CN108769843B - A kind of EPON network optimization method and system for power fiber to the home - Google Patents

Abstract

The invention provides an EPON network optimization method for power optical fiber to the home, including obtaining the OPLC laying network topology of the area to be planned; based on the OPLC laying network topology, establishing a network construction cost model, a network average delay model and a load balancing model; Minimizing network construction cost and average network delay is the optimization goal, with load balancing and OLT access restrictions as constraints, an EPON network optimization model is established; a weight ratio is specified for network construction cost and network average delay, and the EPON network is optimized. The model is solved. The invention combines the actual use and laying scenarios of power optical fiber to the home, flexibly selects the number and location of OLTs, proposes concise and practical index models that meet actual application requirements, and proposes a heuristic EPON solution method to obtain the "global optimal solution", and further Improve resource utilization efficiency and reduce network construction and operation costs. The invention also discloses an EPON network optimization system with power fiber to the home.

Description

A kind of EPON network optimization method and system for power fiber to the home

technical field

The invention relates to the field of computer technology, in particular to an EPON network optimization method and system for power optical fiber to the home.

Background technique

Communication technology is a strong support for the realization of smart grid, triple play, and automatic demand response. Power fiber to the home refers to the use of OPLC (Optical Fiber Composite Low-Voltage Cable, fiber composite low-voltage cable) on the power distribution side to realize the laying of optical fibers with low-voltage power lines to the home, with EPON (Ethernet Passive Optical Network, Ethernet Passive Optical Network) The technology solves the "last mile" problem and meets the user's information, automation and intelligent electricity consumption and living needs. Compared with traditional FTTH (Fiber To the Home, fiber to the home), it greatly reduces the implementation cost, saves resources and improves operational efficiency.

The EPON network planning problem directly affects the implementation effect of power fiber-to-the-home. In the early stage of construction of my country's power communication network, the focus was on catching up with the scale of the power network. Today, this speed-based and extensive construction has been unable to meet the intelligent development needs of my country's power communication network due to hidden dangers and lack of planning. Seeking careful and comprehensive EPON network planning can further improve resource utilization efficiency, reduce network construction and operating costs, provide a good user experience, and effectively support the robustness, reliability and cost-effectiveness of smart grids. Therefore, it is of great significance to study the optimization method of EPON network for the development of my country's smart grid.

In the existing EPON network optimization methods, the number and location of OLTs are generally pre-specified, which will constrain the communication topology to a large extent. It affects the structure of the communication network, which in turn affects the communication performance; secondly, the selection and modeling of the optimization objectives and constraints in the existing EPON network optimization methods do not fully consider the on-site situation of the power fiber to the home, and each index model used has engineering characteristics. The practicability is poor; thirdly, the specified constraints are used in the existing EPON network optimization methods to limit the selected planning scheme, so the obtained optimization scheme may be far from the optimal solution, or even far from the optimal solution.

SUMMARY OF THE INVENTION

In view of this, the present invention provides an EPON network optimization method and system for power fiber to the home. The present invention combines the actual use and laying scenarios of power fiber to the home, flexibly selects the number and location of OLTs, and proposes a concise and practical application. Based on the full understanding of the profound connotation of each index, a heuristic solution method is proposed, so that the solution process can converge to a better "global optimal solution" more quickly and effectively, and further improve the efficiency of resource utilization. Reduce network construction and operating costs.

The invention provides an EPON network optimization method for power optical fiber to the home, the method comprises the following steps:

S1, obtain the OPLC laying network topology of the area to be planned;

S2, based on the OPLC laying network topology, establish a network construction cost model, a network average delay model and a load balancing model;

S3, with the optimization goal of minimizing the network construction cost and the average network delay, and the constraints of load balancing and OLT access restrictions, an EPON network optimization model is established;

S4, a weight ratio is specified for the network construction cost and the average network delay, and the EPON network optimization model is solved.

Preferably, the method further includes:

Normalize the network construction cost model and the network average delay model.

Preferably, the method further includes:

Based on the OPLC laying network topology, the distance from the ONU node to the OLT node is selected as the judgment value, the distance threshold is selected according to the size of the area to be planned, and on the premise of satisfying the OLT access restrictions, the EPON network optimization model is obtained through clustering the initial solution of .

