At present,health care applications,government services,and banking applications use big data with cloud storage to process and implement data.Data mobility in cloud environments uses protection protocols and algorith...At present,health care applications,government services,and banking applications use big data with cloud storage to process and implement data.Data mobility in cloud environments uses protection protocols and algorithms to secure sensitive user data.Sometimes,data may have highly sensitive information,lead-ing users to consider using big data and cloud processing regardless of whether they are secured are not.Threats to sensitive data in cloud systems produce high risks,and existing security methods do not provide enough security to sensitive user data in cloud and big data environments.At present,several security solu-tions support cloud systems.Some of them include Hadoop Distributed File Sys-tem(HDFS)baseline Kerberos security,socket layer-based HDFS security,and hybrid security systems,which have time complexity in providing security inter-actions.Thus,mobile data security algorithms are necessary in cloud environ-ments to avoid time risks in providing security.In our study,we propose a data mobility and security(DMoS)algorithm to provide security of data mobility in cloud environments.By analyzing metadata,data are classified as secured and open data based on their importance.Secured data are sensitive user data,whereas open data are open to the public.On the basis of data classification,secured data are applied to the DMoS algorithm to achieve high security in HDFS.The pro-posed approach is compared with the time complexity of three existing algo-rithms,and results are evaluated.展开更多
Recently,Wireless sensor networks(WSNs)have become very popular research topics which are applied to many applications.They provide pervasive computing services and techniques in various potential applications for the...Recently,Wireless sensor networks(WSNs)have become very popular research topics which are applied to many applications.They provide pervasive computing services and techniques in various potential applications for the Internet of Things(IoT).An Asynchronous Clustering and Mobile Data Gathering based on Timer Mechanism(ACMDGTM)algorithm is proposed which would mitigate the problem of“hot spots”among sensors to enhance the lifetime of networks.The clustering process takes sensors’location and residual energy into consideration to elect suitable cluster heads.Furthermore,one mobile sink node is employed to access cluster heads in accordance with the data overflow time and moving time from cluster heads to itself.Related experimental results display that the presented method can avoid long distance communicate between sensor nodes.Furthermore,this algorithm reduces energy consumption effectively and improves package delivery rate.展开更多
The increasing availability of data in the urban context(e.g.,mobile phone,smart card and social media data)allows us to study urban dynamics at much finer temporal resolutions(e.g.,diurnal urban dynamics).Mobile phon...The increasing availability of data in the urban context(e.g.,mobile phone,smart card and social media data)allows us to study urban dynamics at much finer temporal resolutions(e.g.,diurnal urban dynamics).Mobile phone data,for instance,are found to be a useful data source for extracting diurnal human mobility patterns and for understanding urban dynamics.While previous studies often use call detail record(CDR)data,this study deploys aggregated network-driven mobile phone data that may reveal human mobility patterns more comprehensively and can mitigate some of the privacy concerns raised by mobile phone data usage.We first propose an analytical framework for characterizing and classifying urban areas based on their temporal activity patterns extracted from mobile phone data.Specifically,urban areas’diurnal spatiotemporal signatures of human mobility patterns are obtained through longitudinal mobile phone data.Urban areas are then classified based on the obtained signatures.The classification provides insights into city planning and development.Using the proposed framework,a case study was implemented in the city of Wuhu,China to understand its urban dynamics.The empirical study suggests that human activities in the city of Wuhu are highly concentrated at the Traffic Analysis Zone(TAZ)level.This large portion of local activities suggests that development and planning strategies that are different from those used by metropolitan Chinese cities should be applied in the city of Wuhu.This article concludes with discussions on several common challenges associated with using network-driven mobile phone data,which should be addressed in future studies.展开更多
Identifying an unfamiliar caller's profession is important to protect citizens' personal safety and property. Owing to the limited data protection of various popular online services in some countries, such as ...Identifying an unfamiliar caller's profession is important to protect citizens' personal safety and property. Owing to the limited data protection of various popular online services in some countries, such as taxi hailing and ordering takeouts, many users presently encounter an increasing number of phone calls from strangers. The situation may be aggravated when criminals pretend to be such service delivery staff, threatening the user individuals as well as the society. In addition, numerous people experience excessive digital marketing and fraudulent phone calls because of personal information leakage. However, previous works on malicious call detection only focused on binary classification, which does not work for the identification of multiple professions. We observed that web service requests issued from users' mobile phones might exhibit their application preferences, spatial and temporal patterns, and other profession-related information. This offers researchers and engineers a hint to identify unfamiliar callers. In fact, some previous works already leveraged raw data from mobile phones (which includes sensitive information) for personality studies. However, accessing users' mobile phone raw data may violate the more and more strict private data protection policies and regulations (e.g., General Data Protection Regulation). We observe that appropriate statistical methods can offer an effective means to eliminate private information and preserve personal characteristics, thus enabling the identification of the types of mobile phone callers without privacy concerns. In this paper, we develop CPFinder —- a system that exploits privacy-preserving mobile data to automatically identify callers who are divided into four categories of users: taxi drivers, delivery and takeouts staffs, telemarketers and fraudsters, and normal users (other professions). Our evaluation of an anonymized dataset of 1,282 users over a period of 3 months in Shanghai City shows that the CPFinder can achieve accuracies of more than 75.0% and 92.4% for multiclass and binary classifications, respectively.展开更多
With the advent of digital therapeutics(DTx),the development of software as a medical device(SaMD)for mobile and wearable devices has gained significant attention in recent years.Existing DTx evaluations,such as rando...With the advent of digital therapeutics(DTx),the development of software as a medical device(SaMD)for mobile and wearable devices has gained significant attention in recent years.Existing DTx evaluations,such as randomized clinical trials,mostly focus on verifying the effectiveness of DTx products.To acquire a deeper understanding of DTx engagement and behavioral adherence,beyond efficacy,a large amount of contextual and interaction data from mobile and wearable devices during field deployment would be required for analysis.In this work,the overall flow of the data-driven DTx analytics is reviewed to help researchers and practitioners to explore DTx datasets,to investigate contextual patterns associated with DTx usage,and to establish the(causal)relationship between DTx engagement and behavioral adherence.This review of the key components of datadriven analytics provides novel research directions in the analysis of mobile sensor and interaction datasets,which helps to iteratively improve the receptivity of existing DTx.展开更多
