CN113473498B - Network slice resource arrangement method, slice arrangement device and arrangement system - Google Patents
Network slice resource arrangement method, slice arrangement device and arrangement system Download PDFInfo
- Publication number
- CN113473498B CN113473498B CN202110659280.7A CN202110659280A CN113473498B CN 113473498 B CN113473498 B CN 113473498B CN 202110659280 A CN202110659280 A CN 202110659280A CN 113473498 B CN113473498 B CN 113473498B
- Authority
- CN
- China
- Prior art keywords
- network
- function
- period
- slice
- terminal
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Images
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W24/00—Supervisory, monitoring or testing arrangements
- H04W24/02—Arrangements for optimising operational condition
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
- Y02D30/00—Reducing energy consumption in communication networks
- Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks
Abstract
The present disclosure provides a network slice resource orchestration method, a slice orchestrator, a system, an electronic device, and a storage medium, the method comprising: the slice orchestrator converts the slice order into a performance index; obtaining a network end optimization function and a weight function of a wireless access network, a transmission bearing network and a core network in a preset period based on an end-to-end network performance index; obtaining a penalty function according to network end optimization functions and weight functions of the wireless access network, the transmission bearing network and the core network; transmitting the end-to-end network performance index to the terminal so that the terminal measures the end-to-end performance in the period to obtain a terminal optimization function; obtaining the overall resource state of the network based on the terminal optimization function and the penalty function, and inputting the correction parameters of the programming algorithm in the period; and carrying out resource arrangement correction of the current period according to the correction parameters of the input arrangement algorithm in the period. The technical scheme disclosed by the disclosure can carry out global resource optimization arrangement.
Description
Technical Field
The present disclosure relates to the field of communication technology, and in particular, to a network slice resource scheduling method, a slice scheduler, a network slice resource scheduling system, an electronic device, and a computer-readable storage medium.
Background
5G network slicing is a technology defined by 3GPP, and aims to open up a special virtual network on the 5G network of an operator for different industries or enterprises so as to meet the requirements of service characterization.
Network slicing allows configuration and reuse of network elements and functions in each network slicing sub-network instance to meet specific application requirements, an operator can slice multiple virtual end-to-end networks in one hardware infrastructure, each network slicing sub-network implements logical isolation in terminal devices, radio access networks, transport bearer networks, and core networks, adapts to various types of services, and meets different requirements of users. The network slicing technology can enable a CT (Communications technology, communication technology) system IT (Information Technology ) to realize virtualization management and maintenance on the premise of network SDN (Software Defined Network )/NFV (Network Function Virtualization, network function virtualization). Virtual matching and mapping are carried out on network resources through an SDN/NFV platform, different logic functions are generated, corresponding services are provided through an orchestrator to meet the requirements of each application scene on network capacity, and dedicated resources such as network bandwidth, service quality and security of each network slice are ensured. Thereby implementing network slicing.
The current network slice arrangement algorithm is numerous, but is generally based on greedy strategy, as shown in fig. 1, a slice arrangement device respectively arranges a wireless access network subdomain, a transmission bearing network subdomain and a core network subdomain, namely, the network slice needs are divided and routed one by one, global optimization is lacked, and as three subdomains of a 5G network are self-organized, the technical isolation among all subdomains is high, and the network performance index disassembly difficulty required by a slice instance is high; especially in the initial stage of slice network application, the one-time in-place arrangement capability cannot be achieved for many services and end-to-end performance decomposition, and the optimization arrangement of global resources cannot be achieved when correction is carried out.
Disclosure of Invention
The disclosure provides a network slice resource arrangement method, a slice arrangement device, a network slice resource arrangement system, electronic equipment and a computer readable storage medium, which can make optimization arrangement of global resources aiming at business characteristics and performance indexes of network slice services.
