457881","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 Abnormal State Detection Method for Power Distribution Network Based on Big Data Technology 基于大数据技术的配电网异常状态检测方法
Lijuan Hu, Ke-yan Liu, Zhi Lin, Yinglong Diao, W. Sheng
{"title":"An Abnormal State Detection Method for Power Distribution Network Based on Big Data Technology","authors":"Lijuan Hu, Ke-yan Liu, Zhi Lin, Yinglong Diao, W. Sheng","doi":"10.1109/CYBERC.2018.00042","DOIUrl":"https://doi.org/10.1109/CYBERC.2018.00042","url":null,"abstract":"This paper focuses on using big data technology to solve the abnormal state detection problem in power distribution system. With the increasingly more widespread use of digitalization technology, various related systems have been embedded extensively in power system, resulting in a large number of interconnected observations. In order to discover more complex deep-seated rules and provide more effective decision support for power system decision-making, it is necessary to study data mining and analysis methods that are suitable for massive data under current situation. This paper studies the method to identify abnormal data from multi-temporal and multi-spatial data in distribution networks and propose a method to detective abnormal operation state using likelihood-ratio test for three-dimensional spatiotemporal data. In order to speed up the data processing rate, an anomaly detection method based on multi-threading and Hadoop parallelization methods and techniques is proposed.","PeriodicalId":282903,"journal":{"name":"2018 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123812031","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
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
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
确定
请完成安全验证×
相关产品
×
本文献相关产品
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信