Classifications

• • H—ELECTRICITY
  • H04—ELECTRIC COMMUNICATION TECHNIQUE
  • H04W—WIRELESS COMMUNICATION NETWORKS
  • H04W84/00—Network topologies
  • H04W84/18—Self-organising networks, e.g. ad-hoc networks or sensor networks

Definitions

• the invention relates to a method for reconstructing an ad hoc network, in particular a ZigBee type network, and corresponding network nodes.
• an ad hoc network The purpose of an ad hoc network is to connect potentially mobile communicating entities, outside of any pre-existing infrastructure within spontaneous networks. Each entity communicates directly with its neighbors, each of which can play the role of client, server and router.
• ZigBee networks meet a standard for wireless data transmission, the IEEE 802.15.4 standard, enabling machine-to-machine communication. In addition to their great flexibility of use, these networks are characterized by very low power consumption and very low production costs, which, for a range between 30 meters and 100 meters and a data transfer rate of between 20 and 250 kbits / s, reserves them for applications in home automation or sensor-type equipment, remote control or industrial sector control equipment.
• the addressing of the nodes of the network is constructed either from a technique of hierarchical distribution of addresses, according to a tree construction procedure according to initial parameters of the tree, or by allocation of address blocks, managed at the application level according to an unspecified process, which can be a centralized agent for distributing address blocks.
• the process of allocating address blocks has the advantage of being highly adapted to the addressing needs of routers.
• the process using the hierarchical address distribution technique has the disadvantage, when the tree parameters have been set, of obeying static rules and therefore of being subject to structural limits due to the allocation process, after that the ZigBee coordinator has been chosen for the network.
• the number of children of a parent node of the tree is defined once and for all for the tree considered.
• each router can allocate addresses independently of the others and a default routing is applicable.
• the above process is therefore simple and is particularly suitable for small networks in number of nodes.
• a first solution consists in carrying out a dynamic management of the parameters of the tree, node by node. Each node can determine the number of its child nodes.
• This solution has the major drawback that the addressing is not adaptive and requires manual configuration, router by router.
• the proposed implementations implementing this solution are not able to calculate the address block (Cship) from the parameters of the latter but use tables, which can pose a major problem when the above parameters are not fixed .
• a second solution proposes to fix the addresses node by node with a suitable installation tool.
• a third solution recommended by G. CHEGARAY consisted in making the tree of the addresses of the nodes more adaptive, by tolerating outgrowths exceptional after the last level, in order to overcome the tree depth limit.
• the IEEE 802.15.4 standard relating to ZigBee networks establishes a difference between coordinators and routers. Consequently, the aforementioned method only presents a prospect of development success insofar as the address space is much larger than the network or even if the coordinator authorizes a fish eye structure of the network, it is that is to say a geographical centering of the ZigBee coordinator.
• the second aforementioned condition requires, in fact, preliminary calculations, before the installation of the network, all the more hypothetical to be carried out in an efficient manner, which would then be necessary to presume in advance of the quality of each radio link , in order to provide the link from a router node to another router node.
• the formation of a ZigBee network consisting of the introduction of 2 nodes A and B into the network, the node A shown in gray becoming the ZigBee coordinator, as shown in figure la, then the random addition of nodes in this network, as represented in figure Ib, vis-à-vis the initial coordinating node, has the effect of offsetting the latter: the ZigBee network obtained is not optimal. If the maximum depth of the ZigBee network, equal to 4 for example, is reached, it is no longer possible to add a node from the router node of corresponding depth, shown hatched in Figure Ib.
• the object of the present invention is to remedy all or part of the aforementioned drawbacks of ad hoc networks, in particular of the ZigBee type, of the prior art.
• the subject of the present invention is the implementation of a method and a device for reconstructing an ad hoc network making it possible to calculate and establish an optimized structure in terms of extensibility and transmission of communications between nodes. of the network.
