Abstract: A system and integration infrastructure to provide a distributed matrix or neural network of connected real-time decision support modules designed to perform business intelligence evaluations in real time. The system and integration infrastructure provide a network of intelligence superimposed upon any company's existing IT data centers, and cloud computing connections. The system is highly customizable to the unique business model deployed by the client company within the best practices of the client company's industry. Whether or not the client company has integrated their diverse enterprise systems, the elements of the matrix are annealed to the various data sources, transaction logs and client software installations currently deployed. These matrix elements or neurons are designed to house critical operational data, determined by the operational model of the client company to be of critical importance.

Abstract: A system and method 10 that provides legacy software applications 12 to be incorporated into a massively parallel and distribution processing model in the Cloud, with a high performance parallel and distributed computing (cloud) “wrapper” 14 around legacy and current systems to enable, without legacy product code change or invasive addition/editing, the legacy product to access and fully utilize the power and ability of distributed computing within the cloud through a Pneuron “cortex” platform virtual server 10. The system and method also provides the ability to distribute multiple, concurrent instances of the legacy applications, dynamically manage the load volumes, and automatically create and remove new virtual machines based upon demand requirements.

Abstract: A method and system for large data and distributed disk cache processing in a Pneuron platform 100. The system and method include three specific interoperable but distributed functions: the adapter/cache Pneuron 14 and distributed disk files 34, a dynamic memory mapping tree 50, and distributed disk file cleanup 28. The system allows for large data processing considerations and the ability to access and acquire information from large data sets 102a, 102b and rapidly distribute and provide the information to subsequent Pneurons 104 for processing. The system also provides the ability to store large result sets, the ability to deal with sequential as well as asynchronous parallel processing, the ability to address large unstructured data; web logs, email, web pages, etc., as well as the ability to handle failures to large block processing.

Abstract: A method and system for the integration of disparate data stored within an Information Technology infrastructure of a company is provided. The system and method enables holistic, real time control of data discovery, retrieval and analysis. The system combines data mining, retrieval and analytics at the source of the data, thereby solving traditional problems with disparate and distributed data, systems, business processes and analytics across an organization. The system enables a user to configure and target data, then apply rules, workflows and analytics from one central source. This process is accomplished by distributing functions in the form of software pneurons against the existing infrastructure for maximum processing while preserving a robust and extendable suite of definitions.

Abstract: A method and system for large data and distributed disk cache processing in a Pneuron platform 100. The system and method include three specific interoperable but distributed functions: the adapter/cache Pneuron 14 and distributed disk files 34, a dynamic memory mapping tree 50, and distributed disk file cleanup 28. The system allows for large data processing considerations and the ability to access and acquire information from large data files 102 and rapidly distribute and provide the information to subsequent Pneurons 104 for processing. The system also provides the ability to store large result sets, the ability to deal with sequential as well as asynchronous parallel processing, the ability to address large unstructured data; web logs, email, web pages, etc., as well as the ability to handle failures to large block processing.

Abstract: A method and system for large data and distributed disk cache processing in a Pneuron platform 100. The system and method include three specific interoperable but distributed functions: the adapter/cache Pneuron 14 and distributed disk files 34, a dynamic memory mapping tree 50, and distributed disk file cleanup 28. The system allows for large data processing considerations and the ability to access and acquire information from large data files 102 and rapidly distribute and provide the information to subsequent Pneurons 104 for processing. The system also provides the ability to store large result sets, the ability to deal with sequential as well as asynchronous parallel processing, the ability to address large unstructured data; web logs, email, web pages, etc., as well as the ability to handle failures to large block processing.

Abstract: A method and system for the integration of disparate data stored within an Information Technology infrastructure of a company is provided. The system and method enables holistic, real time control of data discovery, retrieval and analysis. The system combines data mining, retrieval and analytics at the source of the data, thereby solving traditional problems with disparate and distributed data, systems, business processes and analytics across an organization. The system enables a user to configure and target data, then apply rules, workflows and analytics from one central source. This process is accomplished by distributing functions in the form of software pneurons against the existing infrastructure for maximum processing while preserving a robust and extendable suite of definitions.

Abstract: A hardware and operating system independent platform and/or run time architecture that implements a configuration and algorithmic based application and process for enabling multiple virtual machines or internal networked physical servers (hosts) to be organized into groups or “realms” in real time and against specific configurable metrics. The configurable metrics include one or more of the following; load or processing capacity availability, cost of CPU processing, location based on risk, importance to business continuity priority requirements, disaster recovery strength and priority, geographic location of host aligned to IP, and any other client specific or custom requirements. A realm manager balances all of these configurable metrics and creates an algorithm to address allocation. The algorithm is fully elastic, allowing for automatic opening and closing of virtual machines to accommodate any internal or external changes.

Abstract: A system and method 10 that provides legacy software applications 12 to be incorporated into a massively parallel and distribution processing model in the Cloud, with a high performance parallel and distributed computing (cloud) “wrapper” 14 around legacy and current systems to enable, without legacy product code change or invasive addition/editing, the legacy product to access and fully utilize the power and ability of distributed computing within the cloud through a Pneuron “cortex” platform virtual server 10. The system and method also provides the ability to distribute multiple, concurrent instances of the legacy applications, dynamically manage the load volumes, and automatically create and remove new virtual machines based upon demand requirements.