CN107786449B - FSR protocol-based path selection method, device, server and storage medium - Google Patents
FSR protocol-based path selection method, device, server and storage medium Download PDFInfo
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Abstract
The invention discloses a path selection method, a device, a server and a storage medium based on an FSR protocol, wherein the method comprises the following steps: determining objective weight of each index according to sample data corresponding to each index in the pre-acquired ad hoc network; calculating a metric value between each adjacent node in the ad hoc network according to the objective weight of each index and pre-acquired real-time communication quality data of the ad hoc network, wherein the real-time communication quality data are data which are acquired between each adjacent node of the ad hoc network in real time and correspond to each index; calculating the metric values of all paths from the starting node to the destination node in the ad hoc network according to the metric values between the adjacent nodes; and taking the path with the minimum metric value of the path as the optimal path between the starting node and the destination node. The invention realizes the accurate selection of the optimal path with the best communication quality in the ad hoc network by comprehensively considering each index of the ad hoc network and accurately determining the objective weight of each index.
Description
Technical Field
The invention relates to the technical field of computer networks, in particular to a path selection method, a path selection device, a path selection server and a storage medium based on an FSR protocol.
Background
The self-organizing network is a network combining mobile communication and computer network, each node in the self-organizing network has the function of a router, namely an optimal transmission path is found for a data packet passing through the router, and the data is quickly, accurately and efficiently transmitted to a destination node in the shortest possible time.
In the FSR (fish eye State Routing Protocol) Protocol, Dijkstra's algorithm is typically used to compute the shortest path in an ad hoc network. The Dijkstra algorithm is centered on an initial node, expands layer by layer to a destination node according to the topological structure of the network, and measures and compares all paths passing through the Dijkstra algorithm to select the shortest path. The traditional Dijkstra algorithm can assign a designated weight to a designated evaluation index in the network according to the needs of users, and calculate the metric value of the path according to the data of each index in the path and the given weight of each index, thereby selecting the path with the minimum metric value of the path as the shortest path.
However, the traditional Dijkstra algorithm only uses the designated index as the measurement basis of the path, and the weight of each index is determined according to the needs of the user, so that the subjectivity is high. Therefore, the influence of other index parameters in QoS (Quality of Service) is not fully considered, and objective weights are not given to each index according to the influence of different importance degrees of each index on network transmission, so that the calculation of the path metric value is not accurate enough, and the selection of the optimal path is not accurate enough.
Disclosure of Invention
The embodiment of the invention provides a path selection method, a device, a server and a storage medium based on an FSR protocol, which can accurately select an optimal path with the best communication quality in an ad hoc network.
In a first aspect, an embodiment of the present invention provides a path selection method based on an FSR protocol, which is applied to a fisheye state routing protocol FSR, and the method includes:
determining objective weight of each index according to sample data corresponding to each index in the pre-acquired ad hoc network;
calculating a metric value between each adjacent node in the ad hoc network according to the objective weight of each index and pre-acquired real-time communication quality data of the ad hoc network, wherein the real-time communication quality data are data which are acquired between each adjacent node of the ad hoc network in real time and correspond to each index;
calculating the metric values of all paths from the starting node to the destination node in the ad hoc network according to the metric values between the adjacent nodes;
and taking the path with the minimum metric value of the path as the optimal path from the starting node to the destination node.
In a second aspect, an embodiment of the present invention provides a path selection apparatus based on an FSR protocol, where the apparatus is applied in a fisheye state routing protocol FSR, and the apparatus includes:
the weight determining module is used for determining the objective weight of each index according to the sample data corresponding to each index in the pre-acquired ad hoc network;
the inter-node metric value acquisition module is used for calculating the metric value between each adjacent node in the ad hoc network according to the objective weight of each index and pre-acquired real-time communication quality data of the ad hoc network, wherein the real-time communication quality data are data which are acquired in real time between each adjacent node of the ad hoc network and correspond to each index;
a path metric value obtaining module, configured to calculate metric values of all paths from a starting node to a destination node in the ad hoc network according to the metric values between adjacent nodes;
and the optimal path acquisition module is used for taking the path with the minimum metric value as the optimal path between the starting node and the destination node.
In a third aspect, an embodiment of the present invention provides a server, including:
one or more processors;
a memory for storing one or more programs;
when executed by the one or more processors, cause the one or more processors to implement the FSR protocol-based path selection method of any of the embodiments of the present invention.
In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the FSR protocol-based path selection method according to any embodiment of the present invention.
