FR2895614A1 - Network functional entity encoding method for telecommunication network, involves encoding paired regrouping of two network entities into single current functional entity based on regrouping relevance threshold and regrouping gain values - Google Patents

Network functional entity encoding method for telecommunication network, involves encoding paired regrouping of two network entities into single current functional entity based on regrouping relevance threshold and regrouping gain values Download PDF

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FR2895614A1
FR2895614A1 FR0513162A FR0513162A FR2895614A1 FR 2895614 A1 FR2895614 A1 FR 2895614A1 FR 0513162 A FR0513162 A FR 0513162A FR 0513162 A FR0513162 A FR 0513162A FR 2895614 A1 FR2895614 A1 FR 2895614A1
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network
grouping
functional entity
functional
functions
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Jacques Simonin
Mohamed Fouz Menai
Francis Alizon
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France Telecom SA
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France Telecom SA
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    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L41/00Arrangements for maintenance or administration or management of packet switching networks
    • H04L41/02Arrangements for maintenance or administration or management of packet switching networks involving integration or standardization
    • H04L41/0233Arrangements for maintenance or administration or management of packet switching networks involving integration or standardization using object oriented techniques, e.g. common object request broker architecture [CORBA] for representation of network management data
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F8/00Arrangements for software engineering
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L41/00Arrangements for maintenance or administration or management of packet switching networks
    • H04L41/14Arrangements for maintenance or administration or management of packet switching networks involving network analysis or design, e.g. simulation, network model or planning
    • H04L41/145Arrangements for maintenance or administration or management of packet switching networks involving network analysis or design, e.g. simulation, network model or planning involving simulating, designing, planning or modelling of a network

Abstract

The method involves representing signal exchanges in the form of a modeling sequence diagram, where the signal exchanges are made between network functions. Each function is encoded according to a unary functional network entity. A calculation is performed repeatedly based on a scenario of a business relevance indicator for regrouping the functional entities into a same functional network entity. Paired regrouping of two functional network entities into a single current functional entity is encoded according to a regrouping relevance threshold value and a regrouping gain value. The regrouping gain value is equal to a relation of a value of the business relevance indicator of the paired regrouping of the network entities and the regrouping relevance threshold value. Independent claims are also included for the following: (1) a tool for modeling a telecommunication network and comprising a functional entity encoding module permitting the implementation of a network functional entity encoding method (2) a computer program product stored in a storage medium and executable by a computer or by a telecommunication network modeling tool.

Description

METHOD FOR ENCODING FUNCTIONAL ENTITIES NETWORK FROM FUNCTIONS

  The invention relates to a method for defining and coding network functional entities from network functions of a telecommunications network and a corresponding modeling tool making it possible to optimize, in particular, the volume of the telecommunications network. data flows exchanged on this network necessary to optimize the performance of all the network functions and their maintenance. The network functions may for example represent a distribution service for audiovisual content on this network. The industrial implementation of telecommunications networks is of crucial importance because of the exponential increase in the exchange of data of all kinds on the latter. For the implementation of modern telecommunication networks, those of the present and those of the future, to ensure their maintenance, and, of course, their evolution in terms of capacity and / or new functionalities, it has appeared essential to ensure the definition. and coherently encoding the network functional entities, due to their involvement in the optimal implementation of the network functionalities and network services ensuring the operation of the telecommunications networks.

  The architecture of the network functions of a telecommunications network can be modeled according to an oriented graph consisting of two types of nodes: the functions; reference points.

  In the context of modeling from a commercially available modeling language, such as the UML (Unified Modeling Language), for a presentation of the UML language, reference may be made to the G. Booch, J. Rumbaugh and I. Jacobson entitled "The Unified Modeling Language User Guide", Addison-Wesley, 1999) in its UML 2.0 version, the aforementioned functions and reference points are respectively components and functions. connectors. In general terms, the functions constitute logical and / or arithmetic processing nodes capable of acting on the data, that is to say, producing, recording or using them. They thus have interfaces enabling the intrinsic processing procedures to be activated or to activate the procedures for processing other functions, thanks to the operations offered respectively to the operations required, in the sense of the aforementioned UML 2.0 language. Each instance of a function defines a link between the function and the reference points associated with it. The link between two or more instances of these functions is thus modeled by the abovementioned reference points. Thus, information produced or transformed by a function can be sent to another function under the control of a reference point in two ways: by the user side, to initiate or transfer a processing by the provider side function; by the provider side to respond to a request for processing initiated by the user side function. An information model is a set of concepts and associations that can be used to map information related to a given domain or profession in a consistent manner. The set of concepts can be represented by UML classes when the UML modeling language is used. The information model is obtained, in general, following a business analysis phase. However, the means necessary for grouping network functions into a network functional entity have never been published in the state of the art. In fact, only the knowledge of the business experts in telecommunications network is used in the definition of network functional entities or groupings of network functions in the prior art. The aforementioned prior art is an important part of know-how, if not empiricism, and can not therefore allow the study of all possible choices concerning the groupings of a large number of network functions. The present invention aims to overcome the disadvantages and limitations of the techniques of the prior art.

  In particular, an object of the present invention is the implementation of a method for defining and coding network functional entities making it possible to simplify the industrial development of the latter and the network functionalities of telecommunications networks for their implementation. .