In a first aspect, an embodiment of the present disclosure provides a network slice resource orchestration method, applied to a slice orchestrator, the method including:
after receiving a slice order, converting the business requirement of the order into an end-to-end network performance index;
obtaining a network end optimization function and a weight function of a wireless access network, a transmission bearing network and a core network in a preset period based on the end-to-end network performance index;
obtaining a penalty function according to network end optimization functions and weight functions of the wireless access network, the transmission bearing network and the core network;
transmitting the end-to-end network performance index to a terminal so that the terminal measures the end-to-end performance in the period to obtain a terminal optimization function, and transmitting the terminal optimization function to a slice composer;
obtaining the overall resource state of the network and the correction parameters of the input arrangement algorithm in the period based on the terminal optimization function and the penalty function;
and carrying out resource arrangement correction of the current period according to the correction parameters of the input arrangement algorithm in the period.
Further, obtaining a network end optimization function and a weight function of the radio access network, the transmission bearer network and the core network in a preset period based on the end-to-end network performance index comprises:
decomposing the end-to-end network performance index into a wireless network target index, a transmission network target index and a core network target index;
respectively distributing a wireless network target index, a transmission network target index and a core network target index to three subdomains of a wireless access network, a transmission bearing network and a core network, respectively monitoring performance indexes in respective network segments in a preset period to obtain the performance indexes monitored in the period, respectively obtaining respective corresponding network end optimization functions according to the difference between the respective monitored performance indexes and the respective target indexes, respectively evaluating optimizable spaces of the respective monitored performance indexes in the period according to the performance upper limit capability of the respective network segments to respectively give respective corresponding weight functions in the period, and respectively sending the respective network end optimization functions and the weight functions to a slice orchestrator;
and receiving respective network end optimization functions and weight functions respectively sent by the wireless access network, the transmission bearing network and the core network.
Further, the end-to-end network performance index includes one or more of: average rate, peak rate, delay and packet loss rate.
Further, the obtaining a penalty function according to the network side optimization functions and the weight functions of the radio access network, the transmission bearer network and the core network includes:
respectively multiplying the network end optimization functions of the wireless access network, the transmission bearing network and the core network by the weight functions of the wireless access network, the transmission bearing network and the core network to obtain the subdomain penalty functions of the wireless access network, the transmission bearing network and the core network;
and collecting the punishment functions of the subdomains of the wireless access network, the transmission bearing network and the core network to obtain punishment functions.
Further, obtaining the overall network resource state and the correction parameters of the input arrangement algorithm in the period based on the terminal optimization function and the penalty function includes:
comparing the terminal optimization function with the penalty function,
if the penalty function is smaller than the terminal optimization function, indicating that the network overall resources are in a state to be expanded or optimized, and taking the terminal optimization function as a correction parameter of an input arrangement algorithm in the period;
and if the penalty function is greater than or equal to the terminal optimization function, the penalty function is used as a correction parameter of the input arrangement algorithm in the period, wherein the penalty function indicates that the overall network resources are sufficient.
In a second aspect, embodiments of the present disclosure provide a slice orchestrator comprising:
the conversion module is used for converting the business requirement of the order into an end-to-end network performance index after the slicing orchestrator receives the slicing ordering order;
the acquisition module is used for acquiring a network end optimization function and a weight function of the wireless access network, the transmission bearing network and the core network in a preset period based on the end-to-end network performance index;
the computing module is arranged to obtain a punishment function according to a network end optimization function and a weight function of the wireless access network, the transmission bearing network and the core network;
the sending module is configured to send the end-to-end network performance index to a terminal, so that the terminal measures the end-to-end performance in the period to obtain a terminal optimization function and send the terminal optimization function to the slice composer;
the acquisition module is further configured to obtain a network overall resource state based on the terminal optimization function and the penalty function, and input correction parameters of an arrangement algorithm in the period;
and the resource arrangement module is set to carry out resource arrangement correction of the current period according to the correction parameters of the arrangement algorithm input in the period.