The objective weight of each index in the service quality of the self-organizing network based on the FSR routing protocol is determined, and the metric values of all paths from the starting node to the destination node in the self-organizing network are calculated according to the determined objective weight of the index, so that the path with the minimum metric value of the path is selected as the optimal path from the starting node to the destination node. The method and the device solve the problems that in the prior art, all indexes in the service quality of the ad hoc network are not comprehensively considered and the weight assignment of the indexes is not objective enough, and realize accurate selection of the optimal path with the best communication quality in the ad hoc network.
Drawings
Fig. 1 is a flowchart of a path selection method based on an FSR protocol according to an embodiment of the present invention;
fig. 2 is a flowchart of a path selection method based on an FSR protocol according to a second embodiment of the present invention;
fig. 3 is a diagram illustrating a topology structure of a network according to a second embodiment of the present invention;
fig. 4 is a schematic structural diagram of a path selection device based on an FSR protocol according to a third embodiment of the present invention;
fig. 5 is a schematic structural diagram of a server according to a fourth embodiment of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the invention and are not limiting of the invention. It should be further noted that, for the convenience of description, only some of the structures related to the present invention are shown in the drawings, not all of the structures.
Example one
Fig. 1 is a flowchart of a path selection method based on an FSR protocol according to an embodiment of the present invention, where the embodiment is applicable to a case of optimal path selection in an autonomous network based on the FSR protocol, and the method may be executed by a path selection apparatus based on the FSR protocol. The method specifically comprises the following steps:
and step 110, determining the objective weight of each index according to the sample data corresponding to each index in the self-organized network acquired in advance.
The FSR protocol is a proactive link state protocol, which simulates the function of a fisheye, and by adopting different route update frequencies for nodes at different distances, the more the nodes at closer distances are, the more accurate the grasped route information is.
Indicators in network quality of service include, but are not limited to: bandwidth, communication delay, delay jitter, packet loss rate, or hop count. Generally, the larger the difference between all sample data under the same index is, the larger the amount of information contained therein is. Therefore, when determining the objective weight of each index in the service quality of the ad hoc network, it is necessary to take into account the difference between all sample data under the same index, and generally describe the difference between data by using the contrast strength, which is expressed by calculating the standard deviation of all data.
In addition, since each index for balancing the network service quality is not completely independent, and there are correlation and conflict between each index, the correlation and conflict between each index need to be considered in calculating the weight of each index. For example, the four indexes, i.e., bandwidth, communication delay, packet loss rate, and delay jitter, are not completely independent, and therefore, the correlation among the four indexes needs to be considered when calculating the weights of the four indexes; in addition, in the four indicators, the delay variation and the packet loss rate are calculated based on the communication delay, so that the correlation between the delay variation and the packet loss rate with respect to the communication delay indicator needs to be considered. The correlation coefficient is used to describe the correlation between the indexes, and the conflict parameter is used to describe the conflict between the indexes. After the correlation coefficient between the indexes is calculated, the conflict parameter between the indexes can be obtained by calculating the absolute value of the difference between the correlation coefficient and 1. For example, after the correlation coefficient of the delay jitter and the communication delay is calculated, the conflict parameter between the two indexes of the delay jitter and the communication delay can be obtained by subtracting the correlation coefficient of the delay jitter and the communication delay from 1 and taking the absolute value.
In this embodiment, an index weight determination method (CRITIC algorithm) based on index correlation is adopted, and objective weights of indexes in network service quality are calculated by acquiring a large amount of sample data corresponding to each index in advance. The standard deviation of all sample data under the same index, the correlation coefficient and the conflict parameter among all indexes are calculated, and the influence of the relation of data in the same index and the relation of data among all indexes in the network service quality on the network is comprehensively considered, so that the accurate determination of the optimal path is facilitated.
The network topology represents the shape of the network or the physical connectivity of the network. The network topology structure gives the network configuration of the devices such as the server, the workstation and the terminal in the network and the connection relation among the devices. Therefore, according to the connection relationship among the nodes in the topology structure of the network, all the paths which may pass from the starting node to the destination node can be found in the ad hoc network. The metric value of each path is the sum of the metric values of the adjacent nodes passed by the path, so that the metric values of all paths possibly passed by the starting node to the destination node are calculated on the premise of calculating the metric values of the adjacent nodes in the ad hoc network.
The metric between adjacent nodes is determined by real-time communication quality data of the ad hoc network and objective weights of the indicators. The real-time communication quality data is data corresponding to each index acquired in real time among each adjacent node of the ad hoc network, and reflects the communication quality among each adjacent node in the ad hoc network in real time. Therefore, in practical application, after objective weights of all communication indexes of the self-organizing network are scientifically calculated through a large amount of sample data acquired in an early stage, the metric values between all adjacent nodes can be calculated in a weighted summation mode according to actual real-time communication quality data.
