CN102098686A - 'Three-layer and one-experience' evaluation model for mobile communication network optimization - Google Patents
'Three-layer and one-experience' evaluation model for mobile communication network optimization Download PDFInfo
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Abstract
The invention provides a 'three-layer and one-experience' evaluation model for mobile communication network optimization, which comprises a 'three-layer and one-experience' evaluation model, a 'three-layer and one-experience' indicator system, a network optimization comprehensive evaluation parameter and calculation method, a constraint threshold value-based network comprehensive optimization indicator configuration algorism and other parts. The 'three-layer and one-experience' model establishes an indicator system key quality indicator (KQI) of a comprehensive measurement network service and a corresponding client experience through the overall investigation of the actual requirement of the full service mobile communication client experience quality, and establishes a uniform network evaluation indicator key performance indicator (KPI) system facing the comprehensive optimization on the basis of three layer key indicators of a comprehensive measurement network element, an access network and a core network. The indicator system key quality indicator (KQI) and the network evaluation indicator key performance indicator (KPI) system are combined into a whole through an associating map to form a complete network optimization and quantification evaluation system. A network optimization comprehensive evaluation parameter which is further designed on such basis can fast evaluate the network comprehensive optimization effect overall. An indicator system constraint threshold value allocation method is capable of effectively solving a contradictory problem among multi targets/multi parameters during the network comprehensive optimization and ensuring the overall efficiency of the network optimization.
Description
Technical field
The present invention relates to the invention belongs to the mobile communication network optimization management domain, by setting up mobile communication network optimization evaluation system model, realize normalized network optimization comprehensive assessment, for improving mobile network property, making full use of Internet resources, provide better and ensure that Network provides foundation.
Technical field, specifically a kind of mobile communication network optimization " three layers of one " assessment models.
Background technology
In mobile communications network, the network optimization is a vital job, be operator how to make full use of Internet resources, for the user better service is provided, for enterprise brings the more main path of benefit, be one of work of being concerned about most of operator.Particularly, 3G popularizes along with moving current professional development, increased newly in a large number such as a series of new problems such as 2G/3G fusion, speech and data full-service operation, data service assurance, switching continuously, network securitys, require network to be optimized, thereby make network optimization work difficulty, more important more from the angle of integrated service, whole structure.
The purpose of the network optimization has two: consider that from operator benefit aspect under conventional network resources, the reasonable disposition network improves utilization rate of equipment and installations and optimizes network running quality; Consider from the user satisfaction aspect, satisfy the requirement of user, improve the key index that call completing rate, cutting off rate etc. directly influence user's subjective feeling, network service reliable more, stable, high-quality is provided by optimization for service quality.Yet the network optimization is the work that technology content is very high, up to the present, though mobile communication network optimization work has obtained certain effect, reaches desirable target far away.A crucial reason that wherein influences network optimization work is exactly the evaluation system model that shortage section emulates the advanced.The evaluation index of diverse network optimization system employing before this and model all are to be confined to specific field or local, for example transmission optimization assessment models, wireless access evaluation index system, network resource evaluation model or the like, these assessment models all provide directive function from an aspect to the network optimization, but one-sidedness that ubiquity is serious and limitation, be difficult to solve the contradiction between the evaluation index of different aspect, what can not provide the network optimization on the whole comprehensively leads control, thereby has had a strong impact on the whole structure of the network optimization.
Specifically, the excellent assessment technology of legacy network exists serious problems to mainly contain the following aspects:
(1) fails to take all factors into consideration influencing each other between the heterogeneous networks aspect
Traditional network optimization is by the data acquisition means, in conjunction with industry standard element individuality or local attribute in the network is assessed audit, ignored between the of paramount importance network component influence each other and to the importance of network synthesis operation.And in fact, most of network defective and hidden danger are not to be caused by isolated element.
(2) can not reflect customer experience comprehensively
The subjective feeling of the service feature that the terminal use provides the mobile network more and more becomes the critical elements of the network optimization, and how assesses user Quality of experience and being mapped in the network optimization, business support and the service also becomes the focus that the boundary already pays close attention to.Quality index system in the past mainly is confined to equipment and specialized subsystem category, less reflection the whole network business is running quality and the actual use of client perception end to end, and existing significantly inconsistent or reverse correlation between the actual impression of user, is not fairly obvious by improving the legacy network quality evaluation index effect of improving customer satisfaction.
