CN117729149A - SDN multi-constraint path calculation method based on fuzzy analytic hierarchy process and storage medium - Google Patents
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Abstract
The invention relates to an SDN multi-constraint path calculation method based on a fuzzy analytic hierarchy process and a storage medium, wherein the SDN multi-constraint path calculation method comprises the steps that an SDN control plane acquires global state information by issuing a message to a switch of a data plane, and a network tool iggraph is utilized to store a basic topological relation; searching an optimal path based on a Floyd algorithm, selecting an optimal path meeting the constraint of a link state, and storing the optimal path in a path set; deleting the current optimal path based on the intersection constraint, and carrying out iterative updating on the topological relation to obtain a disjoint path set; the path composite quality evaluation module selects a plurality of evaluation parameters, calculates the weight of each parameter through a fuzzy analytic hierarchy process, compares the priorities of available paths and arranges the available paths in descending order; the route decision module selects the route with the highest priority as the optimal route, and can adjust the weight coefficient to update the iterative path priority according to the service attribute of the data flow until the route process is finished.
Description
Technical Field
The invention relates to the technical field of networks, in particular to an SDN multi-constraint path calculation method, equipment and storage medium based on a fuzzy analytic hierarchy process.
Background
In recent years, under the common promotion of the rise of 5G and the popularization of cloud computing, everything interconnection becomes reality gradually, and a data center is used as an infrastructure supporting communication of the everything, and needs to bear thousands of computers with huge bandwidth requirements for simultaneous communication, so that network traffic is increased sharply, and meanwhile, the problems of network congestion and uneven traffic load distribution are brought. In order to meet these high-performance demands of high throughput, low latency, etc., the first problem that data centers need to deal with is network congestion.
A software defined network (Software Defined Network, SDN) which is a new network architecture is an ideal choice for data center applications to meet high bandwidth, dynamic characteristics. Compared with the traditional network, the SDN has a control plane with a logic set, and a control layer can control the behavior of a data layer by using a programming method, so that the SDN is considered as an effective method for managing a complex network environment. The forwarding device is not focused on control decisions, focuses on efficient forwarding and processing of data, and relatively reduces design difficulty and cost of the forwarding device. Various self-defined network functions can be realized through programming through an open API interface under the SDN architecture, so that the oriented management and maintenance of the network are achieved. The manager centrally manages the whole network condition through the controller, controls the forwarding decision of the data layer, collects and processes the state of the network link, and sends the management command of the application layer to the switch of the bottom layer. Whether it is a traditional network or an SDN network, the routing is an essential component, however, the existing path calculation algorithm of the SDN is basically Dijkstra (shortest path) algorithm, and if all data packets depend on only the shortest path algorithm, the data flow easily causes link congestion due to the selection of the same link. On the other hand, the problem of uneven load of a congestion link is solved by dynamically rerouting and dispatching traffic in the SDN, but the periodically reconfigured route brings larger calculation pressure and interaction pressure to the controller, is not beneficial to the stability of traffic transmission and cannot meet the service requirements of different types of data flows. Therefore, research on a fast and effective path calculation method in an SDN network is particularly important.
Disclosure of Invention
The SDN multi-constraint path calculation method, the SDN multi-constraint path calculation equipment and the storage medium based on the fuzzy analytic hierarchy process can at least solve one of the technical problems in the background technology.
In order to achieve the above purpose, the present invention adopts the following technical scheme:
an SDN multi-constraint path calculation method based on a fuzzy analytic hierarchy process comprises the following steps:
s1, firstly, acquiring a path set;
s2, selecting a plurality of evaluation parameters based on the available paths obtained in the step S1, comparing path quality and arranging according to priority;
s3, sequencing based on the composite quality of each available path calculated in the S2, selecting a route with the highest priority as an optimal route by a route decision module, and updating a path monitoring list;
s4, re-selecting the routing path based on the updated path monitoring list.
In yet another aspect, the invention also discloses a computer readable storage medium storing a computer program which, when executed by a processor, causes the processor to perform the steps of the method as described above.
