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Modeling and Analysis of Mobile Data...

Wang, Jie.

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Modeling and Analysis of Mobile Data Dynamics in Heterogeneous Wireless Networks.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Modeling and Analysis of Mobile Data Dynamics in Heterogeneous Wireless Networks./
作者:	Wang, Jie.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2019,
面頁冊數:	179 p.
附註:	Source: Dissertations Abstracts International, Volume: 81-10, Section: B.
Contained By:	Dissertations Abstracts International81-10B.
標題:	Computer engineering. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=27732075
ISBN:	9781392490389

Modeling and Analysis of Mobile Data Dynamics in Heterogeneous Wireless Networks.
Wang, Jie.

Modeling and Analysis of Mobile Data Dynamics in Heterogeneous Wireless Networks. - Ann Arbor : ProQuest Dissertations & Theses, 2019 - 179 p.

Source: Dissertations Abstracts International, Volume: 81-10, Section: B.

Thesis (Ph.D.)--North Carolina State University, 2019.

This item must not be sold to any third party vendors.

Owing to advances in wireless communication, networking and data analysis technologies,the generation, dissemination andacquisition of data are more frequent and accessible thanever. Consequently, data services, whichmove data from its generator(s) to its consumer(s)through individual connections, arequickly migrating to the edge of networks. Such wirelesssystems are composed of numerous devicesthat are different in many aspects, e.g., communicationtechnology, mobility pattern, and so on.Despite the benefits they brings, such as reducingservice latency, emerging data servicesat the edge create new challenges to the network: heterogeneityof individuals adds to the complexity ofsystem design, management, and performanceevaluation, while proliferating enddevices impose an ever-increasing demand on resources, thatare already scarce at the edge. Toexploit the full potential of data services, it is essential tounderstand the cause, governing rules,and impact of data's mobility in such heterogeneouswireless networks, for the benefit ofdata owners, service providers, and network operators.Therefore, this dissertation isdedicated to study mobile data dynamics, that is, dynamicprocesses of mobile data. Specifially,we identify three dynamic processes, of information,coverage, and spectrum, as the cause,manifestation, and impact of mobile data, respectively.Then we examine these dynamics processand the governing rule of data movements, through amodeling and analysis approach to answerthe following questions: when data move and stop,where data are, how data move, and whatimpact mobile data induce on network resources.In particular, we rst study conflictinginformation propagation with a novel Susceptible-Infectious-Cured (SIC) model to answerthe when question. Our results reveal the impact ofnetwork topology on the lifetime of theundesired information, which provides bounds, scalinglaws, and guidelines for practicalinformation control measures. For the where question, wequantify the whereabouts of data, thatis, data coverage, with a data-strength metric, and findthe change of data coverage dependsheavily on user mobility, based on which we establisha framework to predict data coverage,and achieve over 80% accuracy in tests with real-worldtraces. Then, we consider disseminationprocesses of multiple data blocks in the emerging DSA-enabledfog paradigm, to answer the how and whatquestions. We propose a gravity model todescribe how data move in an offloadingprocess, based on which we find that, the amount ofstorage and communication resourceneeded for data offloading scales linearly with the networksize. Particularly for the spectrumresource, a scarce resource in wireless networks, we studyspectrum activity surveillance (SAS) toobserve the impact of mobile data, and propose multimonitordeployment strategies with guaranteedperformances for both the dedicated and crowdsourceSAS scenarios. The work in thisdissertation advances our understanding on mobile data,and provides design guidelines for dataservices in heterogeneous wireless networks.

ISBN: 9781392490389Subjects--Topical Terms:

621879
Computer engineering.
Subjects--Index Terms:

Mobile data dynamics

Modeling and Analysis of Mobile Data Dynamics in Heterogeneous Wireless Networks.
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520 $a Owing to advances in wireless communication, networking and data analysis technologies,the generation, dissemination andacquisition of data are more frequent and accessible thanever. Consequently, data services, whichmove data from its generator(s) to its consumer(s)through individual connections, arequickly migrating to the edge of networks. Such wirelesssystems are composed of numerous devicesthat are different in many aspects, e.g., communicationtechnology, mobility pattern, and so on.Despite the benefits they brings, such as reducingservice latency, emerging data servicesat the edge create new challenges to the network: heterogeneityof individuals adds to the complexity ofsystem design, management, and performanceevaluation, while proliferating enddevices impose an ever-increasing demand on resources, thatare already scarce at the edge. Toexploit the full potential of data services, it is essential tounderstand the cause, governing rules,and impact of data's mobility in such heterogeneouswireless networks, for the benefit ofdata owners, service providers, and network operators.Therefore, this dissertation isdedicated to study mobile data dynamics, that is, dynamicprocesses of mobile data. Specifially,we identify three dynamic processes, of information,coverage, and spectrum, as the cause,manifestation, and impact of mobile data, respectively.Then we examine these dynamics processand the governing rule of data movements, through amodeling and analysis approach to answerthe following questions: when data move and stop,where data are, how data move, and whatimpact mobile data induce on network resources.In particular, we rst study conflictinginformation propagation with a novel Susceptible-Infectious-Cured (SIC) model to answerthe when question. Our results reveal the impact ofnetwork topology on the lifetime of theundesired information, which provides bounds, scalinglaws, and guidelines for practicalinformation control measures. For the where question, wequantify the whereabouts of data, thatis, data coverage, with a data-strength metric, and findthe change of data coverage dependsheavily on user mobility, based on which we establisha framework to predict data coverage,and achieve over 80% accuracy in tests with real-worldtraces. Then, we consider disseminationprocesses of multiple data blocks in the emerging DSA-enabledfog paradigm, to answer the how and whatquestions. We propose a gravity model todescribe how data move in an offloadingprocess, based on which we find that, the amount ofstorage and communication resourceneeded for data offloading scales linearly with the networksize. Particularly for the spectrumresource, a scarce resource in wireless networks, we studyspectrum activity surveillance (SAS) toobserve the impact of mobile data, and propose multimonitordeployment strategies with guaranteedperformances for both the dedicated and crowdsourceSAS scenarios. The work in thisdissertation advances our understanding on mobile data,and provides design guidelines for dataservices in heterogeneous wireless networks.
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