CN108418756B - Software defined backhaul network access selection method based on similarity measurement - Google Patents
Software defined backhaul network access selection method based on similarity measurement Download PDFInfo
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
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- H04L45/00—Routing or path finding of packets in data switching networks
- H04L45/12—Shortest path evaluation
- H04L45/124—Shortest path evaluation using a combination of metrics
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L45/00—Routing or path finding of packets in data switching networks
- H04L45/12—Shortest path evaluation
- H04L45/121—Shortest path evaluation by minimising delays
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L45/00—Routing or path finding of packets in data switching networks
- H04L45/12—Shortest path evaluation
- H04L45/123—Evaluation of link metrics
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L45/00—Routing or path finding of packets in data switching networks
- H04L45/12—Shortest path evaluation
- H04L45/125—Shortest path evaluation based on throughput or bandwidth
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L45/00—Routing or path finding of packets in data switching networks
- H04L45/302—Route determination based on requested QoS
- H04L45/306—Route determination based on the nature of the carried application
- H04L45/3065—Route determination based on the nature of the carried application for real time traffic
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W40/00—Communication routing or communication path finding
- H04W40/02—Communication route or path selection, e.g. power-based or shortest path routing
- H04W40/12—Communication route or path selection, e.g. power-based or shortest path routing based on transmission quality or channel quality
Abstract
The invention discloses a software defined backhaul network access selection method based on similarity measurement, which comprises the steps of firstly generating a network flow output to a backhaul network for each base station; secondly, selecting edge nodes meeting the bandwidth resource requirement as candidate nodes in a backhaul network for the network flow; then calculating the weighted Euclidean distance between the two-dimensional vector of the performance parameter at the candidate node and the two-dimensional vector of the service characteristic parameter; then, selecting the candidate node with the minimum average distance as a primary access node; and finally, when the overloaded edge node exists in the backhaul network, performing access selection operation on the network flow accessed to the node again, eliminating the overload problem and obtaining the final access node of each network flow. The invention selects the optimal return access node for the network flow on the premise of considering the service characteristics at the base station, so that the service can be closer to the link and the node meeting the characteristics when entering the return network, and the satisfaction of different service types in the return network routing is improved.
Description
Technical Field
The invention relates to the field of Software Defined Networking (SDN), in particular to a software defined backhaul network access selection method based on similarity measurement under the scene of considering the service characteristic requirements of a wireless access network.
Background
With the full development and gradual deepening of 5G research, core concepts of network service fusion and on-demand service provision are followed, and the service types in the wireless access network are no longer limited to the service data between people, but are expanded to the data interaction between people and things, such as: real-time services with different requirements on time delay, or non-real-time services such as Web page browsing and the like responding as required, and best-effort services such as e-mails and the like without specific requirements on time delay; and various Internet of things intelligent terminal services, sensor data, short-distance wireless communication and other service types under the scene of Internet of things equipment interconnection. In addition to the rich and diverse types of services, the throughput that the future network needs to bear will be several times that of the present network. Therefore, the industry focuses on improving the efficiency of the backhaul network between the radio access network and the core network.
In the face of an access scene with abundant service types and huge data volume, the defects of the traditional wired or wireless backhaul technology gradually appear, so that a network control and forwarding mechanism must be reconstructed to meet the requirement of mass data forwarding processing in a future network. With the continuous deep and development of Software Defined Networking (SDN) research, in a scenario in which a radio access Network service is considered, it is possible to select a better access for the service by using a Software Defined backhaul Network.
Disclosure of Invention
The invention aims to solve the technical problem of the prior art and provides a software-defined backhaul network access selection method based on similarity measurement, which measures the similarity between the total service characteristics and the node performance in a network flow by calculating the weighted Euclidean distance between service characteristic parameter vectors and node performance parameter vectors, and selects an optimal backhaul access node for the network flow, so that the service can be closer to links and nodes meeting the characteristic requirements when entering a backhaul network, and the satisfaction degree of different service requirements in backhaul network routing is improved.
