Jinsong Wu

Dr. Jinsong Wu

1. School of Artificial Intelligence, Guilin University of Electronic Technology, Guilin, China.
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Academic Career Length

25Years (2002-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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5 March 2018 in IEEE Communications Surveys & Tutorials
Verified
Journal Article
Closed access
JWJinsong Wu
Jinsong Wu
SGSong Guo
Song Guo
HHHuawei Huang
Huawei Huang
WLWilliam Liu
William Liu
YXYong Xiang
Yong Xiang
In September 2015, the United Nations General Assembly accepted the 2030 Development Agenda, which has included 92 paragraphs, and the Paragraph 91 defined 17 sustainable development goals (SDGs) and 169 associated targets. The goal of this paper is to discover the correlations among SDGs and information and communications technologies (ICTs). This paper discusses the roles and opportunities that ICTs play in pursuing the SDGs. We identify a number of research gaps to those three pillars, social, economic, and environmental perspectives, of sustainable development. After extensive literature reviews on the SDG-related research initiatives and activities, we find that the majority of contributions to SDGs recognized by the IEEE and ACM research communities have mainly focused on the technical aspects while there are lack of the holistic social good perspectives. Therefore, there are essential and urgent needs to raise the awareness and call for attentions on how to innovate and energize ICTs in order to best assist all nations to achieve the SDGs by 2030.
16 December 2016 in IEEE Communications Magazine
Verified
Journal Article
Closed access
KWKun Wang
Kun Wang
YWYihui Wang
Yihui Wang
YSYanfei Sun
Yanfei Sun
SGSong Guo
Song Guo
JWJinsong Wu
Jinsong Wu
The Internet of Things (IoT) can support collaboration and communication between objects automatically. However, with the increasing number of involved devices, IoT systems may consume substantial amounts of energy. Thus, the relevant energy efficiency issues have recently been attracting much attention from both academia and industry. In this article we adopt an energy-efficient architecture for Industrial IoT (IIoT), which consists of a sense entities domain, RESTful service hosted networks, a cloud server, and user applications. Under this architecture, we focus on the sense entities domain where huge amounts of energy are consumed by a tremendous number of nodes. The proposed framework includes three layers: the sense layer, the gateway layer, and the control layer. This hierarchical framework balances the traffic load and enables a longer lifetime of the whole system. Based on this deployment, a sleep scheduling and wake-up protocol is designed, supporting the prediction of sleep intervals. The shifts of states support the use of the entire system resources in an energy-efficient way. Simulation results demonstrate the significant advantages of our proposed architecture in resource utilization and energy consumption.
19 May 2016 in IEEE Systems Journal
Verified
Journal Article
Closed access
JWJinsong Wu
Jinsong Wu
SGSong Guo
Song Guo
JLJie Li
Jie Li
DZDeze Zeng
Deze Zeng
Big data are widely recognized as being one of the most powerful drivers to promote productivity, improve efficiency, and support innovation. It is highly expected to explore the power of big data and turn big data into big values. To answer the interesting question whether there are inherent correlations between the two tendencies of big data and green challenges, a recent study has investigated the issues on greening the whole life cycle of big data systems. This paper would like to discover the relations between the trend of big data era and that of the new generation green revolution through a comprehensive and panoramic literature survey in big data technologies toward various green objectives and a discussion on relevant challenges and future directions.
5 January 2017 in IEEE Systems Journal
Verified
Journal Article
Closed access
KWKun Wang
Kun Wang
JYJun Yu
Jun Yu
YYYan Yu
Yan Yu
YQYirou Qian
Yirou Qian
DZDeze Zeng
Deze Zeng
JWJinsong Wu
Jinsong Wu
Energy crisis and carbon emission have become two seriously concerned issues universally. As a feasible solution, Energy Internet (EI) has aroused global concern once proposed. EI is a new power generation developing a vision of evolution of smart grids into the Internet. The communication infrastructure is an essential component to the implementation of EI. A scalable and permanent communication infrastructure is crucial in both construction and operation of EI. In this paper, we present an introduction and the motivation to the evolution from smart grid to EI. We also introduce a representative EI architecture, i.e., the future renewable electric energy delivery and management system. Four critical EI features are emphasized. Then, we summarize the essential requirements that EI systems have to meet. With several key supporting technologies, EI shall realize the optimal utilization of highly scalable and distributed green energy resources, so that the situation of severe energy source crisis and carbon emission can be efficiently relieved. Since an EI system might have extensively distributed consumers and devices, the guarantee of its reliability and security is extremely significant. The further specific exploration for challenges, including reliability and security, will be stated in this paper.
3 June 2019 in IEEE Access
Verified
Journal Article
Open access
SCSonglin Chen
Songlin Chen
HWHong Wen
Hong Wen
JWJinsong Wu
Jinsong Wu
WLWenxin Lei
Wenxin Lei
WHWenjing Hou
Wenjing Hou
YJYixin Jiang
Yixin Jiang
In this paper, an edge computing system for IoTbased (Internet of Things) smart grids is proposed to overcome the drawbacks in the current cloud computing paradigm in power systems, where many problems have yet to be addressed such as fully realizing the requirements of high bandwidth with low latency. The new system mainly introduces edge computing in the traditional cloud-based power system and establishes a new hardware and software architecture. Therefore, a considerable amount of data generated in electrical grid will be analyses, processed and stored at the edge of the network. Aided with edge computing paradigm, IoT-based smart grids will realize the connection and management of substantial terminals, provide the real-time analysis and processing of massive data and foster the digitalization of smart grids. In addition, we propose a privacy protection strategy via edge computing, data prediction strategy and preprocessing strategy of hierarchical decisionmaking based on task grading (HDTG) for IoT-based smart girds. The effectiveness of our proposed approaches has been demonstrated via numerical simulations.
22 January 2015 in IEEE Transactions on Wireless Communications
Verified
Journal Article
Closed access
QSQingjiang Shi
Qingjiang Shi
WXWeiqiang Xu
Weiqiang Xu
JWJinsong Wu
Jinsong Wu
ESEnbin Song
Enbin Song
YWYaming Wang
Yaming Wang
This paper considers a basic MIMO information-energy broadcast system, where a multi-antenna transmitter transmits information and energy simultaneously to a multi-antenna information receiver and a dual-functional multi-antenna energy receiver which is also capable of decoding information. Due to the open nature of wireless medium and the dual purpose of information and energy transmission, secure information transmission while ensuring efficient energy harvesting is a critical issue for such a broadcast system. Providing that physical layer security techniques are adopted for secure transmission, we study beamforming design to maximize the achievable secrecy rate subject to a total power constraint and an energy harvesting constraint. First, based on semidefinite relaxation, we propose global optimal solutions to the secrecy rate maximization (SRM) problem in the single-stream case and a specific full-stream case. Then, we propose inexact block coordinate descent (IBCD) algorithm to tackle the SRM problem of general case with arbitrary number of streams. We prove that the IBCD algorithm can monotonically converge to a Karush-Kuhn-Tucker (KKT) solution to the SRM problem. Furthermore, we extend the IBCD algorithm to the joint beamforming and artificial noise design problem. Finally, simulations are performed to validate the effectiveness of the proposed beamforming algorithms.