Further, the obtaining module includes:
a decomposition unit configured to decompose the end-to-end network performance index into a wireless network target index, a transmission network target index, and a core network target index;
the transmitting unit is configured to respectively allocate the wireless network target index, the transmission network target index and the core network target index to three subdomains of the wireless access network, the transmission bearing network and the core network through the transmitting module, so that the wireless access network, the transmission bearing network and the core network respectively monitor performance indexes in respective network segments in a preset period to obtain the monitored performance indexes in the period, respectively obtain respective corresponding network end optimization functions according to the difference between the respective monitored performance indexes and the respective target indexes, respectively evaluate the optimizable space of the respective monitored performance indexes in the period according to the performance upper limit capability of the respective network segments to respectively give respective corresponding weight functions in the period, and respectively send the respective network end optimization functions and the weight functions to the slicing orchestrator;
the receiving unit is configured to receive respective network end optimization functions and weight functions respectively sent by the radio access network, the transmission bearer network and the core network.
Further, the end-to-end network performance index includes one or more of: average rate, peak rate, delay and packet loss rate.
Further, the obtaining module is specifically configured to:
comparing the terminal optimization function with the penalty function,
if the penalty function is smaller than the terminal optimization function, indicating that the network overall resources are in a state to be expanded or optimized, and taking the terminal optimization function as a correction parameter of an input arrangement algorithm in the period;
and if the penalty function is greater than or equal to the terminal optimization function, the penalty function is used as a correction parameter of the input arrangement algorithm in the period, wherein the penalty function indicates that the overall network resources are sufficient.
In a third aspect, embodiments of the present disclosure provide a network slice resource orchestration system comprising a terminal, and a slice orchestrator according to any one of the second aspects.
In a fourth aspect, an embodiment of the present disclosure further provides an electronic device, including a memory and a processor, where the memory stores a computer program, and when the processor runs the computer program stored in the memory, the processor executes the network slice resource orchestration method according to any one of the first aspects.
In a sixth aspect, embodiments of the present disclosure also provide a computer-readable storage medium, comprising: a computer program which, when run on a computer, causes the computer to perform the network slice resource orchestration method according to any one of the first aspects.
The beneficial effects are that:
the network slice resource arrangement method, the slice arrangement device, the network slice resource arrangement system, the electronic equipment and the computer readable storage medium provided by the disclosure are used for converting the business requirement of a slice order into an end-to-end network performance index after the slice arrangement device receives the order; obtaining a network end optimization function and a weight function of a wireless access network, a transmission bearing network and a core network in a preset period based on the end-to-end network performance index; obtaining a penalty function according to network end optimization functions and weight functions of the wireless access network, the transmission bearing network and the core network; transmitting the end-to-end network performance index to a terminal so that the terminal measures the end-to-end performance in the period to obtain a terminal optimization function, and transmitting the terminal optimization function to a slice composer; obtaining the overall resource state of the network and the correction parameters of the input arrangement algorithm in the period based on the terminal optimization function and the penalty function; and carrying out resource arrangement correction of the current period according to the correction parameters of the input arrangement algorithm in the period. According to the technical scheme, through end-to-end performance feedback iteration, global resource optimization arrangement is made according to the service characteristics and performance indexes of the network slice service.
Drawings
Fig. 1 is a diagram of an architecture of a conventional slice orchestrator for orchestrating radio access network subzones, transport bearer network subzones, and core network subzones;
fig. 2 is a flow chart of a network slice resource scheduling method according to a first embodiment of the disclosure;
FIG. 3 is a schematic flow chart of resource scheduling of network slices in a period according to an embodiment of the disclosure;
fig. 4 is a flow chart of a network slice resource scheduling method according to a second embodiment of the disclosure;
FIG. 5 is a block diagram of a slice orchestrator according to a third embodiment of the present disclosure;
fig. 6 is a architecture diagram of a network slice resource scheduling system according to a fourth embodiment of the present disclosure;
fig. 7 is a schematic diagram of an electronic device according to a fifth embodiment of the disclosure.