The metric value of the path from the starting node to the destination node is the sum of the metric values of the adjacent nodes passed by the path.
And step 140, taking the path with the minimum metric value of the path as the optimal path from the starting node to the destination node.
The metric value of the path is obtained by carrying out objective evaluation on each index after the comprehensive analysis of each index, and comprehensively expresses the quality of the communication quality of the path. The smaller the measurement value of the path is, the more the path is in data transmission, the more the indexes reach the optimal state in a balanced manner, so that the loss in data transmission is smaller and the transmission speed is higher. Therefore, in order to ensure the transmission quality of data, a path with the minimum metric value of the path needs to be searched among all paths from the starting node to the destination node as the optimal path from the starting node to the destination node, so as to improve the transmission quality of data in the network.
In the technical scheme of this embodiment, objective weights of indexes in service quality of the ad hoc network based on the FSR routing protocol are determined, and metric values of all paths from an initial node to a destination node in the ad hoc network are calculated according to the determined objective weights of the indexes, so that a path with the minimum metric value of the paths is selected as an optimal path from the initial node to the destination node. The method and the device solve the problems that in the prior art, when the optimal path is selected in the self-organized network based on the FSR protocol, all indexes in the service quality of the self-organized network are not comprehensively considered and the weight assignment of the indexes is not objective enough, and realize the accurate selection of the optimal path with the best communication quality in the self-organized network.
Example two
Based on the first embodiment, this embodiment provides a preferred implementation of a path selection method based on an FSR protocol, which can accurately determine objective weights of indexes in the service quality of an ad hoc network. Fig. 2 is a flowchart of a path selection method based on an FSR protocol according to a second embodiment of the present invention, as shown in fig. 2, the method includes the following specific steps:
And obtaining sample data of each index in the service quality of the ad hoc network according to the experimental data, wherein the larger the sample data amount is, the more accurate the objective weight of each index obtained by the sample data is. For example, table 1 shows sample data of each index in network service quality of an ad hoc network, where the sample data includes 10 groups of sample data, and each group of sample data includes four index parameters, i.e., bandwidth, communication delay, delay jitter, and packet loss rate.
TABLE 1 sample data for each index in network QoS for an ad hoc network
Because the unit of each index in the service quality is different, the dimension is different and the order of magnitude is different, the analysis is inconvenient, and even the evaluation result is influenced. For example, in the four indexes in table 1, the unit of bandwidth is mega (M), the unit of communication delay and time delay is millisecond (ms), the unit of packet loss rate is percentage (%), and by observing each group of data under each index, the magnitude of each index data is also different. Therefore, in order to unify the standards, the sample data of all the evaluation indexes are standardized to eliminate the dimension, converted into the standard numerical value without dimension and order difference, and then subjected to comprehensive analysis and evaluation.
In this embodiment, dimensionless processing is performed on the dimensional sample data by using a range normalization method. Generally, the level of the index value directly reflects the performance of each index, and the higher the value of some indexes is, the better the corresponding performance is, for example, the bandwidth is, the wider the bandwidth is, the faster the transmission speed of data is during communication; while lower values of some metrics indicate better performance, such as communication delay, the lower the communication delay, the shorter the time required for data to travel from one end of a network to the other. Therefore, according to the index correspondenceThe relationship between the performance and the trend of each index value is subjected to non-dimensionalization treatment by adopting different calculation formulas. For indexes with higher numerical values and better corresponding performance, such as bandwidth, a calculation formula of positive indexes is adopted, namely
Wherein x isijDenotes the jth data under the ith index in the sample data, MINiDenotes the minimum value, MAX, of all data under the ith index in the sample dataiRepresents the maximum value of all data under the ith index in the sample data, yijRepresenting dimensionalized data xijThe numerical values after dimensionless processing. For indexes with lower numerical values and better corresponding performance, such as communication delay, delay jitter and packet loss rate, a calculation formula of negative indexes is adopted, namely
Wherein x isijDenotes the jth data under the ith index in the sample data, MINiDenotes the minimum value, MAX, of all data under the ith index in the sample dataiRepresents the maximum value of all data under the ith index in the sample data, yijRepresenting data xijThe values after dimensionless processing.