The rapid growth of 3G/4G enabled devices such as smartphones and tablets in large numbers has created increased demand for mobile data services. Wi-Fi offloading helps satisfy the requirements of data-rich applicatio...The rapid growth of 3G/4G enabled devices such as smartphones and tablets in large numbers has created increased demand for mobile data services. Wi-Fi offloading helps satisfy the requirements of data-rich applications and terminals with improved multi- media. Wi-Fi is an essential approach to alleviating mobile data traffic load on a cellular network because it provides extra capacity and improves overall performance. In this paper, we propose an integrated LTE/Wi-Fi architecture with software-defined networking （SDN） abstraction in mobile baekhaul and enhanced components that facilitate the move towards next-generation 5G mo- bile networks. Our proposed architecture enables programmable offloading policies that take into account real-time network conditions as well as the status of devices and applications. This mechanism improves overall network performance by deriving real- time policies and steering traffic between cellular and Wi-Fi networks more efficiently.展开更多
Understanding complex urban systems necessitates untangling the relationships between diverse urban elements such as population,infrastructure,and socioeconomic activities.Scaling laws are basic but effective rules fo...Understanding complex urban systems necessitates untangling the relationships between diverse urban elements such as population,infrastructure,and socioeconomic activities.Scaling laws are basic but effective rules for evaluating a city’s internal growth logic and assessing its efficiency by investigating whether urban indicators scale with population.To date,only limited research has empirically explored the scaling relations between variables of urban mobility in mega-cities at an intra-urban scale of a few meters.Using multiple urban-sensed and human-sensed data,this study proposes a thorough framework for quantifying the scaling laws in a city.To begin,urban mobility networks are built by aggregating population flows using large-scale mobile phone tracking data.To demonstrate the spatiotemporal variability of urban mobility,various network-based mobility measures are proposed.Following that,three different features of urban mobility laws are exposed,explaining spatial agglomeration,spatial hierarchical structures,and the temporal growth process.The scaling correlations between urban indicators pertaining to socioeconomic features and infrastructure and a mobility-population measure are then quantified using multi-sourced urban-sensed data.Applying this framework to the case study of Shenzhen,China revealed(a)spatial travel heterogeneity,hierarchical spatial structures,and mobility growth,and(b)not only a robust sub-linear relationship between infrastructure volume and population,but also a sub-linear relationship for socioeconomic activity.The identified scaling laws,both in terms of mobility measures and urban indicators,provide a multi-faceted portrait of the spatio-temporal variations of urban settings,allowing us to better understand intra-urban developments and,consequently,provide critical policy evaluations and suggestions for improving intra-urban efficiency in the future.展开更多
This paper considers an underwater acoustic sensor network with one mobile surface node to collect data from multiple underwater nodes,where the mobile destination requests retransmission from each underwater node ind...This paper considers an underwater acoustic sensor network with one mobile surface node to collect data from multiple underwater nodes,where the mobile destination requests retransmission from each underwater node individually employing traditional automatic-repeat-request(ARQ) protocol.We propose a practical node cooperation(NC) protocol to enhance the collection efficiency,utilizing the fact that underwater nodes can overhear the transmission of others.To reduce the source level of underwater nodes,the underwater data collection area is divided into several sub-zones,and in each sub-zone,the mobile surface node adopting the NC protocol could switch adaptively between selective relay cooperation(SRC) and dynamic network coded cooperation(DNC) .The difference of SRC and DNC lies in whether or not the selected relay node combines the local data and the data overheard from undecoded node(s) to form network coded packets in the retransmission phase.The NC protocol could also be applied across the sub-zones due to the wiretap property.In addition,we investigate the effects of different mobile collection paths,collection area division and cooperative zone design for energy saving.The numerical results showthat the proposed NC protocol can effectively save energy compared with the traditional ARQ scheme.展开更多
City regions often have great diversity in form and function. To better understand the role of each region, the relations between city regions need to be carefully studied. In this work, the human mobility relations b...City regions often have great diversity in form and function. To better understand the role of each region, the relations between city regions need to be carefully studied. In this work, the human mobility relations between regions of Shanghai based on mobile phone data is explored. By formulating the regions as nodes in a network and the commuting between each pair of regions as link weights, the distribution of nodes degree, and spatial structures of communities in this relation network are studied. Statistics show that regions locate in urban centers and traffic hubs have significantly larger degrees. Moreover, two kinds of spatial structures of communities are found. In most communities, nodes are spatially neighboring. However, in the communities that cover traffic hubs, nodes often locate along corridors.展开更多
This special issue of ZTE Communications focuses on recent advances in mobile data communications for the ICT and telecommunications industries. The ever-increasing amount of mobile data traffic has beenthe subject of...This special issue of ZTE Communications focuses on recent advances in mobile data communications for the ICT and telecommunications industries. The ever-increasing amount of mobile data traffic has beenthe subject of many studies. This research area is widely applicable to contemporary technology and network optimization techniques.展开更多
For China’s telecom industry,2009 is destined to be an extraordinary year due to the approach of long-thirsted-for mobile 3G era,which will have significant impact on current work and lifestyles.2009 will also be a y...For China’s telecom industry,2009 is destined to be an extraordinary year due to the approach of long-thirsted-for mobile 3G era,which will have significant impact on current work and lifestyles.2009 will also be a year full of opportunities and challenges because the coming 3G era will bring limitless business opportunities and impose more challenges on Chinese telecom operators.The reshuffling of Chinese telecom markets has been brought to an end.The new China Unicom,China Mobile and China Telecom all focus their strategies on broadband mobile data services in order to achieve the objective of a smooth transforming from voice services to data services.Technologically,various 3G technologies and their evolutions become great concerns of telecom operators;while in terms of services,the key for 3G systems is their data services.As a result,high speed broadband data services see an era of rapid development.展开更多
