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WO2018196953A1 - Méthode et système de diagnostic de défaillance de noeuds de réseau - Google Patents

Méthode et système de diagnostic de défaillance de noeuds de réseau Download PDF

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Publication number
WO2018196953A1
WO2018196953A1 PCT/EP2017/059754 EP2017059754W WO2018196953A1 WO 2018196953 A1 WO2018196953 A1 WO 2018196953A1 EP 2017059754 W EP2017059754 W EP 2017059754W WO 2018196953 A1 WO2018196953 A1 WO 2018196953A1
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WO
WIPO (PCT)
Prior art keywords
workflow
network node
processor
user
update
Prior art date
Application number
PCT/EP2017/059754
Other languages
English (en)
Inventor
Athanasios KARAPANTELAKIS
Aneta VULGARAKIS FELJAN
Erlendur Karlsson
Original Assignee
Telefonaktiebolaget Lm Ericsson (Publ)
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Telefonaktiebolaget Lm Ericsson (Publ) filed Critical Telefonaktiebolaget Lm Ericsson (Publ)
Priority to PCT/EP2017/059754 priority Critical patent/WO2018196953A1/fr
Publication of WO2018196953A1 publication Critical patent/WO2018196953A1/fr

Links

Classifications

    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
    • G10L15/00—Speech recognition
    • G10L15/22—Procedures used during a speech recognition process, e.g. man-machine dialogue
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F11/00—Error detection; Error correction; Monitoring
    • G06F11/07—Responding to the occurrence of a fault, e.g. fault tolerance
    • G06F11/0703—Error or fault processing not based on redundancy, i.e. by taking additional measures to deal with the error or fault not making use of redundancy in operation, in hardware, or in data representation
    • G06F11/0706—Error or fault processing not based on redundancy, i.e. by taking additional measures to deal with the error or fault not making use of redundancy in operation, in hardware, or in data representation the processing taking place on a specific hardware platform or in a specific software environment
    • G06F11/0709—Error or fault processing not based on redundancy, i.e. by taking additional measures to deal with the error or fault not making use of redundancy in operation, in hardware, or in data representation the processing taking place on a specific hardware platform or in a specific software environment in a distributed system consisting of a plurality of standalone computer nodes, e.g. clusters, client-server systems
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F11/00—Error detection; Error correction; Monitoring
    • G06F11/07—Responding to the occurrence of a fault, e.g. fault tolerance
    • G06F11/0703—Error or fault processing not based on redundancy, i.e. by taking additional measures to deal with the error or fault not making use of redundancy in operation, in hardware, or in data representation
    • G06F11/079—Root cause analysis, i.e. error or fault diagnosis
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F11/00—Error detection; Error correction; Monitoring
    • G06F11/07—Responding to the occurrence of a fault, e.g. fault tolerance
    • G06F11/0703—Error or fault processing not based on redundancy, i.e. by taking additional measures to deal with the error or fault not making use of redundancy in operation, in hardware, or in data representation
    • G06F11/0766—Error or fault reporting or storing
    • G06F11/0778—Dumping, i.e. gathering error/state information after a fault for later diagnosis
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
    • G10L15/00—Speech recognition
    • G10L15/26—Speech to text systems

