Full Text:
<1918>
Summary: 
<1479>
CLC number: TP393
On-line Access: 2019-10-08
Received: 2018-07-23
Revision Accepted: 2018-12-14
Crosschecked: 2019-08-15
Cited: 0
Clicked: 5201
Future Internet: trends and challenges
| ||||||||||||||
Jiao Zhang, Tao Huang, Shuo Wang, Yun-jie Liu. Future Internet: trends and challenges[J]. Frontiers of Information Technology & Electronic Engineering, 2019, 20(9): 1185-1194.
@article{title="Future Internet: trends and challenges",
author="Jiao Zhang, Tao Huang, Shuo Wang, Yun-jie Liu",
journal="Frontiers of Information Technology & Electronic Engineering",
volume="20",
number="9",
pages="1185-1194",
year="2019",
publisher="Zhejiang University Press & Springer",
doi="10.1631/FITEE.1800445"
}
%0 Journal Article
%T Future Internet: trends and challenges
%A Jiao Zhang
%A Tao Huang
%A Shuo Wang
%A Yun-jie Liu
%J Frontiers of Information Technology & Electronic Engineering
%V 20
%N 9
%P 1185-1194
%@ 2095-9184
%D 2019
%I Zhejiang University Press & Springer
%DOI 10.1631/FITEE.1800445
TY - JOUR
T1 - Future Internet: trends and challenges
A1 - Jiao Zhang
A1 - Tao Huang
A1 - Shuo Wang
A1 - Yun-jie Liu
J0 - Frontiers of Information Technology & Electronic Engineering
VL - 20
IS - 9
SP - 1185
EP - 1194
%@ 2095-9184
Y1 - 2019
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/FITEE.1800445
Abstract: Traditional networks face many challenges due to the diversity of applications, such as cloud computing, Internet of Things, and the industrial Internet. future Internet needs to address these challenges to improve network scalability, security, mobility, and quality of service. In this work, we survey the recently proposed architectures and the emerging technologies that meet these new demands. Some cases for these architectures and technologies are also presented. We propose an integrated framework called the service customized network which combines the strength of current architectures, and discuss some of the open challenges and opportunities for future Internet. We hope that this work can help readers quickly understand the problems and challenges in the current research and serves as a guide and motivation for future network research.
[1]Akyildiz IF, Nie S, Lin SC, et al., 2016. 5G roadmap: 10 key enabling technologies. Comput Netw, 106:17-48.
[2]Bannour F, Souihi S, Mellouk A, 2018. Distributed SDN control: survey, taxonomy, and challenges. IEEE Commun Surv Tut, 20(1):333-354.
[3]Bosshart P, Daly D, Gibb G, et al., 2014. P4: programming protocol-independent packet processors. ACM SIGCOMM Comput Commun Rev, 44(3):87-95.
[4]Chinchali S, Hu P, Chu TS, et al., 2018. Cellular network traffic scheduling with deep reinforcement learning. Pros 32nd AAAI Conf on Artificial Intelligence, p.766-774.
[5]Chowdhury M, Zaharia M, Ma J, et al., 2011. Managing data transfers in computer clusters with orchestra. Proc ACM SIGCOMM, p.98-109.
[6]Fisher D, 2014. A look behind the future Internet architectures efforts. ACM SIGCOMM Comput Commun Rev, 44(3):45-49.
[7]Jacobson V, Smetters DK, Thornton JD, et al., 2009. Networking named content. Proc 5th Int Conf on Emerging Networking Experiments and Technologies, p.1-12.
[8]Jain S, Kumar A, Mandal S, et al., 2013. B4: experience with a globally-deployed software defined WAN. Proc ACM SIGCOMM Conf on SIGCOMM, p.3-14.
[9]Kim C, Sivaraman A, Katta N, et al., 2015. In-band network telemetry via programmable dataplanes. Proc ACM SIGCOMM, p.1-2.
[10]Li Y, Chen M, 2015. Software-defined network function virtualization: a survey. IEEE Access, 3:2542-2553.
[11]Mao HZ, Alizadeh M, Menache I, et al., 2016. Resource management with deep reinforcement learning. Proc 15th ACM Workshop on Hot Topics in Networks, p.50-56.
[12]Mao HZ, Netravali R, Alizadeh M, 2017. Neural adaptive video streaming with Pensieve. Proc Conf of the ACM Special Interest Group on Data Communication, p.197-210.
[13]McKeown N, Anderson T, Balakrishnan H, et al., 2008. OpenFlow: enabling innovation in campus networks. ACM SIGCOMM Comput Commun Rev, 38(2):69-74.
[14]Mestres A, Rodriguez-Natal A, Carner J, et al., 2017. Knowledge-defined networking. ACM SIGCOMM Comput Commun Rev, 47(3):2-10.
[15]SDxCentral, 2018. Google Brings SDN to the Public Internet. https://www.sdxcentral.com/articles/news/google-brings-sdn-public-internet/2017/04 [Accessed on July 23, 2018].
[16]Shalom N, 2010. Amazon Found Every 100ms of Latency Cost Them 1% in Sales. https://blog.gigaspaces.com/ amazon-found-every-100ms-of-latency-cost-them-1-in-sales [Accessed on July 23, 2018].
[17]Shi WS, Cao J, Zhang Q, et al., 2016. Edge computing: vision and challenges. IEEE Int Things J, 3(5):637-646.
[18]Taleb T, Samdanis K, Mada B, et al., 2017. {On multi-access edge computing: a survey of the emerging 5G network edge cloud architecture and orchestration}. IEEE Commun Surv Tut, 19(3):1657-1681.
[19]Valadarsky A, Schapira M, Shahaf D, et al., 2017. Learning to route. Proc 16$^rm th$ ACM Workshop on Hot Topics in Networks, p.185-191.
[20]Varga B, 2017. DetNet Service Model: draft-varga-detnet-service-model-02. https://datatracker.ietf.org/doc/html/draft-varga-detnet-service-model-02 [Accessed on July 23, 2018].
[21]Wollschlaeger M, Sauter T, Jasperneite J, 2017. The future of industrial communication: automation networks in the era of the Internet of Things and Industry 4.0. IEEE Ind Electron Mag, 11(1):17-27.
[22]Xu XW, Pan YC, Lwin PPMY, et al., 2011. 3D holographic display and its data transmission requirement. Proc Int Conf on Information Photonics and Optical Communications, p.1-4.
[23]Zhang LX, Afanasyev A, Burke J, et al., 2014. Named data networking. ACM SIGCOMM Comput Commun Rev, 44(3):66-73.
ORCID: 
Open peer comments: Debate/Discuss/Question/Opinion
<1>