O2O service composition with social collaboration

• Main Authors: QIAN, Wenyi, PENG, Xin, SUN, Jun, YU, Yijun, NUSEIBEH, Bashar, ZHAO, Wenyun
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2017
• Subjects: Markov processes; Model checking; Quality of service; Software Engineering
• Online Access: https://ink.library.smu.edu.sg/sis_research/4711; https://ink.library.smu.edu.sg/context/sis_research/article/5714/viewcontent/O2O_service_composition_ase2017_av.pdf
• Institution: Singapore Management University

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.