CN104394567A - Selection method and system for wireless sensor network aggregation nodes of intelligent power grid - Google Patents
Selection method and system for wireless sensor network aggregation nodes of intelligent power grid Download PDFInfo
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- CN104394567A CN104394567A CN201410708993.8A CN201410708993A CN104394567A CN 104394567 A CN104394567 A CN 104394567A CN 201410708993 A CN201410708993 A CN 201410708993A CN 104394567 A CN104394567 A CN 104394567A
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- H—ELECTRICITY
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- H04W40/00—Communication routing or communication path finding
- H04W40/02—Communication route or path selection, e.g. power-based or shortest path routing
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W40/00—Communication routing or communication path finding
- H04W40/02—Communication route or path selection, e.g. power-based or shortest path routing
- H04W40/023—Limited or focused flooding to selected areas of a network
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
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- Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
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- Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks
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Abstract
The invention relates to a selection method and a system for wireless sensor network aggregation nodes of an intelligent power grid. The selection method comprises steps of: obtaining the link spending between any two nodes in the wireless sensor network of the intelligent power grid and the sending frequency of each node; taking each node as a simulate aggregation node, calculating the total link spending corresponding to the simulate aggregation nodes through undirected weighted graph according to the link spending and the sending frequency; respectively judging whether the residual energy of each node exceeds the energy threshold value corresponding to the node, and the simulate aggregation node, which has the minimum total link spending, among the nodes that the residual energy exceeds the corresponding energy threshold value is judged to the best aggregation node. The selection method and the system for the wireless sensor network aggregation nodes of the intelligent power grid can efficiently find the best aggregation node, thus being beneficial to improving the efficiency of the intelligent power grid and ensuring the real-time performance of the intelligent power grid. Furthermore, the lifecycle of the whole wireless sensor network of the intelligent power grid is ensured, and the reliability of the wireless sensor network of the intelligent power grid is improved.
Description
[technical field]
The present invention relates to intelligent power grid technology, particularly relate to a kind of system of selection and system of intelligent grid wireless sensor network aggregation.
[background technology]
Intelligent grid is considered follow-on power network, and it is by the two-way flow of electric power and information, creates the automatic energy transport net of an extensive distribution.In this network, the electricity of generation can adjust according to the real-time requirement of user.This can not only ensure meeting of user's request, also can avoid the generation of excess power.A notable feature of intelligent grid is the large scale deployment of transducer and intelligent electric meter.Therefore, a large amount of data and information will by generations such as measurement, sensing and monitorings.Data aggregate is intended to the data merged from different concept type various in network node and structure type.Owing to producing a large amount of data in the communication of intelligent grid, data aggregate must produce in specific place, to meet the demand of different information flows.Data aggregation service layout in intelligent grid communication network is an important design problem, therefore, chooses for the aggregation of data aggregate and important in intelligent grid wireless sensor network.
Usually adopt the way selection aggregation of inundation at present, as long as each node receives less than original link overhead information of preserving, just replace former expense by less expense, and this Overhead is transmitted to other all nodes in link.This algorithm can find out best aggregation, but can cause a large amount of link overhead, and the mode of this ' little, to forward ' easily causes the inefficiency of intelligent grid, cannot ensure the real-time of intelligent grid.In addition in the selection course of aggregation, only considered link overhead factor, and the dump energy of transducer is related to whole Network morals, aggregation is chosen and is improperly easily caused whole intelligent grid sensor network short for life cycle, reduces the reliability of whole intelligent grid sensor network.
[summary of the invention]
Based on this, when being necessary to choose aggregation for prior art, link overhead causes greatly intelligent grid inefficiency problem, there is provided a kind of system of selection of intelligent grid wireless sensor network aggregation, the method can improve the real-time of the efficiency guarantee intelligent grid of intelligent grid.
A system of selection for intelligent grid wireless sensor network aggregation, comprises step:
Link overhead between any two nodes of acquisition intelligent grid wireless sensor network and the transmission frequency of each node;
Respectively with each node for replica polymerization node, calculate the link overhead corresponding to described replica polymerization node according to described link overhead and transmission frequency by undirected weighted graph;
Judge whether the dump energy of each node exceedes energy threshold corresponding to this node respectively, replica polymerization node dump energy being exceeded the node link overhead of corresponding energy threshold minimum is judged to be best aggregation.