  Another object of the present invention, in addition to the aforementioned simplification, is the implementation of a method for defining and coding network functional entities that, because of the reduction in the number and the volume of network control data manipulated and the number of reference points provided or used by the network functions of a telecommunications network and necessary for the manipulation of these network control data, an optimal modeling of this telecommunications network. Another object of the present invention is to provide the means necessary to achieve the objects just mentioned in a completely automated manner. The method of encoding network functional entities from network functions exchanging at least one signal via a reference point of a telecommunications network model, object of the invention, is remarkable in that it consists at least in establishing and representing the signal exchanges in the form of a modeling sequence diagram, highlighting, for at least one feature and / or network service scenario, the successive exchanges of signals between these network functions , and, each network function being encoded according to a unary network functional entity, iteratively executing steps for calculating, from at least one scenario, a business relevance indicator of grouping network functional entities into a single network functional entity in said functionality and / or said network service into at least one current network functional entity, according to a value a grouping relevance threshold and a grouping gain value, said grouping gain value being defined as the ratio of the value of the business relevance indicator of the two-by-two grouping of said network functional entities and the threshold value of relevance of said grouping. The method which is the subject of the invention is furthermore remarkable in that the modeling sequence is constituted either by the successive signal sequences exchanged by these network functions or by the network function sequences corresponding to these successive signal exchanges. . The method which is the subject of the invention is also remarkable in that, for any network functional entity, the business relevance indicator of grouping is taken equal to the ratio of the total number of groupings of the network function of a unary network functional entity and from another network functional entity to the total number of distinct network function sequences, regardless of the content of the signals. The method which is the subject of the invention is furthermore remarkable in that the network function sequences taken into account for calculating the business relevance indicator of grouping a network functional entity are the maximum internal network function sequences. to this network functional entity. The method which is the subject of the invention is finally remarkable in that for a first and a second network functional entity grouping together a first and a second number of network functions respectively, the threshold value of grouping the network functions belonging to the first and second entities functional network is taken equal to the ratio of the weighted total number of groupings of a network function belonging to the first respectively to the second network functional entity with the second respectively the first network functional entity to the total number of network function sequences distinct from the first and the second network functional entity. The invention also covers a tool for modeling a telecommunications network, in the form of network functions, network functional entities and network elements arranged according to an architecture of network functions exchanging the signals, which comprises, in addition to a central unit process and a modeling module, a module for encoding network functional entities from network functions exchanging at least one signal via a reference point of a model of this telecommunications network, this module of encoding for establishing and representing signal exchanges in the form of a modeling sequence diagram, showing, for at least one feature and / or network service scenario, the successive exchanges of signals between these network functions, and, each network function being coded according to a unary network functional entity, to iteratively execute steps allowing t calculating, from at least one scenario, a network functional entity grouping business relevance indicator in the same network functional entity in said functionality and / or said network service into at least one current network functional entity, in according to a grouping relevance threshold value and a grouping gain value, said grouping gain value being defined as the ratio of the business relevance indicator value of the two-to-two grouping of said functional entities network and the threshold value of relevance of said grouping. The method and the modeling tool, which are the subject of the invention, are applicable to the development and evolutionary maintenance of telecommunication networks of all types. The method and the modeling tool that are the subject of the invention will be better understood on reading the description and on observing the drawings below, in which: FIG. 1 represents the architecture of the network functions of an entity functional network designated Network Network Network Service Attachment My TV line, Figure 2 represents, for illustrative purposes, a flow chart of the essential steps of implementation of the method of encoding network functional entities object of the present invention; FIG. 3a represents, for purely illustrative purposes, a modeling sequence diagram representing the successive signal exchanges between network functions of a telecommunications network during the execution of a first scenario of execution of these network functions for execution. a determined network functionality; FIG. 3b represents, for purely illustrative purposes, a modeling sequence diagram representing the successive exchanges of signals between network functions during the execution of a second scenario of execution of these network functions for the execution of the same network functionality than that described with reference to FIG. 3a; FIG. 3c represents, for purely illustrative purposes, a preferred embodiment of the method that is the subject of the invention, making it possible to manage the grouping of network functional entities, for a plurality of distinct network functionalities, each network functionality being obtained thanks to at the execution of a determined number of successive iterations; and FIG. 4 represents, by way of nonlimiting example, a modeling tool, in accordance with the subject of the present invention, incorporating a functional entity coding module enabling the implementation of the method that is the subject of the invention. invention. A more detailed description of the network functional entity coding method from network function according to the subject of the present invention will be given below. This description presents, for illustrative purposes only, the network service Ma ligne TV, which is a television broadcasting service over an IP network or telephone line marketed by France Telecom. Appendix 1 provides a descriptive list of the functions and messages used to implement this "My TV Line" service.

  Prior to the description of the coding method which is the subject of the invention, indications will be given in connection with FIG. 1 relative to various general definitions involved in the context of the implementation of the method which is the subject of the invention. Network Control Information: any information produced, transmitted or stored within a telecommunications network enabling the implementation of all the network functionalities of the latter; network functionality: set of network functions; a network service provided by a telecommunications network such as missed call management, consists of a set of network features; network control data: any digital data produced transmitted or stored within a telecommunications network, and serving as information carrier for the network control; network planning rule: a rule for the conditional establishment of the relative arrangement and interaction of network functions, network functional entities, grouping of network functions, and network devices allowing the legitimate implementation of network functions or entities network functionalities for performing network functionality. As part of the network function architecture of the Network Attachment feature shown in Figure 1, network functions, excluding support network functions, are: Access Management, Line Identification, - Line Authentication.

  The support network function of the User Information Function type is the following: - User Profile Resource Control Database.

  The reference points RPX, RP3, RP4, RP4bis, RP6, RP6b, s as shown in FIG. 1, are the reference points which connect the corresponding network functions. The network control signals exchanged between the network function are the following: S2 Network Address Request, S7 Line Identification Request, S8 Line Identification Information Request; - S9 Line Identification Information Response; - S10 Line Identification Response, - S11 Line Authentication Request, - S12 Line Authentication Information Request, - S13 Line Authentication Information Response, - S14 Line Authentication Response.

