Marcelo Perazolo

Using Formal Ontology Representation and Alignment Strategies to Enhance Resource Integration in Multi Vendor Autonomic Environments

The success of the autonomic computing vision [KephartO3] relies in its capacity of correlating heterogeneous resources such as databases, switches, routers, server systems, load balancers, Web servers and/or application servers are just a few possibilities of resources that coexist in a data center today. These resources are provided by multiple vendors, and consequently implement different manageability interfaces. This multiplicity of resources also requires an ecosystem of multiple different management applications, delivered by a number of different management application vendors. Many of these vendors are now re-engineering their management infrastructure to become more autonomic and achieve the inherent value associated to a more independent management solution. Unfortunately many of the existing autonomic capabilities today are point solutions that are not easily integrated in a multi-vendor environment, nor emphasize the necessary collaboration. A true multi-vendor autonomic solution would enable the sharing and reuse of management information between heterogeneous management applications. In this paper we argue in favor of formalizing resource representations in a way that allows for automatic negotiation and integration of heterogeneous resources. We propose the use of formal ontology as a conceptual model in which to represent IT resources and present CATO, an ontology integration engine developed to provide semantic interoperability among resources in a heterogeneous environment

A Symptoms Extraction Method for Self-Management based on Decomposition of Disturbances

In this paper we present a simple but effective methodology based on the decomposition of system test disturbances and their associated incidents in order to create complex symptoms that can be used in the enablement of a completely autonomic solution and be used for self-management purposes

Shaping the future of online payment processing: an autonomic approach applied to intelligent payment brokers

As e-Commerce systems evolve, and B2B models flourish, more and more complex payment transactions are performed electronically. A consistent topic periodically addressed by e-Commerce systems is how to reduce the costs associated with these electronic transactions, such that it is of minimal detriment to the growth in the volume of transactions that are conducted online. This question is of particular interest in the area of micro-payments, where the cost of the transaction is a significant percentage of the total cost of the goods exchanged between the merchant and the buyer. This paper proposes a novel architecture and associated artifacts for online payment processing providers and their client applications (online order capture and processing systems, payment capture and processing systems, and other online-based merchant software). New data structures, message exchange patterns and optimization algorithms are developed to support this new paradigm. These artifacts are molded following the concepts defined by the Autonomic Computing and Intelligent Agents disciplines.