Determining and implementing optimized network plans using segmented routing data and network data
阅读说明：本技术 利用分段路由数据和网络数据确定和实现优化网络规划 (Determining and implementing optimized network plans using segmented routing data and network data ) 是由 C·马加里亚 A·古普塔 于 2019-12-27 设计创作，主要内容包括：本发明提供了一种设备,该设备接收与网络相关联的网络数据,网络包括通过链路互连的网络设备,其中网络设备利用分段路由。设备接收与网络相关联的分段路由数据,其中分段路由数据至少包括：与由所述网络设备中的两个或多个网络设备通过网络提供的路径、以及对应的链路相关联的分段列表。该设备合并网络数据和分段路由数据以生成合并数据,并且利用优化模型处理合并数据,以确定特定时段内的潜在网络规划。该设备标识潜在网络规划中将与操作网络相关联的吞吐量最大化的潜在网络规划,并且基于潜在网络规划来执行一个或多个动作。(The present invention provides a device that receives network data associated with a network, the network including network devices interconnected by links, wherein the network devices utilize segmented routing. A device receives segment routing data associated with a network, wherein the segment routing data includes at least: a segment list associated with paths provided by two or more of the network devices through the network and corresponding links. The device merges the network data and the segment routing data to generate merged data, and processes the merged data using an optimization model to determine potential network plans over a particular time period. The apparatus identifies a potential network plan that maximizes throughput associated with the operating network in the potential network plan and performs one or more actions based on the potential network plan.)
1. A method, comprising:
receiving, by a device, network data associated with a network,
wherein the network comprises a plurality of network devices interconnected by links, an
Wherein the plurality of network devices utilize segmented routing;
receiving, by the device, segment routing data associated with the network,
wherein the segment routing data comprises at least: a segment list associated with paths provided by two or more of the plurality of network devices through the network and corresponding ones of the links;
receiving, by the device, a constraint associated with determining a network plan for the network,
wherein the constraints comprise at least a constraint indicating a particular time period associated with determining a plurality of potential network plans for the network;
merging, by the device, the network data and the segment routing data to generate merged data;
processing, by the appliance, the constraints and the consolidated data with an optimization model to determine a plurality of potential network plans within the particular time period;
identifying, by the device, a potential network plan of the plurality of potential network plans that maximizes throughput associated with operating the network; and
performing, by the device, one or more actions based on the potential network plan.
2. The method of claim 1, wherein the constraints further comprise one or more of:
a constraint indicating a failure threshold associated with a path provided by the plurality of network devices through the network and the link,
a constraint indicative of a capacity of the link,
constraints indicating possible paths for traffic demand of the network, or
A constraint indicating that there is no possible path for the traffic demand.
3. The method of claim 1, wherein the segment routing data further comprises data identifying one or more of:
the segments provided in the segment list,
statistics associated with the segments, or
A forwarding instruction associated with the segment.
4. The method of claim 1, wherein performing the one or more actions comprises one or more of:
causing the potential network plan to be implemented in the network by the plurality of network devices; or
Providing information identifying the potential network plan to a client device.
5. The method of claim 1, wherein identifying the potential network plan of the plurality of potential network plans that maximizes throughput associated with operating the network comprises:
determining a plurality of throughputs associated with the plurality of potential network plans based on the network data; and
identifying the potential network plan that maximizes throughput associated with operating the network based on the plurality of throughputs associated with the plurality of potential network plans.
6. The method of claim 1, wherein the constraints comprise a particular constraint indicating a failure threshold associated with the path provided through the network, an
Wherein the method further comprises:
determining one or more of the plurality of potential network plans that fail to satisfy the particular constraint; and
removing the one or more of the plurality of potential network plans from the plurality of potential network plans to generate a subset of the plurality of potential network plans, an
Wherein identifying the potential network plan comprises:
identifying the potential network plan from the subset of the plurality of potential network plans.
7. The method of claim 1, further comprising:
causing the potential network plan to be implemented in the network by the plurality of network devices;
receiving additional network data and additional segment routing data based on having the potential network plan implemented in the network by the plurality of network devices;
modifying the potential network plan based on the additional network data and the additional segment routing data to generate a modified potential network plan; and
causing the modified potential network plan to be implemented in the network by the plurality of network devices.
8. An apparatus, comprising:
one or more memories; and
one or more processors communicatively coupled to the one or more memories to:
network data associated with a network is received,
wherein the network comprises a plurality of network devices interconnected by links, an
Wherein the plurality of network devices utilize segmented routing;
receiving segment routing data associated with the network,
wherein the segment routing data comprises at least: a segment list associated with paths provided by two or more of the plurality of network devices through the network and corresponding ones of the links;
merging the network data and the segment routing data to generate merged data;
processing the consolidated data with a model to determine a plurality of potential network plans;
identifying a potential network plan of the plurality of potential network plans that maximizes throughput associated with operating the network; and
performing one or more actions based on the potential network plan.
9. The device of claim 8, wherein the network data comprises data identifying one or more of:
the plurality of network devices are connected to the network,
the link interconnecting the plurality of network devices,
the capabilities of the plurality of network devices,
a capacity of the link interconnecting the plurality of network devices,
by means of the path provided by the network,
a source of the path provided through the network,
a destination of the path provided through the network, or
Capacity of the path provided through the network.
10. The apparatus of claim 8, wherein the one or more processors are further to:
providing information identifying the plurality of potential network plans to a client device; and
receiving information from the client device indicating a selection of the potential network plan,
wherein the one or more processors, in identifying the potential network plan, are to:
based on the selection, the potential network plan is identified.
11. The apparatus of claim 8, wherein the one or more processors, in identifying the potential network plan of the plurality of potential network plans that maximizes throughput associated with operating the network, are to:
identifying the potential network plan of the plurality of potential network plans that minimizes a cost associated with operating the network.
12. The apparatus of claim 15, wherein the one or more processors, in identifying the potential network plan of the plurality of potential network plans that minimizes a cost associated with operating the network, are to:
determining a plurality of costs associated with the plurality of potential network plans based on the network data; and
identifying the potential network plan that minimizes a cost associated with operating the network based on the plurality of costs associated with the plurality of potential network plans.