  It is understood in particular that the aforementioned functions represented by ovals in FIG. 1 and the aforementioned signals S2 to S14 and the reference points connecting these functions correspond to elements known from the state of the art, because implemented in the Network Attachment feature of My TV Line Network Service. Accordingly, the designation of the above-mentioned network functions, network control signals is the original designation of the latter. It is understood, in particular, that the implementation of the method which is the subject of the invention is not limited to the example given with reference to FIG. 1, but on the contrary can perhaps be applied to any set of network functions {F ,,} v:, these functions being connected by reference points forming a set of reference points {RP ,. ,, = R, the set of signals exchanged by the aforementioned functions being noted with reference to FIG. 2, the method which is the subject of the invention includes a step A of establishing and representing the signal exchanges. in the form of a modeling sequence diagram, this diagram being denoted K., F ,, Si} ''.

  Such a diagram makes it possible to highlight, for at least one scenario of functionality and / or network service, the successive exchanges of signals between the aforementioned network functions. In addition, step A consists in a remarkable way in coding each network function F a according to a unary network functional entity comprising, by definition, at the start and before the implementation of the coding method which is the subject of the invention itself, one and one only network function F. The coding operation according to a unary network functional entity is noted in step A of FIG. 2: {FI. } v = 1 ù + {EFV {v = / It is understood, for example, that the operation of coding according to a unary network functional entity consists in a practical way in declaring any network function Fä as a network functional entity EFä within the framework of the implementation of the method according to the invention by means of a modeling language, such as the UML modeling language for example. Step A corresponds substantially to an initialization step. The above-mentioned step A is followed by an iterative process comprising the step B of calculating, from at least one scenario, a business relevance indicator for grouping network functional entities into a single network functional entity. the functionality and / or network service considered. In general, in step B, the network functional entity grouping business relevance indicator is a function, for one or more telecommunications services existing or to be developed, of distinct sequences of signals transmitted to network functions capable of to be grouped into network functional entities. More specifically, it is indicated that the sequences are independent given the signals exchanged successively between the network functions that can be grouped together. According to a remarkable aspect of the network functional entity coding method from network functions that are the subject of the invention, for any existing or future EFä network functional entity, the indicator of the business relevance of grouping satisfies the relation: 2 * (+ t (i -1) * NS; (EF) 2 * C, +1 NS; (EF) I (EF) = (1) S (EFI U EFz). (2) In the previous relation and in the In the present description, the symbol U represents the grouping of two unary or non-unary functional entities.According to a remarkable aspect of the coding method that is the subject of the invention, the grouping gain value is defined as the ratio of the value of the indicator of the business relevance of the two-to-two grouping I (EF1U EF2) of the network functional entities EF1 and EF2 and of the relevance threshold value of the grouping S (EF1, EF2), It is understood, in particular, that the coding of the grouping two to two of the functional entities mentioned above, as represented n Figure 2, includes a step Co allowing the effective calculation of the grouping relevance threshold value which satisfies the relation: 2 • r, + 12 <+1 (3) 1 1 NSr (EFI) * NSi (EF2) 25 i = li = 1 Referring to the aforementioned relation (3) giving the threshold value Step B is then followed by a step C consisting in coding the two by two grouping of network functional entities in at least one entity functional current network function EFc according to a grouping relevance threshold value denoted S (EF1, EF2) and a group gain value noted according to the relation: F (EF, U EFz) = I (EF 'U EF2) 2 • C + 1 2 * c, + 1 1 1 (i + jù1) * (NSi (EF1) * NS5 (EF,)) S (EF1, EF2) = '_I' _ 'of grouping relevance, we It is understood that the method which is the subject of the invention consists in grouping together two iteratively the functional entities present during the implementation of the method. Thus, this grouping concerns not only the unary network functional entities defined in step A of FIG. 2, but also any current functional entity obtained by grouping previous functional entities and another existing functional entity. The aggregation threshold of two network functional entities is therefore proposed as a minimum to be achieved for the business relevance indicator of the result group business entity. The proposed choice is therefore to obtain at least one additional signal exchange in each sequence deduced from the combinations of the sequences extracted from the two functional entities to be grouped together.

  For network functional entities EF1 and EF2 for example grouping respectively n and m network functions, then the threshold value S (EF1, EF2) beyond which the grouping of the network functions belonging to the network functional entities EF1 and EF2 is relevant, verifies the relation (2) previously mentioned in the description.

  It is understood, in particular, that for any functional network entity the business relevance indicator for grouping functional entities I (EF) represented by the relation (1) in step B is taken equal to the ratio of the total number of groupings of a network function and a network functional entity, the total number given by the numerator of the relation (1) executed in the previous step B, to the total number of distinct network function sequences given by the denominator of the relation ( 1), regardless of the content of the signals. In particular, it is indicated that the maximum number of network functions in a sequence of n network functions is 2 * C, 2, +1. Indeed, by hypothesis, each pair of functions can involve at most an exchange of two signals between these functions. From the relevance threshold value S (EF1, EF2) as calculated according to the relation (3) in step Co for the grouping of the two functional network entities EF1 and EF2 mentioned above and in order to define the best possible groupings of entities, the estimation of the grouping gain of two network functional entities EF1 and EF2 is defined according to the relation (2) as described previously in the description. To ensure the iterative nature of the calculation steps B and C above, step C shown in FIG. 2 may advantageously comprise a step CI comparing the value of the gain by comparison of superiority or equality to the value 1.

  On a positive response to the above-mentioned CI test, the functions EF1 and EF2 are grouped together in a step C3 to generate the current network functional entity EFc according to the relation: EF, U EF2 = EF ~ represented in FIG.

  Step C3 can then be followed by a step C4 of deleting the functional entities EF1 and EF2, which have been grouped together in the previous step C3, and of introducing the current functional entity EF, in the set of functional entities, noted {EF} v = j,. Step C4 is then followed by a step back to step B of computation of the business relevance indicator of functional entity grouping, due to the introduction of the new current functional entity and the deletion of functional entities EFi and EF2 which have been grouped together. On the contrary, on a negative response to the IC test the grouping gain is not significant, the step CI is then followed by a step C2 in which the presumed grouping of the functional entities EF1 and EF2 is ignored. Step C2 is then followed by a return to step B to ensure the iterative process from the set of starting unary functional entities and / or the current functional entity EFc for example. An example of the implementation of the method of encoding network functional entities, object of the present invention, from network function will now be given in a concrete case in connection with Figures 3a and 3b.

