CN106302221A - Traffic scheduling method based on end office's cloud and system - Google Patents
Traffic scheduling method based on end office's cloud and system Download PDFInfo
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L47/00—Traffic control in data switching networks
- H04L47/10—Flow control; Congestion control
- H04L47/12—Avoiding congestion; Recovering from congestion
- H04L47/125—Avoiding congestion; Recovering from congestion by balancing the load, e.g. traffic engineering
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L47/00—Traffic control in data switching networks
- H04L47/10—Flow control; Congestion control
- H04L47/24—Traffic characterised by specific attributes, e.g. priority or QoS
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L47/00—Traffic control in data switching networks
- H04L47/50—Queue scheduling
- H04L47/52—Queue scheduling by attributing bandwidth to queues
- H04L47/527—Quantum based scheduling, e.g. credit or deficit based scheduling or token bank
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L47/00—Traffic control in data switching networks
- H04L47/50—Queue scheduling
- H04L47/62—Queue scheduling characterised by scheduling criteria
- H04L47/625—Queue scheduling characterised by scheduling criteria for service slots or service orders
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Abstract
The present invention provides a kind of traffic scheduling method based on end office's cloud and system, and wherein, the method includes: vCPE obtains the flow load data of each port；The flow load data of each port that vCPE will get, store in the first storage matrix；VCPE is optimized lexical analysis to the flow load data of each port in the first storage matrix, to determine the Optimized Operation strategy of each port；The flow of each port, according to the Optimized Operation strategy of each port, is scheduling by vCPE.New adjustment decision-making is obtained according to real-time each port flow state, determine the port of imbalance, the port of imbalance is adjusted, the each port i.e. network traffics of node are made to carry out overall situationization Optimized Operation, achieve the floating resources of each port can reach optimization, the response service time can the least, network traffics throughput can be the biggest, and then reduce network congestion degree, improve network utilization, reduce consumption.
Description
Technical Field
The invention relates to the technical field of communication, in particular to a traffic scheduling method and system based on end office clouding.
Background
End office clouding has become an important trend in the development of the global telecommunication industry, and an end office clouding technology is generated to solve the defects of the existing professional communication equipment. Its functions may be aggregated or decomposed and the aggregated or decomposed functions instantiated on the infrastructure. Currently, end office clouding has become a key development point in the global telecommunications industry. With the rapid growth of telecommunication application services, the flow in a network rapidly grows, and the flow needs to be scheduled and controlled in the existing end office cloud application system. The problems of high network congestion degree, low utilization rate, high consumption and the like are increasingly highlighted.
In the prior art, an end office cloud application system mainly adopts a static centralized traffic scheduling mode to perform traffic scheduling, the static centralized traffic scheduling mode has a connection-oriented characteristic, and the scheduling and control of traffic are realized through mechanisms such as QoS negotiation, admission control, bandwidth reservation and the like.
However, in the prior art, the mechanisms such as QoS negotiation, admission control, bandwidth reservation and the like adopted in the static centralized traffic scheduling manner still cannot solve the problem of high network congestion degree well, and the network utilization rate is low and the consumption is high.
Disclosure of Invention
The invention provides a traffic scheduling method and system based on end office clouding, which are used for solving the problems that the prior art cannot well solve the problem of high network congestion degree, and the problems of low network utilization rate and high consumption.
One aspect of the present invention provides a traffic scheduling method based on end office clouding, including:
the vCPE acquires flow load data of each port;
the vCPE stores the acquired traffic load data of each port into a first storage matrix;
the vCPE performs optimized scheduling analysis on the traffic load data of each port in the first storage matrix to determine an optimized scheduling strategy of each port;
and the vCPE schedules the flow of each port according to the optimized scheduling strategy of each port.
Another aspect of the present invention provides a traffic scheduling system based on end office clouding, including:
vCPE and ports;
the vCPE is used for acquiring flow load data of each port; storing the acquired traffic load data of each port into a first storage matrix; performing optimized scheduling analysis on the traffic load data of each port in the first storage matrix to determine an optimized scheduling strategy of each port; and scheduling the flow of each port according to the optimized scheduling strategy of each port.
