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Pervasive and Mobile Computing

Special Issue on Mobile Crowdsourcing and Pervasive Computing for Smart Cities

Submission Deadline: April 15, 2018


With the rapid development of metropolitan areas, urban problems, such as environment pollution, traffic congestion and increased energy consumption, increase more and more.

Smart cities are emerging as a novel and promising paradigm to tackle existing problems and avoid potential issues in our cities. Recently, with the pervasive usage of intelligent equipment – e.g., GPS devices, GIS tools, traffic cameras, smart cards, smartphones and road deceleration devices --, Mobile Crowdsourcing (MCS) enables citizens to collect and share data to make our cities smart. MCS can be applied in several urban scenarios, including traffic planning, mobile social recommendation, public safety, and so on.

Meanwhile, pervasive computing has been widely used to develop smart cities by utilizing emerging computing technologies. However, several challenges still exist for an effective use of MCS and pervasive computing technologies in smart cities. Research challenges include (but are not limited to): (1) How to build a MCS architecture to sense urban pulse and investigate the spatio-temporal mobility patterns comprehensively? (2) How to compute
and analyze urban big data generated by large amount of participants/devices? (3) How to fuse multi-sourced and heterogeneous data to facilitate applications towards smart cities?

To address these challenges and find effective solutions for smart cities, this special issue focuses on mobile crowdsourcing and pervasive computing research challenges in urban scenarios. Specifically, researchers are encouraged to present their latest achievements, and research directions in this area.


Topics of interest include, but are not limited to:


Mobile crowdsourcing technology for smart cities

Crowdsourcing systems and services for smart cities

Application of pervasive and mobile computing technology for smart cities

Fault tolerance, reliability and survivability in smart cities

Vehicular social networks in smart cities

Network communications technology for smart cities

Data mining and analytics of urban big data

Safety, security, privacy and trust in applications and services for smart cities

Human mobility models for smart cities

Multi-sourced heterogeneous data acquisition and fusion for smart cities

Case studies and testbeds.



[1] Azizur Rahim, Xiangjie Kong, Feng Xia, Zhaolong Ning, Noor Ullah, Jinzhong Wang, Sajal K. Das. Vehicular Social Networks: A Survey, Pervasive and Mobile Computing, 43, Jan 2018, pp: 96-113. DOI: 10.1016/j.pmcj.2017.12.004

[2] Zhaolong Ning, Feng Xia, Noor Ullah, Xiangjie Kong, and Xiping Hu. Vehicular Social Networks: Enabling Smart Mobility, IEEE Communications Magazine, May 2017. DOI: 10.1109/MCOM.2017.1600263


Guest Editors of the Special Issue:

Xiangjie Kong, Dalian University of Technology, China, [log in to unmask]

Jiannong Cao, The Hong Kong Polytechnic University, Hong Kong, [log in to unmask]

Hongyi Wu, Old Dominion University, USA, [log in to unmask]

Ching-Hsien (Robert) Hsu, Chung Hua University, Taiwan, [log in to unmask]


For inquiries regarding this Special Issue, please contact: [log in to unmask]

Xiangjie Kong (孔祥杰), PhD, Associate Professor
IEEE/CCF Senior Member,  ACM Member
The Alpha Lab  (
School of Software, Dalian University of Technology, Development Zone, Dalian 116620, China
Email: [log in to unmask][log in to unmask];  [log in to unmask]
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