Classifications

• • H—ELECTRICITY
  • H04—ELECTRIC COMMUNICATION TECHNIQUE
  • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
  • H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
  • H04L41/50—Network service management, e.g. ensuring proper service fulfilment according to agreements
  • H04L41/5003—Managing SLA; Interaction between SLA and QoS
  • H04L41/5009—Determining service level performance parameters or violations of service level contracts, e.g. violations of agreed response time or mean time between failures [MTBF]
• • H—ELECTRICITY
  • H04—ELECTRIC COMMUNICATION TECHNIQUE
  • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
  • H04L43/00—Arrangements for monitoring or testing data switching networks
  • H04L43/08—Monitoring or testing based on specific metrics, e.g. QoS, energy consumption or environmental parameters
  • H04L43/091—Measuring contribution of individual network components to actual service level
• • H—ELECTRICITY
  • H04—ELECTRIC COMMUNICATION TECHNIQUE
  • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
  • H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
  • H04L41/50—Network service management, e.g. ensuring proper service fulfilment according to agreements
  • H04L41/5032—Generating service level reports

Definitions

• the present invention relates to a network management system and a method for identifying and accessing Quality of Service (QoS) issues within a communications network.
• QoS Quality of Service
• QoS Quality of Serv ice
• Modem network operators try to continuously monitor the performance of their communications network with respect to the individual services they offer by using service-centric management systems.
• These service-centric management systems aim to detect changes (drops) in service quality and then the operator tries to find the reason and solution for the QoS degradation to please its customers and to avoid such further drops in service quality.
• SQM service quality metrics
• MOS mean opinion score
• typical factors are for instance the current network load, i.e., the number of parallel active users in the same cell where the service is used, the type of user equipment participating in the service usage transaction, or the current physical radio conditions, which are measured through several factors such as tor instance channel quality information, signal strength, and the congestion situation on the transport links.
• factors and effects which can come from outside of the network operator's domain, but their effect such as a loss on the internet side outside of the operator's core network can be detected as well.
• the first and probably one of the most important issues for the performance monitoring module is to collect the correct performance data from inside the communication network that can later be used to assess the QoS in a reliable way. This means that the correct granularity, the detail level, all relevant data related to factors that can affect the final QoS should be carefully selected and included in the data collection.
• these individual data pieces in a good performance management system should be correlated to each other, in order to put the pieces together to see ail the aspects affecting the performance of the communications network.
• a network management system, a method, a factor scoring system, a factor strength analysis module, and a service performance unit are described in the independent claims of the present application.
• Advantageous embodiments of the network management system, the method, the factor scoring system, the factor strength analysis module, and the service performance unit are described in the dependent claims.
• the present invention provides a network management system for identifying and accessing QoS issues within a communications network.
• the network management system comprises: (a) a service performance unit that (1) captures traffic and performance related data on interfaces in the communications network and at nodes in the communications network, (2) formats the captured traffic and performance related data into individual service usage transactions each including an identification field and a factor, where the factor describes an aspect of the communications network when the corresponding service usage transaction has taken place, and (3) correlates the individual service usage transactions based on the identification fields to create service performance records each including one of the identification fields, multiple factors, and a service quality metric; (b) a service performance database, coupled to the service performance unit, that stores the service performance records; (c) a factor scoring system, coupled to the service performance database, that computes a score for each factor in each service performance record, where the score indicates an influence the corresponding factor has on the corresponding service quality metric; (d) a factor score database, coupled to the factor scoring system, that stores the computed factor scores for each service performance record together with a reference to the corresponding service performance record; and (e) a tactor strength analysis module, coupled to
• the present invention provides a method for identifying and accessing QoS issues within a communications network.
• the method comprises the steps of: (a) creating service performance records by (I) capturing traffic and performance related data on interfaces in the communications network and at nodes in the communications network, (2) formatting the captured traffic and performance related data into individual service usage transactions each including an identification field and a factor, where the factor describes an aspect of the communications network when the corresponding service usage transaction has taken place, and (3) correlating the individual service usage transactions based on the identification fields to create the service performance records each including one of the identification fields, multiple factors, and a service quality metric; (b) storing the service performance records; (c) computing a score for each factor in each service performance record, where the score indicates an influence the corresponding factor has on the corresponding service quality metric; (d) storing the computed factor scores for each service performance record together with a reference to the corresponding service performance record; and (e) aggregating at least a subset of the service performance records together with the corresponding factor scores and using
• the present invention provides a factor scoring system for identifying and accessing QoS issues within a communications network.
