Traffic Prediction in 3G Mobile Networks Based on Multifractal Exploration

Traffic prediction plays an integral role in telecommunication network planning and network optimization. In this paper, we investigate the traffic forecasting for data services in 3G mobile networks. Although the Box-Jenkins model has been proven to be appropriate for voice traffic (since the arrival of calls follows a Poisson distribution), it has been demonstrated that the Internet traffic exhibits statistical self-similarity and has to be modeled using the Fractional AutoRegressive Integrated Moving Average (FARIMA) process. However, a few studies have concluded that the FARIMA process may fail in modeling the Internet traffic. To this end, we conducted experiments on the modeling of benchmark Internet traffic and found that the FARIMA process fails because of the significant multifractal characteristic inherent in the traffic series. Thereafter, we investigate the traffic series of data services in a 3G mobile network from a province in China. Rich multifractal spectra are found in this series. Based on this observation, an integrated method combining the AutoRegressive Moving Average (ARMA) and FARIMA processes is applied. The obtained experimental results verify the effectiveness of the integrated prediction method.     

MobSafe:Cloud Computing Based Forensic Analysis for Massive Mobile Applications Using Data Mining

With the explosive increase in mobile apps, more and more threats migrate from traditional PC client to mobile device. Compared with traditional Win+Intel alliance in PC, Android+ARM alliance dominates in Mobile Internet, the apps replace the PC client software as the major target of malicious usage. In this paper, to improve the security status of current mobile apps, we propose a methodology to evaluate mobile apps based on cloud computing platform and data mining. We also present a prototype system named MobSafe to identify the mobile app’s virulence or benignancy. Compared with traditional method, such as permission pattern based method, MobSafe combines the dynamic and static analysis methods to comprehensively evaluate an Android app. In the implementation, we adopt Android Security Evaluation Framework (ASEF) and Static Android Analysis Framework (SAAF), the two representative dynamic and static analysis methods, to evaluate the Android apps and estimate the total time needed to evaluate all the apps stored in one mobile app market. Based on the real trace from a commercial mobile app market called AppChina, we can collect the statistics of the number of active Android apps, the average number apps installed in one Android device, and the expanding ratio of mobile apps. As mobile app market serves as the main line of defence against mobile malwares, our evaluation results show that it is practical to use cloud computing platform and data mining to verify all stored apps routinely to filter out malware apps from mobile app markets. As the future work, MobSafe can extensively use machine learning to conduct automotive forensic analysis of mobile apps based on the generated multifaceted data in this stage.     

A Survey of Bitmap Index Compression Algorithms for Big Data

With the growing popularity of Internet applications and the widespread use of mobile Internet, Internet traffic has maintained rapid growth over the past two decades. Internet Traffic Archival Systems(ITAS) for packets or flow records have become more and more widely used in network monitoring, network troubleshooting, and user behavior and experience analysis. Among the three key technologies in ITAS, we focus on bitmap index compression algorithm and give a detailed survey in this paper. The current state-of-the-art bitmap index encoding schemes include: BBC, WAH, PLWAH, EWAH, PWAH, CONCISE, COMPAX, VLC, DF-WAH, and VAL-WAH. Based on differences in segmentation, chunking, merge compress, and Near Identical(NI) features, we provide a thorough categorization of the state-of-the-art bitmap index compression algorithms. We also propose some new bitmap index encoding algorithms, such as SECOMPAX, ICX, MASC, and PLWAH+, and present the state diagrams for their encoding algorithms. We then evaluate their CPU and GPU implementations with a real Internet trace from CAIDA. Finally, we summarize and discuss the future direction of bitmap index compression algorithms. Beyond the application in network security and network forensic, bitmap index compression with faster bitwise-logical operations and reduced search space is widely used in analysis in genome data, geographical information system, graph databases, image retrieval, Internet of things, etc. It is expected that bitmap index compression will thrive and be prosperous again in Big Data era since 1980s.     

Scientific big data and Digital Earth

Big data has been a focus of research in sci- ence, technology, economics, and social studies. Many countries have already incorporated big data research into their national strategies. This paper elaborates upon the origin, connotation, and development of big data from both a spatial and temporal perspective. It proposes that scien- tific big data will become a new solution in scientific research as the paradigm changes from being model-driven to data-driven. This paper defines the concept of ＂scientific big data＂ and proposes strategies for solving ＂big data problems＂. Theoretical frameworks and data systems for Digital Earth are discussed with a clear conclusion that scientific big data is a prominent feature of Digital Earth. As an example, spatial cognition of the formation mecha- nism of China＇s Heihe-Tengchong Line--a geo-demo- graphic demarcation line dividing China into two parts--is discussed within the context of big data computation and analysis for Digital Earth.     