In recent years,major cities around the world such as New York in USA,Melbourne in Australia,and Shanghai in China,have planned to boost their nighttime urban vibrancy levels to spur the economy and achieve cultural d...In recent years,major cities around the world such as New York in USA,Melbourne in Australia,and Shanghai in China,have planned to boost their nighttime urban vibrancy levels to spur the economy and achieve cultural diversity.The study of nighttime urban vibrancy from the perspective of spatiotemporal characteristics is increasingly being recognized as part of the essential work in the field of urban planning and geography.This research used mobile phone signaling records to measure urban vibrancy in central Shanghai and revealed its spatiotemporal patterns during nighttime.Specifically,this research explored the changes of urban vibrancy within a day,studied the distribution of urban vibrancy during the nighttime,and visually presented the spatiotemporal changes of nighttime urban vibrancy in central Shanghai.Moreover,on the basis of the behavior pattern of each mobile user,we classified nighttime urban vibrancy into three different types:nighttime working vibrancy,nighttime leisure vibrancy,and nighttime floating vibrancy.We then tried to determine how land use affected nighttime leisure vibrancy.The results showed that urban vibrancy in central Shanghai exhibits a periodic pattern over one-day period.A high-level nighttime urban vibrancy belt is present within central Shanghai.Business offices,hotels,entertainment and recreational districts,wholesale markets,and express services contribute most to the vibrancy at nighttime.In addition,the correlation analysis shows that public and commercial facilities generate high levels of nighttime leisure vibrancy than residential facilities.The mixed land use of public and commercial facilities and residential facilities within 500 m is more critical than the mixed use of a single land lot.The research can be a basis for supporting land use planning and providing evidence for policy-making to improve the level of nighttime urban vibrancy in cities.展开更多
Many existing efforts have taken advantage of large-scale spatial-temporal data to partition cities via constructed human interaction networks.However,few studies focus on communities emerging between adjacent cities ...Many existing efforts have taken advantage of large-scale spatial-temporal data to partition cities via constructed human interaction networks.However,few studies focus on communities emerging between adjacent cities in big urban agglomerations,which we call“cross-city”communities.In this study,we introduce a novel framework to detect cross-city communities in urban agglomerations under different scales leveraging a large number of fine-grained mobile signaling data aiming to break the original administrative boundaries.Taking the Pearl River Delta(PRD)urban agglomeration in China as study area,we investigate the existence of potential communities at three scales,i.e.city-group level,city level and sub-city level.The partition results are expected to benefit transportation planning,urban zoning and administrative boundary re-delineation.The results from our study highlight the necessity of considering cross-city communities and their scale effects when examining urban spatial interactions.展开更多
Nowadays, more and more digitalized spatial data are sold and transmitted on the Internet. Thus, there arises an important issue about copyright protection of the digital data. To solve this problem, this paper has de...Nowadays, more and more digitalized spatial data are sold and transmitted on the Internet. Thus, there arises an important issue about copyright protection of the digital data. To solve this problem, this paper has designed and implemented a spatial data watermarking service (SDWS) system which can provide a secure framework for data transaction and transfer via the Internet and protect the rights of both copyright owners and consumers at the same time.展开更多
Control signaling is mandatory for the operation and management of all types of communication networks,including the Third Generation Partnership Project(3GPP)mobile broadband networks.However,they consume important a...Control signaling is mandatory for the operation and management of all types of communication networks,including the Third Generation Partnership Project(3GPP)mobile broadband networks.However,they consume important and scarce network resources such as bandwidth and processing power.There have been several reports of these control signaling turning into signaling storms halting network operations and causing the respective Telecom companies big financial losses.This paper draws its motivation from such real network disaster incidents attributed to signaling storms.In this paper,we present a thorough survey of the causes,of the signaling storm problems in 3GPP-based mobile broadband networks and discuss in detail their possible solutions and countermeasures.We provide relevant analytical models to help quantify the effect of the potential causes and benefits of their corresponding solutions.Another important contribution of this paper is the comparison of the possible causes and solutions/countermeasures,concerning their effect on several important network aspects such as architecture,additional signaling,fidelity,etc.,in the form of a table.This paper presents an update and an extension of our earlier conference publication.To our knowledge,no similar survey study exists on the subject.展开更多
The diurnal shifts in population distribution increase uncertainty in healthcare demand patterns,posing a substantial challenge to the traditional principles of healthcare facility allocation.This has generated a subs...The diurnal shifts in population distribution increase uncertainty in healthcare demand patterns,posing a substantial challenge to the traditional principles of healthcare facility allocation.This has generated a substantial demand near workplaces.In response,this paper introduces the worktime population.It combines residents and workers with convenient healthcare access near workplaces,offering a comprehensive measure of healthcare demand.Using Beijing as a case,we explore the unique distributions and scales of healthcare demands,considering both residential and worktime populations.Through meticulous analysis,we evaluate healthcare accessibility for these groups and compare their spatiotemporal variations.Our findings highlight significant statistical and spatial disparities in healthcare demand and accessibility between worktime and residential populations.Overall,healthcare demand from worktime populations surpasses that of residential populations,while accessibility is lower for worktime populations.Traditional accessibility metrics often neglect commuter demands,especially in business and technical districts.Incorporating working-hour constraints further diminishes the accessibility advantage of city centers.These insights facilitate more precise,strategic healthcare facility allocation,assisting policymakers and urban planners enhancing equitable access and mitigating spatial inequities.展开更多
