@article{df09573890364dc9a4e52a7ab609a138,
title = "Adaptive and aggressive transport protocol to provide QoS in cloud data exchange over Long Fat Networks",
abstract = "This paper analyses the different transport protocols used in transfers over high capacity and high delay networks, commonly known as Long Fat Networks (LFNs). After analysing relevant solutions that provide reliable communications, this article presents the design and performance of the Adaptative and Aggressive Transport Protocol (AATP) for the optimisation of data transfers in a LFN Cloud Content Sharing Use Case. Cloud server farms are geographically separated and there is a need to exchange and replicate large amounts of data. By providing calculations of the status of the network and an estimation of the bandwidth of the link, the performance rate of this protocol is high. Moreover, it also includes an adaptative sending rate in the case of packet loss and, as a result of AATP aggressiveness, only the residual bandwidth is left to other protocol flows. To demonstrate AATP performance, different tests have been carried out over a Network Simulator and a Testbed on Field.",
keywords = "Cloud, Flow control, High-bandwidth delay network, Performance, Quality of service, Transport protocol",
author = "Alan Briones and Adri{\`a} Mallorqu{\'i} and Agust{\'i}n Zaballos and {de Pozuelo}, {Ramon Martin}",
note = "Funding Information: This article in journal has been possible with the support from the “Secretaria d{\textquoteright}Universitats i Recerca del Departament d{\textquoteright}Empresa i Coneixement de la Generalitat de Catalunya”, the European Union (EU) and the European Social Fund (ESF) [ 2020 FI_B 00448 ]. The authors would like to thank “La Salle-URL” (University Ramon Llull) for their encouragement and assistance. Also, part of the work of this article was carried out within the framework of ENVISERA project, funded by Spanish Ministerio de Econom{\'i}a y Competitividad (Plan Estatal de Investigaci{\'o}n Cient{\'i}fica y T{\'e}cnica y de Innovaci{\'o}n 2013–2016, grant reference CTM2015-68902-R ). This work received funding from the “Ag{\`e}ncia de Gesti{\'o} d{\textquoteright}Ajuts Universitaris i de Recerca (AGAUR)” of “ Generalitat de Catalunya ”[http://dx.doi.org/10.13039/501100002809] (grant identification “ 2017 SGR 977 ”). Publisher Copyright: {\textcopyright} 2020 Elsevier B.V.",
year = "2021",
month = feb,
doi = "10.1016/j.future.2020.08.043",
language = "English",
volume = "115",
pages = "34--44",
journal = "Future Generation Computer Systems",
issn = "0167-739X",
publisher = "Elsevier B.V.",
}