The invention adopts the following technical scheme for solving the technical problems:
a software defined backhaul network access selection method based on similarity measurement comprises the following steps:
step 1), after the characteristics of the service at the base station are obtained, generating a network flow meeting the requirement of service bandwidth for the base station;
step 2), after the nodes of the backhaul network and the link state information are collected, for each network flow, selecting the nodes of which the residual available bandwidth resources exceed the bandwidth of the network flow from the edge nodes as candidate nodes of the network flow;
step 3), for each network flow with candidate nodes:
step 3.1), enabling a two-dimensional vector formed by the time delay and the packet loss rate parameters of the time delay sensitive service in the network flow to be a first two-dimensional vector of the network flow, and enabling a two-dimensional vector formed by the time delay and the packet loss rate parameters of the packet loss sensitive service in the network flow to be a second two-dimensional vector of the network flow;
step 3.2), respectively calculating the weighted Euclidean distance between the first two-dimensional vector of the network flow and the two-dimensional vector formed by the network performance parameters at each candidate node, namely the first weighted Euclidean distance of the network flow corresponding to each candidate node;
step 3.3), respectively calculating the weighted Euclidean distance between the second two-dimensional vector of the network flow and the two-dimensional vector formed by the network performance parameters at each candidate node, namely the second weighted Euclidean distance of the network flow corresponding to each candidate node;
step 4), for each network flow with candidate nodes, calculating the average value of the first weighted Euclidean distance and the second weighted Euclidean distance of each candidate node corresponding to the network flow, and selecting the candidate node with the minimum average value as the primary access node of the network flow;
and 5) after each network flow with the candidate nodes is accessed to the backhaul edge node, determining whether an overload node with the total bandwidth requirement of the accessed network flow exceeding the residual available bandwidth resource of the node exists in the network, and if so, adjusting the network flow accessed to the overload node to eliminate the overload problem.
As a further optimization scheme of the software-defined backhaul network access selection method based on the similarity metric, the detailed steps of step 1) are as follows:
in the current access selection process, the characteristics of the service accessed to each base station comprise a bandwidth parameter, a time delay parameter and a packet loss rate parameter, and the sum of the bandwidth requirements of the service accessed to the base station is used as the bandwidth size output to the backhaul network flow at the base station to generate the network flow.
As a further optimization scheme of the software-defined backhaul network access selection method based on the similarity metric, the detailed steps of step 2) are as follows:
after state information of edge nodes and connecting links of the software-defined backhaul network is collected, edge nodes conforming to the principle are selected as candidate nodes for the network flow of each base station according to the principle that the remaining available bandwidth resources at the nodes can meet the network flow of the base station, wherein the remaining available bandwidth resources are calculated by the difference between the sum of the upper capacity limits of the links connected with the nodes and the sum of the used bandwidths of the links.
In the step 3), the time delay and packet loss rate parameters of the network performance of the candidate nodes corresponding to the network flow are expressed in a two-dimensional vector form, and if the candidate nodes are connected with a plurality of links, the time delay and packet loss rate values in the vector respectively select the time delay average value and the packet loss rate average value of the plurality of links; similarly, for the delay and packet loss sensitive services in the network flow, the characteristic requirement parameters of each service on the delay and packet loss rate are expressed in a two-dimensional vector form; and calculating the weighted Euclidean distance between the two-dimensional vectors by adjusting different service characteristic weight coefficients, and respectively measuring the similarity between the delay sensitive service and the network performance of the candidate node and the similarity between the packet loss rate sensitive service and the network performance of the candidate node by using the calculated Euclidean distance, wherein the weight coefficient of the service characteristic is the weight given to the delay or the packet loss rate according to the importance of the delay or the packet loss rate when the Euclidean distance is calculated.
In step 4), because there is only one network flow from each base station, and the network flow contains different service characteristic requirements, in order to better satisfy each service requirement simultaneously, an average value of euclidean distances between delay and packet loss sensitive service characteristic requirement parameter vectors and candidate node performance parameter vectors in the network flow is calculated, and a candidate node with the minimum average distance is selected as a primary access node of the base station.