Preferably, the obtaining the OPLC laying network topology of the area to be planned includes:

obtaining the distribution network structure information of the to-be-planned area;

Selecting the location nodes where the OLT can be installed in the to-be-planned area based on the distribution network structure information, and numbering them in the order of locations;

Numbering the location nodes of all ONUs on the user side in the to-be-planned area based on the distribution network structure information in a location sequence;

Calculate the actual power line laying distance from the location node of the ONU to each of the location nodes where the OLT can be installed.

Preferably, the network construction cost model described in step S2 is as follows:

Among them, C is the network construction cost, C ₁ is the construction cost of the power optical cable per unit distance, C ₂ is the construction cost of one OLT node, N is the number of OLT nodes that can be built in the area to be planned, and M is the area to be planned that needs full coverage Number of users, d _nm is the distance from the mth ONU node to the nth OLT node, where 0<n≤N, 0<m≤M, e _nm is a 0-1 variable, where e _nm =1 means The nth OLT is connected to the mth ONU, and e _nm =0 indicates that the nth OLT is not connected to the mth ONU;

Preferably, the network average delay model described in step S2 is as follows:

Among them, T is the average transmission delay of the network, T _OLT is the processing delay of the OLT node, T _ONU is the processing delay of the ONU node, T _line is the line transmission delay of the network, and M is the user who needs full coverage in the area to be planned. quantity.

Preferably, the load balancing model in step S2 is as follows:

Among them, D(x _n ) is the mean square error of the number of ONU node accesses of the selected OLT node, x _n is the number of ONU node accesses of the nth OLT node, E(x _n ) is the average value of x _n , N is the number of OLT nodes that can be built in the area to be planned, M is the number of users that need full coverage in the area to be planned, d _nm is the distance from the mth ONU node to the nth OLT node, where 0<n≤N, 0<m≤M, e _nm is a 0-1 variable, where e _nm =1 indicates that the n th OLT is connected to the m th ONU, and e _nm =0 indicates that the n th OLT is not connected to the m th ONU.

Preferably, the step S3 includes:

Taking minimizing the network construction cost and the average network delay as the core optimization goals, and taking the load balancing and OLT access restrictions as constraints, the EPON network optimization model is obtained:

F=min(α·C+β·T)

C为建设成本，T为网络平均传输延时，α为建设成本的权重系数，β为网络平均延时的权重系数，α、β分别表示网络规划时对两项参数的重视程度，且α+β＝1，D(x_n)为选中的OLT节点的ONU节点接入数量的均方差，D(x_n)广义的取值范围为[0，+∞)，其一方面是网络规划的约束条件，另一方面也为EPON网络优化模型提供求解初始值；x_n为第n个OLT节点的ONU节点接入数量，X为OLT允许接入ONU数量的上限值，N为待规划区域可建OLT节点的数量。where D _max is the maximum value of D(x _n ),

C is the construction cost, T is the average transmission delay of the network, α is the weight coefficient of the construction cost, β is the weight coefficient of the average delay of the network, α and β respectively indicate the importance of the two parameters in network planning, and α+ β=1, D(x _n ) is the mean square error of the number of ONU nodes connected to the selected OLT node, and the generalized value range of D(x _n ) is [0, +∞), on the one hand, it is a constraint of network planning On the other hand, it also provides the initial value of the solution for the EPON network optimization model; x _n is the number of ONU nodes connected to the nth OLT node, X is the upper limit of the number of ONUs allowed by the OLT, and N is the available area to be planned. The number of OLT nodes to be built.

The invention provides an EPON network optimization system for power fiber-to-the-home, the system includes:

Obtaining module: used to obtain the OPLC laying network topology of the area to be planned;

The first modeling module: used for laying a network topology based on the OPLC, and establishing a network construction cost model, a network average delay model and a load balancing model;

The second modeling module: used to minimize the network construction cost and the average network delay as the optimization goal, with load balancing and OLT access restrictions as constraints, to establish an EPON network optimization model;

Solving module: used to specify a weight ratio for the network construction cost and the average network delay, and solve the EPON network optimization model.

