Fast Modeling of Analytics Workloads for Big Data Services
Lin Yang, Changsheng Li, et al.
ICSS 2014
Analytical solutions are considered as increasingly important for modern enterprises. Currently, systematical adoption of analytical solutions is limited to only a small set of large enterprises, as the deployment cost is high due to high performance hardware requirement and expensive analytics software. Moreover, such on-premises solutions are not suitable for the occasional analytics consumers. In order to accelerate the prevalence of analytical solutions, this paper explores the feasibility of leveraging SaaS (Software-as-a-Service) delivery model to provide analytics capabilities as services in a cost-effective way. The main contributions of our work include: (1) proposing a framework to enable enterprise tenants to consume analytics capabilities as services; (2) developing a method to enhance existing analytics platform to support multi-tenancy so that a single software instance can effectively support multiple concurrent tenants; (3) designing an SLA (Service Level Agreement) customization mechanism to satisfy the diverse analytics capability demands of tenants. A prototype system has been developed to evaluate the feasibility of our approach. © 2012 IEEE.
Lin Yang, Changsheng Li, et al.
ICSS 2014
Liya Fan, Fa Zhang, et al.
JPDC
Xibo Jin, Fa Zhang, et al.
JPDC
Roman Vaculín, Terry Heath, et al.
ICWS 2012