Detailed Description
In order that those skilled in the art will better understand the technical solutions of the present disclosure, the present disclosure will be described in further detail with reference to the accompanying drawings and examples.
Wherein the terminology used in the embodiments of the disclosure is for the purpose of describing particular embodiments only and is not intended to be limiting of the disclosure. As used in this disclosure of embodiments and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.
The current network slice resource arrangement is to divide and route resources one by one according to the demands of the network slices, global optimization is lacked, and as three subdomains of the 5G network are high in technical isolation among the subdomains, network performance indexes required by slice examples are difficult to disassemble; especially in the initial stage of slice network application, the one-time in-place arrangement capability cannot be achieved for many services and end-to-end performance decomposition, and the optimization arrangement of global resources cannot be achieved when correction is carried out.
The following describes the technical solutions of the present disclosure and how the technical solutions of the present disclosure solve the above-mentioned problems in detail with specific embodiments. The following embodiments may be combined with each other, and the same or similar concepts or processes may not be described in detail in some embodiments.
Fig. 2 is a flow chart of a network slice resource scheduling method according to an embodiment of the present disclosure, which is applied to a slice scheduler, as shown in fig. 2, and the method includes:
step S101: after receiving a slice order, converting the business requirement of the order into an end-to-end network performance index;
step S102: obtaining a network end optimization function and a weight function of a wireless access network, a transmission bearing network and a core network in a preset period based on the end-to-end network performance index;
step S103: obtaining a penalty function according to network end optimization functions and weight functions of the wireless access network, the transmission bearing network and the core network;
step S104: transmitting the end-to-end network performance index to a terminal so that the terminal measures the end-to-end performance in the period to obtain a terminal optimization function, and transmitting the terminal optimization function to a slice composer;
step S105: obtaining the overall resource state of the network and the correction parameters of the input arrangement algorithm in the period based on the terminal optimization function and the penalty function;
step S106: and carrying out resource arrangement correction of the current period according to the correction parameters of the input arrangement algorithm in the period.
The life cycle of the network slice is closely related to the quality of the network slice, and the cycle of the network slice is also the guarantee of providing high-quality service by the network. Through reasonable network slice arrangement, the utilization efficiency of resources can be improved, and the utilization rate of the network slices is improved, so that the network slices play an important role. Network slicing orchestration occurs throughout the process of network slicing, with an important impact on network slicing. The arrangement of the network slices can be understood as reasonably dividing the resources according to the actual relevant requirements of the users, so that the resources can be more completely utilized. However, the resource arrangement of the existing network slice is to divide and route resources one by one according to the demands of the network slice, so global optimization is lacking, and the optimization arrangement of the global resources cannot be realized. For this reason, the slice composer of the present embodiment converts the business requirement into the end-to-end network performance index P according to the slice order after receiving the slice order total Network technical indexes such as average speed, peak speed, time delay, packet loss rate and the like; the slice composer performs initialization resource allocation to three subdomains of a wireless network, a transmission network and a core network according to the converted end-to-end network performance index; including radio network resource Res RAN Transmission network resource Res CT And core network resource Res CN Decomposing the target performance index of the end-to-end network performance index into a wireless network target index P RAN Target index P of transmission network CT Target index P of core network CN The method comprises the steps of carrying out a first treatment on the surface of the And respectively and correspondingly distributes to wireless access, transmission bearing and coreThree sub-domains of the heart network, which are used for end-to-end network performance index P total Transmitting to the terminal; as shown in fig. 3, the slice composer interacts with three subzones of the wireless access, transmission bearing and core network and the terminal to complete slice resource composition, after the slice composer performs initialization composition, radio resources are distributed to the three subzones, subzone index monitoring is performed in the three subzones respectively in a period, and network end optimization functions and weight functions of the wireless access, transmission bearing and core network in a preset period are obtained based on the end-to-end network performance indexes; namely, calculating through each sub-domain index optimization function, acquiring a sub-domain weight function, and then obtaining a punishment function. And (3) performing index monitoring on a terminal side to obtain an end-to-end terminal optimization function, and performing the arrangement correction of the periodic resources by taking the penalty function and the terminal optimization function as boundary constraint conditions.