As can be seen from the above technical solutions, the present invention provides an EPON network optimization method for power optical fiber to the home, including obtaining the OPLC laying network topology of the area to be planned; Average delay model and load balancing model; with the optimization goal of minimizing network construction cost and network average delay, and with load balancing and OLT access restrictions as constraints, an EPON network optimization model is established; When specifying a weight ratio, the EPON network optimization model is solved. The invention combines the actual use and laying scenarios of power optical fiber to the home, flexibly selects the number and location of OLTs, proposes concise and practical index models that meet the needs of practical applications, and proposes heuristic solutions on the basis of fully understanding the profound connotation of each index. This method makes the solution process converge to a better "global optimal solution" more quickly and effectively, further improves resource utilization efficiency, and reduces network construction and operation costs.

Description of drawings

In order to explain the embodiments of the present invention or the technical solutions in the prior art more clearly, the following briefly introduces the accompanying drawings that need to be used in the description of the embodiments or the prior art. Obviously, the accompanying drawings in the following description are only These are some embodiments of the present invention. For those of ordinary skill in the art, other drawings can also be obtained according to these drawings without creative efforts.

Fig. 1 is the method flow chart of Embodiment 1 of the EPON network optimization method of a kind of power fiber-to-the-home disclosed by the present invention;

2 is a schematic structural diagram of Embodiment 1 of an EPON network optimization system of a power fiber-to-the-home disclosed in the present invention;

FIG. 3 is a schematic diagram of a power optical fiber laying topology of a planning example disclosed in the present invention;

4 is a schematic diagram of a planning result obtained by solving the power optical fiber laying topology of the planning example shown in FIG. 3 when α<β using the EPON network optimization method disclosed in the present invention;

FIG. 5 is a schematic diagram of a planning result obtained by solving the power optical fiber laying topology of the planning example shown in FIG. 3 when α > β using the EPON network optimization method of the present application disclosed in the present invention.

Detailed ways

The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

As shown in FIG. 1, it is a method flow chart of Embodiment 1 of an EPON network optimization method for power fiber-to-the-home disclosed in the present invention, and the method includes:

S101, obtaining the OPLC laying network topology of the area to be planned;

The power optical cable is constructed along the primary line of the distribution network, so the EPON network planning of the distribution network is related to the erection structure of the distribution network. Before planning and optimizing the EPON network, it is necessary to obtain the structural information of the OPLC laying network in the required planning area.

S102, based on the OPLC laying network topology, establish a network construction cost model, a network average delay model and a load balancing model;

After the OPLC laying network topology is obtained, the relevant optimization indicators and constraints are modeled according to the specific number and location information of each OLT node and ONU node in the OPLC laying network topology in the area to be planned. The constraint indicators include network construction cost and network Average delay, the constraint condition is load balancing, that is, to provide equal bandwidth and service usage conditions as much as possible.

S103, with the optimization goal of minimizing the network construction cost and the average network delay, and the load balancing and OLT access restrictions as constraints, establish an EPON network optimization model;

According to each optimization index model and constraint condition model, considering network load balancing and OLT access restrictions, and taking minimizing network construction cost and average network delay as the core optimization goals, an EPON network optimization model is established.

S104 , specifying a weight ratio for the network construction cost and the average network delay, and solving the EPON network optimization model.

According to the established EPON network optimization model, a weight ratio is set for the network construction cost and the average network delay in the model, and the intelligent search algorithm is used to solve the model quickly to obtain the optimal solution based on the set weight ratio.

To sum up, in the above embodiment, first obtain the OPLC laying network topology of the area to be planned; then based on the OPLC laying network topology, establish a network construction cost model, a network average delay model and a load balancing model; then minimize the network The construction cost and average network delay are the optimization goals, and the EPON network optimization model is established with load balancing and OLT access restrictions as constraints; Solve. The invention combines the actual use and laying scene of the power fiber to the home, flexibly selects the number and position of the OLT (Optical Line Terminal), proposes a concise model of each index that meets actual application requirements, and fully understands the profound connotation of each index. On the basis of , a heuristic solution method is proposed to make the solution process converge to a better "global optimal solution" more quickly and effectively, further improve resource utilization efficiency, and reduce network construction and operation costs.

