Patent Issued for Error monitoring and prevention in computing systems based on determined trends and routing a data stream over a second network having less latency (USPTO 11836032): State Farm Mutual Automobile Insurance Company
2023 DEC 26 (NewsRx) -- By a
The assignee for this patent, patent number 11836032, is
Reporters obtained the following quote from the background information supplied by the inventors: “Collaboration across multiple disparate computing systems and platforms is becoming increasingly common in business. Often, a particular business will utilize services provided by external computing platforms, such as externally provided applications, as well as in-house computing platforms and/or applications, to conduct business, such as to provide a service to a customer. For example, a business may utilize local, company-owned assets, combined with a platform as a service (PaaS) or application platform as a service (aPaaS), to provide a service to a customer. By outsourcing at least a portion of the service provided to the customer, the particular business may more effectively and efficiently complete tasks for the customer. However, utilizing the external computing platforms and/or applications (e.g., third-party resource) increases complexity in the overall computing architecture (e.g., collaborative computing system) used to provide the service, thereby increasing the probability of encountering an error while providing the service to the customer. For example, one computing platform or network over which data is transmitted may experience a technical issue, thereby affecting the speed at which the business can provide the service to the customer.
“Each computing platform, application, and/or network operating in the collaborative process may include a monitoring system to periodically and/or continually evaluate the health of the respective system and/or computing devices associated therewith. However, the individual monitoring systems may not communicate with one another to alert other computing systems of faults or potential future failures (e.g., high probability of a future system failure). As such, determining a root cause of a problem or fault associated with a collaborative computing system may be time and resource intensive. Furthermore, it may not be possible, with little or no insight into the individual monitoring systems associated with external computing platforms and/or applications, to identify a potential future failure associated with a third-party resource used in the collaborative computing system.
“Examples of the present disclosure are directed toward overcoming the deficiencies noted above, as well as other deficiencies.”
In addition to obtaining background information on this patent, NewsRx editors also obtained the inventors’ summary information for this patent: “This disclosure is directed to an intelligent error monitoring and alert system configured to identify faults and/or potential future faults in a collaborative computing system (“collaborative system”). The collaborative system may include a plurality of computing devices configured to communicate with one another via one or more networks. The plurality of computing devices may include computing devices that are managed by one or more disparate entities (e.g., businesses, companies, organizations, etc.) and/or located in geographically separated locations. For example, one or more first computing devices may be associated with a platform as a service and one or more second computing devices may be associated with an enterprise private cloud. In some examples, at least one computing device of the plurality of computing device may be separated from other computing devices of the collaborative system by a firewall.
“The intelligent error monitoring and alert system may receive data from the plurality of computing devices and may monitor the health of the collaborative system. In some examples, the intelligent error monitoring and alert system may be configured to analyze the data and identify one or more faults associated with a portion of the collaborative system (e.g., an associated computing device, platform, network, etc.). In some examples, the intelligent error monitoring and alert system may be configured to identify potential future faults associated with the portion of the collaborative system. In some examples, the intelligent error monitoring and alert system may identify a computing system associated with the fault and/or potential future fault. In some examples, the intelligent error monitoring and alert system may send a notification of the fault and/or the potential future fault to the computing system associated therewith. In some examples, the intelligent error monitoring and alert system may determine an action to perform to remedy (e.g., resolve, etc.) the fault and/or prevent the potential future fault. In such examples, the intelligent error monitoring and alert system may cause the associated computing system to perform the action.
“In various examples, a computing system may receive a plurality of data streams from a plurality of computing devices via one or more networks, wherein a first computing device of the plurality of computing devices is associated with a first organization and a second computing device of the plurality of computing devices is associated with a second organization that is different from the first organization. The computing system may determine a characteristic associated with a first data stream of the plurality of data streams. The computing system may determine, based at least in part on a set of rules, that a value associated with the characteristic meets or exceeds a threshold value. The computing system may identify a computing device associated with the first data stream. The computing system may determine, based on determining that the value exceeds the threshold value, a fault associated with the computing device. The computing system may identify an action to perform based at least in part on the fault and perform the action, wherein performing the action causes the fault associated with the computing device to be resolved.
“In some examples, a method includes receiving, with a computing device of a computing system, a plurality of data streams from a plurality of computing devices via one or more networks, wherein a first computing device of the plurality of computing devices is associated with a first organization corresponding to the computing device and a second computing device of the plurality of computing devices is associated with a second organization that is different from the first organization. The method may further include determining that a value associated with a characteristic associated with a first data stream of the plurality of data streams meets or exceeds a threshold value. The method may further include determining, based on determining that the value meets or exceeds the threshold value, a fault associated with the first computing device associated with the first data stream. The method may further include identifying an action to perform based at least in part on the fault and performing the action, wherein performing the action includes causing the fault associated with the first computing device to be resolved.