Further, obtaining a network end optimization function and a weight function of the radio access network, the transmission bearer network and the core network in a preset period based on the end-to-end network performance index comprises:
decomposing the end-to-end network performance index into a wireless network target index, a transmission network target index and a core network target index;
respectively distributing a wireless network target index, a transmission network target index and a core network target index to three subdomains of a wireless access network, a transmission bearing network and a core network, respectively monitoring performance indexes in respective network segments in a preset period to obtain the performance indexes monitored in the period, respectively obtaining respective corresponding network end optimization functions according to the difference between the respective monitored performance indexes and the respective target indexes, respectively evaluating optimizable spaces of the respective monitored performance indexes in the period according to the performance upper limit capability of the respective network segments to respectively give respective corresponding weight functions in the period, and respectively sending the respective network end optimization functions and the weight functions to a slice orchestrator;
and receiving respective network end optimization functions and weight functions respectively sent by the wireless access network, the transmission bearing network and the core network.
Radio access, transport bearer and core network indicator P CT And the three sub-domains respectively receive the wireless network target indexes P corresponding to the three sub-domains RAN Target index P of transmission network target core network CN Thereafter, in one cycle: the three sub-domains monitor the performance index in each network segment respectively, for example, in the jth period, obtain the performance index P in each network segment in the jth period j RAN 、P j CT 、P j CN The method comprises the steps of carrying out a first treatment on the surface of the And respectively obtaining the corresponding network end optimization function O according to the difference between the monitored performance indexes and the target indexes j ＝P j -P. Three sub-domains evaluate P for the current respective segment performance cap capability j RAN 、P j CT 、P j CN The space can be optimized, and the weight function w in the period is given according to the actual load condition of the network and the slicing service characteristics j RAN 、w j CT 、w j CN (wherein the larger the optimizable space, the higher the weight); the wireless access, transmission bearing and core network respectively send the respective network end optimization function and weight function to the slice composer.
The slice composer obtains a penalty function f according to the network end optimization functions and the weight functions of the three subfields j The method comprises the steps of carrying out a first treatment on the surface of the The larger the gap is, the larger the penalty is.
Terminal receives end-to-end network performance index P total Then, in the same period, for example, the jth period, the end-to-end performance index P is measured j UE And obtains a terminal optimization function O j UE ；O j UE ＝P j UE -P total The terminal optimizes the function O j UE And the measurement performance indexes such as speed, time delay, jitter and the like can be measured by the terminal through presetting the end side middleware.
The slice composer obtains the penalty function f j After receiving the terminal optimization function, the terminal optimization function is madeComparing the constraint condition with the penalty function, and taking the larger constraint condition as a correction parameter of an input programming algorithm in the period; and carrying out resource arrangement correction of the current period (the jth period) according to the correction parameters of the input arrangement algorithm in the period. After the arrangement correction, in the next period, the wireless access, transmission bearing and core network and terminal measure the performance index again, and the penalty function f obtained in the next week j And the terminal optimization function is sent to a back slice composer, the slice composer acquires the correction parameter of the next period, and corrects again, and the composer composes the slice once every period.
In the embodiment of the disclosure, the terminal can measure the overall performance of the end-to-end link, and make optimization arrangement of global resources according to the service characteristics and performance indexes of the network slice service through end-to-end performance feedback iteration; and by taking all the influencing factors into consideration, the use state of the resources is continuously adjusted, and finally, the optimal network slicing arrangement is obtained, so that the utilization rate of the resources is maximized.
Further, the end-to-end network performance index includes one or more of: average rate, peak rate, delay and packet loss rate.