(3) needs of incompatibility data service fast development
Along with the development of new technologies such as 3G mobile communication data business and mobile Internet, the proportion that the user accounts for total complaint to the complaint of data business is also in continuous increase, and the professional appraisement system of traditional branch is existing service environment of incompatibility and network environment.Characteristics such as the time bursts that kind is many, variation is fast because data service has, network elements that relate to are many, user behavior is complicated and showing, space clustering go the assessment data business network to be difficult to reach gratifying result with traditional evaluation system.
In sum, existing network optimization evaluation system fails to take all factors into consideration on the whole the mobile communications network characteristic, fail fully to reflect the quality of its bearer service, fail truly to reflect the gap between current business/network quality and user expectation, so must the new network optimization technology of innovative development be solved.
Summary of the invention
Technical assignment of the present invention is business characteristic, network performance and the customer experience quality requirement of third-generation mobile communication during at 3G, solves the deficiencies in the prior art, and a kind of mobile communication network optimization " three layers of one " assessment models is provided.
" three layers of one " model is, actual requirement by comprehensive investigation full-service client mobile communication Quality of experience, set up the index system KQI that comprehensive measurement Network and respective client are experienced, simultaneously at the comprehensive measurement network element, Access Network, on the basis of three layer key indexs of core net, set up unified network evaluation index KPI system towards complex optimum, the two is combined into an integral body by relationship maps, formed complete network optimization quantitative evaluation system, the further on this basis network optimization comprehensive assessment parameter that designs, rapid evaluation network synthesis is optimized effect on the whole.
The present invention realizes that in the following manner content comprises 1) " three layers of one " assessment models index system; 2) refer to the comprehensive network optimization evaluation index and the computational methods of the system of protecting based on " three layers of one "; 3) index optimization based on index constraint threshold value distributes; Wherein,
1) index system of " three layers of one " assessment models, be meant that user experience quality index system KQI comprises: be divided into four and express dimension: network availability, service availability, service guarantee, Information Security, three network levels of three layers of core layer that is meant network performance index system KPI correspondence, Access Layer, resource layer link together by relationship maps between KQI and the KPI; In the KPI system, increased the evaluation index at network synthesis optimization effect such as equilibrium degree, life-span nargin, utilance and cost index.These newly-increased indexs have profoundly reflected the feature of full-service mobile radio communication complex optimum assessment relatively comprehensively, and specific definition is as follows:
Initiation of services: the agility and the validity of expression initiation of services, can read to measure by initiation of services time and success rate;
Professional delivery quality: fluency and integrality that the expression business tine transmits, can determine by business tine result's correctness and subjective assessment grade;
Service stability: professional consistency that provides of expression and business provide the continuity of mass effect in the process, have embodied the hold facility of quality of service, not the variation that can obviously discover along with the time generation;
Mobile continuity: the expression professional consistency that provides spatially, embodied quality of service and along with the migration of space or scene obvious variation do not taken place;
Open time delay: professional formally open the time that provides from applying for;
Safeguard time delay: the normal time of automatic reparation occurs from fault, or occur accusing the time that reparation is finished from the Shen behind the professional obstacle;
Service success rate: refer to the success rate of maintenance service, comprise and once keep in repair probability of successful and the normal characteristic of using of maintenance back maintenance;
Service support ability: refer to ensure professional normal the use and offer technological guidance's ability of client, can run into professional obstacle (non-network system causes itself) by the statistics client and succeed and support the probability of solution;
Anti-attack ability: when referring to that IPization networking such as 3G provides mobile Internet business, prevent and treat the ability of hazard factor such as various viruses, wooden horse, hacker, available harm ability of discovery and kill ability and indicate;
Fragility: refer to the defective and the bottleneck that may cause business (particularly data service) normally not move that exist in the network.Traditional telecommunications network generally all has very strong robustness, but after IPization, after particularly leading directly to external the Internet, the one side of its fragility has just shown especially out.The fragility of mobile radio communication can adopt the method for general the Internet to carry out test analysis;
Threaten index: refer to threaten the various hazards of the normal operation of Network, constitute by directly related network attack source number and threat level thereof.Can determine by the intimidation estimating method analysis of general the Internet;
