@article{dallacosta2020,

title = {Orchestra: A Customizable Split-Aware NFV Orchestrator for Dynamic Cloud Radio Access Networks},

author = {Ariel Galante Dalla-Costa and Lucas Bondan and Juliano Araujo Wickboldt and Cristiano Bonato Both and Lisandro Zambenedetti Granville},

doi = {10.1109/jsac.2020.2986689},

year  = {2020},

date = {2020-06-01},

urldate = {2020-06-01},

journal = {IEEE Journal on Selected Areas in Communications (JSAC)},

volume = {38},

number = {6},

pages = {1014--1024},

publisher = {Institute of Electrical and Electronics Engineers (IEEE)},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{08613268,

title = {FENDE: Marketplace-Based Distribution, Execution, and Life Cycle Management of VNFs},

author = {Lucas Bondan and Muriel F. Franco and Leonardo Marcuzzo and Giovanni Venancio and Ricardo L. Santos and Ricardo J. Pfitscher and Eder J. Scheid and Burkhard Stiller and Filip De Turck and Elias P. Duarte and Alberto E. Schaeffer-Filho and Carlos R. P. Santos and Lisandro Z. Granville},

doi = {10.1109/mcom.2018.1800507},

year  = {2019},

date = {2019-01-01},

urldate = {2019-01-01},

journal = {IEEE Communications Magazine (COMMAG)},

volume = {57},

number = {1},

pages = {13--19},

publisher = {Institute of Electrical and Electronics Engineers (IEEE)},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{dac_3698,

title = {Integrating dynamic spectrum access and device-to-device via cloud radio access networks and cognitive radio},

author = {Marcelo Antonio Marotta and Leonardo Roveda Faganello and Maicon Kist and Lucas Bondan and Juliano Araujo Wickboldt and Lisandro Zambenedetti Granville and Juergen Rochol and Cristiano Bonato Both},

doi = {10.1002/dac.3698},

year  = {2018},

date = {2018-01-01},

urldate = {2018-01-01},

journal = {International Journal of Communication Systems (IJCS)},

volume = {31},

number = {11},

pages = {1--11},

abstract = {Summary Dynamic Spectrum Access (DSA) can be integrated with Device-to-Device (D2D) communications to enable the exploitation of unused spectrum portions and to address the spectrum scarcity problem. Spectrum management mechanisms integrated into DSA and D2D allow low-power communications between User Equipments without interfering with licensed primary users. However, these mechanisms tend to be energy and processing intensive, being unfeasible to implement in User Equipments with strict battery and processing limitations. On the other hand, Cloud Radio Access Networks already leverage the virtually unlimited computing capacity of clouds for baseband processing functions. Thus, in this article, we propose the Cognitive Radio Device-to-Device (CRD2D) approach aiming to offload spectrum management functionality to the cloud taking advantage of Cloud Radio Access Networks architecture to support the integration of DSA and D2D.},

note = {e3698 dac.3698},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{doi_10_1002_nem_2008,

title = {Booter list generation: The basis for investigating DDoS-for-hire websites},

author = {José Jair Santanna and Joey de Vries and Ricardo O. Schmidt and Daphne Tuncer and Lisandro Zambenedetti Granville and Aiko Pras},

doi = {10.1002/nem.2008},

year  = {2018},

date = {2018-01-01},

urldate = {2018-01-01},

journal = {International Journal of Network Management (IJNM)},

volume = {28},

number = {1},

pages = {1--17},

abstract = {Summary The expansion of Distributed Denial of Service (DDoS)–for-hire websites, known as Booters, has radically modified both the scope and stakes of DDoS attacks. Until recently, however, Booters have only received little attention from the research community. Given their impact, addressing the challenges associated with this phenomenon is crucial. In this paper, we present a rigorous methodology to identify a comprehensive set of existing Booters in the Internet. Before presenting our methodology, we illustrate the benefits of a set of booters on monitoring users from the Dutch NREN, SURFNet, from 2015 to 2017. Our methodology relies on well-defined mechanisms to generate a Booter list, from crawling suspect URLs to characterizing and classifying the collected URLs. The list obtained using the methodology presented in this paper has a classification accuracy of 95.5%, which is 10.5% better compared to previous work.},

note = {e2008 nem.2008},

keywords = {},

pubstate = {published},

tppubtype = {article}

}