Application of Multi-tenant Service Customization Algorithm Based on Multi-target Ant Colony Algorithm in Cloud Platform Software as a Service
- DOI
- 10.2991/icmeit-17.2017.75How to use a DOI?
- Keywords
- Ant colony algorithm, Multi-tenant, SaaS, Service customization.
- Abstract
Multi-tenant service customization is one of the core technologies to implement the SaaS multi-tenant software architecture, which can meet the changing needs of individual tenants. In order to broaden the intelligent application of ant colony algorithm in SaaS and improve the service quality and efficiency of SaaS platform, a multi - tenant service customization algorithm based on MapReduce and multi - target ant colony algorithm is proposed. From a number of business processes and mass services, the multi-tenant service customization algorithm sets the most suitable business process and optimized service portfolio for tenants. Multi-tenant service custom algorithm designed multi-target ant colony algorithm, and applied the MapReduce cloud computing technology. In a cloud computing environment, it runs in a distributed and parallel manner to optimize tasks. The results show that the multi - tenant service customization algorithm has a good convergence and expansibility in solving the multi - tenant personalized service customization problem. The algorithm has the ability to handle massive data and large-scale problems.
- Copyright
- © 2017, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Weibo Li PY - 2017/05 DA - 2017/05 TI - Application of Multi-tenant Service Customization Algorithm Based on Multi-target Ant Colony Algorithm in Cloud Platform Software as a Service BT - Proceedings of the 2nd International Conference on Mechatronics Engineering and Information Technology (ICMEIT 2017) PB - Atlantis Press SP - 382 EP - 386 SN - 2352-538X UR - https://doi.org/10.2991/icmeit-17.2017.75 DO - 10.2991/icmeit-17.2017.75 ID - Li2017/05 ER -