565 results about "Failover" patented technology

The invention relates to an equipment fault prediction method based on industrial Internet of Things and related equipment, and the method comprises the following steps: carrying out the physical signal collection of target equipment through a preset industrial Internet of Things, and obtaining an original sequence signal; identifying whether an abnormal signal exists in the original sequence signal to obtain an identification result; if the identification result is that the abnormal signal exists, performing fault type analysis on the target equipment based on the abnormal signal to obtain a fault position and a fault type corresponding to the fault position; performing failover prediction on the target equipment based on the abnormal signal, the fault position and the fault type corresponding to the fault position to obtain a predicted failover path; according to the method, the early warning instruction is generated on the basis of the predicted fault transfer path, and fault alarm is performed on the basis of the early warning instruction, so that the technical problems that a regular inspection or post-fault maintenance mode is mostly adopted in a traditional equipment maintenance mode, the cost is high, and sudden faults cannot be effectively prevented are solved.

An example file server manager updates a selected share of a destination distributed file server based on a snapshot of at least a portion of a selected share of a source distributed file server. The selected share of the destination distributed file server is updated while the source distributed file server serves client requests for storage items of the selected share of the source distributed file server. The file server manager receives a request to failover from the source distributed file server to the destination distributed file server and configures the destination distributed file server to service read and write requests for storage items of the selected share of the destination distributed file server. The file server manager further redirects client requests for storage items of the selected share of the source distributed file server to the destination distributed file server by updating active directory information.

The invention relates to an HTTP (Hyper Text Transport Protocol) short message gateway processing method and device, equipment and a storage medium. The method comprises the following steps: firstly, carrying out multi-dimensional verification on a short message sending request, and then, carrying out auditing and template matching on short message contents. And based on an audit result, considering multiple factors to select an optimal sending channel. Distributing priorities for the short messages according to user characteristics and system states, and putting the short messages into a multi-level feedback queue; and based on the type of the short message, selecting a channel and a user package to carry out charging and quota control. The short message information is stored in a distributed cache system, a sending task is processed through an asynchronous processing queue and a working thread pool, a failover and intelligent retry mechanism is implemented, and efficient and reliable short message sending is ensured. According to the HTTP short message gateway processing scheme, a large number of concurrent requests can be efficiently processed, the sending channel is intelligently selected, the sending priority is flexibly controlled, charging is accurate, and the HTTP short message gateway processing scheme has the fault transfer capability.

The invention provides a multi-platform collaborative data acquisition and analysis method, and relates to the technical field of data processing and analysis. The method comprises the following steps: receiving and converting data from different platforms into a unified intermediate format through a data adaptation intermediate layer, and processing a data structure and an interface of a specific platform by using a plurality of adapters; the data abstraction layer defines a standardized interface, so that multiple platforms request data through a unified interface, and a mapping rule converts the request into calling of the adaptation layer; the data integration engine preprocesses the data to ensure data consistency and accuracy; the data warehouse adopts a distributed architecture to ensure the service continuity through load balancing, data partitioning, a caching mechanism and a redundant storage and fault transfer mechanism; and the data processing and analysis module converts the data into decision suggestions by using a visual tool and a data mining algorithm. According to the method, manual intervention is reduced, the data processing speed and accuracy are improved, the data mode and trend are deeply mined, and service decision is promoted.

A redundancy link includes a first optical splitter and a second optical splitter. The first optical splitter includes (i) a first hub-side port that optically couples to a first optical line terminal, a first hub-side failover-mode port, (iii) a first plurality of node-side splitter-ports each optically coupled to the first hub-side port and the first hub-side failover-mode port, (iii) a first failover-mode port coupled to the first hub-side port. The second optical splitter includes (i) a second hub-side port that optically couples to a second optical line terminal, a second hub-side failover-mode port optically coupled to the first failover-mode port, (iii) a second plurality of node-side splitter-ports each optically coupled to the second hub-side port and the second hub-side failover-mode port, (iii) a second failover-mode port coupled to the second hub-side port.