• the method of reconstructing an ad hoc network, object of the invention is remarkable in that it includes at least the collection of data from the nodes of this network, in terms of the quality of the links and of the trees of the nodes defining a structure of this non-optimal network, the calculation of a current optimized structure from this structure of this non-optimal network, the evaluation, with respect to a stop value of the impact of the current optimized structure vis- with respect to the structure of this non-optimal network, and, if this stop value is not reached by the value of this impact, the current optimized structure defining a pseudo-optimized structure of this non-optimal network, the establishment and injection of optimization data into this network, reconstruction of this network according to the current optimized structure and iterative feedback to the collection of data from the nodes of this network and to the succession of calculation, evaluation steps of establishment smoothing and reconstruction as long as this stop value is not reached by the impact value; otherwise, this stop value being reached by this impact value, the stop of the reconstruction process, to the non-optimal network being allocated the current
• FIG. 2a shows, by way of illustration, a flowchart of the essential steps for implementing the method which is the subject of the invention
• FIG. 2b shows, by way of illustration, a detailed implementation of step B of calculating an optimized structure of Figure 2a;
• FIG. 2c shows, by way of illustration, a non-limiting preferential mode of implementation for calculating the adaptation score of a network tree from an adaptation function, according to step Bl of the figure 2b;
• FIG. 2d shows, by way of illustration, a detailed implementation of step C for assessing the impact of the reconstruction of Figure 2a;
• FIG. 2e represents the structure of a control message transmitted to each node of the network, in the case of an approximate reconstruction
• FIG. 2f represents the structure of a command message transmitted to each node of the network in the case of an exact reconstruction
• FIG. 2g shows the process implemented by each of the network nodes during step E of Figure 2a, in the case of an approximate reconstruction
• FIG. 2h shows the process implemented by each of the network nodes during step E of Figure 2a, in the case of an exact reconstruction
• FIG. 3a shows, by way of illustration, a ZigBee network node, playing the role of aggregator, allowing the implementation of the method object of the present invention, according to an approximate or exact reconstruction;
• FIG. 3b shows, by way of illustration, a ZigBee network node, playing the role of coordinator, allowing the implementation of the method object of the present invention according to an approximate or exact reconstruction.
• FIG. 2a A more detailed description of the method of reconstructing a network, such as a non-optimal ZigBee network, in accordance with the object of the present invention will now be given in conjunction with FIG. 2a and the following figures.
• the process which is the subject of the invention can be implemented either by establishing, according to an agnostic establishment, a ZigBee network in step AA of FIG. 2a, or, on the contrary, in the absence of such an establishment step, on an existing non-optimal ZigBee network.
• step AA of agnostic establishment of the network or finally the agnostic establishment of a ZigBee network independently of the implementation of the method, object of the invention, consists in fact in letting the network be established with the default addressing system as new nodes are added to it.
• the network obtained is thus a non-optimal network in both cases.
• the method which is the subject of the invention then consists of a step A of collecting data from the nodes of the network, in terms of the quality of the links and of the trees of the nodes defining a non-optimal network structure. This step is noted step of recovery of the structural data in FIG. 2 a.
• step A is followed by a step B for calculating a current optimized structure from the aforementioned non-optimal network structure, recovered in step A.
• Step B is itself followed by a step C of evaluation, with respect to a specific stop value, of the impact of the current optimized structure with respect to the structure of the non-optimal network.
• the current optimized structure then defines a pseudo-optimized structure of the network and the method is continued by a step D of establishment and injection of optimization data in the network.
• step E of reconstruction of the network according to the current optimized structure previously calculated in step B.
• step E is itself followed by a step F of iterative return to the collection of data from the nodes of the network in step A, then in the succession of steps for calculating an optimized structure B, for evaluating the impact of the reconstruction C, for injecting data into the network D, then for reconstruction E successively , as long as the stop value is not reached by the impact value evaluated in step C.
• the network is allocated the current optimized structure obtained at the last iteration, the network being thus optimized.
• the method which is the subject of the invention further comprises a step for automatically triggering the first iteration, this step being noted FR in FIG. 2a.
• the aforementioned automatic triggering step is executed on detection of a false distribution signal from a router or on detection of a false distribution signal from an item of equipment.
• the automatic triggering step thus allows a trigger either on a start commanded by an operator, for example at the commissioning of the network or during a maintenance operation, or on detection of a signal of bad distribution of a router or equipment.
• a signal of bad distribution of a router is generated by a router which has the possibility of connecting to the network, but which is in one of the following situations:
• either the router in question is connected to the last level of the tree, level corresponding to the maximum depth of the tree representing the structure of the network;
• the two aforementioned cases correspond to situations where the router cannot play its role of aggregator.
• An equipment misallocation signal is generated when the equipment considered deems it appropriate. For example, if the equipment has to communicate with another equipment which cannot be found in the network, it can consider that the cause comes from a bad network topology and trigger the aforementioned signal.
• the data collection step A of the nodes of the network comprises at least the discovery, by network walk, to recover the address of all the aggregator nodes present in the network and the links seen by each aggregator node in the neighborhood tables of the above aggregating nodes.
• the data collection step further comprises the creation of a first data structure containing all the nodes and all the links for each node, accompanied by the value of the quality of each link, and a second data structure reconstituting the addressing structure of nodes and their parent node / child node relationships, this addressing structure corresponding to the tree of nodes constituting the network and representing the image of the structure and of the network considered.
