Zhu, Konglin

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[["dc.contributor.author","Zhu, Konglin"],["dc.contributor.author","Fu, Xiaoming"],["dc.contributor.author","Li, Wenzhong"],["dc.contributor.author","Lu, Sanglu"],["dc.contributor.author","Nagler, Jan"],["dc.contributor.editor","Fu, Xiaoming"],["dc.contributor.editor","Luo, Jar-Der"],["dc.contributor.editor","Boos, Margarete"],["dc.date.accessioned","2017-09-07T11:50:48Z"],["dc.date.available","2017-09-07T11:50:48Z"],["dc.date.issued","2017"],["dc.identifier.doi","10.1371/journal.pone.0100023"],["dc.identifier.gro","3147824"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/10488"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/5150"],["dc.language.iso","en"],["dc.notes.intern","Merged from goescholar"],["dc.notes.status","final"],["dc.notes.submitter","chake"],["dc.publisher","Taylor & Francis Group"],["dc.publisher.place","Boca Raton"],["dc.relation.isbn","1-4987-3664-5"],["dc.relation.ispartof","Social Network Analysis: Interdisciplinary Approaches and Case"],["dc.rights","CC BY 4.0"],["dc.rights.uri","https://creativecommons.org/licenses/by/4.0"],["dc.title","How Do Online Social Networks Grow?"],["dc.type","book_chapter"],["dc.type.internalPublication","unknown"],["dc.type.peerReviewed","no"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","183"],["dc.bibliographiccitation.journal","Computer Networks"],["dc.bibliographiccitation.lastpage","198"],["dc.bibliographiccitation.volume","93"],["dc.contributor.author","Zhu, Konglin"],["dc.contributor.author","Li, Wenzhong"],["dc.contributor.author","Fu, Xiaoming"],["dc.contributor.author","Zhang, Lin"],["dc.date.accessioned","2017-09-07T11:44:54Z"],["dc.date.available","2017-09-07T11:44:54Z"],["dc.date.issued","2015"],["dc.identifier.doi","10.1016/j.comnet.2015.10.018"],["dc.identifier.gro","3149006"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/5647"],["dc.notes.intern","Fu Crossref Import"],["dc.notes.status","final"],["dc.notes.submitter","chake"],["dc.publisher","Elsevier BV"],["dc.relation.issn","1389-1286"],["dc.title","Data routing strategies in opportunistic mobile social networks: Taxonomy and open challenges"],["dc.type","journal_article"],["dc.type.internalPublication","unknown"],["dc.type.peerReviewed","no"],["dspace.entity.type","Publication"]]

[["dc.contributor.author","Zhu, Konglin"],["dc.contributor.author","Li, Wenzhong"],["dc.contributor.author","Fu, Xiaoming"],["dc.date.accessioned","2018-05-02T11:40:54Z"],["dc.date.available","2018-05-02T11:40:54Z"],["dc.date.issued","2012"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/13814"],["dc.language.iso","en"],["dc.notes.status","final"],["dc.publisher","PdN"],["dc.relation.eventend","2012-05"],["dc.relation.eventlocation","Frankfurt am Main, Germany"],["dc.relation.eventstart","2012-05"],["dc.title","Exploring Regional and Global Population Growth in Online Social Networks"],["dc.type","conference_abstract"],["dc.type.internalPublication","unknown"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","307"],["dc.bibliographiccitation.lastpage","342"],["dc.contributor.author","Li, Wenzhong"],["dc.contributor.author","Lu, Sanglu"],["dc.contributor.author","Zhu, Konglin"],["dc.contributor.author","Chen, Xiao"],["dc.contributor.author","Nagler, Jan"],["dc.contributor.author","Fu, Xiaoming"],["dc.contributor.editor","Fu, Xiaoming"],["dc.contributor.editor","Luo, Jar-Der"],["dc.contributor.editor","Boos, Margarete"],["dc.date.accessioned","2017-09-07T11:44:50Z"],["dc.date.available","2017-09-07T11:44:50Z"],["dc.date.issued","2017"],["dc.identifier.doi","10.1201/9781315369594-14"],["dc.identifier.gro","3148990"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/5629"],["dc.language.iso","en"],["dc.notes.intern","Fu Crossref Import"],["dc.notes.status","final"],["dc.notes.submitter","chake"],["dc.publisher","CRC Press"],["dc.publisher.place","Boca Raton/London/New York"],["dc.relation.eisbn","978-1-4987-3668-8"],["dc.relation.isbn","978-1-4987-3664-0"],["dc.relation.ispartof","Social Network