A technique monitors input / output (I / O) and storage ownership takeover activity patterns to detect degraded performance of a highly available and fault tolerant application executing in a multi-site environment. Multiple instances of the application execute in different containers or pods running on virtual machines (VMs) of a compute layer within a containerized (e.g., Kubernetes) clustering configuration that extends across clusters of the sites. A storage layer of the clusters provides shared storage to the pods running on the VMs across the multiple sites. One of the sites is configured as an active storage site configured to receive and service I / O requests from the compute layer. A single instance of the application is active at a time and configured as a “compute owner” of the shared storage to issue the I / O requests to the shared storage. The compute owner and active storage site may not be co-located on the same site, leading to excessive I / O and storage ownership takeover activity patterns indicative of degraded performance. Upon detecting such patterns, the technique automatically triggers a storage failover to ensure that compute owner and active storage site are co-located at the same site.

The invention discloses a Java-based large language model dynamic adaptation method and system, belongs to the technical field of artificial intelligence, and aims to solve the technical problems of overcoming the interface difference of multiple model interfaces, simplifying the development process and providing standardized and high-expansibility large model management. Comprising the following steps: providing a model registration and dynamic loading service, a protocol conversion and parameter standardization service and a load balancing and failover service; a streaming transmission protocol service, a function call dynamic injection service and a global error processing mechanism are provided; when a user provides a document analysis and partitioning service, a vectorization index construction service and an RAG enhanced generation service to ask questions, relevant document blocks in the Pinecone are retrieved through the RAG enhanced generation service to serve as contexts to be injected into cue words of the large language model, and answers generated by the large language model are returned.

A trusted communications environment includes a primary participant with a group creator and a distributed ledger, and a secondary participant with communication credentials. An Internet of Things (IoT) network includes a trusted execution environment with a chain history for a blockchain, a root-of-trust for chaining, and a root-of-trust for archives. An IoT network includes an IoT device with a communication system, an onboarding tool, a device discoverer, a trust builder, a shared domain creator, and a shared resource directory. An IoT network includes an IoT device with a communication system, a policy decision engine, a policy repository, a policy enforcement engine, and a peer monitor. An IoT network includes an IoT device with a host environment and a trusted reliability engine to apply a failover action if the host environment fails. An IoT network includes an IoT server including secure booter / measurer, trust anchor, authenticator, key manager, and key generator.

The invention belongs to the field of query optimization, and particularly relates to a fragmentation storage and query optimization method and system for a high-concurrency database, and the method comprises the steps: analyzing business features through a preset decision tree model, and selecting an optimal fragmentation key, constructing a fragmentation rule engine and initializing a database in combination with hash, range and list fragmentation rules and a fragmentation splitting-merging strategy; generating a query abstract syntax tree by using an ANTLR4 analyzer, and detecting whether a preset Cube is hit or not to directly return a result; if not, dynamically routing to a target fragment list based on a fragment key field, load balancing and a failover strategy, accelerating data retrieval in combination with a high-frequency index, and combining fragment-level results through a T-TopK algorithm; according to the method, the self-adaptive matching of the fragmentation strategy and the service requirement, the calculation push-down of the query process and the result optimization are realized, and the low delay and the high availability in a high-concurrency scene are ensured.

The technology disclosed herein enables a service manager of a container orchestration platform to handle failovers of pods executing an application in a high availability mode. In a particular example, a method includes receiving pod information including unique application identifiers generated by the application and indications of which of the pods are active and standby. The method further includes configuring service objects provided by the container orchestration platform of the pods to each correspond to respective ones of the pods based on the unique application identifiers. The method also includes receiving updated pod information indicating a first pod of the pods, which was on standby, is now active having first application identifier of the unique application identifiers previously assigned to a second pod that failed. Additionally, the method includes reconfiguring a service object associated with the first application identifier to correspond to the first pod instead of the second pod.