The invention has the technical effects that: acquiring port traffic load data acquired by each port through an OS Server, and storing the acquired port traffic load data of each port into a first storage matrix; optimizing a priority scheduling evaluation function according to the user grade, and determining a port with imbalance of flow, time delay and packet loss rate; and the OS Server submodule triggers a user level priority optimization scheduling algorithm to the maladjusted port, dynamically adjusts the maladjusted port and adjusts a data mapping matrix of the maladjusted port. Therefore, a new adjustment decision can be obtained according to the real-time flow state of each port, the out-of-order port is determined, the out-of-order port is adjusted, the network flow of each port, namely the node, is subjected to global optimization scheduling, the flow resource of each port can be optimized, the response service time can be as short as possible, the network flow throughput rate can be as high as possible, the network congestion degree is reduced, the network utilization rate is improved, and the consumption is reduced.
Drawings
Fig. 1 is a flowchart of a traffic scheduling method based on end office clouding according to an embodiment of the present invention;
fig. 2 is a flowchart of a traffic scheduling method based on end office clouding according to an embodiment of the present invention;
fig. 3 is a schematic structural diagram of a traffic scheduling system based on end office clouding according to a third embodiment of the present invention;
fig. 4 is a schematic structural diagram of a traffic scheduling system based on end office clouding according to a fourth embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Fig. 1 is a flowchart of a traffic scheduling method based on end office clouding according to an embodiment of the present invention, and as shown in fig. 1, the method according to this embodiment includes:
step 101, the vCPE obtains traffic load data of each port.
The specific implementation manner of step 101 is as follows:
each port actively reports the acquired traffic load data to the vCPE every preset time; alternatively, the vCPE periodically queries the traffic load data obtained by each port.
In this embodiment, specifically, the VPN server accesses the vbrs for authentication to access the internal resources of the enterprise, and the terminal of the user of the fixed network enterprise and the enterprise accesses the internal resources of the enterprise, such as the internal office system of the enterprise and the enterprise, through the PG capable of accessing the internal resources of the enterprise. In this process, there are OS Server sub-modules on the vCPE, and one OS Client sub-module per vbrs module. And each OS Client submodule actively reports the flow to the OS Server submodule, and the OS Server submodule automatically and periodically adopts a flow scheduling strategy to perform flow scheduling.
And each port actively reports the acquired traffic load data to the OS Server submodule at preset time intervals, or the OS Server submodule periodically inquires the traffic load data acquired by each port, wherein the traffic load data comprises port traffic load, time delay and packet loss rate data.
Step 102, the vCPE stores the acquired traffic load data of each port in a first storage matrix.
In this embodiment, specifically, the OS Server sub-module of the vCPE stores the acquired port traffic load data of each port in the first storage matrix.
Step 103, the vCPE performs optimized scheduling analysis on the traffic load data of each port in the first storage matrix to determine an optimized scheduling policy of each port.
In this embodiment, specifically, the OS Server sub-module of the vCPE performs optimal scheduling analysis on traffic load data of each port in the first storage matrix to determine an optimal scheduling policy of each port.
And step 104, the vCPE schedules the flow of each port according to the optimized scheduling strategy of each port.
The specific implementation manner of step 104 is as follows: the vCPE determines a port with imbalance of flow, time delay and packet loss rate according to a user grade optimization priority scheduling evaluation function; and the vCPE optimizes and adjusts the flow of the detuned port.