• the factor scoring system comprises, (a) a processor; and (b) a non-transitory memory that stores processor-executable instructions wherein the processor interfaces with die non-transitory memory and executes the processor-executable instructions to: (i) retrieve a plur ality of service performance records each including an identification field, multiple factors, and a service quality metric; and (it) compute a score for each factor in each service performance record, where the score indicates an influence the corresponding factor has on the corresponding service qual ity metric .
• the factor scoring system has an advantage in that it can analyze captured traffic and performance related data to obtain reliable knowledge that can be used to increase the QoS and improve the network performance.
• the present invention provides a factor strength analysis module for identifying and accessing QoS issues within a communications network.
• the factor strength analysis module comprises: (a) a processor; and (b) a non-transitory memory that stores processor-executable instructions wherein the processor interfaces with the non-transitory memory and executes the processor-executable instructions to: (i) retrieve a plurality of serv ice performance records each including an identification field, multiple factors, and a service quality metric; (ii) retrieve computed factor scores for each factor in each of the service performance records; (iii) aggregate the service performance records together with the corresponding factor scores and use a rule set to analyze the aggregated records to indicate a cause for a specific service quality degradation detected within the communications network.
• the factor strength analysis module has an advantage in that it can analyze service performance records and computed factors to obtain reliable knowledge that can be used to increase the QoS and improve the network performance.
• die present invention provides a service performance unit for identifying and accessing QoS issues within a communications network.
• the service performance unit comprises: (a) a processor; and (b) a non-transitory memory that stores processor-executable instructions wherein the processor interfaces with the non-transitory memory and executes the processor-executable instructions to: (i) capture traffic and performance related data on interfaces in the communications network and at nodes in the communications network; (ii) format the captured traffic and performance related data into individual service usage transactions each including an identification field and a factor, where the factor describes an aspect of the communications network when the corresponding service usage transaction has taken place; and (iii) correlate die individual service usage transactions based on the identification fields to create service performance records each including one of the identification fields, multiple factors, and a service quality metric.
• the service performance unit has an advantage in that it can capture, format, and correlate traffic and performance related data which can be analyzed to increase the QoS and improve the network performance.
• FIGURE 1 is a block diagram that illustrates a network management system interfacing with the internet and two exemplary mobile data communications networks in accordance with an embodiment of the present invention
• FIGURE 2 is a block diagram that illustrates in greater detail the components of the network management system in accordance with an embodiment of the present invention
• FIGURE 3 is a flowchart that illustrates the steps of an exemplary method in accordance with an embodiment of the present invention
• FIGURE 4 is a block diagram that illustrates an exemplary function of a service performance unit within the network management system in accordance with an embodiment of the present invention.
• FIGURE 5 is a flowchart that depicts an exemplary continuous scoring function of a factor scoring module within the network management system in accordance with an embodiment of the present invention.
• FIGURE 1 there is a block diagram that illustrates a new network management system 100 interfacing with the internet 102 and two exemplary mobile data communications networks 104 and 106 in accordance with an embodiment of the present invention.
• the two exemplary mobile data communication networks .104 and 106 are well known to those skilled in the art hence a detailed description is not provided herein about their various structures and individual components.
• the network management system 100 of the present invention can interface with any number and any type of communication system.
• the network management system 100 functions to identify and access QoS issues within one or both of the exemplary mobile data communications networks 104 and 106.
• the network management system 100 includes a service performance unit 108, a service performance database 11 0, a factor scoring system 11 2, a factor score database 11 4, and a factor strength analysis module 11 6.
• a service performance unit 108 includes a service performance database 11 0, a factor scoring system 11 2, a factor score database 11 4, and a factor strength analysis module 11 6.
• a detailed discussed about the network- management system 100 and each of these components 108, 110, 112, 11 4 and 11 6 is provided below with respect to FIGURES 2-5.