Definitions

  • Embodiments of the subject matter disclosed herein generally relate to methods and network devices employed in troubleshooting of network nodes, automatically updating a workflow of the troubleshooting using audio analytics and natural-language processing assistance, speech to text, text to speech, and
  • workflows When troubleshooting and recovering network nodes, local technical support personnel relies on fault resolution workflows (henceforth referred to simply as workflows). These workflows typically involve several steps, and some steps have conditional if-then-else scenarios, which branch the original workflow to different sequences of steps. Significant progress has been made relative to the workflows by at least partially automating workflow (see, e.g., U.S. Patent Application Publication Nos. 2007/0100782 and 2006/0233310). Such improvements include a broad range of tools, from use of simple automation scripts to intelligent systems that automatically
  • An example of simple fault resolution workflow by running a shell script is recovery of a website from a backup, with the website being hosted on a network node running the Joomla Content Management System (see, e.g., Joomla's online documentation).
  • An example of a more complex workflow using artificial intelligence is employed in troubleshooting car engine faults (see the article, "Development of an Intelligent Car Engine Fault Troubleshooting System(CEFTS)," by B. I. Ele et al., published in the West African Journal of Industrial & Academic
  • Steps, 1 , 2, 4, 6, 8 in this workflow require manual intervention, i.e., the steps must be manually initiated, and their completion is indicated by an engineer on- site, and steps 3, 5, 7 can be automated (e.g., via scripts).
  • the fault resolution process relies on the expertise of local support personnel, either via local conversation (e.g., with another support engineer on-site) or via conversation with remote so-called "second line" support, for progress toward resolution of the fault.
  • the fault resolution process may be related to certain
  • spatiotemporal conditions which may apply only to the specific geographical location and/or the specific time when the fault occurred.
  • ASR Automated Speech Recognition
  • Updated workflows are versions of workflows augmented with the captured knowledge, and may also include specific spatiotemporal conditions associated with a fault resolution. The updated workflows become immediately available for the workflow's subsequent users.
  • the embodiments improve the troubleshooting process of network nodes by speeding up the validation process of workflow steps, automatically capturing and adding knowledge (or even steps) to the workflow based on captured audio content, i.e., conversations of the engineers involved in a troubleshooting process, and, optionally, adding contextual information to the workflow, for example, specific spatiotemporal conditions, that may speed up resolution of later similar problems in the same context.
  • the method includes capturing audio content while at least one step of the workflow is executed, and causing an update of the workflow based on the captured audio content.
  • a network node having a transceiver, a user interface and a processor.
  • the processor is configured to control the user interface to capture audio content while at least one step of a workflow for troubleshooting a fault is executed, and to cause an update of the workflow based on the captured audio content.
  • a network communication system including a network node and a network device.
  • the network node has a transceiver, a user interface and a network node processor configured to control the user interface to capture audio content while at least one step of a workflow for troubleshooting a fault is executed, and to cause an update of the workflow based on the captured audio content.
  • the network device has a network communication interface, a processor and a memory.
  • the network node processor controls the transceiver to communicate with the processor of the network device via the network communication interface so that the processor of the network device (1 ) to generate the update of the workflow based on knowledge obtained from the captured audio content, (2) to store the update of the workflow in the memory, and/or (3) to perform Automated Speech Recognition, ASR relative to the captured audio content to generate an ASR output, and/or text processing of the ASR output.
  • a network device having a transceiver module, and a control module.
  • the transceiver module is configured to enable communication with other devices in a network.
  • the control module is configured to update a workflow designed for troubleshooting a fault, based on an audio content captured at a network node where at least one step of the workflow is executed and received via the transceiver module.
  • Figure 1 is a sequence diagram of the bootstrapping process
  • Figure 2 exemplarily illustrates a workflow
  • Figure 3 is an example of a workflow description document
  • Figure 4 illustrates a troubleshooting process according to an
  • Figure 5 is flowchart of a method according to an embodiment
  • Figure 6 is block diagram of a device according to an embodiment