13. The apparatus of claim 8, wherein the one or more processors, when processing the consolidated data with the model to determine the plurality of potential network plans, are to:
identifying traffic congestion associated with one of the paths provided through the network based on the consolidated data; and
determining a particular network plan of the plurality of potential network plans that reduces the traffic congestion associated with the one of the paths.
14. The apparatus of claim 8, wherein the one or more processors, when processing the consolidated data with the model to determine the plurality of potential network plans, are to:
identifying, based on the consolidated data, inoperable ones of the links associated with ones of the paths provided through the network; and
determining a particular network plan of the plurality of potential network plans that reroutes traffic away from the inoperable one of the links.
15. A non-transitory computer-readable medium storing instructions, the instructions comprising:
one or more instructions that when executed by one or more processors cause the one or more processors to:
network data associated with a network is received,
wherein the network comprises a plurality of network devices interconnected by links, an
Wherein the plurality of network devices utilize segmented routing;
receiving segment routing data associated with the network,
wherein the segment routing data comprises at least one or more of:
a segment list associated with paths provided by two or more of the plurality of network devices through the network and corresponding ones of the links;
data identifying the segments provided in the segment list,
statistics associated with the segments, or
Forwarding instructions associated with the segments;
merging the network data and the segment routing data to generate merged data;
processing the consolidated data using an optimization model to determine a plurality of potential network plans;
identifying a potential network plan of the plurality of potential network plans that maximizes throughput associated with operating the network; and
performing one or more actions based on the potential network plan.
16. The non-transitory computer-readable medium of claim 15, wherein the one or more instructions that cause the one or more processors to process the consolidated data with the optimization model to determine the plurality of potential network plans cause the one or more processors to:
identifying, based on the consolidated data, an inoperable network device of the plurality of network devices associated with a path of the paths provided through the network; and
determining a particular network plan of the plurality of potential network plans that reroutes traffic away from the inoperable one of the plurality of network devices.
17. The non-transitory computer-readable medium of claim 15, wherein the one or more instructions that cause the one or more processors to perform the one or more actions cause the one or more processors to one or more of:
causing the potential network plan to be implemented in the network by the plurality of network devices; or
Providing information identifying the potential network plan to a client device.
18. The non-transitory computer-readable medium of claim 15, wherein the one or more instructions that cause the one or more processors to identify the potential network plan of the plurality of potential network plans that maximizes throughput associated with operating the network cause the one or more processors to:
determining a plurality of throughputs associated with the plurality of potential network plans based on the network data; and
identifying the potential network plan that maximizes throughput associated with operating the network based on the plurality of throughputs associated with the plurality of potential network plans.
19. The non-transitory computer-readable medium of claim 15, wherein the instructions further comprise:
one or more instructions that when executed by the one or more processors cause the one or more processors to:
causing the potential network plan to be implemented in the network by the plurality of network devices;
receiving additional network data and additional segment routing data based on having the potential network plan implemented in the network by the plurality of network devices;
modifying the potential network plan based on the additional network data and the additional segment routing data to generate a modified potential network plan; and
causing the modified potential network plan to be implemented in the network by the plurality of network devices.
20. The non-transitory computer-readable medium of claim 15, wherein the one or more instructions that cause the one or more processors to process the consolidated data with the optimization model to determine the plurality of potential network plans cause the one or more processors to:
identifying traffic congestion associated with one of the paths provided through the network; and
determining a particular network plan of the plurality of potential network plans that reduces the traffic congestion associated with the one of the paths.
Background
Network planning and design is an iterative process, encompassing topology design, network synthesis, and network implementation. The purpose of network planning and design is to ensure that new or existing networks or services meet the needs of network subscribers and/or network operators.
Disclosure of Invention
According to some implementations, a method may include: network data associated with a network is received, wherein the network includes a plurality of network devices interconnected by links, and wherein the plurality of network devices utilize segment routing. The method can comprise the following steps: receiving segment routing data associated with a network, wherein the segment routing data includes at least: a segment list associated with a path provided by a network device of two or more of the plurality of network devices through the network and a corresponding one of the links. The method can comprise the following steps: constraints associated with determining a network plan for the network are received, wherein the constraints include at least a constraint indicating a particular time period associated with determining a plurality of potential network plans for the network. The method can comprise the following steps: the network data and the segment routing data are merged to generate merged data, and the constraints and the merged data are processed with an optimization model to determine a plurality of potential network plans within a particular time period. The method can comprise the following steps: a potential network plan of the plurality of potential network plans that maximizes throughput associated with the operating network is identified, and one or more actions are performed based on the potential network plan.
According to some implementations, a device may include one or more memories and one or more processors communicatively coupled to the one or more memories to receive network data associated with a network, where the network includes a plurality of network devices interconnected by links, and where the plurality of network devices utilize segmented routing. The one or more processors may receive segment routing data associated with a network, wherein the segment routing data includes at least: a segment list associated with a path provided by a network device of two or more of the plurality of network devices through the network and a corresponding one of the links. The one or more processors may merge the network data and the segment routing data to generate merged data, and may process the merged data using the model to determine a plurality of potential network plans. The one or more processors may identify a potential network plan of the plurality of potential network plans that maximizes throughput associated with the operating network and perform one or more actions based on the potential network plan.
According to some implementations, a non-transitory computer-readable medium may store instructions, which may include one or more instructions, which when executed by one or more processors of a device may cause the one or more processors to receive network data associated with a network, wherein the network includes a plurality of network devices interconnected by links, and wherein the plurality of network devices utilize segment routing. The one or more instructions may cause the one or more processors to receive segment routing data associated with the network, wherein the segment routing data includes at least one or more of: a segment list associated with paths provided through the network by network devices of two or more of the plurality of network devices and corresponding ones of the links, data identifying segments provided in the segment list, statistics associated with the segments, or forwarding instructions associated with the segments. The one or more instructions may cause the one or more processors to merge the network data and the segment routing data to generate merged data, and process the merged data using the optimization model to determine a plurality of potential network plans. The one or more instructions may cause the one or more processors to identify a potential network plan of the plurality of potential network plans that will maximize throughput associated with the operating network, and perform one or more actions based on the potential network plan.
