System, apparatus and methods for adaptive data transport and optimization of application execution

• US 10,163,420 B2
• Filed: 10/08/2015
• Issued: 12/25/2018
• Est. Priority Date: 10/10/2014
• Status: Active Grant

• Current Assignee: DimensionalMechanics, Inc.
• Original Assignee: DimensionalMechanics, Inc.
• Inventors: Dutt, Rajeev
• Primary Examiner(s): Tokuta, Shean
• Assistant Examiner(s): Turriate Gastulo, Juan C
• Application Number:
  US14/878,854
• Publication Number:
  US 20160105308A1
• Time in Patent Office: 1,174 Days
• CPC Class Codes: G06F 9/00 Arrangements for program control, e.g. control units program control for peripheral devices G06F13/10
• CPC Class Codes: G06F 9/4843 by program, e.g. task dispatcher, supervisor, operating system
• CPC Class Codes: G06N 3/044 Recurrent networks, e.g. Hopfield networks
• CPC Class Codes: G06N 3/047 Probabilistic or stochastic networks
• CPC Class Codes: G06N 7/01 Probabilistic graphical models, e.g. probabilistic networks
• CPC Class Codes: G09G 2370/022 Centralised management of display operation, e.g. in a server instead of locally
• CPC Class Codes: G09G 5/006 Details of the interface to the display terminal specific for a display terminal using a CRT G09G1/167; using a flat panel G09G3/2096; circuits for interfacing with colour displays G09G5/04
• CPC Class Codes: H04L 41/083 for increasing network speed
• CPC Class Codes: H04L 41/0886 Fully automatic configuration
• CPC Class Codes: H04L 67/10 in which an application is distributed across nodes in the network software deployment G06F8/60; multiprogramming arrangements G06F9/46
• CPC Class Codes: H04L 67/131 Protocols for games, networked simulations or virtual reality
• CPC Class Codes: H04L 67/60 Scheduling or organising the servicing of application requests, e.g. requests for application data transmissions using the analysis and optimisation of the required network resources admission control or resource allocation H04L47/70

Abstract

Elements and processes used to enable the generation and interaction with complex networks, simulations, models, or environments. In some embodiments, this is accomplished by use of a client-server architecture that implements processes to improve data transport efficiency (and hence network usage), reduce latency experienced by users, and optimize the performance of the network, simulation, model or environment with respect to multiple parameters.

Claims

1. An optimization platform for providing a data processing service to a client device, the platform comprising:

a communicative coupling to a source of the data processing service, the data processing service hosting a data processing application, a set of data, or both; and

;

an electronic processor programmed with a set of executable instructions, which when executed cause the optimization platform to perform;

a first optimization process operable to identify an association between a first subset of the set of data and a second subset of the set of data, wherein the first optimization process includes operating an associative neural network, the neural network including elements operable to determine that a first event and a second event are generated within a specified time interval, and further, wherein the associative neural network further includes a layer resident in the client device for accepting input data and signals;

a second optimization process operable to determine one or more executable instructions that are part of the data processing application and that may be executed by the client device in response to a signal received from the client device;

a data transfer process configured to provide the client device with the second subset of the set of data in response to a signal received from the client device requesting the set of data; and

an application transfer process configured to provide the client device with the one or more executable instructions that are part of the data processing application and that may be executed by the client device in response to the signal received from the client device.

2. The optimization platform of claim 1, wherein the second optimization process includes:

for each of a plurality of a first executable instruction or set of executable instructions and a second executable instruction or set of executable instructions, determining a probability of occurrence between the first executable instruction or first set of executable instructions and the second executable instruction or second set of executable instructions;

constructing a representation of a logic flow of the data processing application, the representation including multiple nodes, wherein a transition between two nodes is associated with the probability of occurrence between the first node and the second node;

based on a current or expected executable instruction or instructions and the constructed representation, determining one or more instructions that may be executed in response to the current or expected executable instruction or instructions; and

providing the one or more instructions that may be executed in response to the current or expected executable instruction or instructions to the application transfer process.

3. The optimization platform of claim 1, wherein the first optimization process operates to identify an association between a first element of an image and a second element of an image.

4. The optimization platform of claim 1, wherein the data processing application includes one or more of an image processing application, a video processing application, an application for processing business related data, an application used to generate a virtual environment, or an application used to construct a simulation.

5. The optimization platform of claim 1, wherein the communicative coupling is a data network.

6. The optimization platform of claim 1, wherein the first event and the second event are associated with the execution of one or more instructions.

7. The optimization platform of claim 1, wherein the first optimization process determines a set of conditional probabilities between the first and second events.

8. The optimization platform of claim 1, wherein the client device is one of a laptop computer, notebook computer, personal digital assistant, smart phone, or cell phone.

9. The optimization platform of claim 2, wherein determining a probability of occurrence between the first executable instruction or first set of executable instructions and the second executable instruction or second set of executable instructions further comprises determining a conditional probability.

10. The optimization platform of claim 2, further comprising:

determining a result of executing the first executable instruction or set of executable instructions;

storing the determined result;

determining that the first executable instruction or set of executable instructions were executed by the client device; and

transferring the determined result of executing the first executable instruction or set of executable instructions to the client device using the application transfer process.