The vCPE determines the ports with imbalance of flow, time delay and packet loss rate according to the user grade optimization priority scheduling evaluation function, and the method comprises the following steps:
determining user-level optimized prioritized scheduling evaluation function Wherein x isij kIs a defined value of whether a port shares traffic and π、ν∈(0,1)，Qij kand Vij kAre respectively port xij kBased on its priority, congestion degree satisfaction and traffic utilization, andadjustment factors of congestion degree satisfaction and flow utilization degree are respectively; k denotes the kth iteration, k ≦ d and k ≦ 1,2, …, d; PRIij k、delayij k、LRij kAnd FLOWij kRespectively port priority, port time delay, port packet loss rate and port flow, wherein theta, sigma, pi and ν are all adjustment factors;
determining the adjusted first memory matrix as Mij k+1＝vij k+1*tuWherein v isij k+1＝τij k*vij k+ρ*(MPk-Mij k)+ξ*(MGk-Mij k)，τij kFor autonomous learning of pheromone concentration weights, vij kFor M in the k-th iterationij kDirection vector of, tuIs a unit time unit, vij k+1For the direction vector of the (k + 1) th iteration, both ρ and ξ are adjustment factors, MPkAnd MGkRespectively obtaining a local optimal port data vector of the current iteration and a global port data vector of the previous k iterations in the kth iteration; mij kFor the first memory matrix, Mij k＝{delayij k,LRij k,FLOWij k}；
And when the user grade optimization priority scheduling evaluation function is determined not to be met or the current iteration times are less than or equal to the maximum iteration times, determining that the flow of the current port is out of order, wherein the user grade optimization priority scheduling evaluation function is not met, and the value of the user grade optimization priority scheduling evaluation function is less than or equal to the average value of the values of the user grade optimization priority scheduling evaluation functions of all ports in the first iteration.
In this embodiment, specifically, the OS Server sub-module of the vCPE schedules the traffic of each port according to the optimized scheduling policy of each port.
The OS Server submodule performs optimized scheduling analysis on the traffic load data of each port in the first storage matrix to determine an optimized scheduling strategy of each port; then, the OS Server sub-module schedules the traffic of each port according to the optimal scheduling policy of each port, which specifically includes: OS SeThe rver submodule determines a port with imbalance of flow, time delay and packet loss rate according to a user grade optimization priority scheduling evaluation function; and the OS Server submodule performs flow optimization and adjustment on the maladjusted port. The OS Server submodule determines a port with maladjusted flow, time delay and packet loss rate according to the user level optimization priority scheduling evaluation function, and comprises the following steps: setting the iteration maximum algebra d as 200, and initializing a port data mapping matrix according to a first storage matrix; m in port data mapping matrixij kA port data vector including three aspects of port time delay, port packet loss rate and port flow is Mij k＝{delayij k,LRij k,FLOWij k}; wherein, the matrix Mij kThe following were used:
the definition value of whether the port shares the flow isThe user grade optimization priority scheduling evaluation function is、Wherein, and is θ、σ∈(0,1)，π、ν∈(0,1)，Qij kAnd Vij kAre respectively port xij kBased on its priority, congestion degree satisfaction and traffic utilization, andadjustment factors for congestion satisfaction and traffic utilization, k representing the k-th iteration, where k must satisfy the condition k ≦ d, the condition k ≦ 1,2, …, d, PRIij k、delayij k、LRij kAnd FLOWij kThe port priority, the port time delay, the packet loss rate of the port and the port flow theta, sigma, pi and v are all adjustment factors. The adjusted first memory matrix is Mij k+1＝vij k+1*tuWherein v isij k+1＝τij k*vij k+ρ*(MPk-Mij k)+ξ*(MGk-Mij k)，τij kFor autonomous learning of pheromone concentration weights, vij kFor M in the k-th iterationij kDirection vector of, tuIs a unit time unit, vij k+1For the direction vector of the (k + 1) th iteration, both ρ and ξ are adjustment factors, MPkAnd MGkRespectively obtaining a local optimal port data vector of the current iteration in the kth iteration and a global port data vector of the previous k iterations (including the current iteration); when determining that the user grade optimization prior scheduling evaluation function is not satisfied or the current iteration times are less than or equal to the maximum iteration times, determining that the flow of the current port is out of order, wherein the user grade optimization prior scheduling evaluation function is not satisfied, the value of the user grade optimization prior scheduling evaluation function is less than or equal to the value of the user grade optimization prior scheduling evaluation function, and the user grade of each port in the first iteration isOptimizing an average value of the values of the priority scheduling evaluation function; the user level priority optimization scheduling algorithm can be triggered to dynamically adjust the maladjusted ports, and the data mapping matrix of the maladjusted ports is adjusted, so that the ports needing to be optimized and adjusted are integrally optimized, and the integral dynamic optimization of the flow load of each port is realized; and adjusting the data of each port according to the adjusted data mapping matrix of the port, and mapping the adjusted data of each port into a second storage matrix.