Drawings
Fig. 1A-1F are schematic diagrams of one or more example embodiments described herein.
FIG. 2 is a schematic illustration of an example environment in which systems and/or methods described herein may be implemented.
FIG. 3 is a schematic diagram of example components of one or more of the devices of FIG. 2.
Fig. 4-6 are flowcharts of example processes for determining and implementing an optimized network plan utilizing segment routing data and network data.
Detailed Description
The following detailed description of example embodiments refers to the accompanying drawings. The same reference numbers may be used in different drawings to identify the same or similar elements.
A network planning and design system may design a network that includes network devices (e.g., routers, switches, gateways, firewalls, etc.) and links provided between the network devices. Segment routing, a form of computer network, is a variation of source routing. In a segment-routed network, an ingress network device may prepend a packet (e.g., traffic) containing a list of segments with a header, which is an instruction to execute on a subsequent network device in the network. These instructions may include forwarding instructions, such as instructions to forward a packet to a particular destination or interface.
However, in segment routing, no state or session information is maintained when creating paths between network devices. Without state or session information, the network device would not be aware of traffic congestion, traffic throughput, operational state, etc. associated with the path. This results in traffic loss and results in computing resources (e.g., processing resources, memory resources, etc.), network resources, etc. being wasted in identifying lost traffic, correcting inoperable paths, rerouting lost traffic, etc.
Some implementations described herein provide a controller platform that utilizes segment routing data and network data to determine and implement an optimized network plan. For example, the controller platform may receive network data associated with a network, wherein the network includes network devices interconnected by links, and wherein the network devices utilize segmented routing. The controller platform may receive segment routing data associated with the network, wherein the segment routing data includes at least: a segment list associated with paths provided by network devices of two or more of the network devices through the network and corresponding ones of the links. The controller platform may merge the network data and the segment routing data to generate merged data, and may process the merged data with a model to determine a plurality of potential network plans. The controller platform may identify a potential network plan that optimizes operation of the network (e.g., maximizes throughput associated with operating the network) among the potential network plans, and may perform one or more actions based on the potential network plan.
In this manner, the segmented routing information may enable the controller platform to determine and implement an optimized network plan in reduced time. This, in turn, saves wasted computational resources (e.g., processing resources, memory resources, etc.), network resources, etc., in identifying suboptimal network plans, correcting inefficient network operation due to suboptimal network plans, correcting inefficient utilization of network resources due to suboptimal network plans, identifying lost traffic, correcting inoperable paths, rerouting lost traffic, etc.
Fig. 1A-1F are schematic diagrams of one or
As further shown in fig. 1A, and as indicated by reference numeral 105, the controller platform may receive network data associated with a network. In some implementations, the network data may include topology data associated with the network, path data associated with the network, and the like. The topology data may include data identifying the network device (e.g., data identifying a type of network device, a network identifier of the network device, a location of the network device, hardware and/or software associated with the network device, other network devices adjacent to the network device, links connected to the network device, ports associated with the network device, etc.), links interconnecting the network devices (e.g., data identifying a type of link, a protocol used by the link, the network device to which the link is connected, ports associated with the network device, operational status of the link, etc.), utilization of the network device (e.g., capacity of the network device, throughput of the network device, operational status of the network device, etc.), and so forth. The path data may include data identifying: a path through a network provided by a network device, a source of the path through the network (e.g., one or more of the network devices, etc.), a destination of the path through the network (e.g., one or more of the network devices, etc.), a utilization of the path through the network (e.g., a capacity of the path, a throughput of the path, etc.), and so forth. In some implementations, the network data may include data identifying problems in the network (such as traffic congestion, inoperable network devices, inoperable links, etc.).
The controller platform may periodically receive network data from the network (e.g., at particular time intervals in units of seconds, minutes, hours, days, etc.), may continuously receive network data from the network, and so forth. For example, the controller platform may provide a request for network data to the network device, and the network device may provide the network data to the controller platform based on the request.
As further shown in fig. 1A, and as indicated by reference numeral 110, the controller platform may receive segment routing data from a network device. In some implementations, the segment routing data may include data identifying: a list of segments associated with paths and corresponding links provided by the network device through the network, segments provided in the segment list, statistics associated with the segments, forwarding instructions associated with the segments, and so forth.
The controller platform may periodically receive segment routing data from the network device (e.g., at particular time intervals in units of seconds, minutes, hours, days, etc.), may continuously receive segment routing data from the network device, and so forth. For example, the controller platform may provide a request for segment routing data to the network device, and the network device may provide the segment routing data to the controller platform based on the request.
As further illustrated in fig. 1A, and as indicated by reference numeral 115, the controller platform can receive (e.g., from a client device) constraints for network optimization. In some implementations, the constraints may include: constraints indicating specific time periods associated with determining a network plan for the network, constraints indicating failure thresholds associated with paths and links provided by network devices through the network, constraints indicating possible paths for traffic demands of the network, constraints indicating unfeasible paths for traffic demands, and the like. The constraints indicating the failure threshold may include a threshold count associated with traffic demand failures of the network plan (e.g., discarding network plans that include traffic demand failures that exceed the threshold count). The threshold count may be based on the capacity of the link, the set of possible paths through the network for the traffic demand, and/or a constraint indicating whether there is a certain path for the traffic demand or an unfeasible path for the traffic demand.
Although fig. 1A shows a specific number of network devices, links, etc., in some implementations, the network may include more (or fewer) network devices, links, etc. than depicted in fig. 1A. For example, a network may include hundreds, thousands, etc. of network devices and/or links that generate thousands, millions, billions, etc. of data points. In this way, the controller platform may process thousands, millions, billions, etc. of data points over a period of time (e.g., when determining a network plan) and thus may provide a "large data" capacity.