Equilibrium degree: refer to homogeneous network resource, the network facilities distributing homogeneity about space, traffic load, client.Generally can test and assess about the relative distribution proportion of Network Access Point and network link according to resource;
Life-span nargin: refer to the surplus of the reliable life of the network equipment or subnet, general requirement can not be lower than the access period of same category of device and open the preventive maintenance time sum;
Cost index: what refer to device resource carries out normalization expense index after the conversion of equal value according to a certain normative reference;
Do not limit special KQI and KPI mapping relations in this model, when using this system model, can be with reference to ripe mapping method such as International Telecommunication Association (ITU-T), and determine concrete incidence relation between KQI and the KPI according to real network topological sum Network structure; Model is not specified the concrete rated value of every index yet, so that guarantee the versatility to the heterogeneous networks scene, determines the concrete standard of every index according to user service requirement and network planning parameter in the practical application, and then judges the performance condition of network;
2) refer to the comprehensive network optimization evaluation index and the calculating of the system of protecting based on " three layers of one "
Three layers of one " on the assessment models index system basis; further the define grid resources performance is than indexs such as, network network resource overall price/performance ratio, network in general optimization indexes; these indexs are used for measuring the general effect of the network optimization, and can calculate fast based on " three layers of one " model; Comprise following content:
(1) Internet resources efficiency ratio Pr=performance index/resource quantity
Performance index mainly optional " covering index ", " capacity ", " inserting or connect into power " " stability " herein, or the weighted mean of individual Key Performance Indicator; Resource quantity refers to the equipment equivalent amount that drops into comprise equivalent port number, equivalent bandwidth, equivalent throughput in the network optimization process; Utilize this parameter can fairly obvious ground the utilization of resources effect of comparing cell before and after optimizing;
(2) Internet resources cost performance Pc=performance index/resources costs
Performance index mainly optional " covering index ", " capacity ", " inserting or connect into power " " stability " herein, or the weighted mean of individual Key Performance Indicator; Resources costs refers to the every resource total cost corresponding with the impact of performance that drop in the network optimization process; By the variation of this parameter before and after the comparing cell optimization, can directly demonstrate the benefit in performance of the network optimization;
(3) network in general is optimized index E I
This index mainly is the curstomer-oriented Quality of experience, by the weighted average to each index among the KQI in the index system, reflects the raising situation of the network optimization for customer satisfaction.Specific algorithm is as follows:
EI＝∑(α
i?I
i)n％
α in the formula
iBe KQI index I
iWeight coefficient, n refers to respectively that for participating in the index sum of assessment weight coefficient relatively can adopt the expert evaluation method to determine, the expert evaluation method is by expert group each index importance to be provided weighted value, and client's participation of proper proportion generally will be arranged in the expert group;
3) index optimization based on index constraint threshold value distributes
In network optimization process, often there is the contradiction between the Different Optimization target, comprise resource utilization and call completing rate, equilibrium degree and safeguard time delay, throughput and congested, can influence or reduce other indexs when improving certain index, particularly the index that ought optimize more for a long time, this association influence meeting intractable, employing constraint threshold value qualification method can solve the index harmony assignment problem in the complex optimum scheme effectively, and detailed process is as follows:
(1) definite threshold value of respectively optimizing index
By statistics, and, can determine the minimum and the highest limit value of each index quickly in conjunction with expert assessment and evaluation to each desired value of network before optimizing.Because each index module of KQI constitutes compatible system in " three layers of one " model---do not have usually between each index conflicting, so emphasis KPI index;
(2) select interrelated, interactive crucial KPI index, hereinafter referred to as characteristic index and threshold value thereof;
(3) divide characteristic index according to the mapping relations of KQI-KPI, the characteristic index that belongs to a PQI mapping territory together is drawn one group, and the characteristic index that does not belong to same mapping territory is drawn different groups;
(4) characteristic index in each group is provided with corresponding threshold value;
(5) in guaranteeing same group, optimize and revise non-characteristic index among the KPI under the prerequisite of each characteristic index threshold value;
(6) to each group traversal execution in step (5);
(7) each characteristic index is optimized adjustment,, in " three layers of one " assessment models index system, generally is no more than 4, in each optimizing process so this step can comparatively fast finish because the extraordinary index that occurs can be not a lot; Adopt the constrained optimization method, at least one all over reaching more satisfactory effect, finish constrained optimization after, can further adopt " three layers of one " model to carry out analysis and assessment.