In this embodiment, port traffic load data acquired by each port is acquired by the OS Server, and the acquired port traffic load data of each port is stored in the first storage matrix; optimizing a priority scheduling evaluation function according to the user grade, and determining a port with imbalance of flow, time delay and packet loss rate; and the OS Server submodule triggers a user level priority optimization scheduling algorithm to the maladjusted port, dynamically adjusts the maladjusted port and adjusts a data mapping matrix of the maladjusted port. Therefore, a new adjustment decision can be obtained according to the real-time flow state of each port, the out-of-order port is determined, the out-of-order port is adjusted, the network flow of each port, namely the node, is subjected to global optimization scheduling, the flow resource of each port can be optimized, the response service time can be as short as possible, the network flow throughput rate can be as high as possible, the network congestion degree is reduced, the network utilization rate is improved, and the consumption is reduced.
Fig. 2 is a flowchart of a traffic scheduling method based on end office clouding according to a first embodiment of the present invention, and on the basis of the first embodiment, as shown in fig. 2, the method according to the present embodiment further includes, before step 101:
step 201, a terminal of a fixed network home user initiates a DHCP request message; the fixed end establishes a Vxlan tunnel through the PG, the Vxlan gateway and the vCPE so as to complete access of a Vxlan two-layer network; the DHCP request message of the USER USER _ PC is transmitted to the vCPE through the Vxlan two-layer network; the vCPE supports to be used as a DHCP Server to distribute an IP address to a down-hung terminal, and supports to be used as an IPoE/PPPoE Client to be processed by a firewall and the like and to be sent to a vBRAS for dial-up access authentication; NAT carries on the conversion of private network and public network address; NAT accesses Internet through gateway; the PG is accessed to the internal resources of the accessible enterprise through a Vxlan two-layer network through an established Vxlan tunnel between the Vxlan gateway and the vCPE; a terminal of a fixed network enterprise user accesses internal resources of an enterprise such as an internal office system of the enterprise through a PG capable of accessing the internal resources of the enterprise;
or the mobile terminal equipment initiates a message request for accessing internal resources of the enterprise and accesses a 3G/4G network of a telecom operator through the base station; the mobile terminal equipment is accessed to the VPN server through a 3G/4G network; the mobile terminal equipment accesses the vBRAS through the VPNserver to carry out authentication so as to access the resources in the enterprise.
In the present embodiment, specifically, a loosely-coupled architecture is adopted, and the overall architecture thereof can be divided into two domains from the horizontal direction: the mobile terminal equipment accesses a domain and a fixed network enterprise user accesses the domain. For a fixed network enterprise and public institution USER access domain, firstly, a fixed network family USER USER _ PC initiates a DHCP request message; the fixed end establishes a Vxlan tunnel through the PG, the Vxlan gateway and the vCPE so as to realize access of a Vxlan two-layer network; a request message of the USER _ PC is transmitted to the vCPE through the Vxlan two-layer network; the vCPE supports to be used as a DHCP Server to distribute an IP address to a down-hung terminal, and supports to be used as an IPoE/PPPoE Client to be processed by a firewall and the like and to be sent to a vBRAS for dial-up access authentication; NAT converts private network and public network address; NAT accesses Internet through gateway; the PG is accessed to the internal resources of the accessible enterprise through a Vxlan two-layer network through an established Vxlan tunnel between the Vxlan gateway and the vCPE; the terminal of the fixed network enterprise user accesses the internal resources of the enterprise, such as the internal office system of the enterprise, through the PG capable of accessing the internal resources of the enterprise. For the access domain of the mobile terminal equipment, the mobile terminal equipment initiates a message request for accessing the internal resources of the enterprise, and accesses a 3G/4G network of a telecom operator through a base station; the mobile terminal equipment is accessed to the VPN server through a 3G/4G network of a telecom operator; and then the mobile terminal equipment accesses the vBRAS through the VPN server to carry out authentication so as to access the resources in the enterprise.