  • Figure 7 is an exemplary illustration of a cloud deployment according to an embodiment.
  • Figure 8 is a schematic representation of a network device according to an embodiment.
  • embodiments are described in the context of a wireless network, but may be applied in a cloud network, and employing devices that may pertain to different communication networks.
  • audio content is captured at the troubleshooting site where a fault at a network node is resolved using a workflow.
  • the workflow is then updated based on the captured audio content.
  • components and actors are described below.
  • the system components are logical and can be implemented in the same or different physical nodes.
  • the term "engineers” refers to technical personal who troubleshoot a faulty network node at its site.
  • the network node exhibiting some type of fault that makes troubleshooting necessary has two interfaces: an operation and maintenance (O&M) interface, and a "Media In” interface.
  • O&M operation and maintenance
  • Media In media In
  • the O&M interface allows engineers access to configure the node and includes user authentication functionality to check user credentials (such as username and password, for example). Additionally, this O&M interface may be configured to request a workflow step-by-step while advancing to fault resolution.
  • the O&M interface may be an interactive audio-visual or augmented reality interface; for example, a digital assistant type of expert system that engages in dialogue with the engineer. Thus, engineers do not have to type commands into a terminal as in the case of a command- line interface.
  • the "Media In” interface is used for capturing audio (and potentially also video) on-site.
  • This interface may include an analog-to-digital convertor, the codecs (e.g., MPEG-3 as described , for example, in ISO/IEC 13818-3:1998 on "Information technology - Generic coding of moving pictures and associated audio information -Part 3: Audio, G.71 1 , as described, for example, in ITU-T G.71 1 entitled “Pulse control modulation (PCM) of voice frequencies" from GENERAL ASPECTS OF DIGITAL TRANSMISSION SYSTEMS - Terminal Equipments etc.) and the protocol stack (e.g., Session Initiation Protocol, SIP, as described for example in Request for Comments 3261 of 2002 or H.323 as described for example in ITU-T H.323 of 2009 entitled "Packet-based multimedia systems” from SERIES H: AUDIOVISUAL AND MULTIMEDIA SYSTEMS Infrastructure of audiovisual services - Systems and
  • a Workflow Processor Node serves a dual purpose: it hosts media- and text-processing functions and authorizes engineers and provides the workflows via the O&M interface to the authorized engineers.
  • the Workflow Processor Node may convert captured audio to text, e.g., using Automated Speech Recognition (ASR), and may also extract text from images using optical image recognition. Text and image analysis may then be used to update the workflow or even generate a new workflow.
  • ASR Automated Speech Recognition
  • Engineers' credentials and other relevant metadata may be stored in a user directory, which may be a directory server such as Active Directory, accessed via Lightweight Directory Access Protocol (LDAP).
  • LDAP Lightweight Directory Access Protocol
  • the user directory enables validation of user credentials (e.g., via LDAP "bind" feature), but can also supply user metadata on request.
  • LDAP Lightweight Directory Access Protocol
  • Of particular interest for some embodiments is the nationality of the user, suggesting his/her mother tongue, and other languages spoken, and therefore can be used as input to the media-processing function mentioned above to increase speech recognition accuracy.
  • a Workflow Store stores workflows described in formal language (such as Yet Another Workflow Language - YAWL, or Common Workflow Language - CWL). Spatiotemporal conditions information such as location of the network node(s) repaired by a workflow as well as when these nodes were repaired may be stored in association with the workflow.
  • the engineers initiate the login process by sending a login request to the network node's O&M interface (OMjnterface) at S1 10.
  • the login request may include user-supplied information, i.e., one or more of the engineers' credentials, the node's location and time of the request.
  • the network node 101 forwards the login request to the workflow processor that is physically located on another network device.
  • the workflow processor 102 is illustrated as executing a localization module (Localization_Module) and a workflow management module (WF_mgmt_Module).
  • the localization module is employed in the login process, and the workflow management module in providing the workflow.
  • These modules may be executed on the same hardware or on different hardware.
  • the localization module sends an authorization and user data retrieval request to the user directory at S120.
  • the user directory authorizes the user if the user- supplied credentials match the corresponding information stored in the directory, for example, a ⁇ username, password> tuple matches one already present in the directory.
  • the user directory may provide information regarding user nationality to the localization module at S125. The nationality may later be used to increase speech recognition accuracy.