Specifically, in the above embodiment, when acquiring the OPLC laying network topology of the to-be-planned area, first obtain the required distribution network structure information of the to-be-planned area. The OLT of the EPON network is generally installed in the distribution box or the distribution room where the outgoing lines are relatively concentrated. Select the location nodes where the OLT can be installed in the area to be planned, and number them according to the location sequence. The ONU (Optical Network Unit) is installed on the user side, and the candidate optical splitter is installed at the same location as the ONU, and all ONU nodes are numbered in the same location sequence. Calculate the actual power line laying distance from the ONU node to each buildable OLT node, and obtain the distance information of the planned network. Assuming that the number of nodes that can build an OLT in the planned network is N, and the number of users requiring full coverage is M, the distance from the mth ONU node to the nth OLT node is d _nm , where 0<n≤N, 0<m≤M.

Specifically, in the above embodiment, the network construction cost and the average network delay are used as optimization indicators. Among them, in the process of establishing the network construction cost model:

The construction cost of the network considers the construction cost of the OLT node, the cost of line laying, and the construction cost of the ONU node. Since all ONU nodes in the planning area need to be fully covered, the construction cost model of any planning scheme includes the construction cost of all ONU nodes, so the construction cost of ONU nodes can be ignored in the construction cost model.

Let e _nm be a 0-1 variable, that is:

Assuming that the laying cost of the power optical cable per unit distance is C ₁ , and the construction cost of one OLT node is C ₂ , the construction cost model is:

During the establishment of the network average delay model:

The average transmission delay T of the network needs to consider the processing delay T _OLT of the OLT node and the processing delay T _ONU of the ONU node and the line transmission delay T _line of the power fiber.

Among them, T _OLT and T _ONU are relatively small and can be regarded as fixed values. Using c to represent the speed of light, the line transmission delay of the network is:

Specifically, in the above embodiment, the load balancing model is used as the constraint condition for establishing and solving the EPON network optimization model. Among them, in the process of establishing the load balancing model:

Because the power fiber to the home treats all users in the planned area equally, that is, to provide equal bandwidth and service usage conditions as much as possible, so that the random or blowout network operation needs of users can be met at any time. In order to achieve this balanced configuration, the power optical fiber network should distribute the number of ONU nodes connected to it as evenly as possible within the scope of OLT access restrictions. The load balancing model described in this application is expressed by the mean square error of the number of ONU node accesses of each selected OLT node.

The ONU node access number x _n of the nth OLT node is:

x _n should be less than the upper limit X of the number of ONUs allowed by the OLT, namely:

x _n ≤X n = 1,2...N

The mean of x _n is:

Then the load balancing model is:

Specifically, in the above embodiment, in the process of establishing the EPON network optimization model, the network construction cost model and the network average delay model may also be normalized first. Among them, in the process of normalizing the network construction cost model:

Since the area to be planned is selected, the network topology of the actual power line laying can be determined by sensor measurement, so the laying cost C _line of the power fiber is determined, so the maximum construction cost is the case where all M OLT nodes are constructed:

C _max =C _line +M·C ₁

Then the normalized construction cost is:

In the process of normalizing the network average delay model:

The maximum value of the average network delay is when each ONU node is connected to the OLT with the farthest communication distance:

Then the normalized average network delay is:

Specifically, in the above-mentioned embodiment, in establishing the EPON network optimization model: considering network load balancing and OLT access restrictions, and taking minimizing the network construction cost and the average network delay as the core optimization goals, the EPON network optimization model is obtained as: :

F=min(α·C+β·T)

C为建设成本，T为网络平均传输延时，α为建设成本的权重系数，β为网络平均延时的权重系数，α、β分别表示网络规划时对两项参数的重视程度，且α+β＝1，D(x_n)为选中的OLT节点的ONU节点接入数量的均方差，D(x_n)广义的取值范围为[0，+∞)，其一方面是网络规划的约束条件，另一方面也为EPON网络优化模型提供求解初始值；x_n为第n个OLT节点的ONU节点接入数量，X为OLT允许接入ONU数量的上限值，N为待规划区域可建OLT节点的数量。where D _max is the maximum value of D(x _n ),

C is the construction cost, T is the average transmission delay of the network, α is the weight coefficient of the construction cost, β is the weight coefficient of the average delay of the network, α and β respectively indicate the importance of the two parameters in network planning, and α+ β=1, D(x _n ) is the mean square error of the number of ONU nodes connected to the selected OLT node, and the generalized value range of D(x _n ) is [0, +∞), on the one hand, it is a constraint of network planning On the other hand, it also provides the initial value of the solution for the EPON network optimization model; x _n is the number of ONU nodes connected to the nth OLT node, X is the upper limit of the number of ONUs allowed by the OLT, and N is the available area to be planned. The number of OLT nodes to be built.