In yet another aspect, the invention also discloses a computer device comprising a memory and a processor, the memory storing a computer program which, when executed by the processor, causes the processor to perform the steps of the method as above.
According to the technical scheme, the SDN multi-constraint path calculation method based on the fuzzy analytic hierarchy process has global visibility to all network equipment such as a switch and a router based on the SDN controller, a multi-parameter path composite quality evaluation model is constructed according to global network state information, the weight coefficient and the path priority of each parameter are determined by adopting the fuzzy analytic hierarchy process, and route iterative optimization is carried out according to the data flow service attribute so as to meet the balanced service requirement in the global network.
The method is based on the multi-constraint optimal path calculation model of the fuzzy analytic hierarchy process, and has high feasibility and high reliability. The forwarding path is dynamically regulated according to the network state in real time, so that the forwarding path is transmitted on the optimal path of the whole network as far as possible, and the routing iteration update is carried out based on the service attribute, so that the routing allocation strategy meeting the service transmission requirement and with low load can be obtained, and the process has good universality without adding additional hardware functions for an SDN switch.
Drawings
FIG. 1 is a schematic diagram of a multi-path topology;
FIG. 2 is a block diagram of a path computation method under multiple constraints according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of a path computation flow based on a fuzzy analytic hierarchy process in an embodiment of the present invention;
fig. 4 is an experimental result of the present embodiment using data throughput as a performance index;
fig. 5 shows experimental results using average delay as performance index in this example.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of 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, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments of the present invention.
The main flow SDN adopts a centralized control plane to conveniently realize accurate control of the route, but the existing multi-path calculation method of the SDN is lack of adapting the service requirement and the network resource, and the routing strategy is difficult to ensure the service quality of different network environments. When designing the path calculation method, the controller is required to acquire relevant resource information in the network in real time, including network topology information, network link resource information, the number of switch nodes and the like. The multi-objective path optimization framework is shown in fig. 1, and the controller performs data interaction with the switch by using modules such as packet_in, packet_out, flow Stats and the like.
By utilizing the advantages of SDN technology, path optimization under multiple constraints is designed, so that the routing strategy can be adaptively adjusted according to the supply-demand relationship between the service demand and the network resource. The overall architecture of the scheme is shown in fig. 2, and mainly comprises a path collection module, a path composite quality evaluation module and a routing decision module.
The SDN control plane obtains global state information by sending a message to a switch of the data plane, and stores the basic topological relation by utilizing a network tool iggraph. And (3) searching an optimal path based on the Floyd algorithm, selecting an optimal path meeting the constraint of the link state, and storing the optimal path in a path set. Deleting the current optimal path based on the intersection constraint, and carrying out iterative updating on the topological relation to obtain a disjoint path set. The path composite quality evaluation module selects a plurality of evaluation parameters, calculates the weight of each parameter through a fuzzy analytic hierarchy process, compares the priorities of available paths and arranges the available paths in descending order. The route decision module selects the route with the highest priority as the optimal route, and can adjust the weight coefficient to update the iterative path priority according to the service attribute of the data flow until the route process is finished.
The following is a specific description:
step S1, obtaining a path set, wherein the step comprises the following steps:
s1.1, the SDN control plane acquires global state information by sending a message to a switch of the data plane, and stores a basic topological relation by using a network tool iggraph.
S1.2, searching an optimal path based on the Floyd algorithm, selecting an optimal path meeting the constraint of the link state, and storing the optimal path in a path set.
S1.3, deleting the current optimal path based on the intersection constraint, and carrying out iterative updating on the topological relation to obtain a disjoint path set. Specifically, assume that a group of switching devices s= { S in the network 1 ,s 2 ,…,s N-1 Composition of F= { F 1 ,f 2 ,…,f n Flow throughThe controller performs path calculation and completes forwarding, and the disjoint path objective function expression is as follows:
in which IS represents a set of switches intersecting different paths, s f Representing a set of available paths for a data stream, whereinConstraint conditions of the multi-objective function are respectively an intersection constraint and a link state constraint expression as follows:
where k represents a path, r l Indicating the availability status of link l.
