2017 International Conference on Computer, Information and Telecommunication Systems (CITS)最新文献_第2页

An effective semi-supervised model for intrusion detection using feature selection based LapSVM 基于特征选择的拉普拉斯支持向量机半监督入侵检测模型

2017 International Conference on Computer, Information and Telecommunication Systems (CITS) Pub Date : 2017-07-01 DOI: 10.1109/CITS.2017.8035323

Xiaofeng Zhang, Peidong Zhu, Jianwei Tian, Jiexin Zhang

引用次数: 7

An investigation for the design of the metal barcode label with patterns read by the eddy current testing 涡流检测读模金属条码标签的设计探讨

2017 International Conference on Computer, Information and Telecommunication Systems (CITS) Pub Date : 2017-07-01 DOI: 10.1109/CITS.2017.8035301

Yin Zhao, Hongguang Xu, Qinyu Zhang

引用次数: 1

An energy-based weight selection algorithm of monitor node in MANETs 基于能量的manet监控节点权重选择算法

2017 International Conference on Computer, Information and Telecommunication Systems (CITS) Pub Date : 2017-07-01 DOI: 10.1109/CITS.2017.8035303

Yongcheng Li, Jinfeng Gao, Yao Yu, Ting Cao

引用次数: 3

Performance analysis of polarization coding BB84 quantum key distribution system under non-Markovian channel 非马尔可夫信道下偏振编码BB84量子密钥分配系统的性能分析

2017 International Conference on Computer, Information and Telecommunication Systems (CITS) Pub Date : 2017-07-01 DOI: 10.1109/CITS.2017.8035309

W. Liu, Changhua Zhu, Linxi Zhang, Changxing Pei

引用次数: 1

Comparative analysis of SDN and conventional networks using routing protocols SDN与使用路由协议的传统网络的对比分析

2017 International Conference on Computer, Information and Telecommunication Systems (CITS) Pub Date : 2017-07-01 DOI: 10.1109/CITS.2017.8035305

D. Gopi, Samuel Cheng, R. Huck

{"title":"Comparative analysis of SDN and conventional networks using routing protocols","authors":"D. Gopi, Samuel Cheng, R. Huck","doi":"10.1109/CITS.2017.8035305","DOIUrl":"https://doi.org/10.1109/CITS.2017.8035305","url":null,"abstract":"Conventional routing protocols such as RIP, OSPF, EIGRP and BGP have a very rigid and intricate system thus narrowing the adaptability of networks to the ever changing Internet. The emergence of Software Defined Networking (SDN) provides a solution for this problem. Due to the handiness of a centralized controller, SDN has provided an effective method in terms of routing computation and fine control over data packets. Due to the increase in unpredicted failures taking place the ability to predict/know the approximate maximum time it takes for these networks to converge in order to avoid and/or minimize loss of packets/data during these failures has become crucial in today's world. This time that the routers in the network take to converge via the implemented routing protocol and resume communication or transfer of information is called the routing convergence time. In this work, the performance is measured using routing convergence time during link failure with respect to the topology scale to show that SDN routing/forwarding is better compared to conventional routing. Further the results indicate that the routing convergence time is less in SDN networks on comparison with conventional networks when the topology scale is increased, indicating that SDN networks converge faster in comparison with Conventional networks and that routing convergence time is greatly influenced with the changing topological size.","PeriodicalId":314150,"journal":{"name":"2017 International Conference on Computer, Information and Telecommunication Systems (CITS)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124038682","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: 35

Deadline-constraint services in cloud with heterogeneous servers 具有异构服务器的云中的截止日期约束服务

2017 International Conference on Computer, Information and Telecommunication Systems (CITS) Pub Date : 2017-07-01 DOI: 10.1109/CITS.2017.8035330

Sampa Sahoo, S. Mishra, B. Sahoo, Deepak Puthal, M. Obaidat

引用次数: 2

Multi-controller collaborative interconnecting for multilayer heterogeneous SDON 多层异构SDON的多控制器协同互连

2017 International Conference on Computer, Information and Telecommunication Systems (CITS) Pub Date : 2017-07-01 DOI: 10.1109/CITS.2017.8035293

