Journal
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
Volume 92, Issue -, Pages 17-28Publisher
ELSEVIER SCIENCE BV
DOI: 10.1016/j.future.2018.09.032
Keywords
IoVs (Internet of Vehicles); IoT(Internet of Things); Optimizing deployment; Cloud computing; Edge computing; Multi-clouds; QoS; CDN (Content Delivery Network, Content Distribution Network)
Categories
Funding
- National Natural Science Foundation of China [61728202, 61572137, 61873309]
- Shanghai 2018 Innovation Action Plan project [18510760200]
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Deploying applications to a centralized cloud for service delivery is infeasible because of the excessive latency and bandwidth limitation of the Internet, such as transporting all IoVs data to big data processing service in a centralized cloud. Therefore, multi-clouds, especially multiple edge clouds is a rising trend for cloud service provision. However, heterogeneity of the cloud service, complex deployment requirements, and large problem space of multi-clouds deployment make how to deploy applications in the multi-clouds environment be a difficult and error-prone decision-making process. Due to these difficulties, current SIA-based solution lacks a unified model to represent functional and non-functional requirements of users. In this background, we propose a QoS-driven IoVs application optimizing deployment scheme in multimedia edge clouds (QaMeC). Our scheme builds a unified QoS model to shield off the inconsistency of QoS calculation. Moreover, we use NSGA-II algorithm to solve the multi-clouds application deployment problem. The implementation and experiments show that our QaMeC scheme can provide optimal and efficient service deployment solutions for a variety of applications with different QoS requirements in CDN multimedia edge clouds environment. (C) 2018 Elsevier B.V. All rights reserved.
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