Aspects of the present disclosure provide a failover service in part by utilizing a smartphone when a business or home modem is inoperable or otherwise unable to provide adequate internet service. Once the smartphone is paired with a communication bridge, the smartphone may be used to provide internet services to wired and wireless devices associated with a first network. The smartphone can utilize its cellular network interface to connect to the internet and provide internet connectivity via the communication bridge to a router or gateway which, in turn, enables devices connected to the router or gateway to access the internet without having to connect directly to a separate network provided by the smartphone. Aspects of the disclosure may rely on machine learning to optimize network and / or device communications, configurations, and / or other failover parameters.

The present application discloses a method, system, and computer system for performing failovers of traffic carrying devices. The method includes (i) generating, by one or more processors a virtual routing IP address that is common to a plurality of network nodes, and (ii) sending to an upstream device a physical IP address for a particular network node of the plurality of network nodes, wherein the physical IP address is sent as metadata in a packet to the upstream device.

A dynamic event-driven API orchestration system (100) for cloud-native environments, including: an event-driven API trigger module configured to wait for system events (100), user actions, or data updates and dynamically invoke API requests; an intelligent workflow orchestration module designed to optimize API execution sequences based on workload, system state (100) and dependency constraints; an AI-based load balancing module that dynamically distributes API requests across multiple servers or endpoints to avoid bottlenecks; a failover and fault tolerance module configured to detect API failures, perform automatic retry attempts, implement fallback strategies, and dynamically redirect requests; a module for asynchronous and parallel execution that enables the simultaneous processing of APIs, reduces response times and improves throughput; a security and compliance module that integrates adaptive authentication mechanisms, real-time threat detection, and policy-based access controls for API interactions; a module for scalability and cloud-native integration for seamless deployment across Kubernetes, serverless architectures, and multi-cloud environments; and a monitoring and analysis module that enables real-time tracking of API performance, failure rates, and traffic patterns to gain predictive insights for optimization.

Solutions for service aware proxy-call session control function (P-CSCF) traffic routing include: receiving, at a master P-CSCF in a pool of a plurality of P-CSCFs, internet protocol (IP) multimedia subsystem (IMS) traffic from a device; determining, by the master P-CSCF, a traffic type (e.g., 5G, 4G, SMS, WiFi, etc.) of the IMS traffic from the device; based on at least the traffic type of the IMS traffic from the device, selecting, by the master P-CSCF, a serving P-CSCF from the pool for the device; and forwarding, by the serving P-CSCF for the device, the IMS traffic from the device to an IMS. In some examples, the serving P-CSCF selection also includes loading considerations. In some examples, an alternate P-CSCF is available for failover as the new master P-CSCF. In some examples, a network includes multiple pools of P-CSCFs, with each pool having its own master P-CSCF and alternate P-CSCF.

Described is an improved approach to IP failover in a computing system. An approach is described which allows each node to perform its own sorted ordering of the interface devices on that node, but in a way where each node will deterministically come up with the exact same sorted order as another node. In this way, each node will select the exact same failover target as any other node, without requiring complicated coordination logic and without the need for a centralized coordinator.

An example file server manager updates a selected share of a destination distributed file server based on a snapshot of at least a portion of a selected share of a source distributed file server. The selected share of the destination distributed file server is updated while the source distributed file server serves client requests for storage items of the selected share of the source distributed file server. The file server manager receives a request to failover from the source distributed file server to the destination distributed file server and configures the destination distributed file server to service read and write requests for storage items of the selected share of the destination distributed file server. The file server manager further redirects client requests for storage items of the selected share of the source distributed file server to the destination distributed file server by updating active directory information.

The invention provides a replication method based on a consensus protocol. For each change operation performed by the leader server on the copy of the database, the leader server creates a copy log record and returns the result to the client. The leader does not wait for a consensus for the change operation from the follower. For submission, the leader creates a submission log record and waits for a consensus. Thus, the leader asynchronously performs database transactions, asynchronously performs replication of change operations, and synchronously performs replication of transaction submissions.