Q. Ou, Jing Wang, Xiao Liao, Wenjing Li, Xiaolong Yang

引用次数: 1

Link congestion and lifetime based in-network caching scheme in Information Centric Networking 信息中心网络中基于链路拥塞和生存期的网络内缓存方案

2017 International Conference on Computer, Information and Telecommunication Systems (CITS) Pub Date : 2017-07-01 DOI: 10.1109/CITS.2017.8035289

Jiahui Kong, Lanlan Rui, Haoqiu Huang, Xiaomei Wang

{"title":"Link congestion and lifetime based in-network caching scheme in Information Centric Networking","authors":"Jiahui Kong, Lanlan Rui, Haoqiu Huang, Xiaomei Wang","doi":"10.1109/CITS.2017.8035289","DOIUrl":"https://doi.org/10.1109/CITS.2017.8035289","url":null,"abstract":"Ubiquitous in-network caching is one of the important aspects of the Information-Centric Networking (ICN), which has been a hot topic of ICN research. Many works have tried to propose better caching schemes to solve the drawbacks of the default en-route scheme, but most of them are insufficient to improve performance of entire network for just considering single layer optimization factor. Also considering that the network exists to serve its users, user-centric performance metrics, in particular the download delay, are equally important as the common metrics such as cache hit rate in performance evaluation. And approaches designed with congestion-sensitive download delay in mind can obtain better performance and user experience. In this paper, we propose and evaluate a novel Link Congestion and lifetime Based In-Networking Caching Schemes (LCLCS), which takes fully account of link congestion, Betweenness centrality and content popularity, aiming to observably optimize network delay and maintain acceptable cache rate. Through simulation, we can prove that network latency and hop reduction rate of our policy are significantly better than existing policies at least 51.5%, while the cache hit ratio is relatively improved by at least 19.1% under network congestion.","PeriodicalId":314150,"journal":{"name":"2017 International Conference on Computer, Information and Telecommunication Systems (CITS)","volume":"123 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115607798","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: 5

Dynamic Adjusting Time Synchronization for sensor networks 传感器网络动态调整时间同步

2017 International Conference on Computer, Information and Telecommunication Systems (CITS) Pub Date : 2017-07-01 DOI: 10.1109/CITS.2017.8035324

Hongcheng Yan, Wenyi Liu, Xianghui Wang, Rui Zhang

引用次数: 1

Application of Deep Learning to Sentiment Analysis for recommender system on cloud 深度学习在云推荐系统情感分析中的应用

2017 International Conference on Computer, Information and Telecommunication Systems (CITS) Pub Date : 2017-07-01 DOI: 10.1109/CITS.2017.8035341

G. Preethi, P. V. Krishna, M. Obaidat, V. Saritha, Sumanth Yenduri

{"title":"Application of Deep Learning to Sentiment Analysis for recommender system on cloud","authors":"G. Preethi, P. V. Krishna, M. Obaidat, V. Saritha, Sumanth Yenduri","doi":"10.1109/CITS.2017.8035341","DOIUrl":"https://doi.org/10.1109/CITS.2017.8035341","url":null,"abstract":"Sentiment analysis of short texts like single sentences and reviews available on different social networking sites is challenging because of the limited contextual information. Based on the sentiments and opinions available, developing a recommendation system is an interesting concept, which includes strategies that combine the small text content with prior knowledge. In this paper, we explore a new application of Recursive Neural Networks (RNN) with deep learning system for sentiment analysis of reviews. The proposed RNN-based Deep-learning Sentiment Analysis (RDSA) recommends the places that are near to the user's current location by analyzing the different reviews and consequently computing the score grounded on it. Deep Learning is used to optimize the recommendations depending on the sentiment analysis performed on the different reviews, which are taken from different social networking sites. The Experiments performed indicate that the RNN based Deep-learning Sentiment Analysis (RDSA) improvises the behavior by increasing the accuracy of the sentiment analysis, which in turn yields better recommendations to the user and thus helps to identify a particular position as per the requirement of the user need.","PeriodicalId":314150,"journal":{"name":"2017 International Conference on Computer, Information and Telecommunication Systems (CITS)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129000186","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: 64