According to the service requirement of the slice order, the end-to-end network performance index can highlight the key points of a certain aspect, such as average speed, peak speed, time delay, packet loss rate and the like, and is determined according to the requirement of a client order, if the slice of the large-bandwidth video service is required, the tenant service requires the slice to ensure that the average downloading speed of a single user is not lower than 100Mbps. The end-to-end network performance index may be an average rate of 100Mbps.
Further, the obtaining the penalty function according to the network side optimization functions and the weight functions of the radio access network, the transmission bearer network and the core network includes:
respectively multiplying the network end optimization functions of the wireless access network, the transmission bearing network and the core network by the weight functions of the wireless access network, the transmission bearing network and the core network to obtain the subdomain penalty functions of the wireless access network, the transmission bearing network and the core network;
and collecting the punishment functions of the subdomains of the wireless access network, the transmission bearing network and the core network to obtain punishment functions.
Penalty function f j ＝{O j ·W j And more specifically, f j＝ {O j RAN ·w j RAN ，O j CT ·w j CT ，O j CN ·w j CN }. The penalty function characterizes the achievable optimization gap from the target index, the larger the gap, the larger the penalty, and is spatially-optimizable in relation to each sub-domain.
Further, obtaining the overall network resource state and the correction parameters of the input arrangement algorithm in the period based on the terminal optimization function and the penalty function includes:
comparing the terminal optimization function with the penalty function,
if the penalty function is smaller than the terminal optimization function, indicating that the network overall resources are in a state to be expanded or optimized, and taking the terminal optimization function as a correction parameter of an input arrangement algorithm in the period;
and if the penalty function is greater than or equal to the terminal optimization function, the penalty function is used as a correction parameter of the input arrangement algorithm in the period, wherein the penalty function indicates that the overall network resources are sufficient.
O is added with j UE As a constraint condition, if f j ＜O j UE The overall network resource is in a state to be expanded/optimized, and the parameter R is corrected j ＝O j UE The method comprises the steps of carrying out a first treatment on the surface of the If f j ≥O j UE The network overall resources are sufficient, and the parameter R is corrected j ＝f j ，R j The correction parameter as the periodic input arrangement algorithm is input into the slice arranger for resource arrangement correction.
According to the embodiment of the disclosure, through end-to-end performance feedback iteration, global resource optimization arrangement is made aiming at the service characteristics and performance indexes of the network slice service.
In order to more clearly illustrate the technical solution of the present disclosure, as shown in fig. 4, a second embodiment of the present disclosure further provides a network slice resource arrangement method, where a slice scheduler receives an ebbe (Enhanced Mobile Broadband ) type slice order (such as a slice requiring a large bandwidth video service), and the tenant service requires a slice to ensure that the average download rate of a single user is not lower than 100Mbps; as shown in fig. 4, the method includes:
step 1: converting into end-to-end network performance index according to service requirement, and marking slicing performance P total =single user|100 Mbps;
step 2: slice orchestrator according to P total Initializing resource allocation Res RAN 、Res CT 、Res CN Decomposing the target performance index into P RAN =single user|100 Mbps, P CT The single user|100 Mbps is distributed to three subdomains of wireless access, transmission bearing and core network;
step 3: network performance index P from end to end total =single user|100 Mbps delivered to the terminal;
step 4: starting a timer, and implementing the steps 5-9 in the period;
step 5: the three sub-domains respectively correspond to the performance index P in the respective network segment RAN 、P CT 、P CN Monitoring and obtaining P in a period RAN =single user|50 Mbps, P CT =single user|80 Mbps to obtain the network end optimization function O RAN ＝{RAN|-50Mbps}，O CT ＝{CT|-20Mbps}；
Step 6: three sub-domains evaluate P for the current respective segment performance cap capability RAN|500Mbps, CT|100Gbps RAN 、P CT 、P CN Can optimize the space and give a weight function W RAN ＝2、W CT =1.25 (wherein the larger the optimizable space, the higher the weight;
step 7: the slice composer obtains a penalty function f= { RAN| -100Mbps, CT| -25Mbps } according to the network side optimization function and the weight function;
step 8: terminal measurement end-to-end performance index P UE =50 Mbps, resulting in a terminal optimization function O UE ＝RAN|-50Mbps；
Step 9: o is added with UE As a constraintUnder the condition that f= { RAN| -100Mbps, CT| -25Mbps } is larger than f, f is used as a correction parameter of the input scheduling algorithm in the period and is input into the slice scheduler;
step 10: the timer returns to zero and the next cycle is entered and step 4 is restarted.