  Recall that FIG. 3a corresponds to a first scenario in which the Line Identification function is called after the Access Management function and where the Line Authentication function is called concomitantly with the call of the Line Identification function whereas in FIG. 3b the Line Authentication and Line Identification functions are switched as well as the signals exchanged by these functions with the Access Management function. In general, it is indicated that the modeling sequence established in step A of FIG. 2 consists either of the successive signal sequences exchanged by the network functions or of the network function sequences corresponding to these exchanges of signals. successive signals. It is understood, in particular, that the signals exchanged between network functions being oriented, there is a one-to-one correspondence between an oriented signal exchanged by two network functions and the corresponding network functions, by means of the reference point which makes it possible to connect the two network functions. In addition, with reference to FIGS. 3a and 3b above, and according to a remarkable aspect of the coding method of the present invention, the network function sequences taken into account in the computation of the business relevance indicator of functional entity grouping. Network I (EF) are the maximum length sequences internally to the functional entity under consideration.

  The preceding rule constituting a network planning rule allowing the implementation of the method of encoding network functional entities from the network function object of the present invention, implies that if a functional entity EF is formed by 3 network functions is EF = {FI, F2, F3} and if there exists an ordered sequence of F1 F2 F3 signals then the ordered sequences FI -> F2 and F2 - + F3 are not to be taken into account for the calculation of the relevance indicator business of grouping of functional entities network I (EF).

  The aforementioned ordered sequences are to be included in the computation of the network functional entity clustering (EF) business relevance indicator only when the aforementioned sequences exist as sequences of maximum length in a scenario. In such a case, there exists a sequence of signals F1 -3 F2 -3 F4 and a sequence F2 - F3 - * F5 such that F4 and F5 do not belong to the functional entity EF. With reference to FIGS. 3a and 3b, for a functional entity EF = {Access Management, Line Identification} then: the network function sequences are: Access Management Line Identification corresponding to the successive signals exchanged S7 or S'7; • Line Identification - Access management successive signals exchanged S10 or S'10; - Access management is the only element of the sequence when in the second scenario it receives the signal S'2 and sends the signal S'11. The number of sequences of i distinct network functions is then given by: NS2 (EF) = 2 and NS1 (EF) = 1 for two distinct network functions. The indicator of business relevance of the aforementioned functional entity EF for the two scenarios chosen and illustrated in FIGS. 3a and 3b is therefore such that:

  (0 * 1) + (1 * 2) + (2 * 0) _2 1 + 2 + 0 3 Finally it is understood that for a first and a second network functional entity comprising a first and a second number of network functions, the S (EF1, EF2) of the network functions belonging to the first and I (EF) = 3 NS; (EF) second network functional entities mentioned above is taken as the ratio of the total weighted number of grouping of a network function belonging to the first and / or the second network functional entity, this weighted total number being represented by the numerator of the relation (3) previously given in the description, to the total number of distinct network function sequences and the first and the second network functional entity, the total number represented by the denominator of the aforementioned relation (3). In the previous relation, the weighting term is given by: (i + j-1), this term corresponding to the sum of the i-1 and j-1 links connecting the functional functions of the network functional entities EF1 and EF2 increased by the link which connects the entities EF1 and EF2 above. Finally, in the particular case of two network functional entities EF1 and EF2 each consisting of one and only one network function, then the number of sequences of i distinct network functions, is given by: NS1 (EF1) = 1 and NS1 (EF2) ) = 1 with n = m = 1. Under these conditions, the network function grouping relevance threshold value is: (i + j1) * (NSi (EFI) * NS; (EF2)) S (EF1, EF2) _ '' 1 * (1 * 1) NS = (EF1) * NS; (EF2) J = I i = 1 The relevance threshold of the grouping of two network functions of the same network functional entity is therefore equal to 1 which of course corresponds to the effective grouping of the aforementioned network functions in the corresponding network functional entity. For an EF = {Access Management, Line Identification} functional functional entity, the relevance indicator calculated for the two scenarios as represented in FIGS. 3a and 3b is such that: I (EF) = 2/3 <1.

  Consequently, the grouping in the same network functional entity 1 * 1 of the Access Management and Line Identification network functions is therefore not relevant for the proposed scenarios as represented in FIGS. 3a and 3b. In the case where the functional entity considered is EF = {Line Identification, User Profile Resource Control Database} then: - the sequence of three network functions is given by: Line Identification -> User Profile Resource Control Database - + Line Identification by successive signals exchanged S8 and S9 or S'8 and S'9 as shown in Figure 3a respectively 3b.