  • Session information is stored in the localization module at S130.
  • the module sends an acknowledgement indicating successful login to the node's O&M interface at S135.
  • the node's O&M interface provides a login complete indication to the engineers at S140.
  • the get-workflow process begins when engineers request a workflow from the workflow management module at S150.
  • the workflow request may include the time of the request, type of fault and the location, as well as other potentially relevant information.
  • the type of fault depends on the hardware and/or software being troubleshooted, and can be in any appropriate format for example, a form containing a few keywords such as "subscriber database corruption” or "memory overflow", to machine-readable descriptions together with error logs.
  • the workflow request is sent from the O&M interface to the workflow
  • the workflow management module processes the received fault type at
  • the workflow management module maps it to a workflow having a predefined workflow ID.
  • the workflow management module then sends a retrieve workflow request, which may include the workflow ID, to the Workflow Store at S165.
  • the workflow management module receives the workflow at 170, which it may temporarily store at S175, before forwarding it to the network node.
  • the workflow may be sent from the workflow management module to the network node step-by-step, beginning with the first step at 180.
  • the network node presents the received step to the engineers at 190.
  • a workflow consists of a series of steps.
  • the execution of a workflow is done in a stepwise manner (i.e., step-by-step) starting from an initial step, then proceeding through the consecutive steps. Every step is characterized by one or more operational parameters defining actions performed to complete the step.
  • Some of the steps can be automated, for example, via automated shell scripts executed by the network node. Some other steps may need engineers' intervention, in which case, the workflow would only include a description of the actions the engineers are instructed to perform.
  • An example of code specifying such operational parameters for a workflow step is provided below.
  • stepNumber 1
  • Figure 2 exemplarily illustrates a workflow presented to the engineers in visual form. Depending on the type and output of actions described in operational parameters, the engineers on-site may take a different sequence of steps (e.g., the branching in step 2 of Figure 2). Operational parameters (p1 , p2, ...) represent the state of the system being troubleshooted at a given step.
  • the Workflow Store stores workflow description documents such as the one in Figure 3, together with workflow metadata.
  • An exemplary set of records is shown below.
  • JavaScript Object Notation JSON
  • JSON JavaScript Object Notation
  • Mapping of fault type of the workflow request from the O&M interface of the network node can be done using lexicographical matching or another type of matching, e.g., using semantic similarity search.
  • Figure 4 illustrates a troubleshooting process according to an exemplary embodiment.
  • An audio capturing interface (MediaJN) enables capturing conversations between engineers while troubleshooting the fault.
  • This interface may be configured to also capture video and/or images.
  • a Radio Base Station (RBS) of a Radio Access Network (RAN) part of the cellular network may be the faulty network node 401. Troubleshooting a remote RBS is a real issue because it may be hard to reach and/or difficult to troubleshoot due to its complexity.
  • the functionality described in the workflow processor 402, the Workflow Store and the user directory, can reside in one or more physical nodes of the cellular network.
  • the troubleshooting process includes a loop 400 over workflow steps and an inner loop 410 that occurs whenever audio data is captured.
  • Loop 400 includes communications (S415, S425, S435, S445) between engineers, the O&M interface and the workflow management module, for providing a workflow step to the engineers.
  • discussion between engineers is captured as audio data by the network node's audio-capturing interface at S450.
  • the network node's audio- capturing interface forwards the audio data to the media-processing module at S455.
  • the media-processing module may retrieve user data such as a user's nationality from the localization module at S460, S465, before applying a speech recognition algorithm to the user data to obtain conversation text at S470, then forwarded to the text- processing module at S475.
  • the text-processing module converts the conversation text into workflow instructions at S480, and then sends the workflow instructions to the workflow management module.
  • the workflow management module updates the workflow at S490.
  • the updated workflow may optionally be presented to experts for validation as illustrated in box 495.
  • the workflow management module sends the updated workflow to the Workflow Store at S497.
  • FIG. 5 is a flowchart of a method 500 for troubleshooting a fault at a network node using a workflow according to an embodiment.