Fig. 5 is a block diagram of a slice orchestrator according to a third embodiment of the present disclosure, as shown in fig. 5, including:
a conversion module 11 configured to convert, after the slice orchestrator receives a slice order, the business requirements of the order into end-to-end network performance metrics;
an obtaining module 12 configured to obtain a network-side optimization function and a weight function of the radio access network, the transport bearer network, and the core network in a preset period based on the end-to-end network performance index;
a calculation module 13 configured to obtain a penalty function according to a network side optimization function and a weight function of the radio access network, the transport bearer network, and the core network;
a transmitting module 14 configured to transmit the end-to-end network performance index to a terminal, so that the terminal measures the end-to-end performance in the period to obtain a terminal optimization function, and transmits the terminal optimization function to a slice composer;
the obtaining module 12 is further configured to obtain a network overall resource state and a correction parameter of the input arrangement algorithm in the period based on the terminal optimization function and the penalty function;
and the resource arrangement module 15 is configured to perform resource arrangement correction of the current period according to the correction parameters of the arrangement algorithm input in the period.
Further, the obtaining module 12 includes:
a decomposition unit configured to decompose the end-to-end network performance index into a wireless network target index, a transmission network target index, and a core network target index;
a transmitting unit configured to allocate, by the transmitting module 14, a wireless network target index, a transmission network target index, and a core network target index to three sub-domains of a wireless access network, a transmission bearer network, and a core network, respectively, so that the wireless access network, the transmission bearer network, and the core network monitor performance indexes in respective network segments in a preset period, obtain performance indexes monitored in the period, obtain respective corresponding network end optimization functions according to differences between the respective monitored performance indexes and the respective target indexes, respectively, evaluate optimizable spaces of the respective monitored performance indexes in the period according to respective network segment performance upper limit capabilities, respectively, give respective corresponding weight functions in the period, and send the respective network end optimization functions and the weight functions to a slice composer;
the receiving unit is configured to receive respective network end optimization functions and weight functions respectively sent by the radio access network, the transmission bearer network and the core network.
Further, the end-to-end network performance index includes one or more of: average rate, peak rate, delay and packet loss rate.
Further, the acquiring module 12 is specifically configured to:
comparing the terminal optimization function with the penalty function,
if the penalty function is smaller than the terminal optimization function, indicating that the network overall resources are in a state to be expanded or optimized, and taking the terminal optimization function as a correction parameter of an input arrangement algorithm in the period;
and if the penalty function is greater than or equal to the terminal optimization function, the penalty function is used as a correction parameter of the input arrangement algorithm in the period, wherein the penalty function indicates that the overall network resources are sufficient.
The slice scheduler in the embodiments of the present disclosure is used to implement the network slice resource scheduling method in the first embodiment and the second embodiment, so that the description is simpler, and specific reference may be made to the related description in the first embodiment and the second embodiment of the foregoing method, which is not repeated here.
Fig. 6 is a block diagram of a network slice resource orchestration system according to a fourth embodiment of the present disclosure, where the network slice resource orchestration system includes a terminal 1 and a slice orchestrator 2 according to any one of the preceding claims, as shown in fig. 6.
Furthermore, the network slice resource orchestration system comprises a radio access network 3, a transport bearer network 4 and a core network 5 as described above.