As shown in fig. 1B, and as indicated by reference numeral 120, the controller platform may merge the network data into the segment routing data to generate merged data. In some implementations, the controller platform may store the network data, segment routing data, and/or consolidated data in one or more data structures (e.g., databases, lists, tables, etc.) associated with the controller platform. In some implementations, the controller platform may utilize a merging technique to merge the network data and the segment routing data. The controller platform may utilize a merging technique to collect data (e.g., network data and segment routing data) for specific variables (e.g., paths provided by network devices through the network) from different sources. In some implementations, the consolidated data may include a unique record for each category of a particular variable. Thus, the controller platform can integrate different network data and segment routing data by utilizing matching merge and non-matching data techniques. For example, the network data may include the following data:
network device ID
Capacity of
Operating state
1
100％
Is operable
2
10％
Is operable
4
20％
Is not operable
5
50％
Is operable
Also, in this example, the segment routing data may include the following data:
network device ID
Route of travel
Number of segments
2
A
2-6-9
4
B
3-4-8
In this example, the controller platform may combine the network routing data and the segment routing data to generate merged data, the merged data including the following data:
in some implementations, the controller platform may remove data from the consolidated data that identifies network devices that are not associated with a path and/or segment number. This may reduce the number of data points associated with the consolidated data. In this manner, the controller platform may conserve resources (e.g., processing resources, memory resources, etc.) associated with processing the consolidated data (e.g., as described below), storing the consolidated data, etc.
As shown in fig. 1C, and as indicated by reference numeral 130, the controller platform may process the constraints and consolidated data using an optimization model to determine potential network plans within a particular time period (e.g., as specified by constraints indicating the particular time period associated with determining the network plans). The controller platform may train the optimization model with historical data (e.g., historical network data, historical segment routing data, historical merge data, etc.) to identify a network plan that improves the throughput of the network.
In some implementations, the controller platform may train an optimization model using historical data to determine potential network plans that improve the throughput of the network. For example, the controller platform may divide the historical data into a training set, a validation set, a test set, and the like. The training set may be utilized to train an optimization model. The validation set may be utilized to validate the results of the trained optimization model. The test set may be utilized to test the operation of the optimization model.
In some implementations, the controller platform can train the optimization model using, for example, an unsupervised training process and based on historical data. For example, the controller platform may perform dimension reduction to reduce historical data to a minimum feature set, thereby reducing resources (e.g., processing resources, memory resources, etc.) used to train the optimization model, and may apply classification techniques to the minimum feature set.
In some implementations, the controller platform may use logistic regression classification techniques to determine the classification results (e.g., historical data identifies potential network plans that improve the throughput of the network). Additionally or alternatively, the controller platform may use a naive bayes classifier technique. In this case, the controller platform may perform a binary recursive partitioning to divide the historical data into partitions and/or branches, and use the partitions and/or branches to determine the outcome (e.g., the historical data identifies potential network plans that improve throughput of the network). Based on using recursive partitioning, the controller platform may reduce utilization of computational resources relative to manual linear classification and analysis of data points, thereby enabling training of optimization models using thousands, millions, or billions of data points, which may result in more accurate models than using fewer data points.
Additionally or alternatively, the controller platform may use Support Vector Machine (SVM) classifier techniques to generate non-linear boundaries between data points of the training set. In this case, the non-linear boundary is used to classify the test data into a particular class.
Additionally or alternatively, the controller platform may train the optimization model using a supervised training process that includes inputs received from the subject matter expert to the optimization model, which may reduce the amount of time, amount of processing resources, etc. used to train the optimization model relative to an unsupervised training process. In some implementations, the controller platform may use one or more other model training techniques, such as neural network techniques, latent semantic indexing techniques, and so forth. For example, the controller platform may execute artificial neural network processing techniques (e.g., using a two-tier feed-forward neural network architecture, a three-tier feed-forward neural network architecture, etc.) to perform pattern identification with respect to historical data. In this case, the use of artificial neural network processing techniques can improve the accuracy of the trained optimization model generated by the controller platform by becoming more robust to noisy, inaccurate, or incomplete data, and by enabling the controller platform to detect patterns and/or trends that are not detectable to human analysts or systems using less complex techniques.
In some implementations, the controller platform may determine a first number of potential network plans if the particular time period is small (e.g., in seconds or minutes), and may determine a second number of potential network plans that is greater than the first number of potential network plans if the particular time period is large (e.g., in minutes or hours). Thus, a particular time period may be utilized (e.g., by a user of the controller platform) to determine resource usage of the controller platform and/or a number of potential network plans generated by the controller platform.
In some implementations, the controller platform can utilize constraints to set values of variables in the consolidated data, specify minimum values of variables, specify maximum values of variables, change values of variables, quickly determine whether values of variables will yield a solution (e.g., a potential network plan), and so forth. The controller platform may utilize this information when determining potential network plans. In some implementations, the controller platform may identify an inoperable one of the links and/or a network device associated with one of the paths provided through the network based on the consolidated data and may determine a particular network plan in which to reroute traffic away from the inoperable one of the links and/or the network device in the potential network plan.
In some implementations, the controller platform may allocate throughput to the potential network plan based on a number of factors, such as the number of network devices utilized in the potential network plan, the number and length of links utilized in the potential network plan, the utilization of network devices utilized, the utilization of links, and so forth. For example, each factor may be associated with a respective throughput (e.g., a particular type of network device may have a greater throughput than another type of network device), and the controller platform may assign the respective throughputs to different factors based on the potential network plan.
In some implementations, the controller platform may assign costs to the potential network plans based on a number of factors, such as the number of network devices utilized in the potential network plans, the number and length of links utilized in the potential network plans, the utilization of the network devices utilized, the utilization of the links, and so forth. For example, each factor may be associated with a respective cost (e.g., the cost of a link may be more than a network device), and the controller platform may assign the respective cost to the plurality of factors based on the potential network plan. In some implementations, the controller platform may determine a penalty associated with the potential network plan failing to meet the traffic demand of the network, and may add the penalty to the cost assigned to the potential network plan.