• To aid in describing the network management system 100 and each of the components 108, 110, 11 2, 114 and 116 the following definitions/notations are provided:
• Service usage transaction a logical entity that represents an individual transaction of the user for using a given service of the communications network 104 or 106.
• Service quality metric a real value (denoted by SQM) that represents an objective evaluation of the service quality during a service usage transaction.
• SQM for mobile broadband session is the throughput value in kbit/s.
• Factor a real or nominal value (denoted by F) which is either a concrete measurement value or it is derived from several individual measurements (see FIGURE 4). By its value, a factor describes one particular aspect of the communications network 104 or 106 when the serv ice usage transaction has taken place.
• F a real or nominal value
• Service performance record a collection of factors with their values and the SQM, for a specific service usage transaction. Denoted by (F 1 , F 2 , .. F n , SQM), where m is the total number of factor values applied to the network management system 100.
• Service Performance database 110 a collection of individual service performance records, with a total of n records, where the /-th record is denoted by: h, ⁇ (F i1 , F i2 , F in , SQM i ).
• Empirical probability of SQM A mapping p(SQM;): H->R+ that gives the empirical probability of the occurrence a given SQM value SQM; among the SQM values belonging to a set of service performance records H.
• Similarity function A mapping that returns a subset of service performance records (R 1 ) for which the value of k-th factor k ik is close to the value of F k .
• the network management system 100 includes the service performance unit 108, the service performance database 11 0, the factor scoring system 11 2, the factor score database 114, and the factor strength analysis module 11 6.
• the service performance unit 108 includes a processor 202 and a non-transitory memory 204 that stores processor-executable instructions wherein the processor 202 interfaces with the non-transitory memory 204 and executes the processor-executable instructions to: (1) capture traffic and performance related data on standardized interfaces (e.g., lu-PS, Gn, Gi in the 3G communications network 104 and/or X2, S1 -UP, S1-CP, S11, SGi in the LT E communications network 106) and at certain nodes that provide performance data collection features (e.g., NodeB, RNC, GGSN, SGSN in the 3G communications network 104 and/or eNodeB, MME, S-GW in the LTE communications network 106): (2) format the captured traffic and performance related data into individual service usage transactions each including an identification field and a factor, where the factor describes an aspect of the communications network when the corresponding service usage transaction has taken place, and (3) correlate the individual service usage transactions based on the identification fields to create
• the service performance database 110 is coupled to the service performance unit 108 and functions to store the service performance records 206 (see step 304 in FIGURE 3).
• the factor scoring system 11 2 is coupled to the service performance database 108 and includes a processor 208 and a non-transitory memory 210 that stores processor-executable instructions wherein the processor 208 interfaces with the non-transitory memory 210 and executes the processor-executable instructions to compute a score for each possible influencing network factor for each individual service performance record 206 in the service performance database 110.
• the score indicates the possible influence of the given concrete factor value on the service quality metric of the given service performance record 206 (see step 306 in FIGURE 3).
• the factor score database 114 is coupled to the factor scoring system 11 2 and functions to store the computed factor scores for each service performance record 206 together with a reference to the corresponding service performance record 206 (see step 308 in FIGURE 3).
• the factor strength analysis module 11 6 is coupled to the factor score database 11 4 and the service performance database 110.
• the factor strength analysis module 11 6 includes a processor 212 and a non-transitory memory 214 that stores processor-executable instructions wherein the processor 212 interfaces with the non-transitory memory 214 and executes the processor-executable instructions to aggregate at least a subset of the service performance records 206 (obtained from the service performance database 11 0) together with the corresponding factor scores (obtained from the factor score database 114) and uses a rule set to analyze the aggregated records to indicate a cause for a specific service quality degradation detected within the communications network(s) 104 and 106 (see step 310 in FIGUR E 3).
• the factor strength analysis module 11 6 can aggregate the service performance records 206 and the factor score records on cell basis to identify one or more factors (root cause(s) ) which have an impact on cell performance quality of one or more cells in the communications network's) 104 and 106. Then, the factor strength analysis module 116 can generate alarms for the cell(s) with considerable service quality degradation. In another application, the factor strength analysis module 11 6 can aggregate the service performance records 206 and the factor score records for each user, taking into account ail the different service usage transactions of the same user, and then generate customer reports for a customer care system for users suffering significant service quality degradation. The customer reports can reveal the main reason for the QoS degradation for a given user.