Illustratively, according to the four indexes in table 1, the sample data of the index bandwidth adopts a calculation formula of a positive index, and the sample data of the index communication delay, the delay jitter and the packet loss rate adopts a calculation formula of a negative index. For example, taking the first data under the first index in the sample data in Table 1 as an example,
the data of the sample data in table 1 after the non-dimensionalization processing is shown in table 2. As can be seen from Table 2, the sample data under each index has no dimension and the same order of magnitude, the numerical values are all between 0 and 1, the minimum numerical value is 0, and the maximum numerical value is 1. And standard sample data is unified after non-dimensionalization processing, so that subsequent comprehensive analysis and evaluation are facilitated.
TABLE 2 non-dimensionalized data
And step 230, calculating the contrast intensity parameter of each index according to the sample data corresponding to each index.
The contrast intensity describes the difference of all data under the same index, the larger the difference is, the larger the information content contained in the data under the index is, therefore, the more the index plays a role in comprehensive evaluation, the more the index occupies weight in all indexes in the comprehensive evaluation; on the contrary, the smaller the difference of all data under the same index is, the smaller the information content of the data under the index is, and therefore the smaller the role of the index in the comprehensive evaluation is, the smaller the weight of the index in all indexes in the comprehensive evaluation is.
The standard deviation is used in this example to describe the contrast, i.e., contrast intensity, of all data under the same index. On the basis of the non-dimensionalized data, the calculation formula of the contrast intensity parameter is
Wherein S isiA contrast intensity parameter, y, representing the ith index in the sample dataijRepresents the j data, y under the i index in the sample data after non-dimensionalization processingi' represents an average value of all data under the ith index in the sample data, and n represents the number of the sample data under the index. The contrast intensity parameter s obtained by the aboveiThe contrast intensity parameter matrix S ═ S of all indexes under sample data can be obtained1s2 s3 … sm]Wherein m is the number of indexes. For example, based on the above examples, the contrast strength parameters of the indexes in table 2 are calculated by the formula: bandwidth s10.2976 communication delay s20.3813, delay jitter s30.3540, packet loss rate s40.3343. From this, it can be obtained that the contrast intensity parameter matrix of the four indexes under the sample data in the example is S ═ 0.29760.38130.35400.3343]。
And 240, calculating a correlation coefficient between any two indexes according to the sample data corresponding to each index.
The correlation coefficient is a statistical index for reflecting the degree of closeness of the correlation between the variables, and in this embodiment, the product difference method is used to calculate the correlation coefficient between the indexes, and similarly, the product of the dispersion of the sample data of the two indexes on the average value of each index is used as the basis to reflect the degree of correlation between the two indexes. The calculation formula is
Wherein r isabRepresenting the correlation coefficient between index a and index b, ajDenotes the jth data under index a, a' denotes the average of all data under index a, bjThe j-th data under the index b is shown, b' represents the average value of all data under the index b, and n represents the number of sample data under the index. The correlation coefficient matrix among all indexes under the sample data can be obtained through the obtained correlation coefficient r
The value of the correlation coefficient is between-1 and 1, i.e., -1 ≦ rabLess than or equal to 1. When r isab>When 0, the index a and the index b are positively correlated; when r isab<When 0, the index a and the index b are inversely correlated; when rabWhen | ═ 1, it means that index a and index b are completely linearly related; when r isabWhen the index a and the index b are 0, the index a and the index b are in a wireless correlation relationship. When 0 is present<|rab|<1, the index a and the index b have a certain linear relation; and rabThe closer the | is to 1, the more closely the linear relationship between the index a and the index b is; | rabThe closer to 0, | is, the weaker the linear relationship between the index a and the index b is.
Illustratively, on the basis of the above embodiment, it is assumed that a represents the indicator bandwidth, b represents the indicator communication delay, e represents the indicator delay jitter, and f represents the indicator packet loss rate. The correlation coefficient of the index bandwidth and the index communication delay in table 2 is r after formula calculationab0.8401, the correlation coefficient of the index bandwidth and the index delay jitter is rae0.7122, the correlation coefficient between the index bandwidth and the index packet loss rate is raf0.7195, and so on, rbe＝0.9003、rbf＝0.8964、ref0.7530. Since the correlation coefficient between the index itself and itself is 1, it can be obtained that the correlation coefficient matrix of the four indexes under the sample data in the example is a symmetric matrix, that is, it is a symmetric matrix
And step 250, calculating a conflict parameter between any two indexes according to the correlation coefficient.