  The User Profile Resource Control Database function is the only element in the sequence when it receives the signal S12 and transmits the signal S13 or receives the signal S'12 and transmits S'13. This implies the value of the number of sequences of i distinct network functions according to: NS3 (EF) = 1 and NS1 (EF) = 1 for two distinct network functions. The business relevance indicator of grouping for the functional entity EF for the two scenarios chosen and represented in FIGS. 3a and 3b has the value: I (EF) _ (0 * 1) + (1 * 0) + (2 * 1) = 1? . 1 + 1 As a result, the bundling of the Line Identification and User Profile Resource Control Database network functions in a single network functional entity is therefore relevant for the service scenarios as shown in Figures 3a and 3b. The gain of this grouping is: F (EF) = A more detailed description of a preferred implementation of the coding method that is the subject of the present invention making it possible to define the network functional entities by grouping network and / or entity functions Network functionalities of a telecommunications service will now be given in connection with Figure 3c. The above implementation mode makes it possible, in particular, to consolidate the network functions and network functional entities exhaustively for any set of network functions. The exhaustive character of the grouping is understood to mean that for each network functional entity resulting from a grouping of network functions and in particular of unary network functional entities declared at initialization, that is to say at the stage In FIG. 2, the grouping gain of all the network functions of each network functional entity thus obtained by grouping is at least equal to 1. In these conditions, with reference to FIG. 3c, it is considered that step A of FIG. Figure 2 has been executed for example. The process described in connection with FIG. 3c therefore relates to a preferential embodiment of the iterative process of FIG. 2. Consequently, in addition to the set of network functions {EFF} v- ', all of the functions unary network functional entities {EF ,,} v-,, the number Nk_1 of unary or non-unary network functional entities as a function of the rank k-1 of the iteration and the number No = V number of network functions and unary network functional entities initialized, following the implementation of step A of Figure 2. With reference to Figure 3c above, to define the network functional entities by grouping the network functions and / or network functional entities, the process object of the The invention comprises a step of initializing the iteration variables denoted by BC0 in FIG. 3c. The aforementioned step consists, for each clustering iteration of rank k determined for any pair of network functions of rank i and j = "; - 'and for the corresponding unary functional entities to initialize the clustering gain values of a matrix grouping gains of functional entities of rank (k-1) i and (k-1) j The above-mentioned gain matrix is noted: GM {r (kI) i, (kI) j Lk-1 The step d initialization of the iteration variables also consists in initializing to 1 a grouping authorization variable of any network functional entity of rank (k-1) i with another network functional entity, the aggregation authorization variables being thus constituted in a set of values noted: GA A ~ k_I ~ i k-1 In the aforementioned step BC0, one thus considers any pair of functional entities of rank i and j.The step BC0 is followed by a step BC1 consisting of for any pair of functional entities mentioned above, to verify proud that the value of the business relevance indicator is greater than or equal to the value of the relevance of the grouping. This operation in step BC1 is performed by a test verifying the relation: (k-I) i, (k-I) j i by comparison of superiority or equality at the value 1, F (k_I) i. (k_I) j designating the value of the gain for each pair of functional entities EF (k-1) i, EF (k-1) i. On a negative response to the aforementioned BC1 test, a step BC2 is called, which consists of passing to the following index values i and j for another pair of functional entities considered in the same value of iteration rank k. Step BC2 is followed by a return to the previous step BC0. The return is made as long as the test executed in step BC1 provides a negative response.

  On the contrary, on a positive response to the test of the aforementioned step BC1, the method which is the subject of the invention, the implementation of which is represented in FIG. 3c, consists of a step BC3 to update the value of the grouping gain of the functional entities of rank (k-1) i and (k-1) j. During the same step BC3, the value of the grouping gain updated, that is to say the matrix of the corresponding gain values GM (F (k,), (k _,) i) is then traversed in descending order of grouping gain values. As long as the grouping gain value is not 0 and if the grouping permission values of the (k-1) i and (k-1) i functional entities allow groupings, a corresponding test on the values of grouping authorization being carried out in step BC4 according to the relation: A (k_1) i = 1 AND A (k_1) j = 1 on positive response to the aforementioned BC4 test, grouping of the current functional entities of rank (k -1) i and (k-1) j in step BC5 according to the relation: EF (k_1) i U EF (k-1) j - * EFkc. The step BC5 may be followed by a step BC6 of deleting the functional entities EF (k_1) i, EF (k_1) j from the set of unary functions {FE}: v and setting to zero of A (k_1) i and A (k_1) j, and step BC6 is itself followed by a step BC7 in which the current functional entity EFkc is included in the set of functional entities that are iterated and noted {ET ',} ::, v. Step BC7 is itself followed by a return to step BC0. On the contrary, in a negative response to the BC4 test, that is, if the grouping authorization values of the functional entities of rank (k-1) i and (k-1) j no longer allow grouping, then the grouping assumed in step BC8 of the functional entities EF (k_1) i, EF (k_1) j is ignored. For i and for any functional entity of rank i whose grouping authorization variable is equal to 1, this condition being executed by checking in step BC9 by the relation: A (k-1) i = 1 or A (k_1) j = 1, in a step BC10, a recovery of the non-grouped network functional entities, that is to say the functional entities EF (k_1) i or EF (k_1) j, is carried out and the entities are reassigned. non-grouped network functionalities as unary functional entities. This operation is performed in step BC10 according to the relation EF (k_1); OR EF (k_1) i E {EFv} =; . Step BC10 is then followed by a step BC11 making it possible to call the next iteration as long as there exists a value A (k_1); = 1 or A (k_1) i = 1 verified in step BC9. The return to the next iteration in the step BC11 is carried out until the end of the iterative process which is interrupted when for example there exists no aggregation authorization value A (k_1); = 1 or A (k_1 ) 1 = 1 verified in step BC9. Note that it can occur at the (k-1) th iteration that an entity EF (k-1) i is grouped with another entity EF (k-1) j; this implies that, following the aforementioned BC4 test, it is necessary to provide a test on the existence of a gain greater than or equal to 1, to be implemented during the (k-1) th iteration; if the result of this test is positive, return to step BC0; if the result of this test is negative, it is necessary to replace the step BC8 by a step of insertion of the non-grouped entities, and the BC9 step by a test on the elements A (k-1) i equal to 1; if the response to this test is positive, step BC10 must be replaced by the operation EF (k-1) i -> EFkx. To simplify FIG. 3c, the steps described in this paragraph have not been represented. The pseudo-code allowing the implementation of the method which is the subject of the invention, as represented in FIG. 3c, is given in a specific coding mode given purely by way of illustration in Appendix 2 of the present description. A detailed description of the embodiment of the method according to the invention in accordance with the algorithmic process of FIG. 3c, when this process is applied to the telecommunication service Ma 2 5 line TV is now given by way of illustration hereinafter. This illustration highlights the advantages of simplifying the development of this telecommunications service, both in terms of the number of network data handled and the reference points, provided or used, necessary for the scenarios envisaged for the service. The definition of functional entities from the grouping of network functions is carried out from the extract of the functional architecture of the network functions designed for the Network Attachment part of the My TV Line service with reference to FIGS. 1, 2 and 3a. , 3b. Initialization of network functional entities: EFo1 = {Access Management}; EF02 = {Line Identification}; EF03 = {Line Authentication}; EF04 = {User Profile Resource Control Database}; Thus, No = 4. Iteration of grouping of the network functional entities, with k = 1: The calculation of the indicators of the business relevance of the functional entities thus initialized is the following I (EFo1 U EF02) = 3 and I (EFoi U EF03) = 2 3 since the model does not change if the Line Identification and Line Authentication network functions are exchanged; • I (EF02U EF04) = 1, and • I (EF03U EF04) = 1, since the model does not change if the Line Identification and Line Authentication network functions are exchanged; • I (EFo1 U EFo4) = I (EFo2U EFo3) = 0, since the network functions of these network functional entities do not appear in any sequence induced by the two scenarios of the My TV Line service shown in Figure 3a and 3b.