In the embodiment, the mobile terminal device accesses the vBRAS through the VPN server to perform authentication so as to access the internal resources of the enterprise, and the terminal of the user of the fixed network enterprise and the public institution accesses the internal resources of the enterprise, such as the internal office system of the enterprise and the public institution through the PG capable of accessing the internal resources of the enterprise. In the process, the OS Server acquires port traffic load data acquired by each port, and stores the acquired port traffic load data of each port into a first storage matrix; optimizing a priority scheduling evaluation function according to the user grade, and determining a port with imbalance of flow, time delay and packet loss rate; and the OS Server submodule triggers a user level priority optimization scheduling algorithm to the maladjusted port, dynamically adjusts the maladjusted port and adjusts a data mapping matrix of the maladjusted port. Therefore, a new adjustment decision can be obtained according to the real-time flow state of each port, the out-of-order port is determined, the out-of-order port is adjusted, the network flow of each port, namely the node, is subjected to global optimization scheduling, the flow resource of each port can be optimized, the response service time can be as short as possible, the network flow throughput rate can be as high as possible, the network congestion degree is reduced, the network utilization rate is improved, and the consumption is reduced.
Fig. 3 is a schematic structural diagram of a traffic scheduling system based on end office clouding according to a third embodiment of the present invention, and as shown in fig. 3, the system according to the present embodiment includes:
vCPE31 and ports 32;
the vCPE31 is used for acquiring traffic load data of each port 32; storing the acquired traffic load data of each port 32 in a first storage matrix; performing optimized scheduling analysis on the traffic load data of each port 32 in the first storage matrix to determine an optimized scheduling strategy of each port 32; and scheduling the flow of each port 32 according to the optimized scheduling strategy of each port 32.
Each port 32 is specifically configured to: the acquired traffic load data is actively reported to vCPE31 at preset time intervals; alternatively, vCPE31 is specifically for: the traffic load data obtained by each port 32 is periodically queried.
vCPE31 comprising: the determining module 311 is configured to determine a port with imbalance in traffic, time delay and packet loss rate according to the user-level optimized priority scheduling evaluation function; and an adjusting module 312, configured to perform flow optimization and adjustment on the maladjusted port.
The adjusting module 312 is specifically configured to:
determining user-level optimized prioritized scheduling evaluation function、Wherein x isij kIs a defined value of whether a port shares traffic and π、ν∈(0,1)，Qij kand Vij kAre respectively port xij kBased on its priority, congestion degree satisfaction and traffic utilization, andadjustment factors of congestion degree satisfaction and flow utilization degree are respectively; k denotes the kth iteration, k ≦ d and k ≦ 1,2, …, d; PRIij k、delayij k、LRij kAnd FLOWij kRespectively port priority, port time delay, port packet loss rate and port flow, theta, sigma, pi and vIs an adjustment factor;
determining the adjusted first memory matrix as Mij k+1＝vij k+1*tuWherein v isij k+1＝τij k*vij k+ρ*(MPk-Mij k)+ξ*(MGk-Mij k)，τij kFor autonomous learning of pheromone concentration weights, vij kFor M in the k-th iterationij kDirection vector of, tuIs a unit time unit, vij k+1For the direction vector of the (k + 1) th iteration, both ρ and ξ are adjustment factors, MPkAnd MGkRespectively obtaining a local optimal port data vector of the current iteration and a global port data vector of the previous k iterations in the kth iteration; mij kFor the first memory matrix, Mij k＝{delayij k,LRij k,FLOWij k}；
And when the user grade optimization priority scheduling evaluation function is determined not to be met or the current iteration times are less than or equal to the maximum iteration times, determining that the flow of the current port is out of order, wherein the user grade optimization priority scheduling evaluation function is not met, and the value of the user grade optimization priority scheduling evaluation function is less than or equal to the average value of the values of the user grade optimization priority scheduling evaluation functions of all ports in the first iteration.
The end office clouding-based traffic scheduling method of this embodiment may be implemented by the end office clouding-based traffic scheduling method provided in the first embodiment of the present invention, and the implementation principles are similar, and are not described herein again.
