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20 January 2018, Volume 34 Issue 1

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Analysis on the status and development of quantum secure communication standardization

Junsen LAI,Bingbing WU,Rui TANG,Wenyu ZHAO,Haiyi ZHANG

2018, 34(1):  1-07.  doi:10.11959/j.issn.1000-0801.2018034

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Quantum secure communication based on quantum key distribution,which can provide theoretically unconditional security,is one of the effective solutions to ensure information security in the future.Recently,the application and industrialization of quantum secure communication in China has developed gradually,the demand for standardization has become increasingly apparent.The worldwide project plan,research status and development trend of quantum secure communication standardization were investigated,the problems and prospects of China’s standardization research were analyzed,and further suggestions to accelerate the standardization development were also proposed.

research and development

Service-oriented security framework for datacenter networks

Teng HU,Guanwen LI,Huachun ZHOU

2018, 34(1):  8-16.  doi:10.11959/j.issn.1000-0801.2018031

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With the large-scale deployment of datacenters in cloud computing,there is an increasing attention to their security issues.However,with the ossify deployment of traditional security devices,it is hard to meet the requirements of dynamical network security situation and copy with new kinds of security threats.Therefore,a service-oriented security framework for datacenter networks was proposed,which was able to compose the virtualized security functions flexibly and update the security policies dynamically based on virtualization technology and software-defined networking.With the implementation of prototype,the feasibility and availability of the proposed security framework was proved,and a solution to promote the flexibility and security of datacenter networks was provided.

Analysis of energy consumption of two kinds of edge caching strategies in heterogeneous networks

Yi SUN,Hong WANG,Rongfang SONG

2018, 34(1):  17-26.  doi:10.11959/j.issn.1000-0801.2018035

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The energy consumption of a two-tier heterogeneous network under two different caching strategies was analyzed.Firstly,the energy consumption of each network components was modelled,and the relationship between the energy consumption of heterogeneous networks and the distribution density of small cell,user load per cell and caching capacity was investigated.The simulation results show that edge caching can effectively reduce the energy consumption of heterogeneous networks and the performance of the two caching strategies are different under different density of small base station and user load.Specifically,the energy consumption of both the network and per user under the two caching strategies are reduced with the increase of the density of small base station and the user load per cell,respectively.Furthermore,the influence of small base station’s caching capacity can not be neglected in total energy consumption.

Transmission characteristics of air-ground channel in aerial communication platform

Xiaobin FU,Baohui ZHENG

2018, 34(1):  27-33.  doi:10.11959/j.issn.1000-0801.2018023

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Satellite communication can solve the problem of global communication,at the same time,it follows the problems of difficult deploy and limited satellite resources.Aerial communication platform is consisted of aircraft with payload communication and not more than 10 km from ground.The platform communicating with ground nodes can solve the weakness of traditional satellite communication.The loss of air-to-ground channel was analyzed to model the air-to-ground wideband channel in Ku and Ka band.The consequence of theory and simulation demonstrates that the fading of the model has serious influence on transmission performance.In low elevation transmission,the value of K-factor is small because of multipath reception.Simulation results show that orthogonal frequency division multiplexing (OFDM) can be a good candidate for wideband communications to transmit payload data from aerial platform to ground station.

High-dimensional outlier detection based on deep belief network and linear one-class SVM

Haoqi LI,Na YING,Chunsheng GUO,Jinhua WANG

2018, 34(1):  34-42.  doi:10.11959/j.issn.1000-0801.2018006

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Aiming at the difficulties in high-dimensional outlier detection at present,an algorithm of high-dimensional outlier detection based on deep belief network and linear one-class SVM was proposed.The algorithm firstly used the deep belief network which had a good performance in the feature extraction to realize the dimensionality reduction of high-dimensional data,and then the outlier detection was achieved based on a one-class SVM with the linear kernel function.High-dimensional data sets in UCI machine learning repository were selected to experiment,result shows that the algorithm has obvious advantages in detection accuracy and computational complexity.Compared with the PCA-SVDD algorithm,the detection accuracy is improved by 4.65%.Compared with the automatic encoder algorithm,its training time and testing time decrease significantly.

A bilevel game matching algorithm in cellular-D2D hybrid scenario

Tian YAO,Hui ZHANG

2018, 34(1):  43-51.  doi:10.11959/j.issn.1000-0801.2018027

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With the rapid development of wireless technologies,wireless access networks enter the 5G system phase.5G environment with various technical scenarios is heterogeneous and dynamic,causing great challenges for wireless resource management.Hence,it is significant to achieve the optimal matching between network resources and user demands.Therefore,wireless resource matching algorithms in 5G environment have become one of the hottest research directions.A bilevel game matching algorithm in cellular-D2D hybrid scenario was proposed:a QoE based matching model considering user fairness was constructed,the bilevel matching game theory was used to solve this optimization problem,and the effectiveness of proposed algorithm was verified through simulations.