As shown in fig. 1D, and as indicated by reference numeral 130, the controller platform may identify a potential network plan that maximizes throughput (e.g., reduces resource usage by the network) associated with operating the network among the potential network plans. In some implementations, the controller platform may compare the throughput and/or cost determined for each of the potential network plans, and may select the potential network plan with the highest throughput and/or lowest cost. In some implementations, the controller platform may select the potential network plan with the lowest number of traffic demand failures, even if the potential network plan would not provide the highest throughput and/or lowest cost. The controller platform may select the potential network plan with the lowest number of traffic demand failures, highest throughput, and lowest cost. In some implementations, the controller platform may provide information identifying the potential network plan to the client device, and may receive a selection of the potential network plan from the client device. The controller platform may utilize the potential network plan identified by the selection.
In some implementations, the controller platform may determine that one or more of the potential network plans fail to satisfy a particular constraint and may remove the one or more of the potential network plans from the potential network plans to generate the subset of potential network plans. In these embodiments, the controller platform may identify the potential network plan from a subset of the potential network plans.
As shown in fig. 1E, and as indicated by
In some implementations, the controller platform may receive additional network data and additional segment routing data from the network based on causing the identified potential network plan to be implemented in the network, and may modify the identified potential network plan based on the additional network data and the additional segment routing data to generate a modified potential network plan. For example, if the additional network data indicates that a portion of the network is unable to manage new traffic demands, the controller platform may modify the identified potential network plans to manage the new traffic demands. The controller platform may then cause the modified potential network plan to be implemented in the network, as described above in connection with fig. 1A-1E.
As shown in fig. 1F, and as indicated by reference numeral 140, the controller platform may provide information identifying potential network plans for the network to the client device. The client device may receive information identifying the potential network plan and may provide the information identifying the potential network plan for display via a user interface. The user interface may enable a user of the client device to view features associated with the potential network plans, to view a graphical representation of the selected potential network plan, to select a potential network plan for implementation, and so on.
In some implementations, the controller platform may receive the network data and the segment routing data, and may merge the network data and the segment routing data to generate merged data. The controller platform can utilize the consolidated data and the optimization model to determine a solution to the traffic problem and/or automatically solve the traffic problem, and can perform one or more actions based on the solution (e.g., automatically implement the optimized network plan in a segmented routed network, provide potential network plans that solve the traffic problem to the client device, etc.). For example, if the segment routing data indicates that a path in the segment routing network utilizes a particular segment (e.g., segments 1-6-5) and the network data indicates that the path is from a first network device and a tenth network device, the controller platform may optimize the path (e.g., to utilize other particular segments (e.g., segments 1-6-8), a second network device, and a fifth network device) to have a greater throughput for the path.
In this manner, the controller platform can utilize the segment routing data and the network data to determine and implement an optimized network plan in a shorter amount of time. This, in turn, saves computational resources (e.g., processing resources, memory resources, etc.), network resources, etc., that are wasted in identifying suboptimal network plans, correcting inefficient network operations caused by suboptimal network plans, correcting inefficient utilization of network resources caused by suboptimal network plans, etc. In addition, embodiments described herein use rigorous computerized processes to perform tasks that have not been performed previously. For example, no techniques currently exist for utilizing segmented routing data and network data to determine and implement optimized network plans.
As described above, only fig. 1A to 1F are provided as examples. Other examples may be different than described with respect to fig. 1A-1F.
FIG. 2 is a schematic diagram of an example environment 200 in which systems and/or methods described herein may be implemented. As shown in FIG. 2, environment 200 may include a client device 210, a controller platform 220, a network 230, and a set of network devices 240 of network 230. The devices of environment 200 may be interconnected via wired connections, wireless connections, or a combination of wired and wireless connections.
Client device 210 includes one or more devices capable of receiving, generating, storing, processing, and/or providing information, such as the information described herein. For example, the client device 210 may include a mobile phone (e.g., smartphone, wireless phone, etc.), a laptop computer, a tablet computer, a desktop computer, a handheld computer, a gaming device, a wearable communication device (e.g., smart watch, smart glasses, heart rate monitor, fitness tracker, smart clothing, smart jewelry, head-mounted display, etc.), or similar types of devices. In some implementations, the client device 210 may receive information from the controller platform 220 and/or send information to the controller platform 220 via the network 230 and the network device 240. In some implementations, the client device 210 may receive network traffic from other client devices 210 via the network 230 (e.g., by routing packets using the network device 240 as a mediator) and/or may provide network traffic to other client devices 210.
The controller platform 220 includes one or more devices that utilize the segment routing data and the network data to determine and implement an optimized network plan. In some implementations, the controller platform 220 may be designed to be modular such that certain software components may be swapped in (swap in) or out (swap out) depending on particular needs. Thus, the controller platform 220 may be easily and/or quickly reconfigured for different uses. In some implementations, the controller platform 220 can receive information from one or more client devices 210 and/or network devices 240 and/or send information to one or more client devices 210 and/or network devices 240.
In some implementations, as shown, the controller platform 220 may be hosted in a cloud computing environment 222. Notably, while the implementations described herein describe the controller platform 220 as being hosted in the cloud computing environment 222, in some implementations, the controller platform 220 may not be cloud-based (i.e., may be implemented outside of the cloud computing environment) or may be partially cloud-based.
The cloud computing environment 222 includes an environment hosting the controller platform 220. The cloud computing environment 222 may provide computing, software, data access, storage, etc. services that do not require end-user knowledge of the physical location and configuration of the system(s) and/or device(s) hosting the controller platform 220. As shown, the cloud computing environment 222 may include a set of computing resources 224 (collectively referred to as "computing resources 224" and individually as "computing resources 224").
Computing resources 224 include one or more personal computers, workstation computers, host devices, or other types of computing and/or communication devices. In some implementations, the computing resources 224 may host the controller platform 220. Cloud resources may include computing instances executing in computing resources 224, storage devices provided in computing resources 224, data transfer devices provided by computing resources 224, and so forth. In some implementations, the computing resources 224 may communicate with other computing resources 224 via wired connections, wireless connections, or a combination of wired and wireless connections.
As further shown in FIG. 2, the computing resources 224 include a set of cloud resources, such as one or more applications ("APP") 224-1, one or more virtual machines ("VM") 224-2, virtualized storage ("VS") 224-3, one or more hypervisors ("HYP") 224-4, and so forth.