Urban eco-environmental management is a key focus in the modernization of national governance systems and governance capacity.Advanced information technology should be used to identify ecological problems in urban are...Urban eco-environmental management is a key focus in the modernization of national governance systems and governance capacity.Advanced information technology should be used to identify ecological problems in urban areas accurately while enhancing the environmental management capacity to promote the sustainable development of cities.This study centers on statistical data from PM_(2.5)air monitoring stations in Shenzhen,China,and supplemental data,such as population distribution data from China Unicom’s mobile phone signaling.Data cleaning and fusion are used to construct a spatial dataset of an eco-environmental problem:PM_(2.5)concentrations.The geostatistical analysis tool ArcGIS is used to identify the most suitable interpolation method for reflecting this eco-environmental problem based on multiple parameter adjustments and repeated testing.A hotspot distribution map of PM_(2.5)concentrations is generated,and correlation analysis is conducted on the population density and distribution patterns in these hotspot areas.This enables the quantitative analysis and exploration of the spatial characteristics and coupling relationships of PM_(2.5)concentrations.The results show a positive correlation between the PM_(2.5)concentration distribution and the points of interest,road network density,number of dead-end roads,and average building height in Shenzhen.No correlation is found between population and building densities and the PM_(2.5)concentration distribution,possibly due to the city’s effective environmental management and pollution control measures.These findings help advance the development of precise,scientific,legally compliant pollution control strategies and decision-making processes.Furthermore,they provide technical support for urban eco-environmental planning,management,and sustainable development.展开更多
In intelligent transportation system(ITS), the interworking of vehicular networks(VN) and cellular networks(CN) is proposed to provide high-data-rate services to vehicles. As the network access quality for CN and VN i...In intelligent transportation system(ITS), the interworking of vehicular networks(VN) and cellular networks(CN) is proposed to provide high-data-rate services to vehicles. As the network access quality for CN and VN is location related, mobile data offloading(MDO), which dynamically selects access networks for vehicles, should be considered with vehicle route planning to further improve the wireless data throughput of individual vehicles and to enhance the performance of the entire ITS. In this paper, we investigate joint MDO and route selection for an individual vehicle in a metropolitan scenario. We aim to improve the throughput of the target vehicle while guaranteeing its transportation efficiency requirements in terms of traveling time and distance. To achieve this objective, we first formulate the joint route and access network selection problem as a semi-Markov decision process(SMDP). Then we propose an optimal algorithm to calculate its optimal policy. To further reduce the computation complexity, we derive a suboptimal algorithm which reduces the action space. Simulation results demonstrate that the proposed optimal algorithm significantly outperforms the existing work in total throughput and the late arrival ratio.Moreover, the heuristic algorithm is able to substantially reduce the computation time with only slight performance degradation.展开更多
Population spatialization is widely used for spatially downscaling census population data to finer-scale.The core idea of modern population spatialization is to establish the association between ancillary data and pop...Population spatialization is widely used for spatially downscaling census population data to finer-scale.The core idea of modern population spatialization is to establish the association between ancillary data and population at the administrative-unit-level(AUlevel)and transfer it to generate the gridded population.However,the statistical characteristic of attributes at the pixel-level differs from that at the AU-level,thus leading to prediction bias via the cross-scale modeling(i.e.scale mismatch problem).In addition,integrating multi-source data simply as covariates may underutilize spatial semantics,and lead to incorrect population disaggregation;while neglecting the spatial autocorrelation of population generates excessively heterogeneous population distribution that contradicts to real-world situation.To address the scale mismatch in downscaling,this paper proposes a Cross-Scale Feature Construction(CSFC)method.More specifically,by grading pixel-level attributes,we construct the feature vector of pixel grade proportions to narrow the scale differences in feature representation between AU-level and pixel-level.Meanwhile,fine-grained building patch and mobile positioning data are utilized to adjust the population weighting layer generated from POI-density-based regression modeling.Spatial filtering is furtherly adopted to model the spatial autocorrelation effect of population and reduce the heterogeneity in population caused by pixel-level attribute discretization.Through the comparison with traditional feature construction method and the ablation experiments,the results demonstrate significant accuracy improvements in population spatialization and verify the effectiveness of weight correction steps.Furthermore,accuracy comparisons with WorldPop and GPW datasets quantitatively illustrate the advantages of the proposed method in fine-scale population spatialization.展开更多
This paper presents a universal platform "uSensing" to support smartphones to communicate with sensor nodes in Wireless Sensor Networks (WSNs).Since phones have different CPU processers and operating systems...This paper presents a universal platform "uSensing" to support smartphones to communicate with sensor nodes in Wireless Sensor Networks (WSNs).Since phones have different CPU processers and operating systems,it is a challenge to merge these heterogeneities and develop such a universal platform.In this paper,we design both hardware and software to support the "universal" feature of uSensing:1) "uSD" card:an IEEE 802.15.4 physical communication card with SD interface;2) "uSinkWare":a WSNs middleware running on smartphones.Integrated with uSD card and uSinkWare,phones become mobile data sinks to access into WSNs and parse messages from sensor nodes.We demonstrate the proposed uSensing platform in a commercial smartphone to connect with our WSNs testbed,and validate that the smartphone has the same WSNs functions as commercial fixed sink.Additionally,we evaluate the performance of uSensing platform through measuring phone's CPU load and power consumption,and analyze the performance of these metrics theoretically.The results suggest that the phone-based mobile sink has enough capability to serve as a mobile sink of WSNs and can work up to twenty hours due to low power consumption.展开更多
文摘At present,health care applications,government services,and banking applications use big data with cloud storage to process and implement data.Data mobility in cloud environments uses protection protocols and algorithms to secure sensitive user data.Sometimes,data may have highly sensitive information,lead-ing users to consider using big data and cloud processing regardless of whether they are secured are not.Threats to sensitive data in cloud systems produce high risks,and existing security methods do not provide enough security to sensitive user data in cloud and big data environments.At present,several security solu-tions support cloud systems.Some of them include Hadoop Distributed File Sys-tem(HDFS)baseline Kerberos security,socket layer-based HDFS security,and hybrid security systems,which have time complexity in providing security inter-actions.Thus,mobile data security algorithms are necessary in cloud environ-ments to avoid time risks in providing security.In our study,we propose a data mobility and security(DMoS)algorithm to provide security of data mobility in cloud environments.By analyzing metadata,data are classified as secured and open data based on their importance.Secured data are sensitive user data,whereas open data are open to the public.On the basis of data classification,secured data are applied to the DMoS algorithm to achieve high security in HDFS.The pro-posed approach is compared with the time complexity of three existing algo-rithms,and results are evaluated.