The opposite side of the correlation is the conflict, so the conflict parameter between the indexes can be obtained according to the obtained correlation coefficient between the indexes. The calculation formula is cab＝1·(1-rab)＝1-rab. Through the obtained correlation coefficient c, a conflict parameter matrix among all indexes under the sample data can be obtained according to a calculation formula of the conflict parameter
Illustratively, on the basis of the foregoing embodiments, the parameter c of conflict between the index bandwidth and the index communication delay can be obtainedab＝1-rab0.1598, and so on, cae＝0.2877、caf＝0.2804、cbe＝0.0996、cbf＝0.1035、cef0.2469. Since the conflicting parameters of the index itself and itself are 0, the conflicting parameter matrix of the four indexes under the sample data in the example is a symmetric matrix, that is, the symmetric matrix is obtained
And step 260, calculating objective weight of each index according to each comparative strength parameter and each conflict parameter.
By calculating the contrast strength of all sample data under the same index and the conflict parameters among the indexes, the objective weight of each index in the service quality of the ad hoc network is accurately determined by comprehensively considering the relation of data in the same index in the service quality of the network and the influence of the relation of data among the indexes on the network, thereby being beneficial to accurately determining the optimal path. According to the contrast strength parameter matrix and the conflict parameter matrix, the calculation formula of the intermediate transition matrix of the objective weight of each index is D ═ C · S ', wherein D is the intermediate transition matrix for obtaining the objective weight of each index, the size of the matrix is mx 1, m is the number of the indexes, C is the conflict parameter matrix, S is the contrast strength parameter matrix, and S' is the transpose matrix of the contrast strength parameter matrix S. Therefore, the objective weight of each index is calculated by the formula
Wherein, WiAn objective weight representing the ith index, DiThe ith value of the intermediate transition matrix D is m, which is the number of indexes. Then the objective weight W of each index obtained by the above method is usediAnd obtaining an objective weight matrix W of all indexes under the sample data as W1 W2 W3 … Wm]。
Illustratively, on the basis of the above embodiment, the contrast intensity parameter matrix of four indexes under sample data is obtained as S ═ 0.29760.38130.35400.3343]The conflict parameter matrix of the four indexes is
Therefore, the intermediate transition matrix is obtained as D ═ 0.25650.11740.20610.2103 through the calculation formula of the intermediate transition matrix]', so the objective weights of the four indexes under the sample data are the bandwidth weights W10.3245, when communicatingDelay weight W20.1486, delay jitter weight W30.2607 and packet loss rate weight W40.2661, and W is the objective weight matrix 0.32450.14860.26070.2661]And corresponds one-to-one to the four indices in table 1.
And 270, calculating a metric value between each two adjacent nodes in the ad hoc network according to the objective weight of each index and pre-acquired real-time communication quality data of the ad hoc network, wherein the real-time communication quality data is data corresponding to each index and acquired in real time between each two adjacent nodes of the ad hoc network.
The metric value of each path is the sum of the metric values of the adjacent nodes passed by the path, so that the metric values of all paths possibly passed by the starting node to the destination node are calculated on the premise that the metric values of the adjacent nodes communicated in the ad hoc network are calculated. The metric between adjacent nodes is determined by objective weight of each index in service quality of the ad hoc network and real-time communication quality data of the ad hoc network, wherein the real-time communication quality data is data corresponding to each index collected in real time between the adjacent nodes of the ad hoc network and reflects the communication quality between the adjacent nodes in the ad hoc network in real time. The calculation formula of the metric value between the nodes is Mij＝W1·xij1+W2·xij2+…+Wm·xijmWherein M isijRepresenting a metric, W, between node i and a node j adjacent thereto in the ad hoc networkmObjective weight, x, representing the m-th indexijmAnd (3) the real-time communication quality of the m index between the node i and the node j adjacent to the node i.
Illustratively, on the basis of the above embodiments, it is assumed that the topology of the network is as shown in fig. 3, and real-time communication quality data of each index in the network service quality when the ad hoc network normally communicates is as shown in table 3. In the topological structure of the network, the group 1 real-time communication quality data in the table 3 corresponding to each index in the network service quality between the node 1 and the node 2, the group 2 real-time communication quality data in the table 3 corresponding to each index in the network service quality between the node 2 and the node 3, and the node 1 and the nodeEach index in the network service quality between 4 corresponds to the group 3 real-time communication quality data in table 3, and each index in the network service quality between the node 4 and the node 3 corresponds to the group 4 real-time communication quality data in table 3. The metric between node 1 and node 2 is M114.6408, the metric between node 2 and node 3 is M212.5159, the metric between node 1 and node 4 is M310.4596, the metric between node 4 and node 3 is M4＝13.3404。
TABLE 3 real-time communication quality data of each index in network service quality in normal communication of ad hoc network
And (4) expanding outwards layer by taking the starting node as a center according to the topological structure of the network until the starting node is expanded to the destination node. Calculating the metric values of all the paths passing through the path, wherein the metric value of each path is the sum of the metric values of all the connected adjacent nodes passing through the path, and the calculation formula is that
Wherein, L represents the metric value of a certain path, M represents the metric value between the connected adjacent nodes in the path, and h represents the hop count from the starting node to the destination node in the path.