As a further optimization scheme of the software-defined backhaul network access selection method based on the similarity metric of the present invention, in step 5), when there is an overloaded node in the network where the total bandwidth requirement of the access network flow exceeds the remaining available bandwidth resources of the node, the specific steps of adjusting the network flow accessing the overloaded node and eliminating the overload problem are as follows:
when the network has overload edge nodes, namely after network streams are all accessed to the edge nodes, the residual available bandwidth resources of the nodes cannot meet the bandwidth requirement of the total network streams, firstly, the number of base stations accessed by the overload nodes is judged, and secondly, the base station with the minimum flow is selected from the network streams of the base stations for re-access operation;
the specific process of the re-access operation is as follows: selecting an edge node with a small average Euclidean distance between a service characteristic requirement vector and a candidate node performance parameter vector from candidate nodes of a base station network flow as a next access node of the base station;
continuously repeating the re-access operation process until a node which does not generate overload problem is selected as a final access node for the network flow; meanwhile, if the number of times of the re-access operation of the network flow is greater than the number of the candidate nodes, it indicates that the network flow currently input to the backhaul network by the base station cannot be forwarded temporarily, and the network flow waits for the next access selection process.
Compared with the prior art, the invention adopting the technical scheme has the following technical effects:
1. the invention fully utilizes the software defined network technology to collect the node and link state information and grasps the parameter conditions of the network time delay, the packet loss rate and the like at each return edge node. Because the number and types of the services at each base station are different, the similarity between the services in the network flow and the network performance at the nodes is measured by calculating the average value of the weighted Euclidean distances, and the optimal backhaul access node is selected for the network flow. Different from the situation that the network flow is randomly accessed to the backhaul node, the access node is selected by measuring the similarity, the network flow can be accessed from the node which is more consistent with the service characteristics, when the delay-sensitive service in the network flow is forwarded in the backhaul network, the service which is sensitive to the packet loss rate passes through the link which has better delay performance, and when the packet loss rate is forwarded, the service which is sensitive to the packet loss rate passes through the link which has less packet loss condition, so that different services are closer to the link which meets the requirements when entering the backhaul network for routing, and the satisfaction degree of different service requirements in the network is improved.
2. The invention fully utilizes the idea of similarity measurement, network performance parameters at nodes and service characteristic requirement parameters in network flows to be accessed are expressed by vectors, and the similarity between the service characteristics and the node performance is measured by calculating the weighted Euclidean distance.
Drawings
FIG. 1 is a diagram of an application scenario of the present invention;
FIG. 2 is a schematic diagram of a candidate node based on available bandwidth resources according to the present invention;
fig. 3 is a flowchart of a method for selecting access to a software-defined backhaul network based on a similarity metric according to the present invention.
Detailed Description
The technical scheme of the invention is further explained in detail by combining the attached drawings:
FIG. 1 is a diagram of an application scenario of the present invention: in this scenario, the base station sends the service data to the backhaul network for routing in the form of network flow, and the switch nodes in the backhaul network are divided into two types: the network flow forwarding method comprises a forwarding node and an edge node, wherein the edge node accesses a network flow from a base station, and the two nodes can forward the flow. In addition, the SDN controller can keep track of node and link state information of the entire network, including the time required for one end of a link to transmit to the other end, the packet loss rate of the transmission process, and the link capacity upper limit and the used bandwidth resource condition.
FIG. 2 is a schematic diagram of candidate nodes based on available bandwidth resources:
(1) initializing a base station network flow: after the characteristics of bandwidth, time delay and packet loss rate of all services at a base station are determined, taking the sum of all service bandwidths accessed by the current base station as the size of a network flow;
(2) updating the candidate node set for each network flow: obtaining available bandwidth resources at an edge node according to network state information collected by an SDN controller: the difference between the sum of the upper capacity limits of the connected links and the sum of the used bandwidths of the links; for each network flow, selecting nodes with the residual available bandwidth resources exceeding the bandwidth size of the network flow as candidate nodes, and updating the candidate nodes to a candidate node set Ve,m。
Fig. 3 is a flowchart of a method for selecting access to a software-defined backhaul network based on a similarity metric according to the present invention:
(1) representing the time delay and packet loss rate performance parameters of each node in the candidate node set in a two-dimensional vector form: y (h) ═ th,ph],h∈Ve,m；
(2) The characteristic parameters of time delay and packet loss rate of the time delay sensitive service are converted into [ t ] by a vector epsilon (i)i,pi]I-1, …, u, and similarly, the packet loss sensitive service parameter is expressed as
And u and v represent the number of services, and t and p represent time delay and packet loss requirement parameters of the services.
