Scalable Enterprise Systems: Network-Based Distributed Relational Decision Framework for Scalable Enterprise Systems

Rensselaer Polytechnic Institute, Troy NY

Investigators

Abstract

Advances in information technologies are driving fundamental changes in the processes and organizations of global enterprises. Innovations in software, networks, and database systems enable widely distributed organizations to integrate activities, share information, collaborate on decisions, and execute transactions. While many existing tools and techniques of information infrastructure may be adopted and implemented to support these enterprise applications, there has been little focused research to provide a scientific basis to support these developments. This exploratory project develops a new framework to support enterprise-level decision-making in network-based scalable systems. This exploratory study will address: (1) Basic Principles, (2) Architectures, (3) Simulation and Evaluation, and (4) Applications in the case study of design-supplier-manufacturing decisions with examples drawn from industrial collaborators in the printed circuit board assembly industry. The fundamental principle of this approach asserts that decision tasks over a set of multiple, distributed, logically interrelated databases may be cast in the semantics of the underlying distributed database management system (DBMS). In this form, the augmented relational decision framework takes advantage of the principles of normalization and decomposition that are inherent to the relational DBMS model, while the decision process is viewed as an instantiation of the relational schema, and the resulting representation of normal form hierarchies and data dependencies structures the process. The outcomes of this project offer advantages of local autonomy, reliability, improved performance, scalability, shareability, data confidentiality, and efficient software support for a new class of enterprise-level software systems.