  • the method which may be performed by the network node in Figure 4, includes capturing audio content while at least one step of the workflow is executed at S510, and causing an update of the workflow based on the captured audio content at S520.
  • the method may be performed by another physical device the engineers brought on-site when the network node is incapacitated to the extent of not being able to perform as expected (i.e., execute the modules illustrated in Figures 1 and 4).
  • the update may be generated on the same physical device that captures the audio content.
  • the method may include supplying spatiotemporal conditions information related to the fault for the update (as, for example, indicated in S1 15 of Figure 1 ).
  • the method may further include triggering Automated Speech Recognition, ASR, relative to the captured audio content to generate an ASR output, and initiating text processing of the ASR output (see, e.g., S455 in Figure 4, which causes S460-S470).
  • ASR Automated Speech Recognition
  • the method further includes
  • the parameter(s) may be retrieved (e.g., from User-Directory) or may be acquired via interactions with the engineers.
  • Another parameter that may be acquired during login is expertise level, which may be a valuable indicator for the text processing extracting knowledge in the form of new workflow instructions from the ASR output.
  • the expertise level may be predefined depending on education level, years of experience in the field, etc.
  • the method may also include acquiring video content and/or images to be used for the update.
  • the device executing the method may then trigger, or execute, pattern recognition relative to the acquired video content and/or images.
  • the method may then include submitting the update of the workflow to be stored (see, e.g., S497 in Figure 4).
  • Figure 6 is a block diagram of a device 600 configured to perform at least some of the above-described methods.
  • Device 600 which is connected to network 612, includes a transceiver represented in Figure 6 as separate receiver 610 and transmitter 620, but may be a single piece of hardware.
  • Device 600 further includes at least one processor 630, a data storage unit 640 and a user interface 635.
  • Processor 630 is configured to control the user interface 635 to capture audio content while at least one step of a workflow for troubleshooting a fault is executed, and to cause an update of the workflow based on the captured audio content.
  • the data storage unit 640 may store executable codes which, when executed by the processor, make the processor perform the methods described in this section.
  • the network devices discussed in this section are logical units and may be placed in a distributed fashion across a network.
  • Figure 7 illustrates a potential deployment in the network of a mobile network operator.
  • the network communication system 700 includes a network node 710 (which may be the device illustrated and described relative to Figure 6) and at least another network device 720.
  • Network device 720 also has a network communication interface, a processor and a memory.
  • Additional clouds of ASR solution vendor and TPR vendor provide an Automated Speech Recognition Media Processing Module and Text Processing Module, respectively.
  • a network device 800 includes a transceiver module 810 configured to enable communication with other devices in a network, and a control module 820 configured to update a workflow designed for troubleshooting a fault, based on audio content captured at a network node where at least one step of the workflow is executed and received via the transceiver module.
  • the transceiver module and the control module are combinations of hardware and software.
  • the embodiments disclosed in this section provide methods and network devices that are able to update a workflow based on captured audio content.
  • the embodiments speed up the update and validation of the workflow.
  • New knowledge or a workflow step is added in a workflow using conversational knowledge from engineers involved in a troubleshooting process, without (or with minimal) post-facto human interaction.
  • the embodiments may also enable adding contextual information in a workflow, for example, specific spatiotemporal conditions, that can later be used when similar problems arise under the same context.

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  • Physics & Mathematics (AREA)
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  • General Physics & Mathematics (AREA)
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  • Health & Medical Sciences (AREA)
  • Biomedical Technology (AREA)
  • Computational Linguistics (AREA)
  • Audiology, Speech & Language Pathology (AREA)
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  • Acoustics & Sound (AREA)
  • Multimedia (AREA)
  • Computer Hardware Design (AREA)
  • Telephonic Communication Services (AREA)

Abstract

Des méthodes et des dispositifs de réseau utilisés dans le diagnostic de défaillance de noeuds de réseau mettent automatiquement à jour un flux de travail de ces derniers, en fonction d'un contenu audio capturé.
PCT/EP2017/059754 2017-04-25 2017-04-25 Méthode et système de diagnostic de défaillance de noeuds de réseau WO2018196953A1 (fr)

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