Correspondingly, the present invention also provides a kind of system of selection of intelligent grid wireless sensor network aggregation, comprising:
Acquisition module, for obtaining the transmission frequency of link overhead between any two nodes of intelligent grid wireless sensor network and each node;
Overhead computing module, for respectively with each node for replica polymerization node, calculate the link overhead corresponding to this replica polymerization node according to described link overhead and transmission frequency by undirected weighted graph;
Determination module, for judging whether the dump energy of each node exceedes energy threshold corresponding to this node respectively, replica polymerization node dump energy being exceeded the node link overhead of corresponding energy threshold minimum is judged to be best aggregation.
The present invention is by obtaining the transmission frequency of link overhead in intelligent grid wireless sensor network between any two nodes and each node, then respectively with each node for replica polymerization node, the link overhead corresponding to this replica polymerization node is calculated by undirected weighted graph according to described link overhead and transmission frequency, then judge whether the dump energy of each node exceedes energy threshold corresponding to this node respectively, then dump energy is exceeded the best aggregation that the minimum replica polymerization node of the node link overhead of corresponding energy threshold is judged to be intelligent grid wireless sensor network.The present invention turns to a undirected weighted graph by abstract for intelligent grid transducer, in undirected weighted graph, select best aggregation, can find best aggregation efficiently, is conducive to the efficiency improving intelligent grid, ensures the real-time of intelligent grid.In addition, only when residue energy of node exceedes preset energy threshold value, this node just likely becomes aggregation, thus ensure that the life cycle of whole intelligent grid wireless sensor network, improves the reliability of described intelligent grid wireless sensor network.
[accompanying drawing explanation]
Fig. 1 is the flow chart of a kind of embodiment of system of selection of intelligent grid wireless sensor network aggregation of the present invention;
Fig. 2 is the undirected weighted graph schematic diagram of a kind of embodiment of system of selection of intelligent grid wireless sensor network aggregation of the present invention;
Fig. 3 is the schematic diagram after the undirected weighted graph initialization of a kind of embodiment of system of selection of intelligent grid wireless sensor network aggregation of the present invention;
Fig. 4 is undirected weighted graph solution procedure schematic diagram of a kind of embodiment of system of selection of intelligent grid wireless sensor network aggregation of the present invention;
Another solution procedure schematic diagram of undirected weighted graph of a kind of embodiment of system of selection of Fig. 5 intelligent grid of the present invention wireless sensor network aggregation;
Fig. 6 is the structured flowchart of a kind of embodiment of selective system of intelligent grid wireless sensor network aggregation of the present invention.
[embodiment]
In order to make the object, technical solutions and advantages of the present invention clearly, below in conjunction with accompanying drawing, the present invention is described in further detail.
Refer to Fig. 1, it is the flow chart of a kind of embodiment of system of selection of intelligent grid wireless sensor network aggregation of the present invention.
A system of selection for intelligent grid wireless sensor network aggregation, comprises step:
S101: the link overhead between any two nodes of acquisition intelligent grid wireless sensor network and the transmission frequency of each node;
In intelligent grid wireless sensor network, described node comprises the transducer be deployed in electrical network, wireless monitoring device, wireless measurement equipment etc.Obtain the link overhead between any two nodes in intelligent grid wireless sensor network, wherein, link overhead between described two nodes refers to, two nodes forward without other nodes and send directly to the other side the energy that a packet consumes within the unit interval.Then obtain the transmission frequency of each node, wherein, described transmission frequency for unit time interior nodes to other nodes send the quantity of packet.
S102: respectively with each node for replica polymerization node, calculate the link overhead corresponding to described replica polymerization node according to described link overhead and transmission frequency by undirected weighted graph;
Create the undirected weighted graph based on each node, then aggregation is modeled as with each node respectively, namely respectively with each node for replica polymerization node, then substitute in undirected weighted graph according to the link overhead between any two nodes, and actual overhead corresponding to each node of acquisition is solved to described undirected weighted graph, then be added after actual overhead being multiplied with corresponding transmission frequency, the link overhead corresponding to described replica polymerization node can be obtained.