Specifically, in the above embodiment, in the process of solving the EPON network optimization model:

Considering the constraints of network load balancing, the planning strategy should make the ONU nodes access the selected OLT nodes as evenly as possible. Inspired by this, based on the natural construction attributes of distribution boxes or distribution rooms in the power fiber laying area and the corresponding distribution of user groups, the distance d _nm from the ONU node to the OLT node is selected (where 0<n≤N, 0<m≤ M) As the judgment amount, the distance threshold D _th is selected according to the size of the planning area, and on the premise of satisfying the OLT access restriction, the initial planning solution of the model solution is given by clustering. The initial solution given in this way has good load balance, and the initial solution obtained by clustering combines the distribution characteristics, so that the intelligent search algorithm can quickly and accurately converge to the optimal solution. Among them, the intelligent search algorithm may specifically be a genetic algorithm, a simulated annealing algorithm, a tabu search algorithm, an artificial neural network, a particle swarm algorithm, and the like.

As shown in FIG. 2 , it is a schematic structural diagram of Embodiment 1 of an EPON network optimization system for power fiber-to-the-home disclosed in the present invention, and the system includes:

Obtaining module 201: used to obtain the OPLC laying network topology of the area to be planned;

The power optical cable is constructed along the primary line of the distribution network, so the EPON network planning of the distribution network is related to the erection structure of the distribution network. Before planning and optimizing the EPON network, it is necessary to obtain the structural information of the OPLC laying network in the required planning area.

The first modeling module 202: used for laying a network topology based on the OPLC, and establishing a network construction cost model, an average network delay model and a load balancing model;

After the OPLC laying network topology is obtained, the relevant optimization indicators and constraints are modeled according to the specific number and location information of each OLT node and ONU node in the OPLC laying network topology in the area to be planned. The constraint indicators include network construction cost and network Average delay, the constraint condition is load balancing, that is, to provide equal bandwidth and service usage conditions as much as possible.

The second modeling module 203: used to minimize the network construction cost and the average network delay as the optimization goal, and use the load balancing and OLT access restrictions as the constraints to establish an EPON network optimization model;

According to each optimization index model and constraint condition model, considering network load balancing and OLT access restrictions, and taking minimizing network construction cost and average network delay as the core optimization goals, an EPON network optimization model is established.

Solving module 204: used to specify a weight ratio for the network construction cost and the average network delay, and solve the EPON network optimization model.

According to the established EPON network optimization model, a weight ratio is set for the network construction cost and the average network delay in the model, and the intelligent search algorithm is used to solve the model quickly to obtain the optimal solution based on the set weight ratio.

To sum up, in the above-mentioned embodiment, the OPLC laying network topology of the area to be planned is first obtained through the obtaining module 201; then the network construction cost model and the average network delay are established through the first modeling module 202 based on the OPLC laying network topology. model and load balancing model; then through the second modeling module 203 to minimize the network construction cost and the average network delay as the optimization goal, with load balancing and OLT access restrictions as constraints, establish the EPON network optimization model; finally by solving The module 204 specifies a weight ratio for the network construction cost and the average network delay, and solves the EPON network optimization model. The invention combines the actual use and laying scenarios of the power fiber to the home, flexibly selects the number and position of the OLT (Optical Line Terminal), proposes a concise and practical index model that meets the requirements of practical applications, and fully understands the profound connotation of each index. On this basis, a heuristic solution method is proposed to make the solution process converge to a better "global optimal solution" more quickly and effectively, further improving resource utilization efficiency and reducing network construction and operation costs.