Excellent effect of the present invention is: assessment models that the present invention provides and method, with network service effectiveness and the unified consideration of network performance index, a series of defectives of traditional optimization appraisal procedure have been overcome, provided the complete modeling method that is suitable for the assessment of full-service mobile communication network optimization of a cover, network optimization effect is carried out the comprehensive assessment that curstomer-oriented is experienced, embody the subjective feeling of the service feature that the terminal use provides the mobile network more fully, thereby can effectively instruct the strategy and the direction of the network optimization, significantly improve the effect of the network optimization, improve customer satisfaction.Particularly for the global optimization and the assessment of the network optimization, network index constrained optimization strategy that provides and complex optimum evaluation index have important use for the optimization of large complicated networks such as 3G and are worth.
Description of drawings
Fig. 1 is a mobile communications network element of service model structure schematic diagram;
Fig. 2 is " three layers of one " network optimization evaluation index model general structure schematic diagram.
Embodiment
This model is by every index of comprehensive measurement network element, Access Network, three aspects of core net, set up a cover whole network layer assessment KPI (Key Performance Indicator), further Network and corresponding customer experience index KQI (Key Quality Indicator) are organically combined on this basis, formed the quantitative evaluation system of complete " three network layers+one experiences ".
For rapid evaluation network performance and optimize effect on the whole better, the present invention has further designed a series of comprehensive assessment indexs and computational methods thereof, as complex optimum potency ratio (impact of performance-Resources Consumption ratio), customer experience quality improvement index etc., utilize these indexs, can be fast the whole structure of the supervisory network optimization directly.
1) " three layers of one " network optimization comprehensive assessment index model
From 3G, mobile communications network has entered the full-service operation epoch, is characterized in that network and professional relative separation, voice service and data service comprehensively provide, the customer experience quality becomes important operation key element.The present invention based on network and business model as shown in Figure 1.
Wherein the Network layer has comprised speech business, data service, and the various value-added services of deriving from; Network layer comprises device resource, access, three sublayers of core; Operation comprises contents such as business service, webmaster, information security, charging, customer service with maintenance; Customer experience relates to each aspect, and the most direct is operation layer, Access Layer and customer service.
From the angle of customer experience, network and quality of service are mainly reflected in aspects such as network accessibility, service availability, professional service quality, problem and Breakdown Maintenance efficient.The present invention is based on the client to network and professional use perception, decomposite the series of key techniques requirement from top to bottom, in conjunction with network and professional each professional the key technical indexes, Synthetical Optimization goes out " three layers of one " network optimization evaluation index model shown in Fig. 2, table 1.
In the model general structure, " one " is meant user experience quality index system KQI (be divided into four and express dimension: network availability, service availability, service guarantee, Information Security), and three layers are meant corresponding three network levels (core layer, Access Layer, resource layer) of network performance index system KPI.Link together by relationship maps between KQI and the KPI.
Following table is the index system in " three layers of one " network optimization assessment models
In this model, be designed to four-dimensional structure based on the Network KQI of customer experience---network availability, service availability, service guarantee, Information Security, and being designed to three layers of index arranged side by side, associated network KPI unifies structure.Wherein the four dimensions module of KQI and mutual independence are interrelated again, and never ipsilateral has embodied and the closely-related network service quality index request of customer experience; KPI has mainly expressed the service-oriented quality of whole network layer and the key technical index of management quality, though the requirement that these indexs are had nothing in common with each other for network core layer, Access Layer and resource layer, the pointer type basically identical.KQI is the unified tolerance of Network and customer experience, can simplify the related complexity between customer service and the Network greatly, helps the efficient map analysis between KQI and the KPI.
