72 results about "Network variable" patented technology

A network tool is provided for use when replacing devices in an automatically controlled distributed processing system. The network tool reestablishes all or a portion of the logical connections formerly provided to the node where the replacement device is or will be located. The tool compares data associated with the logical connections of the node and data associated with the logical connections for the replacement device to determine proper logical connection. In one embodiment, the compared data comprises network variables and configuration properties.

The present invention pertains to specifying, analyzing and evaluating systems such as distributed content distribution networks. Systems and methods are provided to predict how new deployments and changes to existing architectures will impact the networks. A network design may prepare a “what-if” scenario and the impact of this scenario may be predicted. Various tools are provided to determine relevant network variables and collect data about such variables, to learn what dependencies may exist among relevant variables, to prepare an input distribution and to output a predicted impact for the what-if scenario. Thus, a system designer is able to see a predicted impact that a network change or new deployment will have without having to resort to back of the envelope calculation or costly field deployments.

The present invention provides a method for route and resource allocation. One embodiment of the method includes determining at least one network variable associated with a network that includes a plurality of nodes connected by a plurality of links. The network variable(s) are determined based on a plurality of basic loads associated with the plurality of links and a plurality of data rates associated with the plurality of links. The method also includes determining at least one communication variable based on the determined network variable(s) and allocating at least one resource for communication over the network based on the determined network variable(s) and the determined communication variable(s).

A tool is provided for use when replacing devices in an automatically controlled distributed processing system. In one embodiment a network management tool reestablishes all or a portion of the logical connections formerly provided to a bound node where a replacement device is or will be located. The network management tool compares data associated with the logical connections of the bound node and data associated with the logical connections for the replacement device to determine proper logical connection. The network management tool identifies network variables associated with the bound node that are not associated with the replacement device and deletes those network variables from other devices on the network if the network variable is not useful in the network after the replacement device is bound.

A method of performing loadflow calculations for controlling voltages and power flow in a power network by reading on-line data of given / specified / scheduled / set network variables / parameters and using control means, so that no component of the power network is overloaded as well as there is no over / under voltage at any nodes in the network following a small or large disturbances. The invented generalized Super Super Decoupled Loadflow (SSDL) calculation method is characterized in that 1) modified real power mismatch at any PQ-node-p is calculated as RPp=[ΔPp′+(Gpp′ / Bpp′)ΔQp′] / Vp2, which takes different form for different manifestation of the generalized version SSDL-X′X′ method, 2) transformed values of known / given / specified / scheduled / set quantities in the diagonal elements of the gain matrix [YV] of the Q-V sub-problem are present, and 3) transformation angles are restricted to maximum of −48° particularly for the most successful version SSDL-YY method, and these inventive loadflow calculation steps together yield some processing acceleration and consequent efficiency gains, and are each individually inventive. The other two Super Super Decoupled Loadflow methods: BGX′ version (SSDL-BGX′) and X′GpvX′ version (SSDL-X′GpvX′) are characterized in the use of simultaneous (1V, 1θ) iteration scheme thereby calculating mismatches only once in each iteration and consequent efficiency gain.

A method of performing loadflow computations for controlling voltages and power flow in a power network by reading on-line data of given / specified / scheduled / set network variables / parameters and using control means, so that no component of the power network is overloaded as well as there is no over / under voltage at any nodes in the network following a small or large disturbances. A loadflow computation method could be any method including invented Patel Decoupled Loadflow (PDL) method, and Decoupled Gauss-Seidel-Patel Loadflow (DGSPL) method. The invented Patel Decoupled Loadflow (PDL) calculation method is characterized in 1) the use of the same coefficient matrix [GB] for both the p-f and q-e sub-problems of the loadflow computation; 2) almost no effort in the modified mismatch calculations in the iteration process; and 3) all the nodes in both the sub-problems being active, no refactorization of [GB] required for implementation of Q-limit violations. These features make the invented PDL method computationally almost two times more efficient than the current state-of-the-art Super Super Decoupled Loadflow (SSDL) method. The invented DGSPL calculation method is characterized in decoupling the calculation of real and imaginary components of complex node voltage leading to increased stability and efficiency of the DGSPL calculation method.

A system for solving a dynamic constraint satisfaction problem comprises a constraint network of variables and constraints. The system creates a first sub-problem model that includes a first model type, one or more first variables and zero or more first constraints. The system propagates the first constraints through the constraint network and determines if a first conflict is detected from propagating the first constraints. If the first conflict is detected, the system restores the constraint network variables to a first previous state before the first constraints were propagated. The system creates a first sub-problem set that includes a second model type and one or more sub-problem models. The system connects the first sub-problem model to the first sub-problem set via a second constraint and propagates the second constraint through the constraint network.

Computing environments employing Artificial Intelligence (AI) are disclosed for enabling network operators to optimize messaging performance, particularly 5G (and future 6G) messaging performance, in real-time. For example, AI structures can assist in the selection and optimization of modulation tables. Three development phases are described: network data acquisition including faults experienced under various network conditions, AI structure tuning for accurate prediction of performance, and implementation of an algorithm based on the AI structure. Network operators can use the algorithm to compare predicted performance metrics according to various operating conditions, such as available modulation tables, and thereby select operating parameters for improved message reliability and throughput. The algorithm can also be used to adjust network variables, such as particular amplitude or phase levels in modulation tables.