• Step B of calculating a current optimized structure will now be described in conjunction with FIGS. 2b and 2c.
• step B of calculating an optimized structure there is an adaptation function FF making it possible to calculate an adaptation value of all or part of the network as will be described below. after.
• the calculation of a current optimized structure comprises at least, as shown in FIG. 2b, the calculation in a step B 1 of a specific adaptation score from the adaptation function FF for all or part of the structure optimized current in the search space of the solution constituted by the table of links occurring between all the nodes of the network.
• step Bi of FIG. 2b the operation for calculating the specific score is noted:
• the above operation allows the creation of a population of individuals formed by a plurality of optimized structures to each of which is associated a specific adaptation score TSj.
• Stage Bi is followed by stage B 2 of population improvement on specific discrimination criteria of individuals to generate an improved population.
• step B 2 the improvement operation is noted:
• Step B 2 is followed by step B 3 consisting in selecting from the improved population a specific structure corresponding to the best adaptation score, the best adaptation score being denoted TSt, m and the selection operation being denoted in FIG. 2b:
• T oc The specific structure presenting the best adaptation score TS bm corresponding to the current optimized structure being denoted T oc .
• adaptation function FF this will be described from the point of view of its implementation in relation to FIG. 2c.
• first and the second data structure Si and S 2 relating to the tree of nodes, with parent- children to create the image of the current network structure.
• the adaptation function FF and the calculation thereof can advantageously include the calculation of an adaptation score for each node of the network structure in step Bn of FIG. 2c in the conditions below.
• the value of the adaptation score is defined according to the relation: nb neighbo) s (N)
• nbjieighbors is the number of neighboring nodes of the considered node N.
• lqi (V) a function which depends on the value of the quality of the radio link vis-à-vis a neighboring node considered, the quality of the link designated by LQI for Link Quality Indicator in English.
• the link quality function lqi (V) can be taken equal to
• r (LQI) is a function of the quality of the LQI link which makes it possible to favor the most efficient radio links.
• Sub-step Bj 1 in FIG. 2c is then followed by sub-step B 12 consisting in calculating an adaptation score for each level of depth of the network structure and of the tree represented by the latter, by summation of the adaptation score of each node of the same level.
• nb_nodes designates the number of nodes belonging to the level of depth considered a is a constant, a> l, determined according to the desired final topology of the optimized network as will be described later in the description.
• Sub-step B 12 is then followed by a sub-step Bi 3 consisting in calculating an adaptation score of the tree formed by the network by summation of the score adaptation of each level of depth of the tree constituting the network considered.
• FF adaptation function By implementing the abovementioned FF adaptation function and the operating and calculation mode thereof, it is thus possible to calculate the adaptation value of the whole of a current optimized network, or of the agnostic network. initial, as well as, of course, a subtree of the latter or of a branch constituting a determined subtree.
• an optimized network structure of the ZigBee type and having the best adaptation value can then be selected as described above in the description as optimum for the network considered.
• Sub-step C 2 is followed by a sub-step C 3 consisting in comparing the adaptation difference ⁇ with a value e, deviation from which the adaptation difference is considered to be significant.
• the decision is to prefer the current optimized tree structure to that existing in the network.
• step C of evaluating the impact of the reconstruction in FIG. 2a it is indicated that the stop value is a value depending on the difference between an adaptation score of the image of the network structure and an adaptation score of the current optimized structure.
• condition ⁇ ⁇ e of the sub-step C 3 of FIG. 2d in fact represents a stop condition.
• the stop value is a number of calculation iterations N.
• step D of injecting optimization data into the network of FIG. 2a it is indicated that this step can be carried out either for an approximate reconstruction of the network, or on the contrary, for an exact reconstruction.
• step D of injecting optimization data into the network as shown in FIG. 2a will now be given in conjunction with FIGS. 2e and 2f.
• the establishment and injection of optimization data consists in transmitting to each node of the network a command including at least, as shown in FIG. 2e, a delay ⁇ T of time delay before operating the disconnection of this node from the network, a sequence number j for the reconstruction of the network, and a variable LV representing the function or role of aggregating router or coordinator of the node considered.
• the variable LV can be a logical variable of value 1 for the role of coordinator and of value 0 for the role of router.
• SNL []
• the above list corresponds to the list of child nodes of the node considered.
• the node N considered has no children and is therefore considered to be a node with no descendants.
• the command message, as represented in FIG. 2f, transmitted to the node considered N furthermore includes information containing the list of child routers of the destination node, the node N, which then constitutes a parent node in the current optimized structure for all of the child nodes in the list.