In the KQI system, service availability, service guarantee and mobile comm message safety evaluation index have been proposed innovatively; In the KPI system, increased the evaluation index at network synthesis optimization effect such as equilibrium degree, life-span nargin, utilance and cost index innovatively.These newly-increased indexs have profoundly reflected the feature of full-service mobile radio communication complex optimum assessment relatively comprehensively, and specific definition is as follows:
Initiation of services: the agility and the validity of expression initiation of services, can read to measure by initiation of services time and success rate;
Professional delivery quality: fluency and integrality that the expression business tine transmits, can determine by business tine result's correctness and subjective assessment grade;
Service stability: professional consistency that provides of expression and business provide the continuity of mass effect in the process, have embodied the hold facility of quality of service, not the variation that can obviously discover along with the time generation;
Mobile continuity: the expression professional consistency that provides spatially, embodied quality of service and along with the migration of space or scene obvious variation do not taken place;
Open time delay: professional formally open the time that provides from applying for;
Safeguard time delay: the normal time of automatic reparation occurs from fault, or occur accusing the time that reparation is finished from the Shen behind the professional obstacle;
Service success rate: refer to the success rate of maintenance service, comprise and once keep in repair probability of successful and the normal characteristic of using of maintenance back maintenance;
Service support ability: refer to ensure professional normal the use and offer technological guidance's ability of client, can run into professional obstacle (non-network system causes itself) by the statistics client and succeed and support the probability of solution;
Anti-attack ability: when referring to that IPization networking such as 3G provides mobile Internet business, prevent and treat the ability of hazard factor such as various viruses, wooden horse, hacker, available harm ability of discovery and kill ability and indicate;
Fragility: refer to the defective and the bottleneck that may cause business (particularly data service) normally not move that exist in the network.Traditional telecommunications network generally all has very strong robustness, but after IPization, after particularly leading directly to external the Internet, the one side of its fragility has just shown especially out.The fragility of mobile radio communication can adopt the method for general the Internet to carry out test analysis;
Threaten index: refer to threaten the various hazards of the normal operation of Network, constitute by directly related network attack source number and threat level thereof.Can determine by the intimidation estimating method analysis of general the Internet;
Equilibrium degree: refer to homogeneous network resource, the network facilities distributing homogeneity about space, traffic load, client.Generally can test and assess about the relative distribution proportion of Network Access Point and network link according to resource;
Life-span nargin: refer to the surplus of the reliable life of the network equipment or subnet, general requirement can not be lower than the access period of same category of device and open the preventive maintenance time sum;
Cost index: what refer to device resource carries out normalization expense index after the conversion of equal value according to a certain normative reference.
Do not limit special KQI and KPI mapping relations in this model, when using this system model, can be with reference to ripe mapping method such as International Telecommunication Association (ITU-T), and determine concrete incidence relation between KQI and the KPI according to real network topological sum Network structure; Model is not specified the concrete rated value of every index yet, so that guarantee the versatility to the heterogeneous networks scene, can determine the concrete standard of every index according to user service requirement and network planning parameter in the practical application, and then judge the performance condition of network.
2) refer to the comprehensive network optimization evaluation index and the calculating of the system of protecting based on " three layers of one "
On " three layers of one " index system model basis, further define grid resources performance ratio, network network resource overall price/performance ratio, network in general are optimized indexs such as index, these indexs can be used to measure the general effect of the network optimization, and can calculate fast based on " three layers of one " model.
(1) Internet resources efficiency ratio Pr (Pr:Performance to resource)=performance index/resource quantity
Performance index mainly optional " covering index ", " capacity ", " inserting or connect into power " " stability " etc. herein, the also weighted mean of a Key Performance Indicator.Resource quantity refers to the equipment equivalent amount that drops in the network optimization process, as equivalent port number, equivalent bandwidth, equivalent throughput etc.Utilize this parameter can fairly obvious ground the utilization of resources effect of comparing cell before and after optimizing.
(2) Internet resources cost performance Pc (Pc:Performance to cost)=performance index/resources costs
Performance index mainly optional " covering index ", " capacity ", " inserting or connect into power " " stability " etc. herein, the also weighted mean of a Key Performance Indicator.Resources costs refers to the every resource total cost corresponding with the impact of performance that drop in the network optimization process.By the variation of this parameter before and after the comparing cell optimization, can directly demonstrate the benefit in performance of the network optimization.