A prediction algorithm of telecom customer churn based on Bayesian network parameters learning under incomplete data

Yuxiang ZHAO,Guangyue LU,Hanglong WANG,Siwei LI

2018, 34(1):  52-60.  doi:10.11959/j.issn.1000-0801.2018018

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Aiming at prediction of telecom customer churn,a novel method was proposed to increase the prediction accuracy with the missing data based on the Bayesian network.This method used k-nearest neighbor algorithm to fill the missing data and adds two types of monotonic influence constraints into the process of learning Bayesian network parameter.Simulations and actual data analysis demonstrate that the proposed algorithm obtains higher prediction accuracy of churn customers with the loss of less cost prediction accuracy of loyal customers,outperforms the classic expectation maximization algorithm.

Efficient parallel MAP timing recovery algorithm for TDS-OFDM systems

Yangguang LI,Jianrong BAO,Bin JIANG,Chao LIU

2018, 34(1):  61-71.  doi:10.11959/j.issn.1000-0801.2018013

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According to the problems of the existing timing recovery algorithm with the time-domain orthogonal frequency division multiplexing (TDS-OFDM) modulation in the wireless multimedia transmissions of 5G communications,such as slow processing speed and big theoretical distance,a parallel MAP timing recovery algorithm was proposed.Specifically,the Lagrangian interpolation was used and the amplitude and polarity change of the optimal sampling points were extracted to detect the timing error efficiently.Meanwhile,with the parallel maximum a posteriori (MAP) criterion,the timing error estimate was obtained at high speed.The simulation results show that the accuracy of the proposed algorithm is improved,when comparing with the existing MM algorithm,Gardner algorithm and others.The estimation result is very close to the MAP timing recovery algorithm,the difference is about 2 dB.

Network intrusion detection method based on improved FCM and rule parameter optimization in cloud environment

Chunqin ZANG,Lichun XIE

2018, 34(1):  72-79.  doi:10.11959/j.issn.1000-0801.2018005

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Aiming at the network intrusion detection problem in cloud environment,a method of network intrusion detection based on fuzzy inference was proposed.Firstly,it used the mutual information feature selection to reduce the feature of the sample.Then,the improved fuzzy C-means clustering method was used to cluster the training sample set,and the initial fuzzy rule base was got by the correspondence between each sample feature and cluster.After that,the refine parameter and consequent parameters of each rule were tuned to obtain an exact rule base.Finally,fuzzy inference was carried out on the input connection data based on the rule base,and it was classified to realize intrusion detection.Experimental results on the cloud intrusion detection dataset show that this method can detect the network intrusion accurately,and it is feasible and effective.

Secure outsource computing scheme of modular exponentiation based on single server

Weijie DING

2018, 34(1):  80-86.  doi:10.11959/j.issn.1000-0801.2018001

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At present,in discrete-log based cryptographic protocols,most of the computational models of modular exponentiation are for primes,while less work has been done for composite.What’s more,most schemes are based on two servers,in which it requires at least one server to be honest.However,there may not be a fully trusted cloud server in the actual environment.Then a new secure method for outsourcing exponentiation modular a composite which based on a single server was proposed.The scheme used a new mathematical division method,it could ensure the privacy of the base and exponentiation.Compared with the existing schemes,the checkability of our scheme can be greatly improved.The user can detect the error result with the probability of 119/120.

Summary

A survey of mobile edge computing

Zishu LI,Renchao XIE,Li SUN,Tao HUANG

2018, 34(1):  87-101.  doi:10.11959/j.issn.1000-0801.2018011

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Mobile edge computing (MEC) technology integrates IT service environment and cloud computing technology at the edge of the network,improving the capacities of computing and storage of the edge of network,reducing network operation and service delivery delay and further enhancing the quality of experience (QoE) of users.Thus,MEC has attracted extensive attention and has been added in the 5G standard as a key technology.Firstly,the basic concept,reference architecture and technical advantages of MEC were introduced,and the current research state of MEC were summarized from three perspectives:academia,industry and standard setting.Then,the key enablers,application scenarios and specific deployment methods of MEC were introduced in detail.Finally,the existing problems of MEC,such as mobility,security and billing,as well as privacy protection,were discussed.

Operator big data column

Suggestions for telecom operators’ big data development

Yunyong ZHANG

2018, 34(1):  103-108.  doi:10.11959/j.issn.1000-0801.2018028

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The development of big data at home and abroad was reviewed.On the basis of carefully analyzing the background,advantages and current situation of the development of big data,it was thought that the further development of telecommunication big data was the main component of promoting the national big data strategy project,and suggestions to promote the deepening development of telecom operators’ big data was proposed.

Way for operators to build the telecommunication big data ecology

Mi LIU,Haichuan YANG,Zhenhua LI

2018, 34(1):  109-119.  doi:10.11959/j.issn.1000-0801.2018030

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In the era of rapid development of big data,telecom operator has abundant big data assets and need to unlock the potential of huge data in pipelines through the innovation and development of big data services urgently.The construction of telecom big data ecosystem would help telecom operator solve the problems encountered in the development of big data services effectively and new value growth would be brought out.The target form and construction steps of telecom big data ecosystem were also clarified.

