A Framework Of Scaling For Inter-Tenant Collaborative Systems

To deliver scalability for business processes running in multi-tenant cloud environment has become a critical goal for enterprise business service providers. Many such software systems are composed of data intensive operations, offered via the Internet as services, and they often perform collaborative analysis of data. Collaborative analysis of data imposes new requirements of scalability on the underneath platform. We need to approach a supporting platform for multiple systems in a multi-tenant cloud environment to achieve better performance. We present our solution of scaling-out for inter-tenant data flows between collaborative data-intensive cloud systems deployed with different VMs. In this paper, we define an abstraction of "shared data flows" to capture data co-analysis and dependency among services of such systems. We describe a model based on the abstraction that is designed with elements to address the challenges in supporting multi-tenant environment to achieve an improved scalability. Our objective is to provide optimization opportunities on bandwidth and throughput of the collaborative service systems of various tenants.