  The threshold of relevance of the grouping of two network functions in the same network functional entity being equal to 1, we obtain M (2, 4) = M (3, 4) = 1, where the notation M (i, j) to represent the quantity GM (ki, kj). The first grouping is therefore EF11 = EF02U EF04 = {Line Identification, User Profile Resource Control Database} The second

  EF03U EF04 grouping is impossible since EF04 is already grouped with EF02 in this first iteration.

  The reassigned network functional entities are:

  EF12 = EF01 = {Access Management} - EF13 = EF03 = {Line Authentication}

Thus, N1 = 3.

  Iteration of grouping of the network functional entities, with k = 2: The calculation of the business relevance indicators of the functional entities defined in the second iteration is as follows: for EF11 U EF12: • the sequence of five network functions is:

  - Access Management ù> Line Identification -> User Profile Resource Control Database Line Identification -> Access Management (successive signals exchanged: S7, S8, Sg and S10, or, S'7, S'8, S'9 and S'1o )

  • Access Management is the only element of the sequence when in the second scenario it receives the signal S'2 and sends the signal S'11,

  • User Profile Resource Control Database is the only element in the sequence when it receives the signal S'12 and sends the signal S'13.

  Then NS5 (EF11 U EF12) = 1 and NS1 (EF11 U EF12) = 2 for three distinct network functions.

  • the indicator I of the business relevance of EF11 U EF12 for the two chosen scenarios and the grouping threshold of EF11 and EF12 are thus such that: I (EF11 U EF12) _ (0 * 2) 3 (4 1) = 3 and

  1 * (1 * 1) + 3 * (1 * 1 S (EF11, EF12) = 2 for EF11 U EF13: • the sequences of three network functions are: - Line Identification -3 User Profile Resource Control Database Line Identification (signals successive exchanges exchanged: S8 and S9, or, S'8 and S'9), - Authentication Line> User Profile Resource Control Database Line Authentication (successive signals exchanged: S12 and S13, or, S'12 and S'13), • Then NS3 (EF11 U EF13) = 2 for three network functions The indicator I of the business relevance of EF11 U EF13 for the two chosen scenarios and the grouping threshold of EF11 and EF13 are thus such that: (2 * 2 ) = 2 and I (EF11 U EF13) = 2 S (EF11, 1 * (1 * 1) + 3 * (1 * 1) = 2 EF13) = 2 I (EF12U EF13) = 3 and S (EF12, EF13) ) = 1. Only the grouping of network functional entities EF11 and EF13 in the same network functional entity is possible since I (EF11 U EF13) '- S (EF11, EF13) implies that M (1, 3) = 1 and EF21 = EF11 U EF13 = {Line Identification, Line Auth entication, User Profile Resource Control Database}. The only reallocated functional entity is therefore: EF22 = EF12 = {Access Management} ie N2 = 2. Iteration of grouping of network functional entities, with k = 3: The calculation of the business relevance indicator of the only functional entity that can be defined in the third iteration is as follows: for EF21 U EF22: • the sequences of nine network functions are: - Access Management - + Line Identification User Profile Resource Control Database - + Line Identification -> Access Management ù> Line Authentication -3 User Profile Resource Control Database -3 Line Authentication - Access Management (successive signals exchanged: S7, S8, Sg, S10, S11, S12, S13, S14), - Access Management Line Authentication User Profile Resource Control Database ù> Line Authentication - Access Management ù > Line Identification User Profile Resource Control Database -3 Line Identification 3 Access Management (successive signals exchanged: S'11, S'12, S'13, S'14, S'7, S'8, S'g and S'10). Thus NS9 (EF21 U EF22) = 2 for four distinct network functions. The indicator I of the business relevance of EF21 U EF22 for the two chosen scenarios and the grouping threshold of EF21 and EF22 are therefore such that: (8 * 2) 3 * (2 * 1) = 3. I (EF21 U EF22) = 2 = 8 and S (EF21, EF22) = 2

  The grouping of the network functional entities EF21 and EF22 in the same network functional entity is therefore possible since I (EF21 U EF22) 'û S (EF21, EF22). Therefore, M (1, 2) = 3 and EF31 = EF21 U EF22 = {Access Management, Line Identification, Line 2 0 Authentication, User Profile Resource Control Database}. Thus, N3 = 1, and the grouping of network functional entities is complete. Finally, the invention furthermore covers a modeling tool for a telecommunications network in the form of network functions and network functional entities and network elements arranged according to an architecture of network functions exchanging signals. As represented in FIG. 4, such a tool conventionally comprises a central processing unit CPU, a working memory RAM and a program memory, for example PM. It further comprises a modeling module MM which can be constituted by a modeling module using the UML language normally available on the market. In addition, and without limitation, the modeling module MM may advantageously consist of the essential elements of the modeling tool described and claimed by the French patent application number FR 05 02022 filed February 28, 2005 in the name of the applicant. In any case, whatever the implementation of the memory module MM, the modeling tool object of the invention comprises a coding module CM, this coding module of course allowing the implementation of steps A, B , C represented in FIG. 2 respectively of the coding steps BC0 to BC9 represented in FIG. 3c. It is understood, in particular, that the CM coding module may be constituted by a program module executable by a computer and in particular by the CPU of the modeling tool object of the present intervention. Of course, the coding module CM allows the implementation and execution of the coding method which is the subject of the invention as described above in the description in conjunction with FIGS. 2 and 3a to 3c.