S103: judge whether the dump energy of each node exceedes energy threshold corresponding to this node respectively, replica polymerization node dump energy being exceeded the node link overhead of corresponding energy threshold minimum is judged to be best aggregation.
Obtain the dump energy of each node, then judge whether the dump energy of each node exceedes energy threshold corresponding to this node respectively, wherein, the energy threshold that node is corresponding is directly proportional to the transmission frequency of this node, that is transmission frequency is higher, the energy threshold that so this node is corresponding is also higher, thus can be different for the transmission frequency of each node, and the energy threshold that setting is corresponding.Filter out the node that energy exceedes corresponding energy threshold, from these nodes, then find the minimum replica polymerization node of link overhead, then this replica polymerization node is judged to be best aggregation.That is, if the dump energy of a certain node is not more than energy threshold corresponding to this node, so this node can not become best aggregation.
The present invention is by obtaining the transmission frequency of link overhead in intelligent grid wireless sensor network between any two nodes and each node, then respectively with each node for replica polymerization node, the link overhead corresponding to this replica polymerization node is calculated by undirected weighted graph according to described link overhead and transmission frequency, then judge whether the dump energy of each node exceedes energy threshold corresponding to this node respectively, then dump energy is exceeded the best aggregation that the minimum replica polymerization node of the node link overhead of corresponding energy threshold is judged to be intelligent grid wireless sensor network.The present invention turns to a undirected weighted graph by abstract for intelligent grid transducer, in undirected weighted graph, select best aggregation, can find best aggregation efficiently, is conducive to the efficiency improving intelligent grid, ensures the real-time of intelligent grid.In addition, only when residue energy of node exceedes preset energy threshold value, this node just likely becomes aggregation, thus ensure that the life cycle of whole intelligent grid wireless sensor network, improves the reliability of described intelligent grid wireless sensor network.
In one embodiment, calculate the step of the link overhead corresponding to this replica polymerization node according to described link overhead and transmission frequency by undirected weighted graph in above-mentioned steps S102, specifically can comprise following sub-step:
S201: with replica polymerization node for other nodes of host node for child node sets up the undirected weighted graph of intelligent grid wireless sensor network;
After have chosen replica polymerization node, with this replica polymerization node for host node, with other nodes for child node sets up the undirected weighted graph of described host node and child node, namely set up the undirected weighted graph of intelligent grid wireless sensor network.For the intelligent grid sensor network of 4 nodes, such as choose node 1 for host node, with node 2, node 3 and node 4 for child node, the undirected weighted graph of establishment as shown in Figure 2, wherein, (In, Jn), n=(1,2,3...N), In is the current expense of the n-th node, and Jn is the time-parameters of the n-th node, Kpq, p=(1,2,3...N), q=(1,2,3...N) be the weight between node P and node q, the link overhead between node p and node q can be expressed as.
S202: the current expense using the link overhead between each child node and host node as this child node, and link overhead between two nodes connected using each link is as the weight of this link, and calculated the time-parameters of each child node by the overhead time proportionate relationship preset according to described current expense;
After creating undirected weighted graph, initialization is carried out to the numerical value on undirected weighted graph.Wherein, using the current expense of the link overhead between each child node and host node as this child node, then the link overhead between two nodes connected by each link, as the weight of this link, finally calculates the time-parameters of each child node by the overhead time proportionate relationship preset according to described current expense.Preferably, described time-parameters should be the integral multiple of described current expense, mutually distinguishes to enable the time-parameters of a child node.
For Fig. 3, child node 2, child node 3 and the link overhead between child node 4 and host node 1 are respectively 1,3,5.Link overhead between child node 2 and child node 3 is 1, between child node 2 and child node 4, link overhead is 2, between child node 3 and child node 4, link overhead is 1, and the time-parameters of each child node is 1 times of current expense, so the time-parameters of child node 2, child node 3 and child node 4 is respectively 1,3,5.So initialized undirected weighted graph as shown in Figure 3.