The applications 224-1 include one or more software applications that may be provided to the client device 210 or accessed by the client device 210. Application 224-1 may eliminate the need to install and execute software applications on client device 210 and/or network device 240. For example, the application 224-1 may include software associated with the controller platform 220 and/or any other software capable of being provided via the cloud computing environment 222. In some implementations, one application 224-1 may send/receive information to/from one or more other applications 224-1 via the virtual machine 224-2.
The virtual machine 224-2 comprises a software implementation of a machine (e.g., a computer) that executes programs, such as a physical machine. Virtual machine 224-2 may be a system virtual machine or a process virtual machine, depending on the application and corresponding level to any real machine. The system virtual machine may provide a complete system platform that supports the execution of a complete operating system ("OS"). The process virtual machine may execute a single program and may support a single process. In some implementations, the virtual machine 224-2 may execute on behalf of a user (e.g., a user of the client device 210 or an operator of the controller platform 220) and may manage the infrastructure of the cloud computing environment 222, such as data management, synchronization, or long data transfers.
Virtualized storage 224-3 includes one or more storage systems and/or one or more devices that use virtualization techniques within the storage systems or devices of computing resources 224. In some implementations, the types of virtualization may include block virtualization and file virtualization in the context of a storage system. Block virtualization may refer to the abstraction (or separation) of logical storage from physical storage so that a storage system may be accessed without regard to physical storage or heterogeneous structure. The separation may allow an administrator of the storage system flexibility in how to manage end-user storage. File virtualization may eliminate dependencies between data accessed at the file level and the location where the file is physically stored. This may support optimization of storage usage, server consolidation, and/or execution without interfering with file migration.
Hypervisor (hypervisor)224-4 may provide hardware virtualization techniques that allow multiple operating systems (e.g., "guest operating systems") to execute concurrently on a host machine, such as computing resources 224. Hypervisor 224-4 may present the virtual operating platform to the guest operating systems and may manage the execution of the guest operating systems. Multiple instances of various operating systems may share virtualized hardware resources.
The network 230 includes one or more wired and/or wireless networks. For example, network 230 may include a cellular network (e.g., a fifth generation (5G) network, a Long Term Evolution (LTE) network, a third generation (3G) network, a code division multiple access (CDDMA) network, etc.), a Public Land Mobile Network (PLMN), a Local Area Network (LAN), a Wide Area Network (WAN), a Metropolitan Area Network (MAN), a telephone network (e.g., the Public Switched Telephone Network (PSTN)), a private network, an ad hoc network, an intranet, the internet, a fiber-based network, etc., and/or a combination of these or other types of networks.
Network device 240 includes one or more devices capable of receiving, processing, storing, routing, and/or providing traffic (e.g., packets, other information or metadata, etc.) in the manner described herein. For example, network device 240 may include routers such as Label Switched Routers (LSRs), Label Edge Routers (LERs), ingress routers, egress routers, provider routers (e.g., provider edge routers, provider core routers, etc.), virtual routers, and so forth. Additionally or alternatively, network device 240 may include a gateway, switch, firewall, hub, bridge, reverse proxy, server (e.g., proxy server, cloud server, data center server, etc.), load balancer, and/or the like. In some implementations, the network device 240 may be a physical device implemented within an enclosure (such as a rack). In some implementations, the network device 240 may be a virtual device implemented by one or more computer devices or data centers of a cloud computing environment. In some implementations, the set of network devices 240 may be a set of data center nodes for routing traffic through the network 230.
The number and arrangement of devices and networks shown in fig. 2 are provided as examples. Indeed, there may be additional devices and/or networks, fewer devices and/or networks, different devices and/or networks, or devices and/or networks arranged in a different manner than those shown in fig. 2. Further, two or more of the devices shown in FIG. 2 may be implemented within a single device, or a single device shown in FIG. 2 may be implemented as multiple distributed devices. Additionally or alternatively, a set of devices (e.g., one or more devices) of environment 200 may perform one or more functions described as being performed by another set of devices of environment 200.
Fig. 3 is a schematic diagram of example components of a device 300. The device 300 may correspond to the client device 210, the controller platform 220, the computing resources 224, and/or the network device 240. In some implementations, client device 210, controller platform 220, computing resources 224, and/or network device 240 may include one or more devices 300 and/or one or more components of devices 300. As shown in fig. 3, device 300 may include a bus 310, a processor 320, a memory 330, a storage component 340, an input component 350, an output component 360, and a communication interface 370.
Bus 310 includes components that allow communication among the components of device 300. The processor 32 is implemented in hardware, firmware, or a combination of hardware and software. Processor 320 is a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), an Accelerated Processing Unit (APU), a microprocessor, a microcontroller, a Digital Signal Processor (DSP), a Field Programmable Gate Array (FPGA), an Application Specific Integrated Circuit (ASIC), or another type of processing component. In some implementations, processor 320 includes one or more processors that can be programmed to perform functions. Memory 330 includes a Random Access Memory (RAM), a Read Only Memory (ROM), and/or another type of dynamic or static storage device (e.g., flash memory, magnetic memory, and/or optical memory) that stores information and/or instructions for use by processor 320.
The storage component 340 stores information and/or software related to the operation and use of the device 300. For example, storage component 340 may include a hard disk (e.g., a magnetic disk, an optical disk, a magneto-optical disk, and/or a solid state disk), a Compact Disc (CD), a Digital Versatile Disc (DVD), a floppy disk, an ink cartridge, a magnetic tape, and/or another type of non-transitory computer-readable medium, and corresponding drives.
Input components 350 include components that allow device 300 to receive information, such as via user input (e.g., a touch screen display, keyboard, keypad, mouse, buttons, switches, and/or microphone). Additionally or alternatively, input component 350 may include sensors for sensing information (e.g., Global Positioning System (GPS) components, accelerometers, gyroscopes, and/or actuators). Output components 360 include components that provide output information from device 300 (e.g., a display, a speaker, and/or one or more Light Emitting Diodes (LEDs)).