S2, selecting a plurality of evaluation parameters based on the available paths obtained in the step S1, comparing path quality and arranging according to priority.
S2.1, as shown in FIG. 2, the path composite quality evaluation module selects a plurality of evaluation parameters, and calculates the weight of each parameter through a fuzzy analytic hierarchy process. And 4 evaluation parameters including hop count, bit error rate, bandwidth and delay are selected from the path composite quality evaluation model to serve as path quality evaluation indexes. The SDN controller calculates link bandwidth and delay through data flow statistical information:
bw＝min{bw l |l∈k} (14)
where m represents the number of links on path k.
S2.2, determining the weight coefficient of the evaluation parameter by adopting a fuzzy analytic hierarchy process because of a certain competition relationship among the optimization targets, and further evaluating the composite quality of the available paths, wherein the flow is shown in figure 2.
Wherein S2.2 specifically comprises:
s2.2.1 it is assumed that the normalized value of the j (j=1, 2,3, 4) th evaluation parameter of the i (i=1, 2,3 … n) th path is x ij (0.ltoreq.i.ltoreq.n, 0.ltoreq.j.ltoreq.4), the sample set of normalized values for the respective composite masses for the respective paths may be written as a fuzzy complementary matrix, as shown in equation (6):
s2.2.2, transforming the fuzzy complementary matrix into a fuzzy consistent matrix, and summing the matrix of the formula (6):
then modifying elements in the fuzzy complementary matrix:
finally, a fuzzy matrix R' is obtained.
S2.2.3 the weighting coefficients corresponding to the 4 evaluation parameters of hop count, bit error rate, bandwidth and delay selected according to S2.1 are w1, w2, w3, w4, which are used for adjusting the importance degree of each evaluation parameter in path quality evaluation.
S2.2.4 by comparing the relative importance of the evaluation parameters in pairs, a fuzzy judgment matrix is constructed, the weight of the evaluation parameters is calculated, and the scale of 0.1 to 0.9 shown in Table 1 is adopted.
S2.2.5, obtaining a composite evaluation function of the path by weighted summation of the weight coefficient of the evaluation parameter and the normalized value of the evaluation parameter:
wherein W is a weight coefficient, and the constraint condition shown in the formula (10) is satisfied.
S3, sorting based on the composite quality of each available path calculated in the S2, selecting a route with the highest priority as the optimal route by a route decision module, and updating a path monitoring list.
S4, reselecting a routing path;
s4.1, for the paths needing to be rerouted, firstly backtracking according to the original forwarding paths, and acquiring relevant path information from a path monitoring list.
S4.2, after the related path information is obtained, the weight coefficient of the evaluation parameter is recalculated according to the existing forwarding condition of the network, and a rerouting path is calculated.
And S4.3, sequencing the composite quality of the available paths, and issuing rerouting paths to a routing decision module.
Specifically, the routing decision module adjusts the path evaluation parameter weight according to the service attribute of the data flow so as to meet the link requirements of different service flows. The paths are adjusted for different data streams through global optimization iteration, so that the path availability is improved, and meanwhile, the self-adaptive matching between the service requirements and the network resources is realized.
The following is a simulation experiment performed on the algorithm by using a Mininet simulation software platform, wherein the network controller uses Ryu v4.3, the OpenFlow switch uses Openvswitch v2.0.2, and the OpenFlow protocol version is 1.4.
Specifically, different groups of experiments were performed with throughput, delay and packet loss rate as indicators. The link bandwidth is set to 1Gpbs, the network delay parameters are all 10ms, and the random packet loss rate parameters are all 0%. The size of each packet is about 1500byte, i.e., 1.5KB, and the static buffer of the switch port is set to 200 packets (300 KB).
The experimental results are shown in fig. 4 and 5, and fig. 4 is an experimental result using data throughput as a performance index. From experimental results, it can be seen that the SDN path planning scheme based on the fuzzy analytic hierarchy process can obtain higher throughput than the original scheme of the SDN network, especially from 200s later, the average throughput of the new scheme can reach about 825.8Mbps, which is 14.5% higher than the average throughput of the original scheme (about 703.2 Mbps).