The invention discloses a multi-modal data source probe state monitoring and failover method and system, and relates to the field of Internet, the method comprises the following steps: respectively deploying data acquisition probes at a wireless access network node and a core network UPF node to obtain preprocessed network data of the wireless access network node and preprocessed network data of the core network UPF; obtaining abnormal risk prediction information through an AI monitoring model; adjusting parameter configuration of a wireless side and a core network UPF side according to the abnormal risk prediction information; and based on the adjusted parameter configuration of the wireless side and the core network UPF side, feeding back to the service awareness module so as to realize failover. According to the method, a cross-domain and cross-layer unified probe monitoring system is realized, a dynamic, explainable and closed-loop network fault analysis and regulation and control mechanism is constructed through AI technologies such as a graph neural network and reinforcement learning, and the network state sensing precision, the response timeliness and the optimization intelligent level can be remarkably improved.

The invention discloses an automatic application management and control method and device, resource isolation is carried out on each middleware WebLogic instance, each middleware WebLogic instance runs on different physical servers and shares respective state information, through transverse expansion and longitudinal expansion, optimization deployment is carried out on each middleware WebLogic instance set after resource isolation, and the management and control efficiency of each middleware WebLogic instance set after resource isolation is improved. The transverse extension is used for sharing loads by increasing the node servers, and when any node server breaks down, other node servers normally provide services; longitudinal expansion is used for ensuring consistency of node servers in load balancing of transverse expansion.

Techniques are described for preserving the inflight sessions failing over from a primary database to the replicated logical database of the primary database. In an implementation, prior to failover, when the primary database server receives a commit for a transaction, the process stores a commit indication that the transaction has been committed by performing a corresponding SQL command. The commit indication is replicated to the logical replica database by virtue of the replication of the SQL command and its execution on the logical replica database. Accordingly, the standby database server in the failover session may successfully request for the outcome of the transaction. Techniques are also described for the client-side LOB references to be preserved when failing over to the logical replica database, for AS OF queries preserved, and for versioning of checksums, signatures and structures across logical replicas.

Techniques for limiting or reducing storage accessibility “hiccups” in active-active clustered systems that perform large writes. The techniques can include executing, by a surviving, failover, or rebooted node of an active-active clustered system, a specialized recovery protocol that includes treating each large write request from a host computer as a plurality of small write requests while execution of the specialized recovery protocol is in progress, draining all dedicated sub-ubers for a primary and secondary node of the active-active clustered system, and, having completed execution of the specialized recovery protocol, resuming normal treatment of large write requests from the host computer. In this way, the need and complexity of managing large writes and maintaining their corresponding sub-uber information during recovery from a forced reboot, crash, or disaster involving the primary or secondary node can be avoided, and storage accessibility hiccups due to performing the large writes can be limited or reduced.

Method and apparatus for performing proactive input-output (IO) failover based on predicting optical transceiver module hardware failures in a host bus adapter (HBA) are described. An example method includes registering with an HBA to receive a notification that a first path via the HBA is predicted to fail. The notification is based on a set of parameters of an optical transceiver module coupled to the first path. A set of parameters of the optical transceiver module are monitored in accordance with the registration. At least one of the set of parameter is determined to satisfy a predetermined criteria. Responsive to the determination, the notification that the first path via the HBA is predicted to fail is sent, a second path via the HBA for issuing an IO operation is determined, and the IO operation is issued via the second path.

A computer-implemented method comprises providing a synchronous replication relationship from one or more storage objects of a first storage node to one or more replicated storage objects of a second storage node, providing an asynchronous replication relationship with an asynchronous update schedule from the one or more storage objects of the first storage node to one or more replicated storage objects of the third storage node to provide a protection configuration, tracking, with the third storage node of the tertiary site, a state of the secondary storage site, automatically performing a failover from the primary storage site to the secondary storage site and activating a synchronous mirror copy for the one or more replicated storage objects of the second storage node, and automatically initiating realignment and reconfiguration of the protection configuration to the tertiary storage site based upon the state of the secondary storage site.

