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A method for detecting system problems and a method for allocating foglets

A system problem and system configuration technology, applied in the directions of resource allocation, error detection/correction, response error generation, etc., can solve problems such as low latency threshold, hindering cloud solution performance requirements, and inefficiency of fog network.

Pending Publication Date: 2021-12-31
ABB (SCHWEIZ) AG
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] Previously available cloud solutions (e.g., compute and storage) have many disadvantages and limitations that prevent previously available cloud solutions from meeting the performance demands of IoT applications
For example, previously available cloud solutions have insufficient performance in meeting low latency thresholds; supporting highly mobile endpoint devices; and providing real-time data analysis and decision making
However, failures of equipment or software components can lead to fog network inefficiencies

Method used

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  • A method for detecting system problems and a method for allocating foglets
  • A method for detecting system problems and a method for allocating foglets
  • A method for detecting system problems and a method for allocating foglets

Examples

Experimental program
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Effect test

example 1

[0058] In this example, the system includes software agents whose role is to detect anomalies in network traffic while keeping overhead low by deploying dedicated agents only when needed. By default, software agents observe and follow simple communication patterns, so that the computational overhead these agents introduce remains low. Once the software agent observes that certain communications do not conform to previously learned patterns, for example, a sudden increase in the use of a specific operational technology (OT) communication protocol, deeper inspection is required. To this end, a set of resting software agents dedicated to inspecting specific OT communication protocols are now awakened and deployed on devices (or fog nodes) that provide better observability of problems. The goal is to assess whether the observed behavior is indeed an intrusion. Once the check is complete, these software agents are removed from their physical devices and become "resting fog agents"...

example 2

[0060]In this example, the system contains software agents whose role is to detect anomalies in network traffic with the goal of early detection and localization of intrusions while keeping system observability low by regulating the number and location of agents deployed. overhead. To reduce overhead, proxies are deployed at network aggregation points in systems such as edge routers to observe all traffic passing between different parts of the system. By observing traffic, the agent learns normal business patterns. Once there is an expected change in the traffic pattern from a certain part of the system, for example, a sudden increase in traffic indicating a denial of service attack or some system nodes suddenly using a new communication protocol, a deeper system inspection is required to learn more about the anomaly and locate potential intrusion. A new set of software agents are then created or woken from quiescence and deployed deep into that part of the system to identif...

example 3

[0062] In Example 3, the system is a fog system in supervisory mode, and a software agent in the form of a Network Anomaly Detection Sensor (NADS) agent is placed on the fog nodes such that at least one of the two endpoints of each Ethernet connection is cover. The agent monitors all network traffic at its location and periodically (eg, every second) evaluates whether the current system is functioning properly. Whether the situation is normal is assessed based on a normal model, which is either designed according to the system configuration or learned by machine learning methods during or before operation (for example, during commissioning). In supervisory mode, normal models are based on simple key performance indicators (KPIs), such as packets per second and number of distinct source-destination pairs (in Ethernet and IP headers).

[0063] If the NADS agent detects an anomaly, it notifies the coordinator software agent. The coordinator software agent in turn initiates a de...

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Abstract

The invention relates to a method for detecting system problems and a method for allocating foglets. A method for detecting system problems in a distributed control system including a plurality of computational devices is suggested. The method includes: deploying one or more software agents on one or more devices of the system; monitoring, via the one or more software agents, a system configuration and / or a system functionality; detecting a problem in the monitored system configuration and / or a system functionality; adding one or more new software agents and deploying the one or more new software agents on one or more devices of the system associated with the problem; and collecting data associated with the problem, via the added software agents.

Description

technical field [0001] The present disclosure relates generally to distributed control systems, fog computing networks, and in particular to managing fog applications in fog networks implemented on automated systems. Background technique [0002] The emergence of the Internet of Things (IoT) is extending the availability of network computing and resources to a variety of devices and systems that were previously excluded from data networking environments. Devices that worked independently of each other and were manually programmed can now work together and interact with each other. A complex system includes multiple devices working together as an automated system that reacts to and interacts with its environment. [0003] The goal of this is to achieve higher levels of automation by enabling machines of various complexities and purposes to communicate without relying on human intervention and / or interaction through manual programming of the machines via interfaces. Most of ...

Claims

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Application Information

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IPC IPC(8): G06F9/50
CPCG06F9/5027G06F9/5072G06F11/0751G06F11/0709G06F11/3051G06F11/3093G06F11/3006G06F11/3013G06F11/0736G06F11/0778G06F11/3409H04L43/08
Inventor 拉斐尔·艾登本茨马里卡琼·坎德安德烈·马考达亚历山德拉·莫加罗伯特·比尔克塔尼克萨万·西范蒂戴维·科扎亚奥格年·武科维奇
Owner ABB (SCHWEIZ) AG
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