• the network management system 100 may have a single processor and a single non-transitory memory that can be used to implement the various functions of the service performance unit 108, the factor scoring system 112, and the factor strength analysis module 116.
• the individual components 108, 110, 11 2, 11 4, and 11 6 associated with the network management system 100 will be described in detail to help further explain some of the features and advantages of the present invention.
• the service performance unit 108 functions to pre-process the measurements obtained at individual data sources in the communications network(s) 104 and 106 by (i) capturing traffic and performance related data on interfaces in the communications network and at nodes in the communications network; (ii) formatting the captured traffic and performance related data into individual service usage transactions each including an identification field and a factor, where the factor describes an aspect of the communications network when the corresponding service usage transaction has taken place: and (iii) correlating the individual service usage transactions based on the identification fields to create service performance records 206 each including one of the identification fields, multiple factors, and a service quality metric.
• FIGURE 4 there is a block diagram that illustrates one exemplary way that the service performance unit 108 can function to pre-process the measurements obtained at individual data sources in the communications network(s) 104 and 106 in accordance with an embodiment of the present invention.
• the service performance unit 108 captures measurements 402 from different data sources and parses those measurements 402 using a parsing module 404 to form a measurement record 406.
• the measurement records 406 (raw measurement data) are formatted by a formatting unit 408 to form extended measurement records 410 which have an identification field (ID) and a factor (Fl, F2,..).
• a multi-factor correlation module 412 correlates the extended measurement records 410 based on their identification fields and a SQM calcuiation unit 414 computes a SQM for each transaction and this computed SQM is added to the correlated extended measurement records to form service performance records 206.
• the main output from the service performance unit 108 is a set of service performance records 206 which are stored in the service performance database 11 0.
• the factor scoring system 11 2 assigns a numeric value tor each factor of each service performance record 206 and then stores the factor scores together with a reference to the respective service performance record 206 in the factor score database 11 4.
• the factor scoring system 11 2 computes a record "S i1 , S i2 , ... , S in " with a reference to the respective service performance record 206 and stores it within the factor score database 11 4.
• the factor scoring system 112 For computing the S score values for an individual factor of a given service performance record 206, the factor scoring system 112 uses statistical information that can be obtained by analyzing the full set of the given factors and SQM values for all of the individual service performance records 206.
• the factor scoring module 11 2 can implement either a discrete scoring process (rule based scoring process) or a continuous scoring process to assign a numeric value for each factor of each service performance record 206. These two exemplary scoring processes are described in detail next.
• the discrete scoring process assigns a discrete score value S to a given factor of a service performance record 206 which is either 0 or 1.
• the determination of the thresholds T can be based on the statistical properties of the service performance records 206.
• the thresholds T can be set according to a specified percentage of the factor distribution, e.g. if the factor value falls into the upper or lower 10 percent of the factor value distribution then in this case this factor is considered to be an influencing factor.
• Received Signal Code Power RSCP
• RSCP Received Signal Code Power
• the factor scoring module 11 2 would mark the RSCP as an influencing factor.
• the thresholds T can be set according to observed SQM values as a function of the given factor where a threshold T is set in a way to ensure that for the "non-influencing" part of the corresponding factor's range that the average value of the SQM is acceptable.
• the SQM values can be checked as a function of the RSCP values (see above example) where if the RSCP is observed to be above -80 and the average throughput (the SQM value) is above 1.5Mbps, which is acceptable for 3G networks. Then, the factor scoring module 11 2 would set the threshold for RSCP to -80.
• An advantage of die discrete scoring approach is its simplicity, easy implementation, and the possibility to incorporate expert knowledge into the factor scoring module 11 2 when defining or computing the thresholds T for each factor.
• a drawback of the discrete scoring approach lies in the discrete marking where a factor can get only 0 or 1 as a score, and often in the "real world" the transition from good to bad with respect to the factor value is not that discrete even though in many cases the discrete score is applicable.
• FIGURE 5 there is a flowchart that depicts an exemplary continuous scoring process 500 that can be implemented by the factor scoring module 11 2 in accordance with an embodiment of the present invention.
• the factor scoring module 112 obtains the service performance records 206.