(3) network in general is optimized index E I (Effect of Integrated optimization)
This index mainly is the curstomer-oriented Quality of experience, by the weighted average to each index among the KQI in the index system, reflects the raising situation of the network optimization for customer satisfaction.Specific algorithm is as follows:
EI＝∑(α
i?I
i)n％
α in the formula
iBe KQI index I
iWeight coefficient, n is for participating in the index sum of assessment.Refer to that respectively weight coefficient relatively can adopt the expert evaluation method to determine.The expert evaluation method is by expert group each index importance to be provided weighted value.Generally to there be the client of proper proportion to participate in the expert group.
3) index optimization based on index constraint threshold value distributes
In network optimization process, often there is the contradiction between the Different Optimization target, such as resource utilization and call completing rate, equilibrium degree and safeguard time delay, throughput and congested or the like, can influence or reduce other indexs when improving certain index, particularly when the index of optimizing more for a long time, this related influence can intractable.The present invention adopts the constraint threshold value to limit method can solve index harmony assignment problem in the complex optimum scheme effectively.Detailed process is as follows:
(1) definite threshold value of respectively optimizing index
By statistics, and, can determine the minimum and the highest limit value of each index quickly in conjunction with expert assessment and evaluation to each desired value of network before optimizing.Because each index module of KQI constitutes compatible system in " three layers of one " model---do not have usually between each index conflicting, so emphasis KPI index;
(2) select interrelated, interactive crucial KPI index (being called characteristic index) and threshold value thereof;
(3) divide characteristic index according to the mapping relations of KQI-KPI, the characteristic index that belongs to a PQI mapping territory together is drawn one group, and the characteristic index that does not belong to same mapping territory is drawn different groups;
(4) characteristic index in each group is provided with corresponding threshold value;
(5) in guaranteeing same group, optimize and revise non-characteristic index among the KPI under the prerequisite of each characteristic index threshold value;
(6) to each group traversal execution in step (5);
(7) each characteristic index is optimized adjustment.Because the extraordinary index that occurs in each optimizing process can a lot (generally not be no more than 4) in " three layers of one " model, so this step can comparatively fast finish.
Adopt this constrained optimization method, can repeat, generally that is optimized by two times, can reach more satisfactory effect.After finishing constrained optimization, can further adopt " three layers of one " model to carry out analysis and assessment.
Embodiment
" three layers of one " model evaluation method both can be used for network optimization recruitment evaluation afterwards, also can be used for network optimization scheme evaluation.Every KQI index can be measured and obtain by customer survey statistics, network monitoring and O﹠M record statistics, specialty; Every KPI basic index can pass through methods such as equipment and technology data, network planning data, O﹠M record statistics, specialty measurement and obtain.After obtaining the basic index data, can utilize the index system model that provides among the present invention to compare analysis, and can further calculate several the complex optimum evaluate parameters that the present invention provides.
When being used for network optimization scheme evaluation, majority parameters is as above-mentioned, but relates to the index of optimization aim, adopt the optimization aim desired value.
" three layers of one " model is, actual requirement by comprehensive investigation full-service client mobile communication Quality of experience, set up the index system KQI that comprehensive measurement Network and respective client are experienced, simultaneously at the comprehensive measurement network element, Access Network, on the basis of three layer key indexs of core net, set up unified network evaluation index KPI system towards complex optimum, the two is combined into an integral body by relationship maps, formed complete network optimization quantitative evaluation system, the further on this basis network optimization comprehensive assessment parameter that designs, rapid evaluation network synthesis is optimized effect on the whole.
The invention solves legacy network and optimize a series of problems that appraisal procedure exists, can fully reflect the quality of Network, truly reflect gap between network servicequality and customer experience quality, carry out complex optimum assessment etc. on the whole, for the complex optimum recruitment evaluation of full-service mobile communication provides a kind of comprehensive high-efficiency method, be particularly suitable for the optimization assessment of 3G mobile communication.
