The present disclosure provides a method for information storage and a system thereof, which adapts to a data storage system. A monitoring unit is configured to detecting and monitoring operations of a storage node in the data storage system to generate corresponding one and more monitoring data. A recording processor is configured to receiving the one or the plurality of monitoring data, and rendering one or a plurality of logs according to the difference of content of the one or the plurality of monitoring data. The adjustment mechanism is performed according to the stored logs, thereby the amount of large data generated during monitoring is effectively reduced.

Out-of-bounds recovery circuits configured to detect an out-of-bounds violation in an electronic device, and cause the electronic device to transition to a predetermined safe state when an out-of-bounds violation is detected. The out-of-bounds recovery circuits include detection logic configured to detect that an out-of-bounds violation has occurred when a processing element of the electronic device has fetched an instruction from an unallowable memory address range for the current operating state of the electronic device; and transition logic configured to cause the electronic device to transition to a predetermined safe state when an out-of-bounds violation has been detected by the detection logic.

Some embodiments described herein include an apparatus having a processor communicatively coupled to a memory. The processor is configured to monitor, at a characteristic controller, a first characteristic of an electronic device. The processor is then configured to receive side-channel signature analysis of the electronic device from a signature analyzer. The processor is configured to determine if the first characteristic of the electronic device has changed or will change in a predefined period of time based on the side-channel signature analysis. The processor is then configured to adjust a second characteristic of the electronic device and/or filtering characteristics such that the side-channel signature analysis reflects predefined side-channel behavior.

A method of detecting anomalous latencies in communications between components on an integrated circuit (IC) chip. The method includes: (i) monitoring communications between a first component of the IC chip and other components of the IC chip, each communication comprising a command sent from the first component to another component, and a response received by the first component from that other component, the monitoring comprising: measuring the number of communications in each of a series of monitored time windows, and measuring the latency of each communication in the series of monitored time windows; (ii) calculating a maximum tolerable latency for each operational time window of the first component from the number of communications in that operational time window, an available stall time of the first component in that operational time window, and a latency penalty factor for that operational time window; and (iii) determining a measured latency to be anomalous if the measured latency is greater than the maximum tolerable latency.

Disclosed are embodiments for automatically resolving faults in a complex network system. Some embodiments monitor one or more of system operational parameter values and message exchanges between network components. A machine learning model detects a fault in the complex network system, and an action is selected based on a cause of the fault. After the action is applied to the complex network system, additional monitoring is performed to either determine the fault has been resolved or additional actions are to be applied to further resolve the fault.

In some examples, an electronic device records, in an entry of a time-state data structure that includes a plurality of entries to store respective times, a time in response to invocation of a time-lapse process that lasts a predefined time duration independently of a time clock of the electronic device. The electronic device determines whether times in successive entries of the plurality of entries of the time-state data structure are within a threshold of one another, the threshold based on the predefined time duration. Based on the determining, the electronic device sets a parameter representing a quality of the time clock.

A failure diagnosis device includes a communication unit, a data comparison unit, and an eligibility determination unit. The communication unit acquires first physical quantity data and second physical quantity data of a type different from that of the first physical quantity data that are used for performing failure diagnosis of a home appliance acquired by a sensor unit, and first control information related to the second physical quantity data acquired by the home appliance. The data comparison unit compares the second physical quantity data with the first control information. The eligibility determination unit determines whether or not the first physical quantity data is eligible as data used for the failure diagnosis based on a comparison result obtained by the data comparison unit.

A network device receives a data packet including a source address and a destination address. The network device drops the data packet before it reaches the destination address and generates an error message indicating that the data packet has been dropped. The network device encapsulates the error message with a segment routing header comprising a list of segments. The first segment of the list of segments in the segment routing header identifies a remote server, and at least one additional segment is an instruction for handling the error message. The network device sends the encapsulated error message to the remote server based on the first segment of the segment routing header.

Automated methods and systems for identifying problems associated with objects of a data center are described. Automated methods and systems are performed by an operations management server. For each object, the server determines a baseline distribution from historical events that are associated with a normal operational state of an object. The server determines a runtime distribution of runtime events that are associated with the object and detected in a runtime window of the object. The management server monitors runtime performance of the object while the object is running in the datacenter. When a performance problem is detected, the management server determines a root cause of a performance problem based on the baseline distribution and the runtime distribution and displays an alert in a graphical user interface of a display.

An electronic evaluation device and method thereof for optimizing an operation of computer-controlled metric appliances in a network. The method includes determining whether a fault associated with computer-controlled metric appliance is valid based on a feedback received in real time from a validation entity and updating pre-defined programmable instructions assigned to the computer-controlled metric appliance in response to determining that the fault is invalid. The predefined programmable instructions are used to determine whether the computer-executable metric is achieved or not. The method includes applying a machine learning model on the plurality of parameters and the computer-executable goal to determine a computer-executable task list to be assigned to the computer-controlled metric appliance in order to achieve the computer-executable goal.