In this embodiment, port traffic load data acquired by each port is acquired by the OS Server, and the acquired port traffic load data of each port is stored in the first storage matrix; optimizing a priority scheduling evaluation function according to the user grade, and determining a port with imbalance of flow, time delay and packet loss rate; and the OS Server submodule triggers a user level priority optimization scheduling algorithm to the maladjusted port, dynamically adjusts the maladjusted port and adjusts a data mapping matrix of the maladjusted port. Therefore, a new adjustment decision can be obtained according to the real-time flow state of each port, the out-of-order port is determined, the out-of-order port is adjusted, the network flow of each port, namely the node, is subjected to global optimization scheduling, the flow resource of each port can be optimized, the response service time can be as short as possible, the network flow throughput rate can be as high as possible, the network congestion degree is reduced, the network utilization rate is improved, and the consumption is reduced.
Fig. 4 is a schematic structural diagram of a traffic scheduling system based on end office clouding according to a fourth embodiment of the present invention, and based on the third embodiment, as shown in fig. 4, the system according to the present embodiment further includes:
a terminal 41 and a mobile terminal device 42 of a fixed network home user;
the fixed network home user terminal 41 is used for initiating a DHCP request message before the vCPE31 acquires the traffic load data of each port 32, so that the fixed terminal establishes a Vxlan tunnel through the PG and Vxlan gateways and the vCPE31 to complete access of a Vxlan two-layer network; the DHCP request message of the USER USER _ PC is transmitted to the vCPE31 through the Vxlan two-layer network; the vCPE31 supports the DHCP Server to distribute IP addresses to the down-hanging terminals, and supports the IPoE/PPPoE Client to be processed by a firewall and the like and sent to the vBRAS for dial-up access authentication; NAT carries on the conversion of private network and public network address; NAT accesses Internet through gateway; the PG is accessed to the accessible enterprise internal resources through a Vxlan two-layer network through an established Vxlan tunnel between the Vxlan gateway and the vCPE 31; a terminal 41 of a fixed network home user accesses internal resources of an enterprise, such as an internal office system of an enterprise and public institution, through a PG which can access the internal resources of the enterprise;
the mobile terminal device 42 is configured to initiate a message request for accessing an enterprise internal resource before the vCPE31 obtains traffic load data of each port 32, and access the 3G/4G network of a telecommunications carrier through a base station; the mobile terminal device 42 accesses the VPN server through the 3G/4G network; the mobile terminal equipment accesses the vBRAS through the VPN server to carry out authentication so as to access the resources in the enterprise.
The end office clouding-based traffic scheduling method of this embodiment may execute the end office clouding-based traffic scheduling method provided in the second embodiment of the present invention, and the implementation principles are similar, and are not described herein again.
In this embodiment, port traffic load data acquired by each port is acquired by the OS Server, and the acquired port traffic load data of each port is stored in the first storage matrix; optimizing a priority scheduling evaluation function according to the user grade, and determining a port with imbalance of flow, time delay and packet loss rate; and the OS Server submodule triggers a user level priority optimization scheduling algorithm to the maladjusted port, dynamically adjusts the maladjusted port and adjusts a data mapping matrix of the maladjusted port. Therefore, a new adjustment decision can be obtained according to the real-time flow state of each port, the out-of-order port is determined, the out-of-order port is adjusted, the network flow of each port, namely the node, is subjected to global optimization scheduling, the flow resource of each port can be optimized, the response service time can be as short as possible, the network flow throughput rate can be as high as possible, the network congestion degree is reduced, the network utilization rate is improved, and the consumption is reduced.
Those of ordinary skill in the art will understand that: all or a portion of the steps of implementing the above-described method embodiments may be performed by hardware associated with program instructions. The program may be stored in a computer-readable storage medium. When executed, the program performs steps comprising the method embodiments described above; and the aforementioned storage medium includes: various media that can store program codes, such as ROM, RAM, magnetic or optical disks.