基金This work is supported by the National Natural Science Foundation of China(61772454,61811530332,61811540410,U1836208).
文摘Recently,Wireless sensor networks(WSNs)have become very popular research topics which are applied to many applications.They provide pervasive computing services and techniques in various potential applications for the Internet of Things(IoT).An Asynchronous Clustering and Mobile Data Gathering based on Timer Mechanism(ACMDGTM)algorithm is proposed which would mitigate the problem of“hot spots”among sensors to enhance the lifetime of networks.The clustering process takes sensors’location and residual energy into consideration to elect suitable cluster heads.Furthermore,one mobile sink node is employed to access cluster heads in accordance with the data overflow time and moving time from cluster heads to itself.Related experimental results display that the presented method can avoid long distance communicate between sensor nodes.Furthermore,this algorithm reduces energy consumption effectively and improves package delivery rate.
基金Under the auspices of the National Natural Science Foundation of China(No.41571146)China Postdoctoral Science Foundation(No.2019M651784)。
文摘The increasing availability of data in the urban context(e.g.,mobile phone,smart card and social media data)allows us to study urban dynamics at much finer temporal resolutions(e.g.,diurnal urban dynamics).Mobile phone data,for instance,are found to be a useful data source for extracting diurnal human mobility patterns and for understanding urban dynamics.While previous studies often use call detail record(CDR)data,this study deploys aggregated network-driven mobile phone data that may reveal human mobility patterns more comprehensively and can mitigate some of the privacy concerns raised by mobile phone data usage.We first propose an analytical framework for characterizing and classifying urban areas based on their temporal activity patterns extracted from mobile phone data.Specifically,urban areas’diurnal spatiotemporal signatures of human mobility patterns are obtained through longitudinal mobile phone data.Urban areas are then classified based on the obtained signatures.The classification provides insights into city planning and development.Using the proposed framework,a case study was implemented in the city of Wuhu,China to understand its urban dynamics.The empirical study suggests that human activities in the city of Wuhu are highly concentrated at the Traffic Analysis Zone(TAZ)level.This large portion of local activities suggests that development and planning strategies that are different from those used by metropolitan Chinese cities should be applied in the city of Wuhu.This article concludes with discussions on several common challenges associated with using network-driven mobile phone data,which should be addressed in future studies.
基金the European Union's Horizon 2020 research and innovation program under the Marie Sklodowska-Curie grant agreement No.824019 and China Scholarship Council(CSC)the Fundamental Research Funds for Central Universities(No.2020JJ014,YY19SSK05).
文摘Identifying an unfamiliar caller's profession is important to protect citizens' personal safety and property. Owing to the limited data protection of various popular online services in some countries, such as taxi hailing and ordering takeouts, many users presently encounter an increasing number of phone calls from strangers. The situation may be aggravated when criminals pretend to be such service delivery staff, threatening the user individuals as well as the society. In addition, numerous people experience excessive digital marketing and fraudulent phone calls because of personal information leakage. However, previous works on malicious call detection only focused on binary classification, which does not work for the identification of multiple professions. We observed that web service requests issued from users' mobile phones might exhibit their application preferences, spatial and temporal patterns, and other profession-related information. This offers researchers and engineers a hint to identify unfamiliar callers. In fact, some previous works already leveraged raw data from mobile phones (which includes sensitive information) for personality studies. However, accessing users' mobile phone raw data may violate the more and more strict private data protection policies and regulations (e.g., General Data Protection Regulation). We observe that appropriate statistical methods can offer an effective means to eliminate private information and preserve personal characteristics, thus enabling the identification of the types of mobile phone callers without privacy concerns. In this paper, we develop CPFinder —- a system that exploits privacy-preserving mobile data to automatically identify callers who are divided into four categories of users: taxi drivers, delivery and takeouts staffs, telemarketers and fraudsters, and normal users (other professions). Our evaluation of an anonymized dataset of 1,282 users over a period of 3 months in Shanghai City shows that the CPFinder can achieve accuracies of more than 75.0% and 92.4% for multiclass and binary classifications, respectively.
基金supported by Basic Science Research Program through the National Research Foundation of Korea(NRF)funded by the Korea government(MSIT)(2020R1A4A1018774)。
文摘With the advent of digital therapeutics(DTx),the development of software as a medical device(SaMD)for mobile and wearable devices has gained significant attention in recent years.Existing DTx evaluations,such as randomized clinical trials,mostly focus on verifying the effectiveness of DTx products.To acquire a deeper understanding of DTx engagement and behavioral adherence,beyond efficacy,a large amount of contextual and interaction data from mobile and wearable devices during field deployment would be required for analysis.In this work,the overall flow of the data-driven DTx analytics is reviewed to help researchers and practitioners to explore DTx datasets,to investigate contextual patterns associated with DTx usage,and to establish the(causal)relationship between DTx engagement and behavioral adherence.This review of the key components of datadriven analytics provides novel research directions in the analysis of mobile sensor and interaction datasets,which helps to iteratively improve the receptivity of existing DTx.