Fig. 5 shows the results of experiments using the average delay as a performance index. It can be observed that the average delay of the new solution is significantly smaller than that of the original solution, with a reduction of about 18% throughout the simulation phase.
In yet another aspect, the invention also discloses a computer readable storage medium storing a computer program which, when executed by a processor, causes the processor to perform the steps of the method as described above.
In yet another aspect, the invention also discloses a computer device comprising a memory and a processor, the memory storing a computer program which, when executed by the processor, causes the processor to perform the steps of the method as above.
In yet another embodiment provided herein, a computer program product containing instructions that, when run on a computer, cause the computer to perform any of the SDN multi-constraint path computation methods based on fuzzy hierarchy analysis of the above embodiments is also provided.
It may be understood that the system provided by the embodiment of the present invention corresponds to the method provided by the embodiment of the present invention, and explanation, examples and beneficial effects of the related content may refer to corresponding parts in the above method.
The embodiment of the application also provides an electronic device, which comprises a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory are communicated with each other through the communication bus,
a memory for storing a computer program;
and the processor is used for realizing the SDN multi-constraint path calculation method based on the fuzzy analytic hierarchy process when executing the program stored in the memory.
The communication bus mentioned by the above electronic device may be a peripheral component interconnect standard (english: peripheral Component Interconnect, abbreviated: PCI) bus or an extended industry standard architecture (english: extended Industry Standard Architecture, abbreviated: EISA) bus, or the like. The communication bus may be classified as an address bus, a data bus, a control bus, or the like.
The communication interface is used for communication between the electronic device and other devices.
The Memory may include random access Memory (Random Access Memory, abbreviated as RAM) or nonvolatile Memory (NVM), such as at least one disk Memory. Optionally, the memory may also be at least one memory device located remotely from the aforementioned processor.
The processor may be a general-purpose processor, including a central processing unit (Central Processing Unit, CPU for short), a network processor (Network Processor, NP for short), etc.; it may also be a digital signal processor (English: digital Signal Processing; DSP; for short), an application specific integrated circuit (English: application Specific Integrated Circuit; ASIC; for short), a Field programmable gate array (English: field-Programmable Gate Array; FPGA; for short), or other programmable logic device, discrete gate or transistor logic device, discrete hardware components.
In the above embodiments, it may be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented in software, may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When loaded and executed on a computer, produces a flow or function in accordance with embodiments of the present application, in whole or in part. The computer may be a general purpose computer, a special purpose computer, a computer network, or other programmable apparatus. The computer instructions may be stored in or transmitted from one computer-readable storage medium to another, for example, by wired (e.g., coaxial cable, optical fiber, digital Subscriber Line (DSL)), or wireless (e.g., infrared, wireless, microwave, etc.). The computer readable storage medium may be any available medium that can be accessed by a computer or a data storage device such as a server, data center, etc. that contains an integration of one or more available media. The usable medium may be a magnetic medium (e.g., floppy Disk, hard Disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., solid State Disk (SSD)), etc.
It is noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
In this specification, each embodiment is described in a related manner, and identical and similar parts of each embodiment are all referred to each other, and each embodiment mainly describes differences from other embodiments. In particular, for system embodiments, since they are substantially similar to method embodiments, the description is relatively simple, as relevant to see a section of the description of method embodiments.
The above embodiments are only for illustrating the technical solution of the present invention, and are not limiting; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention.
Claims (8)
1. An SDN multi-constraint path calculation method based on a fuzzy analytic hierarchy process is characterized by comprising the following steps,
s1, firstly, acquiring a path set;
s2, selecting a plurality of evaluation parameters based on the available paths obtained in the step S1, comparing path quality and arranging according to priority;
s3, sequencing based on the composite quality of each available path calculated in the S2, selecting a route with the highest priority as an optimal route by a route decision module, and updating a path monitoring list;
s4, re-selecting the routing path based on the updated path monitoring list.