“In some examples, a non-transitory computer readable medium may be configured to receive a plurality of data streams from a plurality of computing devices via one or more networks, wherein a first computing device of the plurality of computing devices is associated with a first organization and a second computing device of the plurality of computing devices is associated with a second organization that is different from the first organization. The non-transitory computer readable medium may further be configured to determine, based at least in part on a rule, that a computing system associated with a first data stream of the plurality of data streams has associated therewith at least one of a fault or a potential future fault. The non-transitory computer readable medium may further be configured to identify an action to perform based at least in part on the at least one of the fault or the potential future fault and cause at least one computing device to perform the action, wherein performing the action includes causing the fault associated with the first computing device to be resolved.”
The claims supplied by the inventors are:
“1. A computing system associated with a first organization, comprising: one or more processors; and one or more computer-readable media storing instructions which, when executed by the one or more processors, cause the one or more processors to: receive a plurality of data streams from a plurality of computing devices via one or more networks, wherein a first computing device of the plurality of computing devices is associated with the first organization and a second computing device of the plurality of computing devices is associated with a second organization that is different from the first organization; determine a current value of a characteristic associated with a first data stream of the plurality of data streams, the first data stream being received from the first computing device via a first network of the one or more networks, the first network characterized by a first latency; access historical data associated with the first data stream, wherein the historical data includes values of the characteristic over a first period of time; identify a trend associated with the first data stream based at least in part on the current value of the characteristic and the historical data; predict, based at least in part on the trend, that a future value of the characteristic will be greater than or equal to a threshold value after a second period of time; determine, based on predicting that the future value will be greater than or equal to the threshold value, a potential future fault associated with the first network or the first computing device; based at least in part on the potential future fault, identify a second network of the one or more networks having a second latency that is less than the first latency; identify an action to perform based at least in part on the potential future fault. wherein the action includes routing the first data stream over the second network; and cause the action to be performed, wherein performing the action prevents the potential future fault from occurring.
“2. The computing system of claim 1, wherein the potential future fault is associated with at least one of: a hardware component associated with the first computing device; an application associated with the first computing device; a firewall associated with the first computing device; or the first network.
“3. The computing system of claim 1, wherein the action comprises at least one of: routing at least one data stream of the plurality of data streams from the first network to the second network; allocating additional resources to the first computing device; sending a notification to the first computing device to alert a user of the first computing device of the potential future fault; performing an infrastructure modification associated with an infrastructure of the first computing device; updating software associated with the first computing device; or modifying an application associated with the first computing device.
“4. The computing system of claim 1, wherein, when executed, the instructions further cause the one or more processors to: determine that a second data stream of the plurality of data streams is transmitted via the first network; determine that the first latency is above a latency threshold; determine that the second latency is below the latency threshold; and cause the second data stream to be transmitted via the second network.
“5. The computing system of claim 1, wherein, the trend is indicative of a performance degradation of the first computing device and the action to be performed increases computing resource allocation of the first computing device.
“6. The computing system of claim 1, wherein the plurality of computing devices is associated with a plurality of geographic locations.
“7. The computing system of claim 1, wherein at least one of the potential future fault or the action is determined based at least in part on machine learning techniques.
“8. A method, comprising: receiving, with a computing device of a computing system, a plurality of data streams from a plurality of computing devices via one or more networks, wherein a first computing device of the plurality of computing devices is associated with a first organization corresponding to the computing device and a second computing device of the plurality of computing devices is associated with a second organization that is different from the first organization; determining a current value of a characteristic associated with a first data stream of the plurality of data streams, the first data stream being received from the first computing device via a first network of the one or more networks, the first network characterized by a first latency; accessing historical data associated with the first data stream, wherein the historical data includes values of the characteristic over a first period of time; identifying a trend associated with the first data stream based at least in part on the current value of the characteristic and the historical data; predicting, based at least in part on the trend, that a future value of the characteristic will be greater than or equal to a threshold value after a second period of time; determining, based on predicting that the future value will be greater than or equal to the threshold value, a potential fault associated with the first network or the first computing device; based at least in part on the potential fault, identifying a second network of the one or more networks having a second latency that is less than the first latency; identifying an action to perform based at least in part on the potential fault, wherein the action includes routing the first data stream over the second network; and causing the action to be performed, wherein performing the action prevents the potential fault from occurring.