文摘The rapid growth of 3G/4G enabled devices such as smartphones and tablets in large numbers has created increased demand for mobile data services. Wi-Fi offloading helps satisfy the requirements of data-rich applications and terminals with improved multi- media. Wi-Fi is an essential approach to alleviating mobile data traffic load on a cellular network because it provides extra capacity and improves overall performance. In this paper, we propose an integrated LTE/Wi-Fi architecture with software-defined networking （SDN） abstraction in mobile baekhaul and enhanced components that facilitate the move towards next-generation 5G mo- bile networks. Our proposed architecture enables programmable offloading policies that take into account real-time network conditions as well as the status of devices and applications. This mechanism improves overall network performance by deriving real- time policies and steering traffic between cellular and Wi-Fi networks more efficiently.
基金supported by the National Natural Science Foundation of China[grant numbers 42001393,42071360,71961137003 and 42101472]the Basic Research Program of Shenzhen Science and Technology Innovation Committee[grant number JCYJ20220530152817039]+1 种基金the Natural Science Foundation of Guangdong Province[grant number 2019A1515011049]the Key Laboratory of National Geographic Census and Monitoring,MNR[grant number 2020NGCMZD02].
文摘Understanding complex urban systems necessitates untangling the relationships between diverse urban elements such as population,infrastructure,and socioeconomic activities.Scaling laws are basic but effective rules for evaluating a city’s internal growth logic and assessing its efficiency by investigating whether urban indicators scale with population.To date,only limited research has empirically explored the scaling relations between variables of urban mobility in mega-cities at an intra-urban scale of a few meters.Using multiple urban-sensed and human-sensed data,this study proposes a thorough framework for quantifying the scaling laws in a city.To begin,urban mobility networks are built by aggregating population flows using large-scale mobile phone tracking data.To demonstrate the spatiotemporal variability of urban mobility,various network-based mobility measures are proposed.Following that,three different features of urban mobility laws are exposed,explaining spatial agglomeration,spatial hierarchical structures,and the temporal growth process.The scaling correlations between urban indicators pertaining to socioeconomic features and infrastructure and a mobility-population measure are then quantified using multi-sourced urban-sensed data.Applying this framework to the case study of Shenzhen,China revealed(a)spatial travel heterogeneity,hierarchical spatial structures,and mobility growth,and(b)not only a robust sub-linear relationship between infrastructure volume and population,but also a sub-linear relationship for socioeconomic activity.The identified scaling laws,both in terms of mobility measures and urban indicators,provide a multi-faceted portrait of the spatio-temporal variations of urban settings,allowing us to better understand intra-urban developments and,consequently,provide critical policy evaluations and suggestions for improving intra-urban efficiency in the future.
基金supported in part by National Key Research and Development Program of China under Grants No.2016YFC1400200 and 2016YFC1400204National Natural Science Foundation of China under Grants No.41476026,41676024 and 41376040Fundamental Research Funds for the Central Universities of China under Grant No.220720140506
文摘This paper considers an underwater acoustic sensor network with one mobile surface node to collect data from multiple underwater nodes,where the mobile destination requests retransmission from each underwater node individually employing traditional automatic-repeat-request(ARQ) protocol.We propose a practical node cooperation(NC) protocol to enhance the collection efficiency,utilizing the fact that underwater nodes can overhear the transmission of others.To reduce the source level of underwater nodes,the underwater data collection area is divided into several sub-zones,and in each sub-zone,the mobile surface node adopting the NC protocol could switch adaptively between selective relay cooperation(SRC) and dynamic network coded cooperation(DNC) .The difference of SRC and DNC lies in whether or not the selected relay node combines the local data and the data overheard from undecoded node(s) to form network coded packets in the retransmission phase.The NC protocol could also be applied across the sub-zones due to the wiretap property.In addition,we investigate the effects of different mobile collection paths,collection area division and cooperative zone design for energy saving.The numerical results showthat the proposed NC protocol can effectively save energy compared with the traditional ARQ scheme.
基金Project(71303269)supported by the National Natural Science Foundation of ChinaProject(14ZZD006)supported by the Economics Major Research Task of Fostering,China
文摘City regions often have great diversity in form and function. To better understand the role of each region, the relations between city regions need to be carefully studied. In this work, the human mobility relations between regions of Shanghai based on mobile phone data is explored. By formulating the regions as nodes in a network and the commuting between each pair of regions as link weights, the distribution of nodes degree, and spatial structures of communities in this relation network are studied. Statistics show that regions locate in urban centers and traffic hubs have significantly larger degrees. Moreover, two kinds of spatial structures of communities are found. In most communities, nodes are spatially neighboring. However, in the communities that cover traffic hubs, nodes often locate along corridors.
文摘This special issue of ZTE Communications focuses on recent advances in mobile data communications for the ICT and telecommunications industries. The ever-increasing amount of mobile data traffic has beenthe subject of many studies. This research area is widely applicable to contemporary technology and network optimization techniques.
文摘For China’s telecom industry,2009 is destined to be an extraordinary year due to the approach of long-thirsted-for mobile 3G era,which will have significant impact on current work and lifestyles.2009 will also be a year full of opportunities and challenges because the coming 3G era will bring limitless business opportunities and impose more challenges on Chinese telecom operators.The reshuffling of Chinese telecom markets has been brought to an end.The new China Unicom,China Mobile and China Telecom all focus their strategies on broadband mobile data services in order to achieve the objective of a smooth transforming from voice services to data services.Technologically,various 3G technologies and their evolutions become great concerns of telecom operators;while in terms of services,the key for 3G systems is their data services.As a result,high speed broadband data services see an era of rapid development.
