Software as a service

About: Software as a service is a research topic. Over the lifetime, 8514 publications have been published within this topic receiving 136177 citations. The topic is also known as: Service as a Software Substitute & SaaSS.

Software as a Service: Configuration and Customization Perspectives

Abstract: Software as a service (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. Though SaaS application is usually developed with highly standardized software functionalities to serve as many clients as possible, many clients still ask for function variants according to their unique business needs through easy configuration and customization. Due to the subscription based model, SaaS vendors need take a well designed strategy to enable self serve configuration and customization by their customers without changing the SaaS application source code for any individual customer. In this paper, we will explore the configuration and customization issues and challenges to SaaS vendors, clarify the difference between configuration and customization. A competency model and a methodology framework have been developed to help SaaS vendors to plan and evaluate their capabilities and strategies for service configuration and customization.

Generalized Nash Equilibria for the Service Provisioning Problem in Multi-Cloud Systems

Abstract: In recent years, the evolution and the widespread adoption of virtualization, service-oriented architectures, autonomic, and utility computing have converged letting a new paradigm to emerge: cloud computing. Clouds allow the on-demand delivering of software, hardware, and data as services. Currently, the cloud offer is becoming wider day by day because all the major IT companies and service providers, like Microsoft, Google, Amazon, HP, IBM, and VMWare, have started providing solutions involving this new technological paradigm. As cloud-based services are more numerous and dynamic, the development of efficient service provisioning policies becomes increasingly challenging. In this paper, we take the perspective of Software as a Service (SaaS) providers that host their applications at an Infrastructure as a Service (IaaS) provider. Each SaaS needs to comply with quality-of-service requirements, specified in service-level agreement (SLA) contracts with the end users, which determine the revenues and penalties on the basis of the achieved performance level. SaaS providers want to maximize their revenues from SLAs, while minimizing the cost of use of resources supplied by the IaaS provider. Moreover, SaaS providers compete and bid for the use of infrastructural resources. On the other hand, the IaaS wants to maximize the revenues obtained providing virtualized resources. In this paper, we model the service provisioning problem as a generalized Nash game and we show the existence of equilibria for such game. Moreover, we propose two solution methods based on the best-reply dynamics, and we prove their convergence in a finite number of iterations to a generalized Nash equilibrium. In particular, we develop an efficient distributed algorithm for the runtime allocation of IaaS resources among competing SaaS providers. We demonstrate the effectiveness of our approach by simulation and performing tests on a real prototype environment deployed on Amazon EC2. Results show that, compared to other state-of-the-art solutions, our model can improve the efficiency of the cloud system evaluated in terms of Price of Anarchy by 50-70 percent.

State-of-the-art research study for green cloud computing

Abstract: Although cloud computing has rapidly emerged as a widely accepted computing paradigm, the research on cloud computing is still at an early stage. Cloud computing suffers from different challenging issues related to security, software frameworks, quality of service, standardization, and power consumption. Efficient energy management is one of the most challenging research issues. The core services in cloud computing system are the SaaS (Software as a Service), PaaS (Platform as a Service), and IaaS (Infrastructure as a Service). In this paper, we study state-of-the-art techniques and research related to power saving in the IaaS of a cloud computing system, which consumes a huge part of total energy in a cloud computing system. At the end, some feasible solutions for building green cloud computing are proposed. Our aim is to provide a better understanding of the design challenges of energy management in the IaaS of a cloud computing system.

Software-as-a-Service Model: Elaborating Client-Side Adoption Factors

Abstract: Software-as-a-Service (SaaS) is emerging as a viable outsourcing option for clients interested in paying for the right to access a standardized set of business software functions through the network. SaaS model largely replaced the Application Service Providers (ASPs) model, by creating an architecture that provides no mechanisms for customizing the software on the vendor side; all customization is done on the client side through standardized interfaces. The fact that vendors are not making any client-specific investments makes this outsourcing model quite intriguing. In this paper we investigate client's side determinants the SaaS model adoption. We draw on economic, strategic management, and Information Systems theories to develop a theoretical framework. By integrating diverse literature streams, we are able to develop a more elaborate view of uncertainty arguing that some types uncertainty increase the propensity to adopt SaaS, while other types do not. Finally, we argue that the maturity of the client's internal enterprise IT architecture plays an important role in SaaS adoption decisions.