Communication interface 370 includes transceiver-like components (e.g., a transceiver and/or separate receivers and transmitters) that enable device 300 to communicate with other devices, such as via a wired connection, a wireless connection, or a combination of wired and wireless connections. Communication interface 370 may allow device 300 to receive information from and/or provide information to another device. For example, communication interface 370 may include an ethernet interface, an optical interface, a coaxial interface, an infrared interface, a Radio Frequency (RF) interface, a Universal Serial Bus (USB) interface, a Wi-Fi interface, a cellular network interface, and/or the like.
Device 300 may perform one or more processes described herein. Device 300 may perform these processes based on processor 320 executing software instructions stored by a non-transitory computer-readable medium, such as memory 330 and/or storage component 340. A computer-readable medium is defined herein as a non-transitory memory device. The memory device includes memory space within a single physical memory device or memory space spread to multiple physical memory devices.
The software instructions may be read into memory 330 and/or storage component 340 from another computer-readable medium or from another device via communication interface 370. When executed, software instructions stored in memory 330 and/or storage component 340 may cause processor 320 to perform one or more processes described herein. Additionally or alternatively, hardwired circuitry may be used in place of or in combination with software instructions to implement one or more processes described herein. Thus, embodiments described herein are not limited to any specific combination of hardware circuitry and software.
The number and arrangement of components shown in fig. 3 are provided as examples. Indeed, device 300 may include additional components, fewer components, different components, or components arranged in a different manner than those shown in FIG. 3. Additionally or alternatively, a set of components (e.g., one or more components) of device 300 may perform one or more functions described as being performed by another set of components of device 300.
Fig. 4 is a flow diagram of an example process 400 for determining and implementing an optimized network plan utilizing segment routing data and network data. In some implementations, one or more of the process blocks of fig. 4 may be performed by a controller platform (e.g., controller platform 220). In some implementations, one or more of the process blocks of fig. 4 may be performed by another device or a group of devices separate from or including the controller platform, such as a client device (e.g., client device 210) and/or a network device (e.g., network device 240).
As shown in fig. 4, process 400 may include: network data associated with a network is received, wherein the network includes a plurality of network devices interconnected by links, and wherein the plurality of network devices utilize segment routing (block 410). For example, the controller platform (e.g., using the computing resources 224, the processor 320, the memory 330, the communication interface 370, etc.) may receive network data associated with a network, as described above in connection with fig. 1A-3. In some aspects, a network may include multiple network devices interconnected by links, and the multiple network devices may utilize segmented routing.
As further shown in fig. 4, process 400 may include: segment routing data associated with a network is received, wherein the segment routing data includes at least a list of segments associated with paths provided through the network by network devices of two or more of the plurality of network devices and corresponding ones of the links (block 420). For example, the controller platform (e.g., using the computing resources 224, the processor 320, the communication interface 370, etc.) may receive segment routing data associated with the network, as described above in connection with fig. 1A-3. In some aspects, the segment routing data may include at least a list of segments associated with corresponding ones of the paths and links provided by the network device of the two or more of the plurality of network devices through the network.
As further shown in fig. 4, process 400 may include: constraints associated with determining a network plan for the network are received, where the constraints include at least a constraint indicating a particular time period associated with determining a plurality of potential network plans for the network (block 430). For example, the controller platform (e.g., using the computing resources 224, the processor 320, the communication interface 370, etc.) may receive constraints associated with determining a network plan for the network, as described above in connection with fig. 1A-3. In some aspects, the constraints may include at least a constraint indicating a particular time period associated with determining a plurality of potential network plans for the network.
As further shown in fig. 4, process 400 may include: the network data and the segment routing data are merged to generate merged data (block 440). For example, the controller platform (e.g., using the computing resources 224, the processor 320, the memory 330, etc.) may merge the network data and the segment routing data to generate merged data, as described above in connection with fig. 1A-3.
As further shown in fig. 4, process 400 may include: the constraints and consolidated data are processed using an optimization model to determine a plurality of potential network plans over a particular time period (block 450). For example, the controller platform (e.g., using the computing resources 224, the processor 320, the storage component 340, etc.) may process the constraints and the consolidated data using an optimization model to determine a plurality of potential network plans within a particular time period, as described above in connection with fig. 1A-3.
As further shown in fig. 4, process 400 may include: a potential network plan of the plurality of potential network plans that maximizes throughput associated with the operating network is identified (block 460). For example, the controller platform (e.g., using the computing resources 224, the processor 320, the memory 330, etc.) may identify a potential network plan of the plurality of potential network plans that maximizes throughput associated with operating the network, as described above in connection with fig. 1A-3.
As further shown in fig. 4, process 400 may include: one or more actions are performed based on the potential network plan (block 470). For example, the controller platform (e.g., using the computing resources 224, the processor 320, the memory 330, the storage component 340, the communication interface 370, etc.) may perform one or more actions based on the potential network plan, as described above in connection with fig. 1A-3.
Process 400 may include additional implementations, such as any single implementation or any combination of implementations described below and/or in conjunction with one or more other processes described elsewhere herein.
In some implementations, the constraints may include: a constraint indicating a failure threshold associated with paths and links provided by a plurality of network devices through a network, a constraint indicating a capacity of a link, a constraint indicating possible paths for traffic demand of the network, a constraint indicating no possible paths for traffic demand, and the like. In some implementations, the segment routing data may include data identifying: segments provided in a segment list, statistics associated with the segments, forwarding instructions associated with the segments, and the like.
In some implementations, the controller platform may cause the potential network plan to be implemented in the network through a plurality of network devices when performing the one or more actions, may provide information identifying the potential network plan to a client device, and/or the like. In some implementations, when identifying a potential network plan of the plurality of potential network plans that maximizes throughput associated with the operating network, the controller platform may determine a plurality of throughputs associated with the plurality of potential network plans based on the network data, and may identify a potential network plan that maximizes throughput associated with the operating network based on the plurality of throughputs associated with the plurality of potential network plans.