S203: the weight according to described current expense, time-parameters and each link calculates the actual overhead of described child node when time-parameters reduces to zero by the actual overhead model preset, and to be calculated by the additive model preset according to the actual overhead of each node and transmission frequency and obtain link overhead corresponding to this replica polymerization node.
After initialization is carried out to undirected weighted graph, weight according to the current expense of each child node obtained during initialization, time-parameters and each link is solved described undirected weighted graph by the actual overhead computation model preset, and obtains the actual overhead of described child node when time-parameters reduces to zero.Finally described actual overhead and transmission frequency corresponding to each node are substituted into the additive model preset can calculate and obtain link overhead corresponding to this replica polymerization node.
Wherein, preferably, the formula of described additive model is:
wherein, C
ifor the actual overhead of child node i, F
ifor the transmission frequency of child node i.
By setting up the undirected weighted graph of host node and child node after have chosen host node and child node, then initialization is carried out to undirected weighted graph, participate in the calculating of each child node actual overhead as the part of undirected weighted graph by the link overhead between each node, finally described undirected weighted graph is solved to the actual overhead obtaining each child node, and calculate according to the transmission frequency of this actual overhead and each child node the link overhead obtaining this host node.The link overhead of each replica polymerization node is calculated more fast, thus reduces the link overhead when finding best aggregation, strengthen the real-time of intelligent grid wireless sensor network.
In one embodiment, in above-mentioned steps S203, calculated the step of the actual overhead of described child node when time-parameters reduces to zero according to the weight of described current expense, time-parameters and each link by the actual overhead model preset, specifically can comprise following sub-step.
S301: current node receives the actual overhead that other child nodes send respectively, and the time-parameters of the current node that successively decreases;
If other child nodes send actual overhead to current node, then current node receives the actual overhead that other child nodes send respectively, the time-parameters of the current node that then successively decreases.
For Fig. 3, be the moment of 0 using the weighted graph shown in Fig. 3 as clock signal T, wherein T is rising edge clock signal, trailing edge, high level or low level number.Please consult Fig. 4, in the T=1 moment, the time-parameters of child node 2 is decremented to 0.Now, child node 2 sends the actual overhead of child node 2 to child node 3 and child node 4.Child node 3 and child node 4 receive the actual overhead that child node 2 sends, and the time-parameters of successively decrease child node 3 and child node 4.
S302: if described actual overhead and corresponding weights and the current expense that is less than current node little, then actual overhead and corresponding weights and the current expense that is updated to current node, multiple connection of laying equal stress on receives actual overhead that other child nodes send until the time-parameters of current node is zero;
When the actual overhead received with corresponding weights and less than the current expense of current node, actual overhead and corresponding weights and the current expense that is updated to current node.
As shown in Figure 4, in the T=1 moment, child node 3 and child node 4 have received the actual overhead that child node 2 sends, the current expense of child node 4 is 3, the actual overhead of child node 2 is 1, and the weights between child node 4 and child node 2 are 1, namely to send to host node 1 link overhead that data send directly to host node 1 than child node 4 through the link overhead that child node 2 forwards little for child node 4, now the current expense of child node 4 is updated to 2.The update mode of the current expense of child node 3 is identical with child node 4, therefore repeats no more.
Then current node judges whether its time-parameters is zero, if non-vanishing, then continues to repeat step S301 and S302 until the time-parameters of current node is zero.
Preferably, the actual overhead received and corresponding weights and be more than or equal to child node current expense time, abandon received actual overhead.
S303: when the time-parameters of current node is zero, is judged to be actual overhead by the current expense of current node, and sends the actual overhead of current node to the child node that all time-parameters are non-vanishing.
When the time-parameters of current node is zero, now current node can not receive the actual overhead that other child nodes send, the current expense of current node is judged to be the actual overhead of current node, then sends the actual overhead of current node to the child node that all time-parameters are non-vanishing.
For Fig. 5, in the T=3 moment, the time-parameters of child node 4 is decremented to 0, and now the current expense of child node 4 is 2, using 2 as the actual overhead of child node 4, then actual overhead is issued child node 3 (now only have the time-parameters of child node 3 non-vanishing).