Business Strategy and Perceived Benefits of Internet Banking: Their Impact on Banks'''' Strategic Responses to China''''s Entry to WTO

With the entry to WTO and development of IT, banks in China are adjusting their competitive strategies to meet the competition. Internet banking has become a kind of strategic choice to response to the entry to WTO. Based on relevantly selective reviews of literature of strategy theory and research, a model is developed to study banks' strategic response to entry to WTO. According to a survey of 192 sets of questionnaires, this study finds that external pressure, business strategy and perceived benefits of Internet banking would influence banks' perceived increase in Internet banking investment. And banks' perceived increase in Internet banking investment has no difference between big banks and small banks.     

Framework Construction and Application for Global Health Information Platform

In order to understand the global health related information rapidly and timely, a global health information platform based on big data from internet is constructed. In this paper, we introduce the framework and application of the global health information platform. The functions of information platform mainly include two aspects: to analyze and disseminate theoretical and technological progress of the main research fields in global health and to monitor real-time emergencies, epidemic situation and hot topics related to the field of global health. The objective of this research is to establish a Chinese-English bilingual information platform in the global health field. The platform would help academic researchers understand and master global health progress in time; acquire information of global health comprehensively, accurately and dynamically; and eventually help deal with the risk of global diseases, formulate appropriate health policies and actively participate in the international global health affairs.     

An Integrated Incentive Framework for Mobile Crowdsourced Sensing

Currently,mobile devices(e.g.,smartphones)are equipped with multiple wireless interfaces and rich builtin functional sensors that possess powerful computation and communication capabilities,and enable numerous Mobile Crowdsourced Sensing(MCS)applications.Generally,an MCS system is composed of three components:a publisher of sensing tasks,crowd participants who complete the crowdsourced tasks for some kinds of rewards,and the crowdsourcing platform that facilitates the interaction between publishers and crowd participants.Incentives are a fundamental issue in MCS.This paper proposes an integrated incentive framework for MCS,which appropriately utilizes three widely used incentive methods:reverse auction,gamification,and reputation updating.Firstly,a reverse-auction-based two-round participant selection mechanism is proposed to incentivize crowds to actively participate and provide high-quality sensing data.Secondly,in order to avoid untruthful publisher feedback about sensing-data quality,a gamification-based verification mechanism is designed to evaluate the truthfulness of the publisher’s feedback.Finally,the platform updates the reputation of both participants and publishers based on their corresponding behaviors.This integrated incentive mechanism can motivate participants to provide high-quality sensed contents,stimulate publishers to give truthful feedback,and make the platform profitable.     

Value of ecosystem services in China

The function and services are the important components of the life-support system in the planet, as well as the basic elements for sustainable development of environment and society.It is a must to evaluate it for incorporating it with the social-economic system.It is also an important approach to draw the public attention on the environmental and ecosystem conservation.In this study, the ecosystem function and services in China were estimated by employing the classification and economic parameters from Costanza et al.The type and area of terrestrial ecosystems were extracted from Vegetation Map of China (1:4 000 000), and then the distribution map of ecosystem services of China was drawn.According to our calculation, the total value of ecosystem services in China is 77 834.48′108 RMB yuan per annum.The value for terrestrial ecosystem is 56 098.46′108 yuan per annum, and that for marine ecosystem is 21 736.02′108 yuan per annum.The value of ecosystem services in China is 1.73 times bigger than GDP in 1994.The value for forest ecosystem services is 15 433.98′108 yuan per annum, which is 27.51% of the total annual ecosystem services in China.Although wetland is little in area, its ecosystem service value is huge, which is 26 736.9′108 yuan per annum.The value for grassland ecosystem is 8 697.68′108 yuan per annum.Coastal ecosystem service is 12 223.04′108 yuan per annum.Overall, the ecosystem service in China contributes 2.71% to that of our planet.The estimation method employed in this study was a conservative one, and should be improved in the future studies.     

Joint optimization of serving node selection and wireless resources allocation for transactions data in mobile blockchain enhanced Internet of Things

With the increased emphasis on data security in the Internet of Things(IoT), blockchain has received more and more attention.Due to the computing consuming characteristics of blockchain, mobile edge computing(MEC) is integrated into IoT.However, how to efficiently use edge computing resources to process the computing tasks of blockchain from IoT devices has not been fully studied.In this paper, the MEC and blockchain-enhanced IoT is considered.The transactions recording the data or other applica...     