Specifically, in the above embodiment, when acquiring the OPLC laying network topology of the to-be-planned area, first obtain the required distribution network structure information of the to-be-planned area. The OLT of the EPON network is generally installed in the distribution box or the distribution room where the outgoing lines are relatively concentrated. Select the location nodes where the OLT can be installed in the area to be planned, and number them according to the location sequence. The ONU (Optical Network Unit) is installed on the user side, and the candidate optical splitter is installed at the same location as the ONU, and all ONU nodes are numbered in the same location sequence. Calculate the actual power line laying distance from the ONU node to each buildable OLT node, and obtain the distance information of the planned network. Assuming that the number of nodes that can build an OLT in the planned network is N, and the number of users requiring full coverage is M, the distance from the mth ONU node to the nth OLT node is d _nm , where 0<n≤N, 0<m≤M.

Specifically, in the above embodiment, the network construction cost and the average network delay are used as optimization indicators. Among them, in the process of establishing the network construction cost model:

The construction cost of the network considers the construction cost of the OLT node, the cost of line laying, and the construction cost of the ONU node. Since all ONU nodes in the planning area need to be fully covered, the construction cost model of any planning scheme includes the construction cost of all ONU nodes, so the construction cost of ONU nodes can be ignored in the construction cost model.

Let e _nm be a 0-1 variable, that is:

Assuming that the laying cost of the power optical cable per unit distance is C ₁ , and the construction cost of one OLT node is C ₂ , the construction cost model is:

During the establishment of the network average delay model:

The average transmission delay T of the network needs to consider the processing delay T _OLT of the OLT node and the processing delay T _ONU of the ONU node and the line transmission delay T _line of the power fiber.

Among them, T _OLT and T _ONU are relatively small and can be regarded as fixed values. Using c to represent the speed of light, the line transmission delay of the network is:

Specifically, in the above embodiment, the load balancing model is used as the constraint condition for establishing and solving the EPON network optimization model. Among them, in the process of establishing the load balancing model:

Because the power fiber to the home treats all users in the planned area equally, that is, to provide equal bandwidth and service usage conditions as much as possible, so that the random or blowout network operation needs of users can be met at any time. In order to achieve this balanced configuration, the power optical fiber network should distribute the number of ONU nodes connected to it as evenly as possible within the scope of OLT access restrictions. The load balancing model described in this application is expressed by the mean square error of the number of ONU node accesses of each selected OLT node.

The ONU node access number x _n of the nth OLT node is:

x _n should be less than the upper limit X of the number of ONUs allowed by the OLT, namely:

x _n ≤X n = 1,2...N

The mean of x _n is:

Then the load balancing model is:

Specifically, in the above embodiment, in the process of establishing the EPON network optimization model, the network construction cost model and the network average delay model may also be normalized first. Among them, in the process of normalizing the network construction cost model:

Since the area to be planned is selected, the network topology of the actual power line laying can be determined by sensor measurement, so the laying cost C _line of the power fiber is determined, so the maximum construction cost is the case where all M OLT nodes are constructed:

C _max =C _line +M·C ₁

Then the normalized construction cost is:

In the process of normalizing the network average delay model:

The maximum value of the average network delay is when each ONU node is connected to the OLT with the farthest communication distance:

Then the normalized average network delay is:

Specifically, in the above-mentioned embodiment, in establishing the EPON network optimization model: considering network load balancing and OLT access restrictions, and taking minimizing the network construction cost and the average network delay as the core optimization goals, the EPON network optimization model is obtained as: :

F=min(α·C+β·T)

C为建设成本，T为网络平均传输延时，α为建设成本的权重系数，β为网络平均延时的权重系数，α、β分别表示网络规划时对两项参数的重视程度，且α+β＝1，D(x_n)为选中的OLT节点的ONU节点接入数量的均方差，D(x_n)广义的取值范围为[0，+∞)，其一方面是网络规划的约束条件，另一方面也为EPON网络优化模型提供求解初始值；x_n为第n个OLT节点的ONU节点接入数量，X为OLT允许接入ONU数量的上限值，N为待规划区域可建OLT节点的数量。where D _max is the maximum value of D(x _n ),

C is the construction cost, T is the average transmission delay of the network, α is the weight coefficient of the construction cost, β is the weight coefficient of the average delay of the network, α and β respectively indicate the importance of the two parameters in network planning, and α+ β=1, D(x _n ) is the mean square error of the number of ONU nodes connected to the selected OLT node, and the generalized value range of D(x _n ) is [0, +∞), on the one hand, it is a constraint of network planning On the other hand, it also provides the initial value of the solution for the EPON network optimization model; x _n is the number of ONU nodes connected to the nth OLT node, X is the upper limit of the number of ONUs allowed by the OLT, and N is the available area to be planned. The number of OLT nodes to be built.

