Feature placement algorithms for high-variability applications in cloud environments

While the use of cloud computing is on the rise, many obstacles to its adoption remain. One of the weaknesses of current cloud offerings is the difficulty of developing highly customizable applications while retaining the increased scalability and lower cost offered by the multi-tenant nature of cloud applications. In this paper we describe a Software Product Line Engineering (SPLE) approach to the modelling and deployment of customizable Software as a Service (SaaS) applications. Afterwards we define a formal feature placement problem to manage these applications, and compare several heuristic approaches to solve the problem. The scalability and performance of the algorithms is investigated in detail. Our experiments show that the heuristics scale and perform well for systems with a reasonable load

Evolving multi-tenant SaaS cloud applications using model-driven engineering

Cloud computing promotes multi-tenancy for efficient resource utilization by sharing hardware and software infrastructure among multiple clients. Multi-tenant applications running on a cloud infrastructure are provided to clients as Software-as-a-Service (SaaS) over the network. Despite its benefits, multi-tenancy introduces additional challenges, such as p artitioning, extensibility, and customizability during the application development. Over time, after the application deployment, new requirements of clients and changes in business environment result application evolution. As the application evolves, its complexity also increases. In multi-tenancy, evolution demanded by individual clients should not affect availability , security , and performance of the application for other clients. Thus, the multi- tenancy concerns add more complexity by causing variability in design decisions. Managing this complexity requires adequate approaches and tools. In this paper, we propose modeling techniques from software product lines (SPL) and model-driven engineering (MDE) to manage variability and support evolution of multi-tenant applications and their requirements. Specifically, SPL was ap p lied to define technological and concep tual variabilities during the application design, where MDE was suggested to manage these variabilities. We also present a process of how MDE can address evolution of multi-tenant applications using variability models

Event-based Customization of Multi-tenant SaaS Using Microservices

Popular enterprise software such as ERP, CRM is now being made available on the Cloud in the multi-tenant Software as a Service (SaaS) model. The added values come from the ability of vendors to enable customer-specific business advantage for every different tenant who uses the same main enterprise software product. Software vendors need novel customization solutions for Cloud-based multi-tenant SaaS. In this paper, we present an event-based approach in a non-intrusive customization framework that can enable customization for multi-tenant SaaS and address the problem of too many API calls to the main software product. The experimental results on Microsoft’s eShopOnContainers show that our approach can empower an event bus with the ability to customize the flow of processing events, and integrate with tenant-specific microservices for customization. We have shown how our approach makes sure of tenant-isolation, which is crucial in practice for SaaS vendors. This direction can also reduce the number of API calls to the main software product, even when every tenant has different customization services.publishedVersio

Using Data in Undergraduate Science Classrooms

Provides pedagogical insight concerning the skill of using data The resource being annotated is: http://www.dlese.org/dds/catalog_DATA-CLASS-000-000-000-007.htm