Classification of Tibetan lakes based on variations in seasonal lake water temperature

Widespread lakes on the Tibetan Plateau （TP） are valuable archives for investigating climate and environment changes, which could provide essential information on the mechanisms of past climate changes on the TP and their interaction with the global climate systems. However, there is a lack of in-depth investigation of modern limnological processes in the Tibetan lakes, which hampers the understanding of paleolimnological records and lake ecosystem succession. In this study, we performed continuous temperature monitoring at two lakes, Bangong Co, a freshwater lake in the western TP, and Dagze Co, a brackish lake in the central TP, in order to characterize the patterns of seasonal temperature variability, stratification, and mixing. Temperature data for an entire hydrological year demonstrate that Bangong Co is a dimictic lake and that Dagze Co is a meromictic lake. The higher salinity in the deep water at Dagze Co prevents the lake from overturning completely, and this finding is supported by simulations using a physical limnological model Lake Analyzer. Continuous lake water temperature monitoring provides fundamental data for classifying Tibetan lakes, as well as the hydrological basis for understanding their pa- leolimnological records and ecosystem succession.     

移动通讯产业科技合作模式的国际比较与借鉴——以韩国、日本、香港的合作模式为例

阐述了全球移动运营商与终端厂商合作的三大主流模式,并在此基础上对三种合作模式在形成背景与成因、渠道与品牌策略、对终端厂商的控制力以及各自的优势与劣势等做了对比分析。并对国内移动运营商和终端厂商之间的合作模式提出了建议。     

基于大数据分析的车辆安全检测系统研究

为了检测车辆实时状态和预防交通事故,应采取相应的措施减小交通事故的危害.该文通过物联网与大数据技术,利用Arduino+传感器实现数据整理和采集、MQTT协议+中国移动OneNET云平台消息服务、后端数据处理与感知数据库以及前端实时可视化等技术,对大数据进行数据的清洗及多维度归类,从而达到集预警、报警、分析为一体的服务框架,实现自动预警并发送至用户.     

移动通信CDMA网营销策略研究

从介绍国内电信业的发展过程入手,论述了中国联通移动通信CDMA网营销策略及现状,探讨了中国联通移动通信CDMA网营销对策。     

我国移动通信业价格竞争模型及博弈分析

随着移动通信业务的不断发展和市场规模的不断扩大,中国移动与中国联通之间的价格竞争日趋激烈。本文通过对上市公司数据的整理,运用线性回归的计算方法,构建了双寡头竞争的需求、成本函数,继而对价格竞争进行了博弈分析,并在此基础上对我国移动通信业的发展提出了建议。     

大数据在动漫产业中的应用

作为继云计算、物联网之后IT行业又一颠覆性的技术,大数据已经渗入到社会发展的方方面面.随着“中国动漫数据平台”的成功组建,大数据被应用到动漫产业链的各个环节.大数据在动画电影推荐系统中的应用、整合动漫产业链实现价值最大化,助力动漫产业结构调整、产业融合和转型升级等方面,发挥着重要的技术支撑作用.“大数据+动漫”的融合发展模式,将使动漫产业的未来格局发生根本性变化.     

基于多源大数据的旅游预警系统架构设计

本文在对已有的旅游预警系统及方法综述的基础上,提出基于多源大数据的旅游预警系统架构。构建了多维的预警指标体系,包括区域经济数据、通信及位置数据、互联网搜索数据及社交媒体数据。该框架有望为大数据时代下更加及时和准确的旅游预警提供方法和决策支持。     

移动通信业务代理最优激励问题的研究

移动通信业务市场上的两大巨头:中国移动通信集团公司和中国联合通信有限公司,由于缺少足够的营业网点,都依赖社会代理商为自己发展业务,特别是发展新的客户。因此,如何激励社会代理商发展自己的业务使自己的收益最大化,是两大运营商需要思考的问题。文中应用信息经济学委托 代理理论分析了移动通信业务两类代理最优激励合同的问题:代理放号和区域独家全面代理,得出了帕累托最优解。     

中国联通城域网的建设

在分析中国联通城域网特点及建设的基础上，对联通城域网所承载的移动业务、集团大用户、智能小区等业务需求进行了分析，同时就当前城域网所采用的ATM(Asynchronous Transfer Mode)、千兆以大网、MSTP(Multi Service Ttansport Platform)、DWDM(Dense Wavelength Division Multiplexing)技术进行了论述，提出联通城域网分层（核心层、汇聚层和接入层）结构，并结合联能城域网各层的具体实际情况，提出联通城域网各层应采用的ATM、ASTP等几种技术和几种建设方式的建议，以指导联通公司城域网建设。     

大数据环境下管理科学领域相关问题探讨

近年来,"大数据"作为热门话题,在学术研究领域及日常媒体环境中均受到广泛关注。本文简述了大数据环境下的管理模式在公共管理、工商管理和管理工程这三个方面的体现,并列举了目前我国在电子商务、智慧农业、金融业、环境治理、文化产业、传统医学领域已经有较好发展的大数据应用案例。最后针对大数据环境下的管理创新所面临的问题,提出了一些发展的思路和思考,分析了基于大数据的管理模式创新发展趋势。