Formal Approach to Workow Application Fragmentations Over Cloud Deployment Models
作者机构：Division of Computer Science and EngineeringGyeonggi16227Korea
出 版 物：《Computers, Materials & Continua》 (计算机、材料和连续体（英文）)
年 卷 期：2021年第67卷第6期
页 面：3071-3088页
核心收录：
学科分类：08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）]
基 金：supported by Basic Science Research Program through the National Research Foundation of Korea(NRF) funded by the Ministry of Education(Grant Number 2020R1A6A1A03040583)
主 题：Cloud workows cloud deployment model workow application fragmentations information control net
摘 要：Workow management technologies have been dramatically improving their deployment architectures and systems along with the evolution and proliferation of cloud distributed computing ***,such cloud computing environments ought to be providing a suitable distributed computing paradigm to deploy very large-scale workow processes and applications with scalable on-demand *** this paper,we focus on the distribution paradigm and its deployment formalism for such very large-scale workow applications being deployed and enacted across the multiple and heterogeneous cloud computing *** propose a formal approach to vertically as well as horizontally fragment very large-scale workow processes and their applications and to deploy the workow process and application fragments over three types of cloud deployment models and *** concretize the formal approach,we rstly devise a series of operational situations fragmenting into cloud workow process and application components and deploying onto three different types of cloud deployment models and *** concrete approaches are called the deployment-driven fragmentation mechanism to be applied to such very large-scale workow process and applications as an implementing component for cloud workow management ***,we strongly believe that our approach with the fragmentation formalisms becomes a theoretical basis of designing and implementing very large-scale and maximally distributed workow processes and applications to be deployed on cloud deployment models and architectural computing environments as well.
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