Implementing SaaS Solution for CRM

Greatest innovations in virtualization and distributed computing have accelerated interest in cloud computing (IaaS, PaaS, SaaS, aso). This paper presents the SaaS prototype for Customer Relationship Management of a real estate company. Starting from several approaches of e-marketing and SaaS features and architectures, we adopted a model for a CRM solution using SaaS Level 2 architecture and distributed database. Based on the system objective, functionality, we developed a modular solution for solve CRM and e-marketing targets in real estate companies.E-Marketing, SaaS Architecture, Modular Development

Academic Cloud ERP Quality Assessment Model

In the past few decades, educational institutions have been using conventional academic ERP system to integrate and optimize their business process. In this delivery model, each educational institutions are responsible of their own data, installation, and also maintenance. For some institutions, it might cause not only waste of resources, but also problems in management and financial aspects. Cloud-based Academic ERP, a SaaS-based ERP system, begin to come as a solution with is virtualization technology. It allows institutions to use only the needed ERP resources, without any specific installation, integration, or maintenance needs. As the implementation of Cloud ERP increases, problems arise on how to evaluate this system. Current evaluation approaches are either only evaluating the cloud computing aspects or only evaluating the software quality aspects. This paper proposes an assessment model for Cloud ERP system, considering both software quality characteristics and cloud computing attributes to help strategic decision makers evaluate academic Cloud ERP system

Simulation Software as a Service and Service-Oriented Simulation Experiment

Simulation software is being increasingly used in various domains for system analysis and/or behavior prediction. Traditionally, researchers and field experts need to have access to the computers that host the simulation software to do simulation experiments. With recent advances in cloud computing and Software as a Service (SaaS), a new paradigm is emerging where simulation software is used as services that are composed with others and dynamically influence each other for service-oriented simulation experiment on the Internet. The new service-oriented paradigm brings new research challenges in composing multiple simulation services in a meaningful and correct way for simulation experiments. To systematically support simulation software as a service (SimSaaS) and service-oriented simulation experiment, we propose a layered framework that includes five layers: an infrastructure layer, a simulation execution engine layer, a simulation service layer, a simulation experiment layer and finally a graphical user interface layer. Within this layered framework, we provide a specification for both simulation experiment and the involved individual simulation services. Such a formal specification is useful in order to support systematic compositions of simulation services as well as automatic deployment of composed services for carrying out simulation experiments. Built on this specification, we identify the issue of mismatch of time granularity and event granularity in composing simulation services at the pragmatic level, and develop four types of granularity handling agents to be associated with the couplings between services. The ultimate goal is to achieve standard and automated approaches for simulation service composition in the emerging service-oriented computing environment. Finally, to achieve more efficient service-oriented simulation, we develop a profile-based partitioning method that exploits a system’s dynamic behavior and uses it as a profile to guide the spatial partitioning for more efficient parallel simulation. We develop the work in this dissertation within the application context of wildfire spread simulation, and demonstrate the effectiveness of our work based on this application