(3) Taking into account the different characteristics of the various services in the network flow, a formula is used
Calculating weighted Euclidean distances between a plurality of delay sensitive service vectors epsilon (i) and y (h) in the step (2), and simultaneously utilizing a formula
Calculating a plurality of packet loss sensitive traffic vectors in (2)
And y (h), wherein: alpha is more than 0.5, beta is less than 0.5, alpha + beta is 1, alpha and beta represent service characteristic weight coefficients, namely when measuring the similarity between the delay sensitive service and the network performance of the candidate node, alpha is more than 0.5 represents whether the delay parameters are more similar and is more important when calculating the Euclidean distance, and beta is less than 0.5 represents whether the packet loss rate parameters are more similar and is more important when calculating the Euclidean distance.
(4) Obtaining the weighted Euclidean distance w between a plurality of time delay and packet loss sensitive service parameter vectors and the node performance parameter vector in the network flow by the calculation in the step (3)i,hAnd wj,hWherein i is 1, …, u, j is 1, …, V, h e Ve,mIn each access selection process, the network flow output to the backhaul network by the base station simultaneously contains a plurality of different types of services, so that the candidate node set V is targeted ate,mCalculating the average Euclidean distance of each node
The similarity between the overall service characteristics of the network flow and the node delay and packet loss rate performance is measured by the average Euclidean distance, so that the aim of selecting the node with the maximum similarity from the candidate nodes of the network flow for access is fulfilled, namely: comparing the average Euclidean distance of each node h in the candidate node set
And selecting the node with the minimum average Euclidean distance as the initial access node, and considering the node as the node with the maximum similarity with the overall service characteristics of the network flow.
(5) After the initial access node selection of the network flow is completed, the SDN controller collects the network flow state information at the edge node, judges whether an overload node exists when the total bandwidth demand of the network flow of the network exceeds the residual available bandwidth resource of the node, and if the overload node exists, adjusts the selection of the access node according to the following contents:
firstly, judging the number of base stations accessed by the overload node, namely the number of network flows accessed by the overload node; secondly, selecting the base station with the minimum flow from the network flows of the plurality of base stations to perform the re-access operation: in the candidate nodes of the base station network flow, selecting edge nodes with the minimum average Euclidean distance between the service characteristic request vector and the candidate node performance parameter vector, namely: for the
When in use
When the corresponding node is overloaded, the nodes are selected in sequence
Taking the nodes corresponding to the equal average distance as access nodes until the nodes which can meet the bandwidth requirement and cannot generate overload problems are selected for the base station; in addition, if the number of the re-access operations of the network flow is greater than the number of the candidate nodes, it indicates that the network flow currently input to the backhaul network by the base station cannot be forwarded temporarily, so that the network flow waits for the next access selection process. Through the re-access operation, the problem of node overload in the current access selection process is solved.
It will be understood by those skilled in the art that, unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. It will be further understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the prior art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.
The above-mentioned embodiments, objects, technical solutions and advantages of the present invention are further described in detail, it should be understood that the above-mentioned embodiments are only illustrative of the present invention and are not intended to limit the present invention, and any modifications, equivalents, improvements and the like made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (4)
1. A software defined backhaul network access selection method based on similarity measurement is characterized by comprising the following steps:
step 1), after the characteristics of the service at the base station are obtained, generating a network flow meeting the requirement of service bandwidth for the base station;
step 2), after the backhaul network nodes and the link state information are collected, for each network flow, selecting nodes with the residual available bandwidth resources exceeding the network flow bandwidth from the edge nodes as candidate nodes of the network flow, and representing the nodes by using the following two-dimensional vectors:
y(h)＝[th,ph],h∈Ve,m
wherein, thAs a delay parameter, phAs a packet loss rate parameter, Ve,mA candidate node set is obtained;
step 3), for each network flow with candidate nodes, calculating a first weighted Euclidean distance and a second weighted Euclidean distance between each candidate node and the network flow according to the following steps;
step 3.1), enabling a two-dimensional vector formed by the time delay and the packet loss rate parameters of the time delay sensitive service in the network flow to be a first two-dimensional vector of the network flow, and enabling a two-dimensional vector formed by the time delay and the packet loss rate parameters of the packet loss sensitive service in the network flow to be a second two-dimensional vector of the network flow;
