Fu, Xiaoming

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[["dc.contributor.author","Pu, Lingjun"],["dc.contributor.author","Chen, Xu"],["dc.contributor.author","Xu, Jingdong"],["dc.contributor.author","Fu, Xiaoming"],["dc.date.accessioned","2017-11-29T15:56:52Z"],["dc.date.available","2017-11-29T15:56:52Z"],["dc.date.issued","2016"],["dc.fs.externid","233140"],["dc.fs.pkfprnr","21263"],["dc.identifier.fs","622909"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/11240"],["dc.language.iso","en"],["dc.notes.intern","FactScience-Import"],["dc.notes.status","final"],["dc.publisher","Institute of Electrical and Electronics Engineers (IEEE)"],["dc.publisher.place","New York, NY"],["dc.relation.conference","IEEE INFOCOM"],["dc.relation.ispartof","IEEE INFOCOM 2016"],["dc.title","Crowdlet: Optimal Worker Recruitment for Self-Organized Mobile Crowdsourcing"],["dc.type","conference_paper"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","unknown"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","1"],["dc.bibliographiccitation.lastpage","9"],["dc.contributor.author","Tao, Narisu"],["dc.contributor.author","Chen, Xu"],["dc.contributor.author","Fu, Xiaoming"],["dc.date.accessioned","2018-04-23T09:17:42Z"],["dc.date.available","2018-04-23T09:17:42Z"],["dc.date.issued","2015"],["dc.description.abstract","AS-level end-to-end paths are of great value for ISPs and a variety of network applications. Although tools like traceroute may reveal AS paths, they require the permission to access source hosts and introduce additional probing traffic, which is not feasible in many applications. In contrast, AS path inference based on BGP control plane data and AS relationship information is a more practical and cost-effective approach. However, this approach suffers from a limited accuracy and high traffic, especially when AS paths are long. In this paper, we bring a new angle to the AS path inference problem by exploiting the metrical tree-likeness or low hyperbolicity of the Internet, part of the complex network properties of the Internet. We show that such property can generate a new constraint that narrows down the searching space of possible AS paths to a much smaller size. Based on this observation, we propose two new AS path inference algorithms, namely HyperPath and Valley-free HyperPath. With intensive evaluations on AS paths from real-world BGP Routing Information Bases, we show that the proposed new algorithms can achieve superior performance, in particular, when AS paths are long paths. We demonstrate that our algorithms can significantly reduce inter-AS traffic for P2P applications with an improved AS path prediction accuracy."],["dc.identifier.doi","10.1109/IFIPNetworking.2015.7145303"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/13262"],["dc.language.iso","en"],["dc.notes.preprint","yes"],["dc.notes.status","final"],["dc.publisher","IEEE"],["dc.relation.eventend","2015-05-22"],["dc.relation.eventlocation","Toulouse, France"],["dc.relation.eventstart","2015-05-20"],["dc.relation.isbn","978-3-9018-8268-5"],["dc.relation.iserratumof","yes"],["dc.title","AS path inference: From complex network perspective"],["dc.type","conference_paper"],["dc.type.internalPublication","unknown"],["dspace.entity.type","Publication"]]

