An Extensible Model for Multitask-Oriented Service Composition and Scheduling in Cloud Manufacturing

Journal of Computing and Information Science in Engineering - Tập 16 Số 4 - 2016
Yongkui Liu1,2, Xun Xu3, Zhang Li4,5, Fei Tao6
1Center for Complex Systems, School of Mechano-Electronic Engineering, Xidian University, Xi’an 710071, China
2School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China e-mail:
3Department of Mechanical Engineering, The University of Auckland, Auckland 1142, New Zealand e-mail: [email protected]
4Engineering Research Center of Complex Product Advanced Manufacturing Systems, Ministry of Education, Beihang University, Beijing 100191, China e-mail: [email protected]
5School of Automation Science and Electrical Engineering, Beihang University, Beijing, 100191, China
6School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China e-mail: [email protected]

Tóm tắt

Abstract Cloud manufacturing is an emerging novel business paradigm for the manufacturing industry. In cloud manufacturing, distributed manufacturing resources are encapsulated into services and aggregated in a cloud manufacturing platform. Through centralized service management, cloud manufacturing is capable of dealing with multiple requirement tasks simultaneously. The ability to deal with multiple tasks at the same time is an important characteristic that distinguishes cloud manufacturing from the previous networked manufacturing models such as manufacturing grid. When it comes to multiple tasks in cloud manufacturing, a critical issue is how to schedule massive services to complete them with shortest makespan, lowest cost, and highest quality, etc. In order to facilitate the research on this issue, we in this paper propose a model for multitask-oriented service composition and scheduling in cloud manufacturing, in which key factures of cloud manufacturing such as service orientation, involvement of logistics, and dynamical change of service availability are taken into account. New concepts such as service efficiency, enterprise capability, and task workload are introduced, and various types of times including service time, logistics time, and waiting time are analyzed in detail. Moreover, this model can be conveniently extended by incorporating new elements such as task constraints, task priority, and continuous task arrival. An example that motivates the current model is presented. Simulation experiments with different numbers of tasks are performed to demonstrate the feasibility of the model.

Từ khóa


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Journal of Computing and Information Science in Engineering

Tập 16 Số 4

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