基金the National Natural Science Foundation of China(41771170).
文摘In recent years,major cities around the world such as New York in USA,Melbourne in Australia,and Shanghai in China,have planned to boost their nighttime urban vibrancy levels to spur the economy and achieve cultural diversity.The study of nighttime urban vibrancy from the perspective of spatiotemporal characteristics is increasingly being recognized as part of the essential work in the field of urban planning and geography.This research used mobile phone signaling records to measure urban vibrancy in central Shanghai and revealed its spatiotemporal patterns during nighttime.Specifically,this research explored the changes of urban vibrancy within a day,studied the distribution of urban vibrancy during the nighttime,and visually presented the spatiotemporal changes of nighttime urban vibrancy in central Shanghai.Moreover,on the basis of the behavior pattern of each mobile user,we classified nighttime urban vibrancy into three different types:nighttime working vibrancy,nighttime leisure vibrancy,and nighttime floating vibrancy.We then tried to determine how land use affected nighttime leisure vibrancy.The results showed that urban vibrancy in central Shanghai exhibits a periodic pattern over one-day period.A high-level nighttime urban vibrancy belt is present within central Shanghai.Business offices,hotels,entertainment and recreational districts,wholesale markets,and express services contribute most to the vibrancy at nighttime.In addition,the correlation analysis shows that public and commercial facilities generate high levels of nighttime leisure vibrancy than residential facilities.The mixed land use of public and commercial facilities and residential facilities within 500 m is more critical than the mixed use of a single land lot.The research can be a basis for supporting land use planning and providing evidence for policy-making to improve the level of nighttime urban vibrancy in cities.
基金supported in part by the Guangxi science and technology program(GuiKe 2021AB30019)Sichuan Science and Technology Program(2022YFN0031,2023YFN0022,and 2023YFS0381)+2 种基金Hubei key R&D plan(2022BAA048)Zhuhai industry university research cooperation project of China(ZH22017001210098PWC)Shanxi Science and Technology Program(202201150401020).
文摘Many existing efforts have taken advantage of large-scale spatial-temporal data to partition cities via constructed human interaction networks.However,few studies focus on communities emerging between adjacent cities in big urban agglomerations,which we call“cross-city”communities.In this study,we introduce a novel framework to detect cross-city communities in urban agglomerations under different scales leveraging a large number of fine-grained mobile signaling data aiming to break the original administrative boundaries.Taking the Pearl River Delta(PRD)urban agglomeration in China as study area,we investigate the existence of potential communities at three scales,i.e.city-group level,city level and sub-city level.The partition results are expected to benefit transportation planning,urban zoning and administrative boundary re-delineation.The results from our study highlight the necessity of considering cross-city communities and their scale effects when examining urban spatial interactions.
基金Supported by the National High Technology Research and Development Program of China(No.2006AA12Z210)
文摘Nowadays, more and more digitalized spatial data are sold and transmitted on the Internet. Thus, there arises an important issue about copyright protection of the digital data. To solve this problem, this paper has designed and implemented a spatial data watermarking service (SDWS) system which can provide a secure framework for data transaction and transfer via the Internet and protect the rights of both copyright owners and consumers at the same time.
基金the Deanship of Graduate Studies and Scientific Research at Qassim University for financial support(QU-APC-2024-9/1).
文摘Control signaling is mandatory for the operation and management of all types of communication networks,including the Third Generation Partnership Project(3GPP)mobile broadband networks.However,they consume important and scarce network resources such as bandwidth and processing power.There have been several reports of these control signaling turning into signaling storms halting network operations and causing the respective Telecom companies big financial losses.This paper draws its motivation from such real network disaster incidents attributed to signaling storms.In this paper,we present a thorough survey of the causes,of the signaling storm problems in 3GPP-based mobile broadband networks and discuss in detail their possible solutions and countermeasures.We provide relevant analytical models to help quantify the effect of the potential causes and benefits of their corresponding solutions.Another important contribution of this paper is the comparison of the possible causes and solutions/countermeasures,concerning their effect on several important network aspects such as architecture,additional signaling,fidelity,etc.,in the form of a table.This paper presents an update and an extension of our earlier conference publication.To our knowledge,no similar survey study exists on the subject.
基金National Natural Science Foundation of China,No.42301190China Postdoctoral Science Foundation,No.2023M730493。
文摘The diurnal shifts in population distribution increase uncertainty in healthcare demand patterns,posing a substantial challenge to the traditional principles of healthcare facility allocation.This has generated a substantial demand near workplaces.In response,this paper introduces the worktime population.It combines residents and workers with convenient healthcare access near workplaces,offering a comprehensive measure of healthcare demand.Using Beijing as a case,we explore the unique distributions and scales of healthcare demands,considering both residential and worktime populations.Through meticulous analysis,we evaluate healthcare accessibility for these groups and compare their spatiotemporal variations.Our findings highlight significant statistical and spatial disparities in healthcare demand and accessibility between worktime and residential populations.Overall,healthcare demand from worktime populations surpasses that of residential populations,while accessibility is lower for worktime populations.Traditional accessibility metrics often neglect commuter demands,especially in business and technical districts.Incorporating working-hour constraints further diminishes the accessibility advantage of city centers.These insights facilitate more precise,strategic healthcare facility allocation,assisting policymakers and urban planners enhancing equitable access and mitigating spatial inequities.