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present 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 solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (10)
1. A traffic scheduling method based on end office clouding is characterized by comprising the following steps:
the vCPE acquires flow load data of each port;
the vCPE stores the acquired traffic load data of each port into a first storage matrix;
the vCPE performs optimized scheduling analysis on the traffic load data of each port in the first storage matrix to determine an optimized scheduling strategy of each port;
and the vCPE schedules the flow of each port according to the optimized scheduling strategy of each port.
2. The method of claim 1, wherein the vCPE obtaining traffic load data for each port comprises:
each port actively reports the acquired traffic load data to the vCPE every preset time;
or, the vCPE periodically inquires traffic load data acquired by each port.
3. The method according to claim 1, wherein the vCPE schedules the traffic of each port according to the optimized scheduling policy of each port, and the method includes:
the vCPE determines a port with imbalance of flow, time delay and packet loss rate according to a user grade optimization priority scheduling evaluation function;
and the vCPE optimizes and adjusts the flow of the detuned port.
4. The method according to claim 3, wherein the vCPE determines the ports with maladjusted flow, time delay and packet loss rate according to a user class optimization priority scheduling evaluation function, and the method comprises the following steps:
determining user-level optimized prioritized scheduling evaluation function Wherein x isij kIs a defined value of whether a port shares traffic and π、ν∈(0,1)，Qij kand Vij kAre respectively port xij kBased on its priority, congestion degree satisfaction and traffic utilization, andadjustment factors of congestion degree satisfaction and flow utilization degree are respectively; k denotes the kth iteration, k ≦ d and k ≦ 1,2, …, d; PRIij k、delayij k、LRij kAnd FLOWij kRespectively port priority, port time delay, port packet loss rate and port flow, wherein theta, sigma, pi and ν are all adjustment factors;
determining the adjusted first memory matrix as Mij k+1＝vij k+1*tuWherein v isij k+1＝τij k*vij k+ρ*(MPk-Mij k)+ξ*(MGk-Mij k)，τij kFor autonomous learning of pheromone concentration weights, vij kFor M in the k-th iterationij kDirection vector of, tuIs a unit time unit, vij k+1For the direction vector of the (k + 1) th iteration, both ρ and ξ are adjustment factors, MPkAnd MGkRespectively obtaining a local optimal port data vector of the current iteration and a global port data vector of the previous k iterations in the kth iteration; mij kFor the first memory matrix, Mij k＝{delayij k,LRij k,FLOWij k}；
And when the user grade optimization priority scheduling evaluation function is determined not to be met or the current iteration times are less than or equal to the maximum iteration times, determining that the flow of the current port is out of order, wherein the user grade optimization priority scheduling evaluation function is not met, and the value of the user grade optimization priority scheduling evaluation function is less than or equal to the average value of the values of the user grade optimization priority scheduling evaluation functions of all ports in the first iteration.
5. The method according to any of claims 1-4, wherein before the vCPE acquiring traffic load data for each port, further comprising:
a terminal of a fixed network home user initiates a DHCP request message; the fixed end establishes a Vxlan tunnel through the PG, the Vxlan gateway and the vCPE so as to complete access of a Vxlan two-layer network; the DHCP request message of the USER USER _ PC is transmitted to the vCPE through the Vxlan two-layer network; the vCPE supports to be used as a DHCP Server to distribute an IP address to a down-hung terminal, and supports to be used as IPoE/PPPoEClient to be processed by a firewall and the like and sent to the vBRAS for dial-up access authentication; NAT carries on the conversion of private network and public network address; NAT accesses Internet through gateway; the PG is accessed to the internal resources of the accessible enterprise through a Vxlan two-layer network through an established Vxlan tunnel between the Vxlan gateway and the vCPE; a terminal of a fixed network home user accesses internal resources of an enterprise such as an internal office system of an enterprise and public institution through a PG capable of accessing the internal resources of the enterprise;
or the mobile terminal equipment initiates a message request for accessing internal resources of the enterprise and accesses a 3G/4G network of a telecom operator through the base station; the mobile terminal equipment is accessed to the VPN server through a 3G/4G network; the mobile terminal equipment accesses the vBRAS through the VPNserver to carry out authentication so as to access the resources in the enterprise.