Illustratively, on the basis of the above embodiment, an optimal path from the start node 1 to the destination node 3 in the network topology structure diagram 3 is found. From the starting node 1 to the destination node 3, the layer-by-layer expansion is carried out until the expansion reaches the destination node 3, and there are two paths that may be passed through, namely, the path 1 is from the node 1 to the node 2 to the node 3, and the path 2 is from the node 1 to the node 4 to the node 3. As can be seen in fig. 3, the hop counts of both paths are 2. The metric value of path 1 is
The same way obtains the metric value of path 2 as
Illustratively, based on the above embodiment, according to the topology of the network, finding all paths from the starting node 1 to the destination node 3 includes two paths, i.e. path 1 is from node 1 to node 2 to node 3, and its metric value is L127.1567; path 2 is node 1 to node 4 to node 3 and has a metric value of L223.8000. Because L is1>L2Therefore, the optimal path from the start node 1 to the destination node 3 is path 2, i.e., node 1 to node 4 to node 3.
According to the technical scheme of the embodiment, the sample data under each index in the sample data is subjected to non-dimensionalization processing, the contrast strength parameter of each index and the conflict parameter between any two indexes are calculated according to the non-dimensionalized sample data, the influence of the relation of data in the same index in the network service quality and the relation of data between the indexes on the network is comprehensively considered, the objective weight of each index in the service quality of the ad hoc network is accurately determined, the metric value between adjacent nodes communicated in the network and the metric values of all paths from the starting node to the destination node are calculated, and the optimal path from the starting node to the destination node is accurately selected. The method and the device solve the problems that in the prior art, when the optimal path is selected in the self-organized network based on the FSR protocol, all indexes in the service quality of the self-organized network are not comprehensively considered and the weight assignment of the indexes is not objective enough, and realize the accurate selection of the optimal path with the best communication quality in the self-organized network.
EXAMPLE III
Fig. 4 is a schematic structural diagram of a path selection device based on an FSR protocol according to a third embodiment of the present invention, which is applicable to a case of selecting an optimal path in an autonomous network based on the FSR protocol. The device specifically includes:
a weight determining module 410, configured to determine an objective weight of each index according to sample data corresponding to each index in the ad hoc network acquired in advance;
an inter-node metric value obtaining module 420, configured to calculate a metric value between each adjacent node in the ad hoc network according to an objective weight of each index and pre-obtained real-time communication quality data of the ad hoc network, where the real-time communication quality data is data corresponding to each index and collected in real time between each adjacent node of the ad hoc network;
a path metric value obtaining module 430, configured to calculate metric values of all paths from a starting node to a destination node in the ad hoc network according to the metric values between adjacent nodes;
an optimal path obtaining module 440, configured to use the path with the minimum metric value as the optimal path between the starting node and the destination node.
Further, the weight determining module 410 includes:
an index data obtaining unit 4101, configured to obtain sample data corresponding to each index in the ad hoc network; wherein the indicators include, but are not limited to: bandwidth, communication delay, delay jitter, packet loss rate or hop count;
a parameter obtaining unit 4102, configured to calculate, according to sample data corresponding to each index, a contrast strength parameter of each index and a conflict parameter between any two indexes;
a weight determination unit 4103 for calculating objective weights of the indexes based on the respective comparative strength parameters and the respective conflict parameters.
Further, the parameter acquiring unit 4102 includes:
the contrast intensity parameter acquiring subunit is used for calculating the contrast intensity parameter of each index according to the sample data corresponding to each index;
a correlation coefficient obtaining subunit, configured to calculate a correlation coefficient between any two of the indexes according to the sample data of each index;
and the conflict parameter acquiring subunit is used for calculating the conflict parameter between any two indexes according to the correlation coefficient.
Further, the apparatus further comprises:
the data preprocessing module 450 is configured to perform non-dimensionalization processing on the sample data corresponding to each indicator after the sample data corresponding to each indicator in the ad hoc network is obtained.