基金supported by the National Key Research and Development Program of China under the theme“Research on urban sustainable development evaluation data fusion management technology”[Grant No.2022YFC3802903]Open Fund of Key Laboratory of Urban Land Resources Monitoring and Simulation,Ministry of Natural Resources[Grant No.KF-2022-07-013]。
文摘Urban eco-environmental management is a key focus in the modernization of national governance systems and governance capacity.Advanced information technology should be used to identify ecological problems in urban areas accurately while enhancing the environmental management capacity to promote the sustainable development of cities.This study centers on statistical data from PM_(2.5)air monitoring stations in Shenzhen,China,and supplemental data,such as population distribution data from China Unicom’s mobile phone signaling.Data cleaning and fusion are used to construct a spatial dataset of an eco-environmental problem:PM_(2.5)concentrations.The geostatistical analysis tool ArcGIS is used to identify the most suitable interpolation method for reflecting this eco-environmental problem based on multiple parameter adjustments and repeated testing.A hotspot distribution map of PM_(2.5)concentrations is generated,and correlation analysis is conducted on the population density and distribution patterns in these hotspot areas.This enables the quantitative analysis and exploration of the spatial characteristics and coupling relationships of PM_(2.5)concentrations.The results show a positive correlation between the PM_(2.5)concentration distribution and the points of interest,road network density,number of dead-end roads,and average building height in Shenzhen.No correlation is found between population and building densities and the PM_(2.5)concentration distribution,possibly due to the city’s effective environmental management and pollution control measures.These findings help advance the development of precise,scientific,legally compliant pollution control strategies and decision-making processes.Furthermore,they provide technical support for urban eco-environmental planning,management,and sustainable development.
基金the National Natural Science Foundation of China under Grants 61631005 and U1801261the National Key R&D Program of China under Grant 2018YFB1801105+3 种基金the Central Universities under Grant ZYGX2019Z022the Key Areas of Research and Development Program of Guangdong Province, China, under Grant 2018B010114001the 111 Project under Grant B20064the China Postdoctoral Science Foundation under Grant No. 2018M631075
文摘In intelligent transportation system(ITS), the interworking of vehicular networks(VN) and cellular networks(CN) is proposed to provide high-data-rate services to vehicles. As the network access quality for CN and VN is location related, mobile data offloading(MDO), which dynamically selects access networks for vehicles, should be considered with vehicle route planning to further improve the wireless data throughput of individual vehicles and to enhance the performance of the entire ITS. In this paper, we investigate joint MDO and route selection for an individual vehicle in a metropolitan scenario. We aim to improve the throughput of the target vehicle while guaranteeing its transportation efficiency requirements in terms of traveling time and distance. To achieve this objective, we first formulate the joint route and access network selection problem as a semi-Markov decision process(SMDP). Then we propose an optimal algorithm to calculate its optimal policy. To further reduce the computation complexity, we derive a suboptimal algorithm which reduces the action space. Simulation results demonstrate that the proposed optimal algorithm significantly outperforms the existing work in total throughput and the late arrival ratio.Moreover, the heuristic algorithm is able to substantially reduce the computation time with only slight performance degradation.
基金National Natural Science Foundation of China[Grant Nos.42090010,U20A2091,41971349,and 41930107]National Key R&D Program of China[Grant Nos.2018YFC0809800 and 2017YFB0503704].
文摘Population spatialization is widely used for spatially downscaling census population data to finer-scale.The core idea of modern population spatialization is to establish the association between ancillary data and population at the administrative-unit-level(AUlevel)and transfer it to generate the gridded population.However,the statistical characteristic of attributes at the pixel-level differs from that at the AU-level,thus leading to prediction bias via the cross-scale modeling(i.e.scale mismatch problem).In addition,integrating multi-source data simply as covariates may underutilize spatial semantics,and lead to incorrect population disaggregation;while neglecting the spatial autocorrelation of population generates excessively heterogeneous population distribution that contradicts to real-world situation.To address the scale mismatch in downscaling,this paper proposes a Cross-Scale Feature Construction(CSFC)method.More specifically,by grading pixel-level attributes,we construct the feature vector of pixel grade proportions to narrow the scale differences in feature representation between AU-level and pixel-level.Meanwhile,fine-grained building patch and mobile positioning data are utilized to adjust the population weighting layer generated from POI-density-based regression modeling.Spatial filtering is furtherly adopted to model the spatial autocorrelation effect of population and reduce the heterogeneity in population caused by pixel-level attribute discretization.Through the comparison with traditional feature construction method and the ablation experiments,the results demonstrate significant accuracy improvements in population spatialization and verify the effectiveness of weight correction steps.Furthermore,accuracy comparisons with WorldPop and GPW datasets quantitatively illustrate the advantages of the proposed method in fine-scale population spatialization.
基金supported by the National Natural Science Foundation of China under Grant No.60932005China and Europe Government Cooperation Projects of the Ministry of Science and Technology under Grant No.2010DFA11680the Tsinghua Sci-Tech Project under Grant No.2011THZ0
文摘This paper presents a universal platform "uSensing" to support smartphones to communicate with sensor nodes in Wireless Sensor Networks (WSNs).Since phones have different CPU processers and operating systems,it is a challenge to merge these heterogeneities and develop such a universal platform.In this paper,we design both hardware and software to support the "universal" feature of uSensing:1) "uSD" card:an IEEE 802.15.4 physical communication card with SD interface;2) "uSinkWare":a WSNs middleware running on smartphones.Integrated with uSD card and uSinkWare,phones become mobile data sinks to access into WSNs and parse messages from sensor nodes.We demonstrate the proposed uSensing platform in a commercial smartphone to connect with our WSNs testbed,and validate that the smartphone has the same WSNs functions as commercial fixed sink.Additionally,we evaluate the performance of uSensing platform through measuring phone's CPU load and power consumption,and analyze the performance of these metrics theoretically.The results suggest that the phone-based mobile sink has enough capability to serve as a mobile sink of WSNs and can work up to twenty hours due to low power consumption.