the first two-dimensional vector is represented by:
ε(i)＝[ti,pi],i＝1,…,u
wherein u represents the number of delay-sensitive services in the network flow, and t and p represent the delay and packet loss requirement parameters of the services respectively;
the second two-dimensional vector is represented as follows:
v represents the number of sensitive services with lost packets in the network flow, and t and p represent the time delay and the packet loss requirement parameters of the services respectively;
step 3.2), respectively calculating the weighted Euclidean distance between the first two-dimensional vector of the network flow and the two-dimensional vector formed by the network performance parameters at each candidate node, namely the first weighted Euclidean distance of the network flow corresponding to each candidate node;
calculating a weighted Euclidean distance between each delay sensitive service vector epsilon (i) and a two-dimensional vector y (h) of the candidate node according to a formula, namely a first weighted Euclidean distance;
wherein, alpha represents a business characteristic weight coefficient and is more than 0.5;
step 3.3), respectively calculating the weighted Euclidean distance between the second two-dimensional vector of the network flow and the two-dimensional vector formed by the network performance parameters at each candidate node, namely the second weighted Euclidean distance of the network flow corresponding to each candidate node;
calculating each packet loss sensitive service vector according to the following formula
A weighted euclidean distance, i.e., a second weighted euclidean distance, with the two-dimensional vector y (h) of the candidate node;
wherein beta is less than 0.5, alpha + beta is 1, and beta represents a service characteristic weight coefficient;
step 4), for each network flow with candidate nodes, calculating the average value of the first weighted Euclidean distance and the second weighted Euclidean distance of each candidate node corresponding to the network flow, and selecting the candidate node with the minimum average value as the primary access node of the network flow;
and 5) after each network flow with the candidate nodes is accessed to the backhaul edge node, determining whether an overload node with the total bandwidth requirement of the accessed network flow exceeding the residual available bandwidth resource of the node exists in the network, and if so, adjusting the network flow accessed to the overload node to eliminate the overload problem.
2. The method for selecting the access to the software-defined backhaul network based on the similarity metric of claim 1, wherein the detailed steps of step 1) are as follows:
in the current access selection process, the characteristics of the service accessed to each base station comprise a bandwidth parameter, a time delay parameter and a packet loss rate parameter, and the sum of the bandwidth requirements of the service accessed to the base station is used as the bandwidth size of the network flow output to the backhaul network at the base station to generate the network flow.
3. The method for selecting the access to the software-defined backhaul network based on the similarity metric of claim 1, wherein the detailed steps of the step 2) are as follows:
after state information of edge nodes and connecting links of the software-defined backhaul network is collected, edge nodes conforming to the principle are selected as candidate nodes for the network flow of each base station according to the principle that the remaining available bandwidth resources at the nodes can meet the network flow of the base station, wherein the remaining available bandwidth resources are calculated by the difference between the sum of the upper capacity limits of the links connected with the nodes and the sum of the used bandwidths of the links.
4. The method for selecting access to a software-defined backhaul network based on a similarity metric according to claim 1, wherein in step 5), when there is an overloaded node in the network whose total bandwidth requirement of the access network flows exceeds the remaining available bandwidth resources of the node, the specific steps of adjusting the network flows accessing the overloaded node and eliminating the overload problem are as follows:
when the network has overload edge nodes, namely after network streams are all accessed to the edge nodes, the residual available bandwidth resources of the nodes cannot meet the bandwidth requirement of the total network streams, firstly, the number of base stations accessed by the overload nodes is judged, and secondly, the base station with the minimum flow is selected from the network streams of the base stations for re-access operation;
the specific process of the re-access operation is as follows: selecting an edge node with a small average Euclidean distance between a service characteristic requirement vector and a candidate node performance parameter vector from candidate nodes of a base station network flow as a next access node of the base station;
continuously repeating the re-access operation process until a node which does not generate overload problem is selected as a final access node for the network flow; meanwhile, if the number of times of the re-access operation of the network flow is greater than the number of the candidate nodes, it indicates that the network flow currently input to the backhaul network by the base station cannot be forwarded temporarily, and the network flow waits for the next access selection process.
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