Current node receives the actual overhead that other child nodes send respectively, and when the actual overhead received with corresponding weights and less than the current expense of current node, upgrade the current expense of current node, and when the time-parameters of current node is decremented to zero, be greater than the actual overhead of the child node transmission current node of zero to time-parameters.When the time-parameters vanishing of current node, the actual overhead of this child node is determined, now send actual overhead to the non-vanishing child node of parameter At All Other Times, avoid and actual overhead is issued the child node that time-parameters has been zero, the data traffic volume of current node can be reduced as much as possible, thus substantially reduce the link overhead produced found in best aggregation process.
Refer to Fig. 6, it is the structured flowchart of a kind of embodiment of selective system of intelligent grid wireless sensor network aggregation of the present invention
A selective system for intelligent grid wireless sensor network aggregation, comprising:
Acquisition module 501, for obtaining the transmission frequency of link overhead between any two nodes of intelligent grid wireless sensor network and each node;
In intelligent grid wireless sensor network, described node comprises the transducer be deployed in electrical network, wireless monitoring device, wireless measurement equipment etc.The link overhead in intelligent grid wireless sensor network between any two nodes is obtained by acquisition module 501, wherein, link overhead between described two nodes refers to, two nodes forward without other nodes and send directly to the other side the energy that a packet consumes within the unit interval.Then obtained the transmission frequency of each node by acquisition module 501, wherein, described transmission frequency for unit time interior nodes to other nodes send the quantity of packet.
Overhead computing module 502, for respectively with each node for replica polymerization node, calculate the link overhead corresponding to this replica polymerization node according to described link overhead and transmission frequency by undirected weighted graph;
Overhead computing module 502 creates the undirected weighted graph based on each node, then overhead computing module 502 is modeled as aggregation with each node respectively, namely respectively with each node for replica polymerization node, then overhead computing module 502 substitutes in undirected weighted graph according to the link overhead between any two nodes, and actual overhead corresponding to each node of acquisition is solved to described undirected weighted graph, then be added after actual overhead being multiplied with corresponding transmission frequency, the link overhead corresponding to described replica polymerization node can be obtained.
Determination module 503, for judging whether the dump energy of each node exceedes energy threshold corresponding to this node respectively, replica polymerization node dump energy being exceeded the node link overhead of corresponding energy threshold minimum is judged to be best aggregation.
Determination module 503 obtains the dump energy of each node, then determination module 503 judges whether the dump energy of each node exceedes energy threshold corresponding to this node respectively, wherein, the energy threshold that node is corresponding is directly proportional to the transmission frequency of this node, that is transmission frequency is higher, the energy threshold that so this node is corresponding is also higher, thus can be different for the transmission frequency of each node, and the energy threshold that setting is corresponding.Determination module 503 filters out the node that energy exceedes corresponding energy threshold, from these nodes, then finds the minimum replica polymerization node of link overhead, then this replica polymerization node is judged to be best aggregation.That is, if the dump energy of a certain node is not more than energy threshold corresponding to this node, so this node can not become best aggregation.
The present invention obtains the transmission frequency of link overhead in intelligent grid wireless sensor network between any two nodes and each node by acquisition module 501, then overhead computing module 502 respectively with each node for replica polymerization node, the link overhead corresponding to this replica polymerization node is calculated by undirected weighted graph according to described link overhead and transmission frequency, then judge whether the dump energy of each node exceedes energy threshold corresponding to this node respectively by determination module 503, then dump energy is exceeded the best aggregation that the minimum replica polymerization node of the node link overhead of corresponding energy threshold is judged to be intelligent grid wireless sensor network.The present invention turns to a undirected weighted graph by abstract for intelligent grid transducer, in undirected weighted graph, select best aggregation, can find best aggregation efficiently, is conducive to the efficiency improving intelligent grid, ensures the real-time of intelligent grid.In addition, only when residue energy of node exceedes preset energy threshold value, this node just likely becomes aggregation, thus ensure that the life cycle of whole intelligent grid wireless sensor network, improves the reliability of described intelligent grid wireless sensor network.