6. A traffic scheduling system based on end office clouding is characterized by comprising:
vCPE and ports;
the vCPE is used for acquiring flow load data of each port; storing the acquired traffic load data of each port into a first storage matrix; performing optimized scheduling analysis on the traffic load data of each port in the first storage matrix to determine an optimized scheduling strategy of each port; and scheduling the flow of each port according to the optimized scheduling strategy of each port.
7. The system of claim 6, wherein each port is specifically configured to: actively reporting the acquired traffic load data to the vCPE every preset time;
or, the vCPE is specifically configured to: periodically, the traffic load data obtained by each port is queried.
8. The system of claim 6, wherein the vCPE comprises:
the determining module is used for determining a port with imbalance of flow, time delay and packet loss rate according to the user grade optimization priority scheduling evaluation function;
and the adjusting module is used for optimizing and adjusting the flow of the maladjusted port.
9. The system of claim 8, wherein the adjustment module is specifically configured to:
determining user-level optimized prioritized scheduling evaluation function Wherein x isij kIs a defined value of whether a port shares traffic and π、ν∈(0,1)，Qij kand Vij kAre respectively port xij kBased on its priority, congestion degree satisfaction and traffic utilization, andadjustment factors of congestion degree satisfaction and flow utilization degree are respectively; k denotes the kth iteration, k ≦ d and k ≦ 1,2, …, d; PRIij k、delayij k、LRij kAnd FLOWij kRespectively port priority, port time delay, port packet loss rate and port flow, wherein theta, sigma, pi and ν are all adjustment factors;
determining the adjusted first memory matrix as Mij k+1＝vij k+1*tuWherein v isij k+1＝τij k*vij k+ρ*(MPk-Mij k)+ξ*(MGk-Mij k)，τij kFor autonomous learning of pheromone concentration weights, vij kFor M in the k-th iterationij kDirection vector of, tuIs a unit time unit, vij k+1For the direction vector of the (k + 1) th iteration, both ρ and ξ are adjustment factors, MPkAnd MGkRespectively obtaining a local optimal port data vector of the current iteration and a global port data vector of the previous k iterations in the kth iteration; mij kFor the first memory matrix, Mij k＝{delayij k,LRij k,FLOWij k}；
And when the user grade optimization priority scheduling evaluation function is determined not to be met or the current iteration times are less than or equal to the maximum iteration times, determining that the flow of the current port is out of order, wherein the user grade optimization priority scheduling evaluation function is not met, and the value of the user grade optimization priority scheduling evaluation function is less than or equal to the average value of the values of the user grade optimization priority scheduling evaluation functions of all ports in the first iteration.
10. The system according to any one of claims 6-9, further comprising:
a terminal and a mobile terminal device of a fixed network home user;
the fixed network home user terminal is used for initiating a DHCP request message before the vCPE acquires the flow load data of each port, so that the fixed end establishes a Vxlan tunnel through the PG, the Vxlan gateway and the vCPE to complete the access of a Vxlan two-layer network; the DHCP request message of the USER USER _ PC is transmitted to the vCPE through the Vxlan two-layer network; the vCPE supports to be used as a DHCPServer to distribute an IP address to a down-hung terminal, and supports to be used as an IPoE/PPPoE Client to be processed by a firewall and the like and sent to the vBRAS for dial-up access authentication; NAT carries on the conversion of private network and public network address; NAT accesses Internet through gateway; the PG is accessed to the internal resources of the accessible enterprise through a Vxlan two-layer network through an established Vxlan tunnel between the Vxlan gateway and the vCPE; a terminal of a fixed network home user accesses internal resources of an enterprise such as an internal office system of an enterprise and public institution through a PG capable of accessing the internal resources of the enterprise;
the mobile terminal equipment is used for initiating a message request for accessing internal resources of an enterprise before the vCPE acquires the traffic load data of each port, and accessing a 3G/4G network of a telecom operator through a base station; the mobile terminal equipment is accessed to the VPN server through a 3G/4G network; the mobile terminal equipment accesses the vBRAS through the VPN server to carry out authentication so as to access the resources in the enterprise.
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