Specifically, in the above embodiment, in the process of solving the EPON network optimization model:

Considering the constraints of network load balancing, the planning strategy should make the ONU nodes access the selected OLT nodes as evenly as possible. Inspired by this, based on the natural construction attributes of distribution boxes or distribution rooms in the power fiber laying area and the corresponding distribution of user groups, the distance d _nm from the ONU node to the OLT node is selected (where 0<n≤N, 0<m≤ M) As the judgment amount, the distance threshold D _th is selected according to the size of the planning area, and on the premise of satisfying the OLT access restriction, the initial planning solution of the model solution is given by clustering. The initial solution given in this way has good load balance, and the initial solution obtained by clustering combines the distribution characteristics, so that the intelligent search algorithm can quickly and accurately converge to the optimal solution. Among them, the intelligent search algorithm may specifically be a genetic algorithm, a simulated annealing algorithm, a tabu search algorithm, an artificial neural network, a particle swarm algorithm, and the like.

As shown in FIG. 3 , it is a schematic diagram of the power optical fiber laying topology of the planning example disclosed in the present invention, and a network topology diagram of a power optical fiber laying area measured by a sensor is given. The node is an ONU node that needs full coverage. The distance d _nm (0<n≤N=4, 0<m≤M=11) from the mth ONU node to the nth OLT node is calculated according to the actual length of the power optical fiber obtained by measurement.

According to the EPON network optimization method of the present invention, the network is planned, and the planning results are obtained in the two cases of α<β and α>β, which pay more attention to the average delay of the network and the construction cost, as shown in Figure 4 and shown in Figure 5. The dotted box in the figure shows the relationship between each ONU node and its corresponding connected OLT node. The load balancing constraints D(x _n ) of the corresponding optimization results are also given correspondingly. Wherein, as a constraint condition, D _max =20.25, D(x _n )=0.185 in FIG. 4 , and D(x _n )=0.25 in FIG. 5 . Compared with the traditional method of manually specifying the EPON network and considering only a single indicator or simply integrating multiple complex indicators, the optimization model proposed in this patent can provide users with equal bandwidth and service usage conditions as much as possible in terms of performance. The user's random or blowout network operation needs can be met at the first time at all times.

The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments, and the same and similar parts between the various embodiments can be referred to each other. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant part can be referred to the description of the method.

Professionals may further realize that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two, in order to clearly illustrate the possibilities of hardware and software. Interchangeability, the above description has generally described the components and steps of each example in terms of function. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Skilled artisans may implement the described functionality using different methods for each particular application, but such implementations should not be considered beyond the scope of the present invention.

The steps of a method or algorithm described in conjunction with the embodiments disclosed herein may be directly implemented in hardware, a software module executed by a processor, or a combination of the two. The software module can be placed in random access memory (RAM), internal memory, read only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, removable disk, CD-ROM, or any other in the technical field. in any other known form of storage medium.

The above description of the disclosed embodiments enables any person skilled in the art to make or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims (9)