In one embodiment, above-mentioned overhead computing module 502 can comprise following submodule.
Weighted graph creation module, for replica polymerization node for other nodes of host node for child node sets up the undirected weighted graph of intelligent grid wireless sensor network;
After have chosen replica polymerization node, weighted graph creation module for host node, with other nodes for child node sets up the undirected weighted graph of described host node and child node, namely sets up the undirected weighted graph of intelligent grid wireless sensor network with this replica polymerization node.For the intelligent grid sensor network of 4 nodes, such as choose node 1 for host node, with node 2, node 3 and node 4 for child node, the undirected weighted graph that weighted graph creation module creates as shown in Figure 2, wherein, (In, Jn), n=(1,2,3...N), In is the current expense of the n-th node, and Jn is the time-parameters of the n-th node, Kpq, p=(1,2,3...N), q=(1,2,3...N) be the weight between node P and node q, the link overhead between node p and node q can be expressed as.
Initialization module, for the current expense using the link overhead between each child node and host node as this child node, using the link overhead between two nodes that each link connects as the weight of this link, and calculated the time-parameters of each node by the overhead time proportionate relationship preset according to described current expense;
After weighted graph creation module creates undirected weighted graph, initialization module carries out initialization to the numerical value on undirected weighted graph.Wherein, initialization module is using the current expense of the link overhead between each child node and host node as this child node, then the link overhead between two nodes connected by each link is as the weight of this link, and last initialization module calculates the time-parameters of each child node by the overhead time proportionate relationship preset according to described current expense.Preferably, described time-parameters should be the integral multiple of described current expense, mutually distinguishes to enable the time-parameters of a child node.
For Fig. 3, child node 2, child node 3 and the link overhead between child node 4 and host node 1 are respectively 1,3,5.Link overhead between child node 2 and child node 3 is 1, between child node 2 and child node 4, link overhead is 2, between child node 3 and child node 4, link overhead is 1, and the time-parameters of each child node is 1 times of current expense, so the time-parameters of child node 2, child node 3 and child node 4 is respectively 1,3,5.So initialized undirected weighted graph as shown in Figure 3.
Actual overhead computing module, calculate the actual overhead of described child node when time-parameters reduces to zero for the weight according to described current expense, time-parameters and each link by the actual overhead model preset, and to be calculated by the additive model preset according to the actual overhead of each node and transmission frequency and obtain link overhead corresponding to this replica polymerization node.
After initialization module carries out initialization to undirected weighted graph, actual overhead computing module is solved described undirected weighted graph by the actual overhead computation model preset according to the weight of the current expense of each child node obtained during initialization, time-parameters and each link, obtains the actual overhead of described child node when time-parameters reduces to zero.Described actual overhead and transmission frequency corresponding to each node are substituted into the additive model preset and can calculate and obtain link overhead corresponding to this replica polymerization node by last actual overhead computing module.
Wherein, preferably, the formula of described additive model is:
wherein, Ci is the actual overhead of child node i, and Fi is the transmission frequency of child node i.
Set up the undirected weighted graph of host node and child node by weighted graph creation module after have chosen host node and child node, then initialization module carries out initialization to undirected weighted graph, participate in the calculating of each child node actual overhead as the part of undirected weighted graph by the link overhead between each node, last actual overhead computing module solves the actual overhead obtaining each child node to described undirected weighted graph, and calculates according to the transmission frequency of this actual overhead and each child node the link overhead obtaining this host node.The link overhead of each replica polymerization node is calculated more fast, thus reduces the link overhead when finding best aggregation, strengthen the real-time of intelligent grid wireless sensor network.
In one embodiment, above-mentioned actual overhead computing module can comprise following submodule.
Expense receiver module, receives for current node the actual overhead that other child nodes send respectively, and the time-parameters of the current node that successively decreases;
If other child nodes send actual overhead to current node, then current node receives by expense receiver module the actual overhead that other child nodes send respectively, the time-parameters of the current node that then successively decreases.