ANNEX 1

  Definition of Access Relay Functions: This function introduces local configuration information received from the user. It converts the request into another understandable by the functions of the Access Management functional entity: This function allows to organize and organize the actions and the procedures necessary for the attachment. Network Access Admission Control: It allows to proceed to the control of admission to a network (or a part of the network) well defined. In this case it is the part of the network dedicated to MLTV Line Identification service: It allows to identify the access line of the user. Line Authentication: It allows to authenticate the access line of the user. - Localization Access Admission control: It allows to proceed to the geographical control of admission to a network (or a part of the network) well defined. In this case it is the part of the network dedicated to the MLTV service. Address Allocation: This is used to allocate the IP address of the user.

  The information bearer functions provide a functional representation of the location of the information needed for the other functions (above) for the processing of the network attachment: Network Access Control Database: It contains the information to identify the terminals users who have subscribed to the MLTV service. User Profile Control Database: Contains the credentials and authentication credentials of users' connectivity lines. Localization Database: Contains the geographic location information of the connectivity lines. This information may affect the network configuration process of the user's terminal. Network Address Database: It contains the necessary configuration information as a result of the implementation of the services including IP addresses, DNS servers and service access node addresses. Definition of SI, S2 Network Address Request messages: The message represents the request from the user terminal to attach to the network. It contains its MAC (Layer 2) S3 Network Access Authorization Request: The message represents the request from the Access Management function to verify the existence of the MAC address of the user's terminal. S4 Network Access Information Request: The message represents the request from the Access Management function to poll the database for the MAC address of the user's terminal. S5 Network Access Information Response: The response containing or not information on the MAC address of the user's terminal. S6 Network Access Authorization Response: The response containing verification information for the MAC address of the S7 user terminal. Line Identification Request: The message represents the request from the Access Management function to check for the existence of the line. access used by the user terminal to access the MLTV service.

  S8 Line Identification Information Request: The message represents the request from the Line Identification function to poll the database for the access line used by the user terminal to access the MLTV service. S9 Line Identification Information Response: The response containing or not information on the access line used by the user terminal to access the MLTV service. S10 Line Identification Response: The response containing verification information of the access line used by the user terminal to access the MLTV service. S11 Line Authentication Request: The message represents the request from the Access Management function to authenticate the existence of the access line used by the user terminal to access the MLTV service. - S12 Line Authentication Information Request: The message represents the request from the Line Authentication function to poll the database with respect to the access line used by the user terminal to access the MLTV service. S13 Line Authentication Information Response: The response containing or not information on the access line used by the user terminal to access the MLTV service. - S14 Line Authentication Response: 25 The response containing authentication information of the access line used by the user terminal to access the MLTV service. S15 Address Allocation Request: The message represents the request from the Access Management function to request an IP address for the user terminal. 30 S16 Address Allocation Localization Admission Request: The message represents the request from the Address Allocation function to request verification of non-nomadism the terminal of the user wishing to access the service of My TV Line. The message represents the request from the Location Access Admission Control function to poll the database with respect to the geographic location of access line used by the user terminal to access the MLTV service.

  S18 Address Location Localization Admission Information Response: The response containing information on the geographic location of the access line used by the user terminal to access the MLTV service.

  S19 Address Localization Allocation Admission Response: The response containing information on the nomadism or non-nomadism of the access line used by the user terminal to access the MLTV service. S20 Address Info Request: The message represents the request from the Address Allocation function to request the assignment of an IP address to the user terminal. S21 Address Info Response: The response containing information about assigning an IP address to the user terminal. S22 Address Allocation Response: The response containing the IP address of the user terminal - S23 Network Address Response: The response containing the IP address of the user terminal as well as other information about the service access portal address (Service Access).

ANNEX 2

  START NO = N; For i from 1 to No {EFo; = {F;}; / * Initialization of network functional entities reduced to a network function each * /} k = 0; Make / * k iteration of the grouping of functional entities network * / {n = 0; k ++; For i from 1 to Nk_1 {For j of i + 1 to Nk_1 {M (i, j) = 0; / * Initialization of the elements of the gain matrix of the grouping of EF (k_1); and EF (k_l) * /} AR (i) = 1; / * Initialization of the authorization of the grouping of EF (k_1); with another network functional entity * /} For i from 1 to Nk_1 {For j from i + 1 to Nk_i {If I (EF (k_1); U EF (k_10? S (EF (k_1) j, EF (k_1) 1) / * Verification that the relevance indicator is greater than or equal to the regrouping threshold * / Then M (i, j) = F (EF (k_1) j, EF (k_q); / * updating the gain 20 From the grouping of EF (k_1) and EF (k_I) i * / Finsi}} Proceed in descending order of the values of M (i, j), as long as M (i, j) # 0 {Si (( AR (i) = 1) and (AR (j) = 1)) / * EF (k_1) i and EF (k_1) i can be grouped * / Then {n ++; EFkn = EF (k_1) iU EF (k_1) grouping the network functional entities EF (k_1); and EF (k_1) i in the functional entity EFkä * / AR (i) = 0; AR (j) = 0; / * EF (k_1); and EF (k_1) i can no longer be grouped with other functional entities during k iteration * /} 20 Finsi} Complete For i from 1 to Nk_1 {Si (AR (i) = 1) / * Functional entity retrieval network not regrouped * / Then {n ++; EFkä = EFk;; / * Réaf assignment of ungrouped network functional entities for the entities of the iteration 15 25 30 * /} Finsi} Nk = n; } Up to ((Nk = Nk_1) or (Nk = 1)) Purpose FIN10