Claims (1)
1. mobile communication network optimization " three layers of one " assessment models is characterized in that content comprises 1) " three layers of one " assessment models index system; 2) refer to the comprehensive network optimization evaluation index and the calculating of the system of protecting based on " three layers of one "
Method;3) index optimization based on index constraint threshold value distributes; Wherein,
1) index system of " three layers of one " assessment models, be meant that user experience quality index system KQI comprises: be divided into four and express dimension: network availability, service availability, service guarantee, Information Security, three network levels of three layers of core layer that is meant network performance index system KPI correspondence, Access Layer, resource layer link together by relationship maps between KQI and the KPI; In the KPI system, increased the evaluation index at network synthesis optimization effect such as equilibrium degree, life-span nargin, utilance and cost index, these newly-increased indexs have profoundly reflected the feature of full-service mobile radio communication complex optimum assessment relatively comprehensively, and specific definition is as follows:
Initiation of services: the agility and the validity of expression initiation of services, can read to measure by initiation of services time and success rate;
Professional delivery quality: fluency and integrality that the expression business tine transmits, can determine by business tine result's correctness and subjective assessment grade;
Service stability: professional consistency that provides of expression and business provide the continuity of mass effect in the process, have embodied the hold facility of quality of service, not the variation that can obviously discover along with the time generation;
Mobile continuity: the expression professional consistency that provides spatially, embodied quality of service and along with the migration of space or scene obvious variation do not taken place;
Open time delay: professional formally open the time that provides from applying for;
Safeguard time delay: the normal time of automatic reparation occurs from fault, or occur accusing the time that reparation is finished from the Shen behind the professional obstacle;
Service success rate: refer to the success rate of maintenance service, comprise and once keep in repair probability of successful and the normal characteristic of using of maintenance back maintenance;
The service support ability: refer to ensure professional normal the use and offer technological guidance's ability of client, can run into professional obstacle by the statistics client, non-network system itself causes and succeeds and support the probability that solves;
Anti-attack ability: when referring to that IPization networking such as 3G provides mobile Internet business, prevent and treat the ability of hazard factor such as various viruses, wooden horse, hacker, available harm ability of discovery and kill ability and indicate;
Fragility: what refer to exist in the network may cause business, the data service defective and the bottleneck that can not normally move particularly, traditional telecommunications network generally all has very strong robustness, but after IPization, after particularly leading directly to external the Internet, the one side of its fragility has just shown especially out, and the fragility of mobile radio communication can adopt the method for general the Internet to carry out test analysis;
Threaten index: refer to threaten the various hazards of the normal operation of Network, constitute, determine by the intimidation estimating method analysis of general the Internet by directly related network attack source number and threat level thereof;
Equilibrium degree: refer to homogeneous network resource, the network facilities distributing homogeneity, generally can test and assess about the relative distribution proportion of Network Access Point and network link according to resource about space, traffic load, client;
Life-span nargin: refer to the surplus of the reliable life of the network equipment or subnet, general requirement can not be lower than the access period of same category of device and open the preventive maintenance time sum;
Cost index: what refer to device resource carries out normalization expense index after the conversion of equal value according to a certain normative reference;
Do not limit special KQI and KPI mapping relations in this model, when using this system model, can be with reference to ripe mapping method such as International Telecommunication Association (ITU-T), and determine concrete incidence relation between KQI and the KPI according to real network topological sum Network structure; Model is not specified the concrete rated value of every index yet, so that guarantee the versatility to the heterogeneous networks scene, determines the concrete standard of every index according to user service requirement and network planning parameter in the practical application, and then judges the performance condition of network;
2) refer to the comprehensive network optimization evaluation index and the calculating of the system of protecting based on " three layers of one "
Three layers of one " on the assessment models index system basis; further the define grid resources performance is than indexs such as, network network resource overall price/performance ratio, network in general optimization indexes; these indexs are used for measuring the general effect of the network optimization, and can calculate fast based on " three layers of one " model; Comprise following content:
