Multi-objective optimization for location prediction of mobile devices in sensor-based applications
Document Type
Article
Publication Date
9-11-2018
Abstract
A mobile ad hoc network (MANET) can be constructed when a group of mobile users need to communicate temporarily in an ad hoc manner. It allows mobile services to be shared through device-to-device links and composed by combining a set of services together to create a complex, value-added, and cross-organizational business application. Nevertheless, various challenges, especially the reliability and quality-of-service of such a MANET-based mobile service composition, are yet to be properly tackled. Most studies and related composition strategies assume that mobile users are fully stable and constantly available. However, this is not realistic in most real-world scenarios where mobile users are mobile. The mobility of mobile users impact the reliability of corresponding mobile services and consequently impact the success rate of mobile service compositions. In this paper, we propose a reliability-aware mobile service composition approach based on prediction of mobile users' positions. We model the composition problem as a multi-objective optimization problem and develop an evolutionary multi-objective optimization-based algorithm to solve it. Extensive case studies are performed based on a real-world mobile users' trajectory data set and show that our proposed approach significantly outperforms traditional ones in terms of composition success rate.
Identifier
85053354296 (Scopus)
Publication Title
IEEE Access
External Full Text Location
https://doi.org/10.1109/ACCESS.2018.2869897
e-ISSN
21693536
First Page
77123
Last Page
77132
Volume
6
Grant
cstc2016shmszx90002
Fund Ref
National Natural Science Foundation of China
Recommended Citation
Peng, Qinglan; Zhou, Mengchu; He, Qiang; Xia, Yunni; Wu, Chunrong; and Deng, Shuiguang, "Multi-objective optimization for location prediction of mobile devices in sensor-based applications" (2018). Faculty Publications. 8381.
https://digitalcommons.njit.edu/fac_pubs/8381
