Abstract: A method and system for engramic indexing of information technology (IT) infrastructure. Specifically, the method and system disclosed herein enable the efficient access, search, and/or management of enterprise-scale IT infrastructure and topologies using semantic context and natural language processing. That is, query context may be optimized using mapped semantics based on organizational constructs and machine learning, thereby reducing query overhead, increasing response performance, and improving contextual display capabilities in mass-scale environments.

Abstract: A method and system for engramic indexing of information technology (IT) infrastructure. Specifically, the method and system disclosed herein enable the efficient access, search, and/or management of enterprise-scale IT infrastructure and topologies using semantic context and natural language processing. That is, query context may be optimized using mapped semantics based on organizational constructs and machine learning, thereby reducing query overhead, increasing response performance, and improving contextual display capabilities in mass-scale environments.

Abstract: Described herein are various technologies pertaining to predicting an amount of electrical power that is to be generated by a power system at a future point in time, wherein the power system utilizes a renewable energy resource to generate electrical power. A camera is positioned to capture an image of sky over a geographic region of interest. The image is analyzed to predict an amount of solar radiation that is to be received by the power source at a future point in time. The predicted solar radiation is used to predict an amount of electrical power that will be output by the power system at the future point in time. A computational resource of a data center that is powered by way of the power source is managed as a function of the predicted amount of power.

Abstract: Described herein are various technologies pertaining to predicting an amount of electrical power that is to be generated by a power system at a future point in time, wherein the power system utilizes a renewable energy resource to generate electrical power. A camera is positioned to capture an image of sky over a geographic region of interest. The image is analyzed to predict an amount of solar radiation that is to be received by the power source at a future point in time. The predicted solar radiation is used to predict an amount of electrical power that will be output by the power system at the future point in time. A computational resource of a data center that is powered by way of the power source is managed as a function of the predicted amount of power.

Abstract: Described herein are various technologies pertaining to predicting an amount of electrical power that is to be generated by a power system at a future point in time, wherein the power system utilizes a renewable energy resource to generate electrical power. A camera is positioned to capture an image of sky over a geographic region of interest. The image is analyzed to predict an amount of solar radiation that is to be received by the power source at a future point in time. The predicted solar radiation is used to predict an amount of electrical power that will be output by the power system at the future point in time. A computational resource of a data center that is powered by way of the power source is managed as a function of the predicted amount of power.

Abstract: A framework for building an adaptive management system is described herein. Tools for building customized Agents that communicate by way of an interface abstraction over many mediated and non-mediated communications channels are described herein, wherein such tools allow for the Agents to be decoupled in terms of at least one of space, time, transport, synchronization, or communications direction.

Abstract: Described herein are various technologies pertaining to predicting an amount of electrical power that is to be generated by a power system at a future point in time, wherein the power system utilizes a renewable energy resource to generate electrical power. A camera is positioned to capture an image of sky over a geographic region of interest. The image is analyzed to predict an amount of solar radiation that is to be received by the power source at a future point in time. The predicted solar radiation is used to predict an amount of electrical power that will be output by the power system at the future point in time. A computational resource of a data center that is powered by way of the power source is managed as a function of the predicted amount of power.

Abstract: A framework that enables a local computing cloud infrastructure for rural (and third world) populations with the ability to connect into the global cloud. The framework include is a low cost architecture of long distance, wireless based, renewable energy powered, and small datacenter (DC) (referred to as a pico-DC) nodes that can fully operate off-grid, both power-wise and Internet connection-wise at a very low cost. Additionally, the framework includes power management and storage techniques that effectively enable low power and efficient power use. Thus, systems are self-sufficient, low maintenance and weather proof with no need for power or data connections.

Abstract: Described herein are various technologies pertaining to predicting an amount of electrical power that is to be generated by a power system at a future point in time, wherein the power system utilizes a renewable energy resource to generate electrical power. A camera is positioned to capture an image of sky over a geographic region of interest. The image is analyzed to predict an amount of solar radiation that is to be received by the power source at a future point in time. The predicted solar radiation is used to predict an amount of electrical power that will be output by the power system at the future point in time. A computational resource of a data center that is powered by way of the power source is managed as a function of the predicted amount of power.

Abstract: A framework that enables a local computing cloud infrastructure for rural (and third world) populations with the ability to connect into the global cloud. The framework include is a low cost architecture of long distance, wireless based, renewable energy powered, and small datacenter (DC) (referred to as a pico-DC) nodes that can fully operate off-grid, both power-wise and Internet connection-wise at a very low cost. Additionally, the framework includes power management and storage techniques that effectively enable low power and efficient power use. Thus, systems are self-sufficient, low maintenance and weather proof with no need for power or data connections.

Abstract: Described herein are various technologies pertaining to predicting an amount of electrical power that is to be generated by a power system at a future point in time, wherein the power system utilizes a renewable energy resource to generate electrical power. A camera is positioned to capture an image of sky over a geographic region of interest. The image is analyzed to predict an amount of solar radiation that is to be received by the power source at a future point in time. The predicted solar radiation is used to predict an amount of electrical power that will be output by the power system at the future point in time. A computational resource of a data center that is powered by way of the power source is managed as a function of the predicted amount of power.

Abstract: A framework for building an adaptive management system is described herein. Tools for building customized Agents that communicate by way of an interface abstraction over many mediated and non-mediated communications channels are described herein, wherein such tools allow for the Agents to be decoupled in terms of at least one of space, time, transport, synchronization, or communications direction.

Abstract: Described is a technology by which a payment abstraction layer enables application program developers to setup and/or enhance application programs to accept several payment tenders (e.g., including credit, debit, check and so forth) without requiring the application programs to implement the particular details of each payment solution provider. The payment abstraction layer provides enumeration methods and payment-related methods that are called by an application program to process payment-related input data, and instantiates payment objects to communicate with payment service providers. The payment abstraction layer may further include a hierarchy of tender (payment instrument) classes in which one class encapsulates data for different types of tenders. Some payment-related methods may be independent of any tender type, whereby an application program only need call an appropriate method with tender input data regardless of its source.