• step E of FIG. 2a The reconstruction process of step E of FIG. 2a will now be described in the case of an approximate reconstruction in conjunction with FIG. 2g respectively of an exact reconstruction, in the case of FIG. 2h.
• each node considered the list of son nodes of the latter.
• Np the set of child nodes associated with the latter Np [NFk) ⁇ 1 f.
• Each parent node thus has the address of its pre-registered child nodes.
• each node When they wake up, after a specified period of time, each node, considered as a child node of an existing father node, proceeds to search for the father node with which it is pre-registered as a child node, this sub-step being designated E'i in FIG. 2h and designated Search N p , where N p denotes the father node of the son node considered.
• each child node in substep E 3 connects to the father node considered according to the following relationship:
• each of the abovementioned child nodes Nfk proceeds to a connection to another node of the network by an association procedure in substep E 4 of FIG. 2h.
• connection operation is designated:
• connection procedure as the child node of another node, different from the parent node N p , as described in sub-step E ' 4 of FIG. 2h, allows the abovementioned child node not to remain an orphan.
• the time delay ⁇ t introduced in step E 4 corresponds to a time substantially proportional to the rank of connection j contained in the message CM.
• the method of reconstructing a ZigBee type network allows performance optimization and extension of the network by the edges, which contributes to reducing the depth of the latter.
• the more the depth is limited the more the network is likely to extend around the edges and the fewer jumps there are, which improves the performance of the optimized network.
• the method which is the subject of the invention makes it possible to promote quality radio links.
• the method, object of the invention also makes it possible to promote the completeness of the tree at each level, that is to say the influence of the parameter a previously described in the description in conjunction with the description of the mode of setting. implementation of the FF adaptation function.
• the method, object of the invention also allows the implementation of an optimization of performance and balance.
• n the depth of the tree representing the network, it is then a question of determining the ideal number of child routers, so that each router has the same number of wires close to it. It is also a question of finding what is the ideal number of levels in order to limit the depth to a minimum.
• Ni the ideal number of aforementioned levels
• R t the increasing value of the number of routers desired per son, certain routers having R t -1 son.
• P the population of routers
• N (P) the cardinality of all the routers considered.
• a ZigBee network node as shown in FIG. 3 a, has I / O input / output members, of course allowing the connection of the aforementioned node to the ZigBee network considered, a memory RAM, a storage memory and a central processing unit CPU.
• the storage memory SM can be formed by a non-volatile programmable memory divided or not into storage modules, as will be described below.
• the ZigBee network node shown in FIG. 3 a may advantageously, without limitation, a storage module M 4 allowing the storage of a list of child nodes of the node considered, that is to say the list SNL.
• the node further comprises the modules Mi 5 M 2 , M 3 , M 4 of the aforementioned storage, an executable program module M 5 comprising a series of instructions allowing the execution of the method as described previously in the description in conjunction with Figures 2a to 2h.
• the distinction of the structure of a ZigBee network node object of the present invention, shown in Figures 3a and 3b, is introduced for purely illustrative purposes of understanding in order to show the great flexibility of use of the method which is the subject of the invention, and of implementation of the latter, by simple programming and loading of the values and parameters of the aforementioned variables.
• the storage memory SM can be constituted by a single memory or by the separate modules Mi to M 5 previously mentioned without departing from the scope of the present invention.
• the ad hoc network or ZigBee network node shown in FIGS. 3a and 3b constitutes a device equipped with a module for collecting data from the nodes of the ad hoc network, in terms of the quality of the links and the trees of the nodes. defining a structure of this network, a module for calculating an optimized network structure and a module for reconstructing this network according to this optimized network structure.
• the above-mentioned device can then, according to a variant of implementation, be included in a determined node of a network, or, according to another variant, constitute the aforementioned node.
• the invention covers a computer program product recorded on a storage medium and executable by a computer or by a dedicated device, remarkable in that the computer program comprises a series of instructions allowing execution of the method as described above in connection with Figures 2a to 2h above.
• the aforementioned computer program product recorded on a storage medium can be loaded into the module M 5 of a ZigBee network node playing the role of coordinator, as shown in FIG. 3b or finally on any external tool connected in network to the ZigBee network and allowing to execute the program memorized as product of computer program previously mentioned.
• the aforementioned computer program product can be executed on an external tool in direct connection with the network node playing the role of ZigBee coordinator.

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• 2006
  • 2006-12-01 WO PCT/FR2006/002632 patent/WO2007065987A1/fr active Application Filing
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