• the factor scoring module 112 computes an empirical distribution 506 of one of the SQMs for all of the service performance records 206.
• the factor scoring module 11 2 selects one of the factors (F k , k-1,...m) in the selected service performance record 206.
• the factor scoring module 11 2 computes an empirical distribution 414 of the one SQM for a subset of the service performance records 206 with a similar factor score value for the selected one factor (F i.k - (delta(F i.k ))).
• the factor scoring module 112 computes the factor score 518 (Su) of the selected service performance record 206 by comparing the computed empirical distribution 506 of one of the SQMs ( SQM i ) for all of the service performance records 206 and the computed empirical distribution 514 of the one SQM (SQM,) for the subset of the service performance records 206 with a similar factor score value for the selected one factor.
• the factor scoring module 11 2 determines if all factor scores have been calculated for the selected service performance record 206. If the result of step 520 is no. then the factor scoring module 11 2 returns to the second selecting step 510 to select the next factor in the selected service performance record 206. If the result of step 520 is yes, then the factor scoring module 11 2 at step 522 determines if all the service performance records 206 have been processed. If the result of step 522 is no, then the factor scoring module 112 returns to the first selecting step 508 to select the next service performance record 206. If the result of step 522 is yes, then the factor scoring module 11 2 at step 524 stops since the continuous score value has been assigned to each factor of each service performance record 206.
• the factor score S ik of a given performance record R i is computed by comparing the empirical distribution of the SQM values among a subset of performance records ⁇ (F ik ), - i.e., where the factor value is the same or close to F ik - with the empirical distribution of SQM among all performance records (see step 516).
• S ik will be the function of the two p(SQM,) values p ii and p all computed for the two sets of performance records mentioned above.
• S ik : p ii / p all is a suitable function for meaningful score computation.
• the factor strength analysis module 11 6 is responsible for providing reliable information for determining the reasons for specific QoS degradations detected in the communications network(s) 104 and 106.
• the factor strength analysis module 116 performs this analysis based on the aggregation of the factor scores for a specified subset of the service performance records 206 and a rule set to determine the most influencing factors on the QoS.
• the aggregation function can be e.g. the arithmetic or harmonic mean of the factor scores, and can be performed for each user or for a particular cell or for a given time period (e.g. busy hour). After the aggregation, the factor strength analysis module 116 applies the rule set to pinpoint the important factors.
• a rule can be e.g. that if the aggregated factor score is greater than a predefined value, then the factor is marked as an influencing factor.
• the factor strength analysis module 11 6 uses per-user aggregated records to generate customer reports for a customer care system identifying users suffering significant service quality degradation. The generated reports would identify the main factors having an significant effect on the user perceived service quality.
• the factor strength analysis module 116 uses cell based aggregated records to generate cell based aggregation alarms for cells with considerable service quality degradation which are forwarded to the necessary network management systems. The generated cell based alarms can pinpoint the root cause(s) of the service quality degradation for the particular cell.
• the network management system 300 of the present invention enables automatic selection of performance impacting factors related to performance degradation by utilizing a multifactor analysis and scoring process.
• the measurement preprocessing function brings different forms of performance data into a common format in a way that enables the comparison of factors belonging to one specific service or application enabling unified handling of performance data as one factor vector.
• the factor scoring function analyses the statistical properties of QoS values in relation to the variability found in different factors.
• the factor scoring function enables the weighing of a multitude of performance impacting factors against each other thus providing valuable input to root-cause analysis functions.
• the factor strength analysis function selects and aggregates a large number of weighed and scored factor records and can embody a multitude of performance management and customer care algorithms. As a result, OAM personnel can be provided simple, easy-io-understand reports that locus the attention to those customers, cells and performance degrading factors that have the most impact on the quality of the communication services.

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• 2010
  • 2010-10-11 JP JP2012533728A patent/JP5612696B2/ja not_active Expired - Fee Related
  • 2010-10-11 US US13/501,407 patent/US9015312B2/en not_active Expired - Fee Related
  • 2010-10-11 EP EP10775903.7A patent/EP2489156B1/en not_active Not-in-force
  • 2010-10-11 WO PCT/IB2010/054597 patent/WO2011045736A1/en not_active Ceased

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