2. The SDN multi-constraint path computation method based on fuzzy analytic hierarchy process of claim 1, wherein: the step S1 of firstly acquiring a path set comprises the following steps of,
s1.1, an SDN control plane acquires global state information by issuing a message to a switch of a data plane, and stores a basic topological relation by using a network tool iggraph;
s1.2, carrying out optimal path search based on a Floyd algorithm, selecting an optimal path meeting the constraint of a link state, and storing the optimal path in a path set;
s1.3, deleting the current optimal path based on the intersection constraint, and carrying out iterative updating on the topological relation to obtain a disjoint path set.
3. The SDN multi-constraint path computation method based on fuzzy analytic hierarchy process of claim 2, wherein: the step S1.3 specifically comprises,
assume that a set of switching devices s= { S in the network 1 ,s 2 ,…,s N-1 Composition of F= { F 1 ,f 2 ,…,f n The controller performs path computation and completes forwarding, and the disjoint path objective function expression is as follows:
in which IS represents a set of switches intersecting different paths, s f Representing a set of available paths for a data stream, wherein
Constraint conditions of the multi-objective function are respectively an intersection constraint and a link state constraint expression as follows:
where k represents a path, r l Indicating the availability status of link l.
4. The SDN multi-constraint path computation method based on fuzzy analytic hierarchy process of claim 3, wherein: the step S2 specifically includes the steps of,
s2.1, selecting a plurality of evaluation parameters through a path composite quality evaluation module, and calculating the weight of each parameter through a fuzzy analytic hierarchy process; selecting 4 evaluation parameters of hop count, bit error rate, bandwidth and delay from the path composite quality evaluation model as path quality evaluation indexes; the SDN controller calculates link bandwidth and delay through data flow statistical information:
bw＝min{bw l |l∈k} (4)
where m represents the number of links on path k;
s2.2, determining a weight coefficient of the evaluation parameter by adopting a fuzzy analytic hierarchy process, and further evaluating the composite quality of the available paths.
5. The SDN multi-constraint path computation method based on fuzzy analytic hierarchy process of claim 4, wherein: wherein S2.2 specifically comprises:
s2.2.1 assuming that the normalized value of the j-th evaluation parameter of the i-th path is x ij (0.ltoreq.i.ltoreq.n, 0.ltoreq.j.ltoreq.4), i=1, 2,3 … n, j=1, 2,3,4, the sample set of normalized values of the respective composite masses for the respective paths can be written as a fuzzy complementary matrix, as shown in equation (6):
s2.2.2, transforming the fuzzy complementary matrix into a fuzzy consistent matrix, and summing the matrix of the formula (6):
then modifying elements in the fuzzy complementary matrix:
finally obtaining a fuzzy matrix R';
s2.2.3 the weight coefficients corresponding to the 4 evaluation parameters of hop count, bit error rate, bandwidth and delay selected according to S2.1 are w1, w2, w3 and w4, which are used for adjusting the importance degree of each evaluation parameter in path quality evaluation;
s2.2.4, constructing a fuzzy judgment matrix by comparing the relative importance of the evaluation parameters in pairs and calculating the weight of the evaluation parameters;
s2.2.5, obtaining a composite evaluation function of the path by weighted summation of the weight coefficient of the evaluation parameter and the normalized value of the evaluation parameter:
wherein W is a weight coefficient, and the constraint condition shown in the formula (10) is satisfied.
6. The SDN multi-constraint path computation method based on fuzzy analytic hierarchy process of claim 5, wherein: the step S4 specifically includes the steps of,
s4.1, for the paths needing to be rerouted, firstly backtracking according to the original forwarding paths, and acquiring relevant path information from a path monitoring list;
s4.2, after the related path information is obtained, calculating the weight coefficient of the evaluation parameter again according to the existing forwarding condition of the network, and calculating a rerouting path;
and S4.3, sequencing the composite quality of the available paths, and issuing rerouting paths to a routing decision module.
7. A computer readable storage medium storing a computer program which, when executed by a processor, causes the processor to perform the steps of the method of any one of claims 1 to 6.
8. A computer device comprising a memory and a processor, the memory storing a computer program that, when executed by the processor, causes the processor to perform the steps of the method of any of claims 1 to 6.
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