1. a kind of EPON network optimization method of power optical fiber to the home, is characterized in that, comprises the steps: S1, obtain the OPLC laying network topology of the area to be planned; S2, based on the OPLC laying network topology, establish a network construction cost model, an average network delay model and a load balancing model; wherein, the network construction cost model is established at least according to the construction cost of the OLT node and the line laying cost; according to the OLT The processing delay of the node, the processing delay of the ONU node and the line transmission delay of the power fiber are used to establish the network average delay model; the mean square error of the ONU node access number of each selected OLT node is used to express the load balancing model. ; S3, with the optimization goal of minimizing the network construction cost and the average network delay, and the constraints of load balancing and OLT access restrictions, an EPON network optimization model is established; S4, a weight ratio is specified for the network construction cost and the average network delay, and the EPON network optimization model is solved. 2. The method of claim 1, further comprising: Normalize the network construction cost model and the network average delay model. 3. The method of claim 1, further comprising: Based on the OPLC laying network topology, the distance from the ONU node to the OLT node is selected as the judgment value, the distance threshold is selected according to the size of the area to be planned, and on the premise of satisfying the OLT access restrictions, the EPON network optimization model is obtained through clustering the initial solution of . 4. The method according to claim 1, wherein the obtaining the OPLC laying network topology of the area to be planned comprises: obtaining the distribution network structure information of the to-be-planned area; Selecting the location nodes where the OLT can be installed in the to-be-planned area based on the distribution network structure information, and numbering them in the order of locations; Numbering the location nodes of all ONUs on the user side in the to-be-planned area based on the distribution network structure information in a location sequence; Calculate the actual power line laying distance from the location node of the ONU to each of the location nodes where the OLT can be installed. 5. The method according to claim 1, wherein the network construction cost model described in step S2 is as follows:

Among them, C is the network construction cost, C ₁ is the construction cost of the power optical cable per unit distance, C ₂ is the construction cost of one OLT node, N is the number of OLT nodes that can be built in the area to be planned, and M is the area to be planned that needs full coverage The number of users, d _nm is the distance from the mth ONU node to the nth OLT node, where 0<n≤N, 0<m≤M, e _nm is a 0-1 variable, where e _nm =1 means The nth OLT is connected to the mth ONU, and e _nm =0 indicates that the nth OLT is not connected to the mth ONU. 6. The method according to claim 1, wherein the average network delay model described in step S2 is as follows:

Among them, T is the average transmission delay of the network, T _OLT is the processing delay of the OLT node, T _ONU is the processing delay of the ONU node, T _line is the line transmission delay of the network, and M is the user who needs full coverage in the area to be planned. quantity. 7. The method according to claim 1, wherein the load balancing model described in step S2 is as follows:

Among them, D(x _n ) is the mean square error of the number of ONU node accesses of the selected OLT node, x _n is the number of ONU node accesses of the nth OLT node, E(x _n ) is the average value of x _n , N is the number of OLT nodes that can be built in the area to be planned, M is the number of users that need full coverage in the area to be planned, d _nm is the distance from the mth ONU node to the nth OLT node, where 0<n≤N, 0<m≤M, e _nm is a 0-1 variable, where e _nm =1 indicates that the n th OLT is connected to the m th ONU, and e _nm =0 indicates that the n th OLT is not connected to the m th ONU. 8. The method according to claim 1, wherein the step S3 comprises: Taking minimizing the network construction cost and the average network delay as the core optimization goals, and taking the load balancing and OLT access restrictions as constraints, the EPON network optimization model is obtained: F=min(α.C+β.T)

where D _max is the maximum value of D(x _n ),

C is the construction cost, T is the average transmission delay of the network, α is the weight coefficient of the construction cost, β is the weight coefficient of the average delay of the network, α and β respectively indicate the importance of the two parameters in network planning, and α+ β=1, D(x _n ) is the mean square error of the number of ONU nodes connected to the selected OLT node, and the generalized value range of D(x _n ) is [0, +∞), on the one hand, it is a constraint of network planning On the other hand, it also provides the initial value of the solution for the EPON network optimization model; x _n is the number of ONU nodes connected to the nth OLT node, X is the upper limit of the number of ONUs allowed by the OLT, and N is the available area to be planned. The number of OLT nodes to be built. 9. An EPON network optimization system of electric power fiber to the home, is characterized in that, comprises: Obtaining module: used to obtain the OPLC laying network topology of the area to be planned; The first modeling module is used to establish a network construction cost model, a network average delay model and a load balancing model based on the OPLC laying network topology; wherein, the network is established at least according to the construction cost of the OLT node and the line laying cost Build the cost model; establish the average network delay model according to the processing delay of the OLT node, the processing delay of the ONU node and the line transmission delay of the power fiber; adopt the mean square error of the number of ONU node accesses of each selected OLT node expressing the load balancing model; The second modeling module: used to minimize the network construction cost and the average network delay as the optimization goal, with load balancing and OLT access restrictions as constraints, to establish an EPON network optimization model; Solving module: used to specify a weight ratio for the network construction cost and the average network delay, and solve the EPON network optimization model.

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