Changjie Guo

An Effective Heuristic for On-line Tenant Placement Problem in SaaS

As one of the key characteristics of Software as a Service (SaaS), multi-tenancy aims to support massive customers by sharing application instances and databases. To achieve the high economies of scale, one of the most issues needing to be solved in the real industry is that, given a fixed number of nodes, how to optimally place on-boarding tenants to maximize the total supported number of tenants without violating their SLA requirements. This paper focuses on this problem, which is called On-line Tenant Placement Problem (OTPP). In order to calculate the resource consumption of on-boarding tenants, a novel resource consumption estimation model for multi-tenant pattern is proposed in this paper. Based on this model, we explore the complexity of OTPP. A robust heuristic is proposed for the OTPP. The simulation experimental results show the high effectiveness and the good efficiency of our algorithm.

Study of Software as a Service Support Platform for Small and Medium Businesses

Software as a Serivce (SaaS) provides software application vendors a Web based delivery model to serve big amount of clients with multi-tenancy based infrastructure and application sharing architecture so as to get great benefit from the economy of scale. In this paper, we describe the evolution of the small and medium businesses (SMB) oriented SaaS ecosystem and its key challenges. On particular problem we focus on is how to leverage massive multi-tenancy to balance the cost-effectiveness achieved via high shared efficiency, and the consequent security, performance and availability isolation issues among tenants. Base on this foundation, we further study the concepts, competency model and enablement framework of customization and configuration in SaaS context to satisfy as may tenants’ requirements as possible. We also explore the topics on service lifecycle and the subscription management design of SaaS.