In some implementations, the constraints may include specific constraints that indicate a failure threshold associated with a path provided through the network. In some implementations, the controller platform may cause the potential network plan to be implemented in the network through the plurality of network devices, may be implemented in the network based on causing the potential network plan to be implemented in the network through the plurality of network devices, receives additional network data and additional segment routing data, may modify the potential network plan based on the additional network data and the additional segment routing data to generate a modified potential network plan, and may cause the modified potential network plan to be implemented in the network through the plurality of network devices.
Although fig. 4 shows example blocks of the process 400, in some implementations, the process 400 may include additional blocks, fewer blocks, different blocks, or blocks arranged in a different manner than those shown in fig. 4. Additionally or alternatively, two or more of the blocks of process 400 may be performed in parallel.
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In some implementations, the network data may include data identifying: a plurality of network devices, links interconnecting the plurality of network devices, capacities of the links interconnecting the plurality of network devices, paths provided through the network, sources of the paths provided through the network, destinations of the paths provided through the network, capacities of the paths provided through the network, and the like.
In some implementations, the controller platform may provide information identifying a plurality of potential network plans to the client device; information indicative of a selection of a potential network plan may be received from a client device; and potential network plans may be identified based on the selection. In some implementations, when identifying a potential network plan of the plurality of potential network plans that maximizes throughput associated with the operating network, the controller platform may identify a potential network plan of the plurality of potential network plans that minimizes a cost associated with the operating network.
In some implementations, when identifying a potential network plan of the plurality of potential network plans that minimizes a cost associated with the operating network, the controller platform may determine a plurality of costs associated with the plurality of potential network plans based on the network data, and may identify a potential network plan that minimizes the cost associated with the operating network based on the plurality of costs associated with the plurality of potential network plans.
In some implementations, when the consolidated data is processed with the model to determine the plurality of potential network plans, the controller platform may identify traffic congestion associated with one of the paths provided through the network based on the consolidated data and may determine a particular one of the plurality of potential network plans that reduces the traffic congestion associated with the one of the paths.
In some implementations, when the consolidated data is processed with the model to determine the plurality of potential network plans, the controller platform may identify, based on the consolidated data, an inoperable one of the links associated with one of the paths provided through the network, and may determine a particular one of the plurality of potential network plans that reroutes traffic away from the inoperable one of the links.
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In some implementations, when the consolidated data is processed with the optimization model to determine the plurality of potential network plans, the controller platform may identify, based on the consolidated data, an inoperable network device of the plurality of network devices associated with one of the paths provided through the network, and may determine a particular network plan of the plurality of potential network plans that reroutes traffic away from the inoperable network device of the plurality of network devices.
In some implementations, the controller platform may cause the potential network plan to be implemented in the network through a plurality of network devices when performing the one or more actions, may provide information identifying the potential network plan to a client device, and/or the like.
In some implementations, when identifying a potential network plan of the plurality of potential network plans that maximizes throughput associated with the operating network, the controller platform may determine a plurality of throughputs associated with the plurality of potential network plans based on the network data, and may identify a potential network plan that maximizes throughput associated with the operating network based on the plurality of throughputs associated with the plurality of potential network plans.
In some implementations, the controller platform may cause the potential network plan to be implemented in the network through the plurality of network devices, may be implemented in the network based on causing the potential network plan to be implemented in the network through the plurality of network devices, receives additional network data and additional segment routing data, may modify the potential network plan based on the additional network data and the additional segment routing data to generate a modified potential network plan, and may cause the modified potential network plan to be implemented in the network through the plurality of network devices.
In some implementations, when processing the consolidated data with the optimization model to determine a plurality of potential network plans, the controller platform may identify traffic congestion associated with one of the paths provided through the network and may determine a particular one of the plurality of potential network plans that reduces the traffic congestion associated with the one of the paths.
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The foregoing disclosure provides illustration and description, but is not intended to be exhaustive or to limit the implementation to the precise form disclosed. Modifications and variations are possible in light of the above disclosure or may be acquired from practice of the implementations.
As used herein, the term "component" is intended to be broadly interpreted as hardware, firmware, or a combination of hardware and software.
As used herein, meeting a threshold may refer to a value greater than the threshold, greater than or equal to the threshold, less than or equal to the threshold, etc., depending on the context.
Certain user interfaces have been described and illustrated herein and/or in the accompanying drawings. The user interface may include a graphical user interface, a non-graphical user interface, a text-based user interface, and the like. The user interface may provide information to be displayed. In some implementations, a user may interact with information, such as by providing input via an input component of a device that provides a user interface to be displayed. In some implementations, the user interface may be configured by the device and/or the user (e.g., the user may change the size of the user interface, information provided via the user interface, location of information provided via the user interface, etc.). Additionally or alternatively, the user interface may be pre-configured to a standard configuration, a canonical configuration, based on a specific configuration of the type of device on which the user interface is displayed and/or based on a set of configurations of capabilities and/or specifications associated with the device on which the user interface is displayed.
It is apparent that the systems and/or methods described herein may be implemented in different forms of hardware, firmware, or a combination of hardware and software. The actual specialized control hardware or software code used to implement the systems and/or methods is not limited to this implementation. Thus, the operation and behavior of the systems and/or methods were described herein without reference to the specific software code-it being understood that software and hardware may be designed to implement the systems and/or methods based on the description herein.
Although particular combinations of features are recited in the claims and/or disclosed in the specification, these combinations are not intended to limit the disclosure of the various embodiments. Indeed, many of these features may be combined in ways not specifically recited in the claims and/or not specifically disclosed in the specification. While each of the dependent claims listed below may depend directly on only one claim, the disclosure of the various embodiments includes each dependent claim in combination with every other claim in the set of claims.
No element, act, or instruction used herein should be construed as critical or essential to the invention unless explicitly described as such. Also, as used herein, the articles "a" and "an" are intended to include one or more items, and may be used interchangeably with "one or more". Further, as used herein, the term "group" is intended to include one or more items (e.g., related items, unrelated items, combinations of related and unrelated items, etc.), and may be used interchangeably with "one or more. Where only one item is referred to, the word "only one" or similar language is used. Also, as used herein, the terms "having", and the like are intended to be open-ended terms. Furthermore, the phrase "based on" is intended to mean "based, at least in part, on" unless explicitly stated otherwise.
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