For Fig. 3, be the moment of 0 using the weighted graph shown in Fig. 3 as clock signal T, wherein T is rising edge clock signal, trailing edge, high level or low level number.Refer to Fig. 4, in the T=1 moment, the time-parameters of child node 2 is decremented to 0.Now, child node 2 sends the actual overhead of child node 2 to child node 3 and child node 4.Child node 3 and child node 4 receive the actual overhead that child node 2 sends, and the time-parameters of successively decrease child node 3 and child node 4.,
Expense update module, for described actual overhead and corresponding weights and the current expense hour that is less than current node, actual overhead and corresponding weights and the current expense that is updated to current node, multiple connection of laying equal stress on receives actual overhead that other child nodes send until the time-parameters of current node is zero;
When the actual overhead received with corresponding weights and less than the current expense of current node, expense update module by actual overhead and corresponding weights and the current expense that is updated to current node.
As shown in Figure 4, in the T=1 moment, child node 3 and child node 4 have received the actual overhead that child node 2 sends, the current expense of child node 4 is 3, the actual overhead of child node 2 is 1, and the weights between child node 4 and child node 2 are 1, namely to send to host node 1 link overhead that data send directly to host node 1 than child node 4 through the link overhead that child node 2 forwards little for child node 4, and now the current expense of child node 4 is updated to 2 by expense update module.The update mode of the current expense of child node 3 is identical with child node 4, therefore repeats no more.
Then by expense update module, current node judges whether its time-parameters is zero, if non-vanishing, then continue to repeat call overhead receiver module and receives actual overhead that other child nodes send until the time-parameters of current node is zero.
Preferably, also comprise expense discard module, for the actual overhead received and corresponding weights and be more than or equal to child node current expense time, abandon received actual overhead.Abandon received actual overhead in time, effectively can reduce the memory data output of current node, reduce current node and occur congested possibility.
Expense sending module, for when the time-parameters of current node is zero, is judged to be actual overhead by the current expense of current node, and sends the actual overhead of current node to the child node that all time-parameters are non-vanishing.
When the time-parameters of current node is zero, current node can not receive the actual overhead that other child nodes send, the current expense of current node is judged to be the actual overhead of current node by expense sending module, and then expense sending module sends the actual overhead of current node to the child node that all time-parameters are non-vanishing.
For Fig. 5, in the T=3 moment, the time-parameters of child node 4 is decremented to 0, now the current expense of child node 4 is 2, expense sending module is using 2 as the actual overhead of child node 4, and then actual overhead is issued child node 3 (now only have the time-parameters of child node 3 non-vanishing) by expense sending module.
Current node receives by expense receiver module the actual overhead that other child nodes send respectively, and by expense update module when the actual overhead received with corresponding weights and less than the current expense of current node, upgrade the current expense of current node, and when the time-parameters of current node is decremented to zero, be greater than the actual overhead of the child node transmission current node of zero to time-parameters by expense sending module.When the time-parameters vanishing of current node, the actual overhead of this child node is determined, now send actual overhead to the non-vanishing child node of parameter At All Other Times by expense sending module, avoid and actual overhead is issued the child node that time-parameters has been zero, the data traffic volume of current node can be reduced as much as possible, thus substantially reduce the link overhead produced found in best aggregation process.
The above embodiment only have expressed several execution mode of the present invention, and it describes comparatively concrete and detailed, but therefore can not be interpreted as the restriction to the scope of the claims of the present invention.It should be pointed out that for the person of ordinary skill of the art, without departing from the inventive concept of the premise, can also make some distortion and improvement, these all belong to protection scope of the present invention.Therefore, the protection range of patent of the present invention should be as the criterion with claims.
Claims (8)
1. a system of selection for intelligent grid wireless sensor network aggregation, is characterized in that, comprises step:
Link overhead between any two nodes of acquisition intelligent grid wireless sensor network and the transmission frequency of each node;
Respectively with each node for replica polymerization node, calculate the link overhead corresponding to described replica polymerization node according to described link overhead and transmission frequency by undirected weighted graph;
Judge whether the dump energy of each node exceedes energy threshold corresponding to this node respectively, replica polymerization node dump energy being exceeded the node link overhead of corresponding energy threshold minimum is judged to be best aggregation.