Multi-site distributed storage systems and computer-implemented methods are described for improving a resumption time of input / output (I / O) operations during an automatic unplanned failover (AUFO). A computer-implemented method includes monitoring, with a second cluster, heartbeat information received at ultra-short time intervals from a first connection of one or more storage objects of the first cluster, determining, with the second cluster, whether the heartbeat information from the first connection is received during an ultra-short time interval, and intelligently routing heartbeat information from the one or more storage objects of the first cluster from the first connection to a second connection when the heartbeat information from the first connection is not received during the ultra-short time interval.

Techniques are disclosed for a network device that performs gradual failover of sessions from a first link to a second link. For example, a network device forwards network traffic of a plurality of sessions over the first link. The network device determines that a performance of the first link does not satisfy a performance requirement. Based on the determination, the network device forwards network traffic of a first portion of the plurality of sessions over a second link and not the first link. The network device determines that a performance of the second link satisfies the performance requirement while carrying the network traffic of the first portion. Based on the determination, the network device forwards network traffic of a second, larger portion of the plurality of sessions over the second link and not the first link.

An illustrative data storage management system comprises a management database that stores administrative preferences and system configurations, as well as results and / or statistics of completed secondary storage operations, i.e., information needed by the system to protect customers' data and to track and recover the protected data, including secondary copies such as backup copies, archive copies, etc. The disclosed data storage management system is configured to protect its own system data subject to a very aggressive (short) Recovery Point Objective (RPO), by using an innovative infrastructure that enables the system's storage manager to fail over to any number of other failover destination storage managers, each one comprising a destination management database. An illustrative database granularly tracks whether each and every transaction log file has been successfully applied to each and every destination management database to synchronize with the source management database.

A consensus protocol-based replication approach is provided. For each change operation performed by a leader server on a copy of the database, the leader server creates a replication log record and returns a result to the client. The leader does not wait for consensus for the change operation from the followers. For a commit, the leader creates a commit log record and waits for consensus. Thus, the leader executes database transactions asynchronously, performs replication of change operations asynchronously, and performs replication of transaction commits synchronously.

Methods, systems, and products for sustainable Reliability, Availability, and Serviceability (RAS) balancing based on predictive models includes predicting, based on one or more predictive models, a potential failure within a computing system, and provisioning, based on the potential failure, one or more redundant resources for failover.

Methods and systems for high speed failover in a network are provided. To provide faster Type C GPON redundancy failover, the disclosure herein describes the use of G.8031 1:1 ELPS in a single ended application to ensure path integrity through the network. Single ended 1:1 ELPS means that a network device is configured with 1:1 ELPS and switches paths in the event of disruption of the working communication path without the other underlying transport entities having knowledge of either the ELPS protocol or state machine. ELPS (Ethernet Linear Protection Switching, ITU G.8031) is a standardized method for protection switching between two point-to-point paths through a network, however its application here is quite novel. During a failure on the working path, traffic will switch over to the protection path. Type C PON protection provides a fully redundant path between the OLT and the ONU (2 separate PONs).

A data center, DC includes applications that are controllable by one or more computing entities external to the DC. However, when the DC becomes unavailable to the computing entities, the applications are no longer controllable by the computing entities, which is undesirable. Disclosed techniques include the DC determining, based on an indication that the apps are no longer controllable by the computing entities, that the applications are to operate in a disaster recovery mode. Disclosed techniques include causing an indication that the applications at the DC are to operate in the disaster recovery mode to be communicated to applications that are already executing at the DC when the determination is made and to applications that start to execute at the DC after the determination is made. Disclosed techniques also include a further DC providing a failover for the DC.