Analysis"],["dc.title","Information Dissemination in Social-Featured Opportunistic Networks"],["dc.type","book_chapter"],["dc.type.internalPublication","unknown"],["dc.type.peerReviewed","no"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","3423"],["dc.bibliographiccitation.issue","7"],["dc.bibliographiccitation.journal","IEEE Transactions on Vehicular Technology"],["dc.bibliographiccitation.lastpage","3434"],["dc.bibliographiccitation.volume","63"],["dc.contributor.author","Zhu, Konglin"],["dc.contributor.author","Li, Wenzhong"],["dc.contributor.author","Fu, Xiaoming"],["dc.date.accessioned","2017-09-07T11:44:57Z"],["dc.date.available","2017-09-07T11:44:57Z"],["dc.date.issued","2014"],["dc.identifier.doi","10.1109/tvt.2014.2298494"],["dc.identifier.gro","3149028"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/5671"],["dc.notes.intern","Fu Crossref Import"],["dc.notes.status","final"],["dc.notes.submitter","chake"],["dc.publisher","Institute of Electrical and Electronics Engineers (IEEE)"],["dc.relation.eissn","1939-9359"],["dc.relation.issn","0018-9545"],["dc.title","SMART: A Social- and Mobile-Aware Routing Strategy for Disruption-Tolerant Networks"],["dc.type","journal_article"],["dc.type.internalPublication","unknown"],["dc.type.peerReviewed","no"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.issue","6"],["dc.bibliographiccitation.journal","Journal of High Energy Physics"],["dc.bibliographiccitation.volume","2020"],["dc.contributor.author","Choi, Soo-Min"],["dc.contributor.author","Kim, Jinsu"],["dc.contributor.author","Lee, Hyun Min"],["dc.contributor.author","Zhu, Bin"],["dc.date.accessioned","2021-04-14T08:26:15Z"],["dc.date.available","2021-04-14T08:26:15Z"],["dc.date.issued","2020"],["dc.identifier.doi","10.1007/JHEP06(2020)135"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/81879"],["dc.language.iso","en"],["dc.notes.intern","DOI Import GROB-399"],["dc.relation.eissn","1029-8479"],["dc.title","Connecting between inflation and dark matter in models with gauged Z3 symmetry"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.artnumber","14"],["dc.bibliographiccitation.issue","1"],["dc.bibliographiccitation.journal","Complex Adaptive Systems Modeling"],["dc.bibliographiccitation.volume","1"],["dc.contributor.author","Zhu, Konglin"],["dc.contributor.author","Li, Wenzhong"],["dc.contributor.author","Fu, Xiaoming"],["dc.date.accessioned","2017-09-07T11:44:55Z"],["dc.date.available","2017-09-07T11:44:55Z"],["dc.date.issued","2013"],["dc.description.abstract","Purpose Online social networks (OSNs) are now among the most popular applications on the web offering platforms for people to interact, communicate and collaborate with others. The rapid development of OSNs provides opportunities for people’s daily communication, but also brings problems such as burst network traffic and overload of servers. Studying the population growth pattern in online social networks helps service providers to understand the people communication manners in OSNs and facilitate the management of network resources. In this paper, we propose a population growth model for OSNs based on the study of population distribution and growth in spatiotemporal scale-space. Methods We investigate the population growth in three data sets which are randomly sampled from the popular OSN web sites including Renren, Twitter and Gowalla. We find out that the number of population follows the power-law distribution over different geographic locations, and the population growth of a location fits a power function of time. An aggregated population growth model is conducted by integrating the population growth over geographic locations and time. Results We use the data sets to validate our population growth model. Extensive experiments also show that the proposed model fits the population growth of Facebook and Sina Weibo well. As an application, we use the model to predict the monthly population in three data sets. By comparing the predicted population with ground-truth values, the results show that our model can achieve a prediction