ASE 2017

2017 32nd IEEE/ACM International Conference on Automated Software Engineering (ASE 2017), October 30 – November 3, 2017, Urbana-Champaign, IL, USA

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Technical Research
O2O Service Composition with Social Collaboration
Wenyi Qian, Xin Peng, Jun Sun, Yijun Yu, Bashar Nuseibeh, and Wenyun Zhao
(Fudan University, China; Singapore University of Technology and Design, Singapore; Open University, UK; Lero, Ireland)
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.


Time stamp: 2019-09-21T17:04:18+02:00