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Hai Jin is the Cheung Kung Scholar Chair Professor at
Huazhong University of Science and Technology, Wuhan.
Haibo Chen is a professor and Director of the Institute of
Parallel and Distributed Systems at Shanghai Jiao Tong
Hong Gao is a professor at Harbin Institute of Technology,
Xiang-Yang Li is a professor and Executive Dean of
the School of Computer Science and Technology at the
University of Science and Technology of China, Hefei.
Song Wu is a professor and Director of the Institute
of Parallel and Distributed Computing at Huazhong
University of Science and Technology, Wuhan.
© 2018 ACM 0001-0782/18/11 $15.00..
customized data-processing services,
to a tightly coupled physical installation. It also recently announced it
would produce its own neural processing units for AI-related tasks.
And UCloud, a top-five cloud service
provider, announced its release of
for big-data applications, yielding
China’s cloud infrastructure has
made great strides, supporting large-scale applications and millions of users. The rapid development of cloud
infrastructure has been promoted
both through national research projects and through the corporations
involved. The Chinese central and
local governments now plan to push
development of cloud computing
while mainstream enterprises pursue a new round of cloud computing
The government’s plan for developing cloud computing. The Chinese
central government is emphasizing
development of cloud computing
and its underlying infrastructure.
For example, the 13th Five-Year Plan
identified cloud computing as an important emerging national strategic
industry. 14 And the Ministry of Industry and Information Technology of
China adopted a Three-Year Development Plan for cloud computing, 2017
to 2019, aiming to increase the cloud
computing industry in China to 430
billion RMB by 2019.15 The Chinese
central government is also funding a
series of projects for cloud computing. In 2017, the “Cloud Computing
and Big Data” Special Program of the
National Key Research and Development Plan launched 15 projects with
total funding of 409 million RMB. 16
In 2018, it plans to start 20 projects
with a total budget up to 625 million
Enterprises’ plan for developing
cloud computing. Chinese enterprises
are developing an increasingly powerful cloud infrastructure to provide
competitive cloud computing products and services. For example, Inspur
and Sugon launched a series of scientific projects to research key technologies in cloud datacenters and servers.
And Alibaba expects to use its cloud
unit to carry it through the next de-
cade. According to a Gartner research
report in September 2017, Ali Cloud
has surpassed Google in IaaS Public
Cloud Service and is today the third
largest cloud provider in the world. 23
In 2015, Tencent adopted its “Cloud
Plus” plan to develop Tencent Cloud,
which will invest 10 billion RMB to
build a cloud platform and ecosystem
over the next five years. Meanwhile,
Huawei has established a new busi-
ness group dedicated to developing
Emerging computing paradigms and
cloud computing. Information technology is evolving quickly. Emerging
computing paradigms like AI, the
Io T, and Cloud-Edge computing have
begun to influence the cloud infrastructure and offer opportunities for
addressing cloud-related challenges.
Machine- and deep-learning algorithms and models for AI are relevant
for cloud computing researchers and
practitioners. On the one hand, the
cloud can benefit from machine and
deep learning to support more smart
resource management. On the other,
machine- and deep-learning requires
large-scale computing power, and the
cloud is an essential platform for hosting AI services due to its potential for
high scalability and ready access to
With the rapid development of the
mobile Internet and Io T applications
in China, the existing centralized
cloud computing architecture faces
significant challenges. Edge computing is being investigated as a way to
better exploit capabilities at the edge
of the network to support the Io T. In
edge computing, the massive amount
of data generated by different kinds
of Io T devices can be processed at the
network edge instead of having to first
transmit it to the centralized cloud
infrastructure due to bandwidth- and
energy-consumption concerns. Edge
computing can thus provide services
with quicker response and greater
quality compared to traditional cloud
infrastructure and is more suitable for
being integrated with IoT to provide
more efficient and secure services for
a vast number of end users.
1. 2016 IDG Cloud Computing Survey; https://www.idg.