Claims (9)

  1.   A method of encoding network functional entities from network functions exchanging at least one signal via a reference point of a telecommunications network model, characterized in that said method consists of at least: establishing and representing signal exchanges in the form of a modeling sequence diagram, highlighting, for at least one feature and / or network service scenario, said successive exchanges of signals between said network functions; and, each network function being coded according to a unary network functional entity, iteratively executing steps for calculating, from at least one scenario, a business relevance indicator of grouping network functional entities into a single network functional entity in said functionality and / or said network service; encoding the two-to-two grouping of network functional entities into at least one current network functional entity, based on a grouping relevance threshold value and a grouping gain value, said grouping gain value being defined as the ratio of the value of the business relevance indicator of the two-to-two grouping of said network functional entities and the relevance threshold value of said grouping.
  2.   2. Method according to claim 1, characterized in that said modeling sequence is constituted either by the successive signal sequences, exchanged by said network functions, or by the network function sequences, corresponding to these successive signal exchanges.
  3.   3. Method according to one of claims 1 or 2, characterized in that for any network functional entity said business relevance indicator of grouping is taken equal to the ratio of the total number of groupings of a network function and a network functional entity the total number of distinct network function sequences, independent of the content of the signals.
  4.   4. Method according to one of claims 2 or 3, characterized in that the network function sequences taken into account for calculating the business relevance indicator of grouping a network functional entity are the network function sequences of maximum length internal to said network functional entity.
  5.   5. Method according to one of claims 1 to 4, characterized in that for a first and a second network functional entity grouping a first respectively a second number of network functions, said threshold value of relevance grouping network functions belonging to said first and second network functional entity is taken equal to the ratio of the weighted total number of groupings of a network function belonging to the first and / or the second network functional entity with the second respectively the first network functional entity to the total number of network sequences. distinct network functions of the first and second network functional entities.
  6.   6. Method according to one of claims 1 to 5, characterized in that for a given number of network functions and an initialization of unary network functional entities reduced to only one of these network functions, said method consists, for defining the entities network functionalities by grouping said network functions and / or network functional entities, for: for each clustering iteration of rank k determined: • for any pair of functions of rank i =; , - 'and j - initializing the grouping gain values of a matrix of the grouping gains of the functional entities of rank (k-1)' and (k-1) i; v initialize a grouping authorization variable of any network functional entity of rank (k-1); with another network functional entity; and, • for any functional entity pair of rank i and j - verify that the value of the business relevance indicator is greater than or equal to the relevance threshold value of the grouping; updating the value of the gain of the grouping of the functional entities of rank (k-1 and (k-1) i; and, on the following path in descending order of the grouping gain values of the grouping gain matrix, as long as the grouping gain value is non-zero and if the grouping entitlement values of the (k-1) and (k-1) i functional entities allow grouping, - group the current functional entities of rank (k-1) and (k-1) i in a common functional entity, otherwise, • if the aggregation authorization values of the functional entities of rank (k-1) and (k-1) i n do not allow grouping, ignore the grouping of the current functional units of rank (k-1 and (k-1) i, and for i =; F and for any functional entity of rank i whose aggregation authorization variable is equal to 1, • retrieve ungrouped network functional entities, and, • reassign non-grouped network functional entities as a unary functional entity; and, return to the next iteration until the end of the iterative process.
  7.   7. Modeling tool for a telecommunications network, in the form of network functions, network functional entities and network members arranged according to an architecture of network functions exchanging signals, said tool comprising a central processing unit and a module modeling system, characterized in that it furthermore comprises a module for encoding network functional entities from network functions exchanging at least one signal via a reference point of a model of this telecommunications network, said coding module for implementing the coding method according to one of claims 1 to 6.
  8.   A computer program product stored on a storage medium and executable by a computer or modeling tool according to claim 7.
  9.   9. Computer program product according to claim 8, characterized in that the executable program of this program product is implemented in the coding module of said modeling tool.
FR0513162A 2005-12-22 2005-12-22 Network functional entity encoding method for telecommunication network, involves encoding paired regrouping of two network entities into single current functional entity based on regrouping relevance threshold and regrouping gain values Withdrawn FR2895614A1 (en)

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PCT/FR2006/002794 WO2007077321A1 (en) 2005-12-22 2006-12-19 Method for encoding functional network entities on the basis of network functions of a telecommunications network

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Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
FR2818401A1 (en) * 2000-12-15 2002-06-21 Thomson Csf Automatic generation of embedded distributed control applications in a network of automata, based on modeling of the network, uses UML modeling of functions and data communication to drive automatic code generator
FR2835988A1 (en) * 2002-02-14 2003-08-15 France Telecom Method and system for adjusting values of control parameters of a network optimally
EP1361761A1 (en) * 2002-05-10 2003-11-12 Compaq Information Technologies Group, L.P. Telecommunications network management system and method for service monitoring

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
FR2818401A1 (en) * 2000-12-15 2002-06-21 Thomson Csf Automatic generation of embedded distributed control applications in a network of automata, based on modeling of the network, uses UML modeling of functions and data communication to drive automatic code generator
FR2835988A1 (en) * 2002-02-14 2003-08-15 France Telecom Method and system for adjusting values of control parameters of a network optimally
EP1361761A1 (en) * 2002-05-10 2003-11-12 Compaq Information Technologies Group, L.P. Telecommunications network management system and method for service monitoring

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