According to the technical scheme of the embodiment, through the mutual cooperation of the modules, the objective weight of each index in the service quality of the self-organized network based on the FSR routing protocol is accurately determined, and the metric values of all paths from the starting node to the destination node in the self-organized network are calculated according to the determined objective weight of the index, so that the path with the minimum metric value of the path is selected as the optimal path from the starting node to the destination node. The method and the device solve the problems that in the prior art, when the optimal path is selected in the self-organized network based on the FSR protocol, all indexes in the service quality of the self-organized network are not comprehensively considered and the weight assignment of the indexes is not objective enough, and realize the accurate selection of the optimal path with the best communication quality in the self-organized network.
Example four
Fig. 5 is a schematic structural diagram of a server according to a fourth embodiment of the present invention, which is applicable to a case of selecting an optimal path in an autonomous network based on an FSR protocol. As shown in fig. 5, the server specifically includes: one or more processors 510, one processor 510 being illustrated in FIG. 5; memory 520 to store one or more programs that, when executed by the one or more processors 510, cause the one or more processors 510 to implement the FSR protocol-based path selection method described in any embodiment of the present invention. The processor 510 and the memory 520 may be connected by a bus or other means, such as the bus connection shown in FIG. 5.
The memory 520, which is a computer-readable storage medium, may be used to store software programs, computer-executable programs, and modules, such as program instructions/modules corresponding to the FSR protocol-based path selection method in the embodiments of the present invention (for example, the weight determination module 410 and the optimal path acquisition module 440 in the FSR protocol-based path selection apparatus). The processor 510 executes various functional applications of the server and data processing by executing software programs, instructions, and modules stored in the memory 520, that is, implements the FSR protocol-based path selection method described above.
The memory 520 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application program required for at least one function; the storage data area may store data created according to the use of the server, and the like. Further, the memory 520 may include high speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other non-volatile solid state storage device. In some examples, memory 520 may further include memory located remotely from processor 510, which may be connected to a server over a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
EXAMPLE five
An embodiment of the present invention further provides a computer-readable storage medium, on which a computer program (or referred to as computer-executable instructions) is stored, where the computer program is used for executing a path selection method based on an FSR protocol when executed by a processor, and the method includes:
determining objective weight of each index according to sample data corresponding to each index in the pre-acquired ad hoc network;
calculating a metric value between each adjacent node in the ad hoc network according to the objective weight of each index and pre-acquired real-time communication quality data of the ad hoc network, wherein the real-time communication quality data are data which are acquired between each adjacent node of the ad hoc network in real time and correspond to each index;
calculating the metric values of all paths from the starting node to the destination node in the ad hoc network according to the metric values between the adjacent nodes;
and taking the path with the minimum metric value of the path as the optimal path between the starting node and the destination node.
Of course, the computer-readable storage medium provided by the embodiments of the present invention has computer-executable instructions that are not limited to the method operations described above, and may also perform related operations in the FSR protocol-based path selection method provided by any embodiments of the present invention.
From the above description of the embodiments, it is obvious for those skilled in the art that the present invention can be implemented by software and necessary general hardware, and certainly, can also be implemented by hardware, but the former is a better embodiment in many cases. Based on such understanding, the technical solutions of the present invention may be embodied in the form of a software product, which can be stored in a computer-readable storage medium, such as a floppy disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a FLASH Memory (FLASH), a hard disk or an optical disk of a computer, and includes several instructions for enabling a computer device (which may be a personal computer, a server, or a network device) to execute the methods according to the embodiments of the present invention.
It is to be noted that the foregoing is only illustrative of the preferred embodiments of the present invention and the technical principles employed. It will be understood by those skilled in the art that the present invention is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, although the present invention has been described in greater detail by the above embodiments, the present invention is not limited to the above embodiments, and may include other equivalent embodiments without departing from the spirit of the present invention, and the scope of the present invention is determined by the scope of the appended claims.
