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

Additional URL

https://doi.org/10.1109/ASE.2017.8115657

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