Publication Type
Conference Proceeding Article
Version
acceptedVersion
Publication Date
10-2017
Abstract
In Online-to-Offline (O2O) commerce, customer services may need to be composed from online and offline services. Such composition is challenging, as it requires effective selection of appropriate services that, in turn, support optimal combination of both online and offline services. In this paper, we address this challenge by proposing an approach to O2O service composition which combines offline route planning and social collaboration to optimize service selection. We frame general O2O service composition problems using timed automata and propose an optimization procedure that incorporates: (1) a Markov Chain Monte Carlo (MCMC) algorithm to stochastically select a concrete composite service, and (2) a model checking approach to searching for an optimal collaboration plan with the lowest cost given certain time constraint. Our procedure has been evaluated using the simulation of a rich scenario on effectiveness and scalability.
Keywords
Markov processes, Model checking, Quality of service
Discipline
Software Engineering
Research Areas
Software and Cyber-Physical Systems
Publication
ASE '17:
First Page
451
Last Page
461
ISBN
9781538626849
Identifier
10.1109/ASE.2017.8115657
City or Country
ASE 2017
Citation
QIAN, Wenyi; PENG, Xin; SUN, Jun; YU, Yijun; NUSEIBEH, Bashar; and ZHAO, Wenyun.
O2O service composition with social collaboration. (2017). ASE '17:. 451-461.
Available at: https://ink.library.smu.edu.sg/sis_research/4711
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1109/ASE.2017.8115657