(1) Internet resources efficiency ratio Pr=performance index/resource quantity
Performance index mainly optional " covering index ", " capacity ", " inserting or connect into power " " stability " herein, or the weighted mean of individual Key Performance Indicator; Resource quantity refers to the equipment equivalent amount that drops into comprise equivalent port number, equivalent bandwidth, equivalent throughput in the network optimization process; Utilize this parameter can fairly obvious ground the utilization of resources effect of comparing cell before and after optimizing;
(2) Internet resources cost performance Pc=performance index/resources costs
Performance index mainly optional " covering index ", " capacity ", " inserting or connect into power " " stability " herein, or the weighted mean of individual Key Performance Indicator; Resources costs refers to the every resource total cost corresponding with the impact of performance that drop in the network optimization process; By the variation of this parameter before and after the comparing cell optimization, can directly demonstrate the benefit in performance of the network optimization;
(3) network in general is optimized index E I
This index mainly is the curstomer-oriented Quality of experience, by the weighted average to each index among the KQI in the index system, reflects the raising situation of the network optimization for customer satisfaction, and specific algorithm is as follows:
EI＝∑(α
i?I
i)n％
α in the formula
iBe KQI index I
iWeight coefficient, n refers to respectively that for participating in the index sum of assessment weight coefficient relatively can adopt the expert evaluation method to determine, the expert evaluation method is by expert group each index importance to be provided weighted value, and client's participation of proper proportion generally will be arranged in the expert group;
3) index optimization based on index constraint threshold value distributes
In network optimization process, often there is the contradiction between the Different Optimization target, comprise resource utilization and call completing rate, equilibrium degree and safeguard time delay, throughput and congested, can influence or reduce other indexs when improving certain index, particularly the index that ought optimize more for a long time, this association influence meeting intractable, employing constraint threshold value qualification method can solve the index harmony assignment problem in the complex optimum scheme effectively, and detailed process is as follows:
(1) definite threshold value of respectively optimizing index
By statistics to each desired value of network before optimizing, and in conjunction with expert assessment and evaluation, determine the minimum and the highest limit value of each index quickly, because KQI constitutes compatible system by each index module in " three layers of one " model, do not have between each index conflicting, so emphasis is the KPI index;
(2) select interrelated, interactive crucial KPI index, hereinafter referred to as characteristic index and threshold value thereof;
(3) divide characteristic index according to the mapping relations of KQI-KPI, the characteristic index that belongs to a PQI mapping territory together is drawn one group, and the characteristic index that does not belong to same mapping territory is drawn different groups;
(4) characteristic index in each group is provided with corresponding threshold value;
(5) in guaranteeing same group, optimize and revise non-characteristic index among the KPI under the prerequisite of each characteristic index threshold value;
(6) to each group traversal execution in step (5);
(7) each characteristic index is optimized adjustment,, in " three layers of one " assessment models index system, generally is no more than 4, in each optimizing process so this step can comparatively fast finish because the extraordinary index that occurs can be not a lot; Adopt the constrained optimization method, at least one all over reaching more satisfactory effect, finish constrained optimization after, can further adopt " three layers of one " model to carry out analysis and assessment.
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
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| US11463318B2 (en) * | 2017-11-28 | 2022-10-04 | Hewlett Packard Enterprise Development Lp | Efficiency indexes |
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Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101072121A (en) * | 2007-05-31 | 2007-11-14 | 中国移动通信集团广东有限公司 | System and method for estimating network optimized engineering requirements |
| CN101217770A (en) * | 2008-01-18 | 2008-07-09 | 中国移动通信集团福建有限公司 | An automatic evaluating and analyzing device and method for mobile communication network quality |
| US20100195496A1 (en) * | 2007-03-29 | 2010-08-05 | Holm-Oeste Gerd | Method And Apparatus For Evaluating Services In Communication Networks |
-
2011
- 2011-01-17 CN CN2011100089312A patent/CN102098686A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20100195496A1 (en) * | 2007-03-29 | 2010-08-05 | Holm-Oeste Gerd | Method And Apparatus For Evaluating Services In Communication Networks |
| CN101072121A (en) * | 2007-05-31 | 2007-11-14 | 中国移动通信集团广东有限公司 | System and method for estimating network optimized engineering requirements |
| CN101217770A (en) * | 2008-01-18 | 2008-07-09 | 中国移动通信集团福建有限公司 | An automatic evaluating and analyzing device and method for mobile communication network quality |
Non-Patent Citations (1)
| Title |
|---|
| 杨肖: "下一代电信网安全态势评估系统设计", 《信息科技辑》, no. 11, 15 November 2008 (2008-11-15), pages 136 - 141 * |
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