Strategies for enhancing core capability of large-scalely operation for national telecom operators assisted by big data

Jiarui GUO,Jinwu WEI,Yunyong ZHANG

2018, 34(1):  120-125.  doi:10.11959/j.issn.1000-0801.2018045

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The research has been executed through the history of big data belonging to the international telecom operators.A splendid summary of the practical experience was indicated in four aspects,including the organization of operation,the application of operation,the platform layout and data integration.The concepts will promote national network carriers in scaling up the core operation capability,as well as the development of the future industrialization of internet by applying specifically beneficial strategies and advices.

Prospect of big data stimulating business model innovation of telecom operator

Junlin WANG,Baowang WANG,Fei ZHAO,Chunyu MA,Shaofu TAN

2018, 34(1):  126-134.  doi:10.11959/j.issn.1000-0801.2018032

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Combined with big data research and practice of telecommunication industry,eight business operation areas in which big data can create values were illustrated.Through explaining the definition and characteristics of big data which stimulates business model innovation,the concept of intelligence operations center was illuminated,and the significance,commercial design and supporting elements were introduced.At the same time,the relationship between intelligence operations center and other business platforms was explained.Finally the development opportunities and evolution strategies of intelligence operations center at AI era was introduced.

Construction and application of Anhui Unicom enterprise big data platform

Tao WU,Tao LIU,Bin WANG

2018, 34(1):  135-147.  doi:10.11959/j.issn.1000-0801.2018036

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The challenges and opportunities faced by Anhui Unicom of big data construction,and the experience of Anhui Unicom rapidly constructing B+O convergent smart operation platform which realized multi-dimensional and multi-level fusion management of cross-domain platform were summarized.In addition,the customer off-grid prediction was also deeply studied by Anhui Unicom.Achieving the off-grid prediction model through the big data platform which made the precision ratio get 90% and the recall ration get 9%.On the other hand,the big data platform has been popularized to other departments by integrated applications,such as,user awareness enhancement etc.Internal operation efficiency was improved and NOC (network operations center) was transformed to SOC (service operations center).

Applications of a big data platform based on PaaS

Haiyong XU,Yan HUANG

2018, 34(1):  148-157.  doi:10.11959/j.issn.1000-0801.2018043

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As a platform of data storage,processing,and service,big data platform needs to support internal and external various big data applications.A solution applied PaaS technology to the big data platform was proposed.Details of the key technical solutions such as the architecture of PaaS cloud computing platform,hierarchical scheduling scheme,multi-tenant management and global scheduling of Hadoop tasks were described.It was proved that the platform could remarkably improve big data application development efficiency and help application deployment fast.In the meantime,good elastic scaling capability can effectively improve big data application system resource utilization.

Construction and practice of big data fundamental ability for telecom operators

Jinsong TANG,Yun CAI,Xiaoliang WANG,Yiping FU,Xiaowei TANG,Yonggang CHEN,Ting ZHANG

2018, 34(1):  158-165.  doi:10.11959/j.issn.1000-0801.2018037

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Take Zhejiang Mobile as an example,the big data capability was demonstrated from three aspects:platform,data and technology.Combined with the enterprise practice and exploration,industry cases were shared in terms of credit score and site selection.

Application and research of marketing using automatic similar users extension technology in telecom industry

Xu ZHANG,Yang LIU,Lei HU,Xiaodong ZHAO,Haibin ZHANG

2018, 34(1):  166-173.  doi:10.11959/j.issn.1000-0801.2018029

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With the explosive development of data service,TSP(telecommunication service provider) has taken advantages of owing massive user data.It is a necessity for TSP to develop value added business using big data techniques which explores the data value.The traditional way of marketing utilizes rules or supervised classification method meets the challenge of low success rate and long data acquisition period.Therefore,a new service named Lookalike was proposed.The service supports precision marketing by integrating matric learning and deep learning efficiently based on telecom operators’ data characteristics.The Lookalike service decreases the artificial participation and enhances the efficiency and success rate of marketing activity.The enhancement of TTM (time to market) has been improved in many real programs and the success rate of marketing has increased absolutely.

Personalized recommendation helps carrier’s digital marketing

Chunyu MA,Junlin WANG,Baowang WANG,Bohua GAN

2018, 34(1):  174-180.  doi:10.11959/j.issn.1000-0801.2018033

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The challenge and demands of telecom operator’ digital marketing were briefly analyzed,the advantages of internet thought were also drawled and then the personalized recommendations were proposed to help telecom operator’s digital marketing,and the history of carrier’s personalized recommendation was introduced.Then the principle and implementation process of telecom operator’s personalized recommendation which bases on carrier merchandise,user behavior data and the computing ability of big data platform was described.Finally,the implementation scenario of personalized recommendation in telecom operator digital content business was described,and the value and future of personalized recommendation have prospected.