accuracy between 86.14% and 99.89%. Conclusions With our proposed population growth model, people can estimate the population size of an online social network in a certain time period and it can also be used for population prediction for a future time."],["dc.description.sponsorship","Open-Access-Publikationsfonds 2013"],["dc.identifier.doi","10.1186/2194-3206-1-14"],["dc.identifier.gro","3149016"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/10428"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/5658"],["dc.language.iso","en"],["dc.notes.intern","Fu Crossref Import"],["dc.notes.intern","Merged from goescholar"],["dc.notes.status","final"],["dc.notes.submitter","chake"],["dc.relation.issn","2194-3206"],["dc.rights","Goescholar"],["dc.rights.uri","https://goescholar.uni-goettingen.de/licenses"],["dc.title","Modeling population growth in online social networks"],["dc.type","journal_article"],["dc.type.internalPublication","unknown"],["dc.type.peerReviewed","no"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","24"],["dc.bibliographiccitation.journal","Computer Communications"],["dc.bibliographiccitation.lastpage","37"],["dc.bibliographiccitation.volume","42"],["dc.contributor.author","Zhu, Konglin"],["dc.contributor.author","Li, Wenzhong"],["dc.contributor.author","Fu, Xiaoming"],["dc.date.accessioned","2017-09-07T11:44:57Z"],["dc.date.available","2017-09-07T11:44:57Z"],["dc.date.issued","2014"],["dc.identifier.doi","10.1016/j.comcom.2014.01.008"],["dc.identifier.gro","3149023"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/5666"],["dc.notes.intern","Fu Crossref Import"],["dc.notes.status","final"],["dc.notes.submitter","chake"],["dc.publisher","Elsevier BV"],["dc.relation.issn","0140-3664"],["dc.title","Rethinking routing information in mobile social networks: Location-based or social-based?"],["dc.type","journal_article"],["dc.type.internalPublication","unknown"],["dc.type.peerReviewed","no"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","3234"],["dc.bibliographiccitation.lastpage","3239"],["dc.contributor.author","Zhu, Konglin"],["dc.contributor.author","Li, Wenzhong"],["dc.contributor.author","Fu, Xiaoming"],["dc.contributor.author","Zhang, Lin"],["dc.date.accessioned","2018-04-23T09:08:11Z"],["dc.date.available","2018-04-23T09:08:11Z"],["dc.date.issued","2015"],["dc.description.abstract","Opportunistic Mobile Social Networks (MSNs) as a kind of social network in which nodes are opportunistically connected. Many data routing strategies have been proposed for opportunistic MSNs. Most of them apply a utility for relay selection that a node with a higher utility value is selected as relay. However, such utility-based routing strategies run into dead end problem in which the data is stuck into a node with local maximal utility value. In this paper, we propose a virtual routing method named VIRO, which exerts conformal mapping to convert the local topology of dead end into a virtual geometric map to guarantee data dissemination to the next relay. We first convert the utility into geometric planner, and then conduct the discrete Ricci Flow bypass the gap between the dead end and next relay. Extensive experiment results suggest VIRO can reduce the ratio of dead end effectively so that the data delivery ratio is enhanced up to 42% by increasing only a slight amount of delay and cost."],["dc.identifier.doi","10.1109/ICC.2015.7248822"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/13260"],["dc.language.iso","en"],["dc.notes.preprint","yes"],["dc.notes.status","final"],["dc.publisher","IEEE"],["dc.relation.conference","IEEE International Conference on Communications"],["dc.relation.eventend","2015-06-12"],["dc.relation.eventlocation","London, UK"],["dc.relation.eventstart","2015-06-08"],["dc.relation.isbn","978-1-4673-6432-4"],["dc.relation.iserratumof","yes"],["dc.title","VIRO: A virtual routing method for eliminating dead end in Opportunistic Mobile Social Network"],["dc.type","conference_paper"],["dc.type.internalPublication","unknown"],["dspace.entity.type","Publication"]]