2. the system of selection of intelligent grid wireless sensor network aggregation according to claim 1, it is characterized in that, calculate the step of the link overhead corresponding to this replica polymerization node according to described link overhead and transmission frequency by undirected weighted graph, specifically comprise:
With replica polymerization node for other nodes of host node for child node sets up the undirected weighted graph of intelligent grid wireless sensor network;
Current expense using the link overhead between each child node and host node as this child node, and link overhead between two nodes connected using each link is as the weight of this link, and calculated the time-parameters of each child node by the overhead time proportionate relationship preset according to described current expense;
Weight according to described current expense, time-parameters and each link calculates the actual overhead of described child node when time-parameters reduces to zero by the actual overhead model preset, and to be calculated by the additive model preset according to the actual overhead of each node and transmission frequency and obtain link overhead corresponding to this replica polymerization node.
3. the system of selection of intelligent grid wireless sensor network aggregation according to claim 2, it is characterized in that, calculated the step of the actual overhead of described child node when time-parameters reduces to zero according to the weight of described current expense, time-parameters and each link by the actual overhead model preset, specifically comprise:
Current node receives the actual overhead that other child nodes send respectively, and the time-parameters of the current node that successively decreases;
If described actual overhead is little with the current expense being less than current node with corresponding weights, then actual overhead and corresponding weights and the current expense that is updated to current node, multiple connection of laying equal stress on receives actual overhead that other child nodes send until the time-parameters of current node is zero;
When the time-parameters of current node is zero, the current expense of current node is judged to be actual overhead, and sends the actual overhead of current node to the child node that all time-parameters are non-vanishing.
4. the system of selection of intelligent grid wireless sensor network aggregation according to claim 3, is characterized in that, if described actual overhead and corresponding weights and the current expense that is more than or equal to current node, then abandon received actual overhead.
5. a selective system for intelligent grid wireless sensor network aggregation, is characterized in that, comprising:
Acquisition module, for obtaining the transmission frequency of link overhead between any two nodes of intelligent grid wireless sensor network and each node;
Overhead computing module, for respectively with each node for replica polymerization node, calculate the link overhead corresponding to this replica polymerization node according to described link overhead and transmission frequency by undirected weighted graph;
Determination module, for judging whether the dump energy of each node exceedes energy threshold corresponding to this node respectively, replica polymerization node dump energy being exceeded the node link overhead of corresponding energy threshold minimum is judged to be best aggregation.
6. the selective system of intelligent grid wireless sensor network aggregation according to claim 5, is characterized in that, described overhead computing module comprises:
Weighted graph creation module, for replica polymerization node for other nodes of host node for child node sets up the undirected weighted graph of intelligent grid wireless sensor network;
Initialization module, for the current expense using the link overhead between each child node and host node as this child node, using the link overhead between two nodes that each link connects as the weight of this link, and calculated the time-parameters of each node by the overhead time proportionate relationship preset according to described current expense;
Actual overhead computing module, calculate the actual overhead of described child node when time-parameters reduces to zero for the weight according to described current expense, time-parameters and each link by the actual overhead model preset, and to be calculated by the additive model preset according to the actual overhead of each node and transmission frequency and obtain link overhead corresponding to this replica polymerization node.
7. the selective system of intelligent grid wireless sensor network aggregation according to claim 6, is characterized in that, described actual overhead computing module comprises:
Expense receiver module, receives for current node the actual overhead that other child nodes send respectively, and the time-parameters of the current node that successively decreases;
Expense update module, for described actual overhead and corresponding weights and the current expense hour that is less than current node, actual overhead and corresponding weights and the current expense that is updated to current node, multiple connection of laying equal stress on receives actual overhead that other child nodes send until the time-parameters of current node is zero;
Expense sending module, for when the time-parameters of current node is zero, is judged to be actual overhead by the current expense of current node, and sends the actual overhead of current node to the child node that all time-parameters are non-vanishing.
8. the selective system of intelligent grid wireless sensor network aggregation according to claim 7, is characterized in that, also comprise:
Expense discard module, if for described actual overhead and corresponding weights and be more than or equal to current node current expense time, abandon received actual overhead.
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