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[["dc.bibliographiccitation.firstpage","76098"],["dc.bibliographiccitation.journal","IEEE Access"],["dc.bibliographiccitation.lastpage","76110"],["dc.bibliographiccitation.volume","6"],["dc.contributor.author","Yang, Song"],["dc.contributor.author","Wieder, Philipp"],["dc.contributor.author","Aziz, Muzzamil"],["dc.contributor.author","Yahyapour, Ramin"],["dc.contributor.author","Fu, Xiaoming"],["dc.contributor.author","Chen, Xu"],["dc.date.accessioned","2021-11-22T14:31:45Z"],["dc.date.available","2021-11-22T14:31:45Z"],["dc.date.issued","2018"],["dc.description.abstract","Customers often suffer from the variability of data access time in (edge) cloud storage service, caused by network congestion, load dynamics, and so on. One ef cient solution to guarantee a reliable latency-sensitive service (e.g., for industrial Internet of Things application) is to issue requests with multiple download/upload sessions which access the required data (replicas) stored in one or more servers, and use the earliest response from those sessions. In order to minimize the total storage costs, how to optimally allocate data in a minimum number of servers without violating latency guarantees remains to be a crucial issue for the cloud provider to deal with. In this paper, we study the latency-sensitive data allocation problem, the latency-sensitive data reallocation problem and the latency-sensitive workload consolidation problem for cloud storage. We model the data access time as a given distribution whose cumulative density function is known, and prove that these three problems are NP-hard. To solve them, we propose an exact integer nonlinear program (INLP) and a Tabu Search-based heuristic. The simulation results reveal that the INLP can always achieve the best performance in terms of lower number of used nodes and higher storage and throughput utilization, but this comes at the expense of much higher running time. The Tabu Searchbased heuristic, on the other hand, can obtain close-to-optimal performance, but in a much lower running time."],["dc.identifier.doi","10.1109/ACCESS.2018.2883674"],["dc.identifier.eissn","2169-3536"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/15891"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/93400"],["dc.language.iso","en"],["dc.notes.intern","Migrated from goescholar"],["dc.notes.status","final"],["dc.relation","info:eu-repo/grantAgreement/EC/FP7/607584/EU//CLEANSKY"],["dc.relation.eissn","2169-3536"],["dc.relation.orgunit","Gesellschaft für wissenschaftliche Datenverarbeitung"],["dc.rights.access","openAccess"],["dc.subject","Data Allocation; Workload Consolidation; Cloud Storage"],["dc.subject.ddc","510"],["dc.title","Latency-Sensitive Data Allocation and Workload Consolidation for Cloud Storage"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.subtype","original_ja"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","1"],["dc.bibliographiccitation.issue","2"],["dc.bibliographiccitation.journal","ACM transactions on internet technology"],["dc.bibliographiccitation.lastpage","20"],["dc.bibliographiccitation.volume","22"],["dc.contributor.author","Yuan, Yali"],["dc.contributor.author","Liang, Chencheng"],["dc.contributor.author","Chen, Xu"],["dc.contributor.author","Baker, Thar"],["dc.contributor.author","Fu, Xiaoming"],["dc.date.accessioned","2022-06-08T07:57:06Z"],["dc.date.available","2022-06-08T07:57:06Z"],["dc.date.issued","2022"],["dc.description.abstract","Numerous applications in 3D underwater sensor networks (UWSNs), such as pollution detection, disaster prevention, animal monitoring, navigation assistance, and submarines tracking, heavily rely on accurate localization techniques. However, due to the limited batteries of sensor nodes and the difficulty for energy harvesting in UWSNs, it is challenging to localize sensor nodes successfully within a short sensor node lifetime in an unspecified underwater environment. Therefore, we propose the Adaptive Energy-Efficient Localization Algorithm (Adaptive EELA) to enable energy-efficient node localization while adapting to the dynamic environment changes. Adaptive EELA takes a fuzzy game-theoretic approach, whereby the Stackelberg game is used to model the interactions among sensor and anchor nodes in UWSNs and employs the adaptive neuro-fuzzy method to set the appropriate utility functions. We prove that a socially optimal Stackelberg–Nash equilibrium is achieved in Adaptive EELA. Through extensive numerical simulations under various environmental scenarios, the evaluation results show that our proposed algorithm accomplishes a significant energy reduction, e.g., 66% lower compared to baselines, while achieving a desired performance level in terms of localization coverage, error, and delay."],["dc.identifier.doi","10.1145/3406533"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/109997"],["dc.language.iso","en"],["dc.notes.intern","DOI-Import GROB-575"],["dc.relation.eissn","1557-6051"],["dc.relation.issn","1533-5399"],["dc.title","Adaptive Fuzzy Game-Based Energy-Efficient Localization in 3D Underwater Sensor Networks"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.subtype","original_ja"],["dspace.entity.type","Publication"]]

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