Claims (8)
1. A path selection method based on an FSR protocol is applied to a fisheye state routing protocol FSR, and comprises the following steps:
obtaining sample data corresponding to each index in the ad hoc network, and carrying out dimensionless processing on the sample data corresponding to each index;
the dimensionless processing of the sample data corresponding to each index includes:
formula of calculation using positive index
Or negative index calculation formula
Carrying out dimensionless processing on the sample data corresponding to each index;
wherein x isijDenotes the jth data under the ith index in the sample data, MINiDenotes the minimum value, MAX, of all data under the ith index in the sample dataiRepresents the maximum value of all data under the ith index in the sample data, yijRepresenting dimensioned data x in sample dataijThe numerical values after dimensionless processing;
determining objective weight of each index according to sample data corresponding to each index in the ad hoc network after non-dimensionalization, wherein the indexes include but are not limited to: bandwidth, communication delay, delay jitter, packet loss rate or hop count; when determining the objective weight of each index, considering the difference of all sample data under the same index;
calculating a metric value between each adjacent node in the ad hoc network according to the objective weight of each index and pre-acquired real-time communication quality data of the ad hoc network, wherein the real-time communication quality data are data which are acquired between each adjacent node of the ad hoc network in real time and correspond to each index;
calculating the metric values of all paths from the starting node to the destination node in the ad hoc network according to the metric values between the adjacent nodes, wherein the metric values between the adjacent nodes are determined by the real-time communication quality data of the ad hoc network and the objective weight of each index;
and taking the path with the minimum metric value of the path as the optimal path between the starting node and the destination node.
2. The method according to claim 1, wherein the determining the objective weight of each indicator according to the sample data corresponding to each indicator in the ad hoc network after the non-dimensionalization processing comprises:
obtaining sample data corresponding to each index in the ad hoc network after the dimensionless processing;
according to sample data corresponding to each index after non-dimensionalization processing, calculating a contrast intensity parameter of each index and a conflict parameter between any two indexes;
and calculating the objective weight of each index according to each comparative strength parameter and each conflict parameter.
3. The method of claim 2, wherein said calculating a conflict parameter between any two of said metrics comprises:
calculating a correlation coefficient between any two indexes according to sample data corresponding to each index after non-dimensionalization processing;
and calculating a conflict parameter between any two indexes according to the correlation coefficient.
4. A path selection device based on an FSR protocol, applied in a fisheye state routing protocol FSR, the device comprising:
the data preprocessing module is used for acquiring sample data corresponding to each index in the ad hoc network and carrying out dimensionless processing on the sample data corresponding to each index;
the dimensionless processing of the sample data corresponding to each index includes:
formula of calculation using positive index
Or negative index calculation formula
Carrying out dimensionless processing on the sample data corresponding to each index;
wherein x isijDenotes the jth data under the ith index in the sample data, MINiDenotes the minimum value, MAX, of all data under the ith index in the sample dataiRepresents the maximum value of all data under the ith index in the sample data, yijRepresenting dimensioned data x in sample dataijThe numerical values after dimensionless processing;
a weight determining module, configured to determine an objective weight of each indicator according to sample data corresponding to each indicator in the ad hoc network after the non-dimensionalization processing, where the indicators include, but are not limited to: bandwidth, communication delay, delay jitter, packet loss rate or hop count; when determining the objective weight of each index, considering the difference of all sample data under the same index;
the inter-node metric value acquisition module is used for calculating the metric value between each adjacent node in the ad hoc network according to the objective weight of each index and pre-acquired real-time communication quality data of the ad hoc network, wherein the real-time communication quality data are data which are acquired in real time between each adjacent node of the ad hoc network and correspond to each index;
a path metric value obtaining module, configured to calculate metric values of all paths from a start node to a destination node in the ad hoc network according to metric values between adjacent nodes, where the metric values between adjacent nodes are determined by real-time communication quality data of the ad hoc network and objective weights of the indicators;
and the optimal path acquisition module is used for taking the path with the minimum metric value as the optimal path between the starting node and the destination node.
5. The apparatus of claim 4, wherein the weight determination module comprises:
an index data obtaining unit, configured to obtain sample data corresponding to each index in the ad hoc network after the dimensionless processing
The parameter acquisition unit is used for calculating a contrast intensity parameter of each index and a conflict parameter between any two indexes according to sample data corresponding to each index after the non-dimensionalization processing;
and the weight determining unit is used for calculating the objective weight of each index according to each comparative strength parameter and each conflict parameter.
6. The apparatus of claim 5, wherein the parameter obtaining unit further comprises:
the correlation coefficient acquisition subunit is used for calculating the correlation coefficient between any two indexes according to the sample data corresponding to each index after the dimensionless processing;
and the conflict parameter acquiring subunit is used for calculating the conflict parameter between any two indexes according to the correlation coefficient.
7. A server, comprising:
one or more processors;
a memory for storing one or more programs;
when executed by the one or more processors, cause the one or more processors to implement the FSR protocol-based path selection method of any of claims 1-3.
8. A computer-readable storage medium, on which a computer program is stored, which program, when being executed by a processor, carries out a FSR protocol-based path selection method according to any one of claims 1 to 3.
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