“9. The method of claim 8, wherein the action comprises sending a notification associated with the potential fault, the method further comprising: determining, based on an identifier associated with the first computing device, that the first computing device is associated with the first organization; generating a notification comprising information corresponding to the potential fault, the notification comprising an instruction to prevent the potential fault; sending the notification to at least one of the first computing device or another computing device associated with the first organization; and causing the first computing device to prevent the potential fault based at least in part on the instruction.
“10. The method of claim 8, wherein the action comprises updating software associated with the first computing device, the method further comprising: determining, based on an identifier associated with the first computing device, that the first computing device is associated with the first organization; and identifying a software component of the first computing device to be updated, wherein performing the action comprises automatically updating the software component of the first computing device.
“11. The method of claim 8, wherein the potential fault is associated with an application managed by the first computing device and wherein performing the action comprises: identifying a modification to the application configured to prevent the potential fault; and causing the application to be modified based at least in part on the modification.
“12. The method of claim 8, further comprising: determining that a second data stream of the plurality of data streams is transmitted via the first network; determining that the first latency is above a latency threshold; determining that the second latency is below the latency threshold; and causing the second data stream to be transmitted via the second network.
“13. The method of claim 8, wherein: the potential fault is associated with a resource available to the first computing device, and the action comprises rendering additional resources available to the first computing device.
“14. The method of claim 8, wherein at least one of the potential fault or the action is determined based at least in part on machine learning models trained on the historical data.
“15. A non-transitory computer-readable medium storing instructions which, when executed by one or more processors, cause the one or more processors to: receive a plurality of data streams from a plurality of computing devices via one or more networks, wherein a first computing device of the plurality of computing devices is associated with a first organization and a second computing device of the plurality of computing devices is associated with a second organization that is different from the first organization; determine, based at least in part on a trend, that a first network of the one or more networks characterized by a first latency, associated with a first data stream of the plurality of data streams, has associated therewith at least one of a fault or a potential future fault; determine, based on the determining that the first network has associated therewith at least one of a fault or potential future fault, that a second network has a second latency that is less than the first latency; identify an action to perform based at least in part on the at least one of the fault or the potential future fault, wherein the action includes routing the first data stream over thea second network of the one or more networks; and cause at least one computing device to perform the action, wherein performing the action includes causing the fault or the potential future fault to be resolved.
“16. The non-transitory computer-readable medium as claim 15 recites, wherein the fault is associated with at least one of: a hardware component associated with the first computing device; an application associated with the first computing device; a firewall associated with the first computing device; or the first network via which the first data stream is transmitted.”
There are additional claims. Please visit full patent to read further.
For more information, see this patent: Batronis,
(Our reports deliver fact-based news of research and discoveries from around the world.)
Patent Application Titled “Systems And Methods For Providing An Interactive Digital Personalized Experience Interface For Users To Engage In Various Aspects Of Behavioral Healthcare” Published Online (USPTO 20230395220): Patent Application
Findings from University of Leuven (KU Leuven) Broaden Understanding of Engineering (Claims Fraud Detection With Uncertain Labels): Engineering
Advisor News
- Year-end planning errors retirees should avoid
- Social cultivation: How to talk with wealthy prospects
- How important is a written financial plan?
- Coalition wants to advise people impacted by policy changes in new administration
- Diagnosing miscommunication in retirement planning
More Advisor NewsAnnuity News
Health/Employee Benefits News
- Studies in the Area of Human Papillomavirus Vaccines Reported from University of Connecticut (Accountable Care Organizations and Hpv Vaccine Uptake: a Multilevel Analysis): Immunization and Public Health – Human Papillomavirus Vaccines
- New attempt made to drop circumcision from Medicaid coverage in NH
- National Health Insurance Service Ilsan Hospital Reports Findings in Pneumothorax (Impact of Deep Learning-Based Computer-Aided Detection and Electronic Notification System for Pneumothorax on Time to Treatment: Clinical Implementation): Respiratory Tract Diseases and Conditions – Pneumothorax
- YMCA Produce Prescription Project (YPRx): Clinical Trial Identifier NCT06695104
- New Data from Emory University Illuminate Research in Lymphoma (Medicaid Coverage Continuity is Associated with Lymphoma Stage among Children and Adolescents/Young Adults): Oncology – Lymphoma
More Health/Employee Benefits NewsLife Insurance News