In addition, as shown in fig. 7, a fifth embodiment of the present disclosure further provides an electronic device, including a memory 10 and a processor 20, where the memory 10 stores a computer program, and when the processor 20 runs the computer program stored in the memory 10, the processor 20 executes the above-mentioned various possible network slice resource scheduling methods.
The memory 10 is connected to the processor 20, the memory 10 may be a flash memory, a read-only memory, or other memories, and the processor 20 may be a central processing unit or a single chip microcomputer.
Furthermore, embodiments of the present disclosure provide a computer-readable storage medium having stored therein computer-executable instructions that, when executed by at least one processor of a user device, perform the various possible methods described above.
Among them, computer-readable media include computer storage media and communication media including any medium that facilitates transfer of a computer program from one place to another. A storage media may be any available media that can be accessed by a general purpose or special purpose computer. An exemplary storage medium is coupled to the processor such the processor can read information from, and write information to, the storage medium. In the alternative, the storage medium may be integral to the processor. The processor and the storage medium may reside in an ASIC (Application Specific Integrated Circuit ). In addition, the ASIC may reside in a user device. The processor and the storage medium may reside as discrete components in a communication device.
It is to be understood that the above embodiments are merely exemplary embodiments employed to illustrate the principles of the present disclosure, however, the present disclosure is not limited thereto. Various modifications and improvements may be made by those skilled in the art without departing from the spirit and substance of the disclosure, and are also considered to be within the scope of the disclosure.
Claims (12)
1. A network slice resource orchestration method, applied to a slice orchestrator, the method comprising:
after receiving a slice order, converting the business requirement of the order into an end-to-end network performance index;
obtaining a network end optimization function and a weight function of a wireless access network, a transmission bearing network and a core network in a preset period based on the end-to-end network performance index;
obtaining a penalty function according to network end optimization functions and weight functions of the wireless access network, the transmission bearing network and the core network;
transmitting the end-to-end network performance index to a terminal so that the terminal measures the end-to-end performance in the period to obtain a terminal optimization function, and transmitting the terminal optimization function to a slice composer;
obtaining the overall resource state of the network and the correction parameters of the input arrangement algorithm in the period based on the terminal optimization function and the penalty function;
and carrying out resource arrangement correction of the current period according to the correction parameters of the input arrangement algorithm in the period.
2. The resource orchestration method according to claim 1, wherein obtaining network-side optimization functions and weight functions of the radio access network, the transport bearer network, and the core network in a preset period based on the end-to-end network performance index comprises:
decomposing the end-to-end network performance index into a wireless network target index, a transmission network target index and a core network target index;
respectively distributing a wireless network target index, a transmission network target index and a core network target index to three subdomains of a wireless access network, a transmission bearing network and a core network, respectively monitoring performance indexes in respective network segments in a preset period to obtain the performance indexes monitored in the period, respectively obtaining respective corresponding network end optimization functions according to the difference between the respective monitored performance indexes and the respective target indexes, respectively evaluating optimizable spaces of the respective monitored performance indexes in the period according to the performance upper limit capability of the respective network segments to respectively give respective corresponding weight functions in the period, and respectively sending the respective network end optimization functions and the weight functions to a slice orchestrator;
and receiving respective network end optimization functions and weight functions respectively sent by the wireless access network, the transmission bearing network and the core network.
3. The resource orchestration method according to claim 1, wherein the end-to-end network performance metrics comprise one or more of: average rate, peak rate, delay and packet loss rate.
4. The resource scheduling method according to claim 1, wherein the deriving the penalty function from the network side optimization functions and the weight functions of the radio access network, the transport bearer network, and the core network comprises:
respectively multiplying the network end optimization functions of the wireless access network, the transmission bearing network and the core network by the weight functions of the wireless access network, the transmission bearing network and the core network to obtain the subdomain penalty functions of the wireless access network, the transmission bearing network and the core network;
and collecting the punishment functions of the subdomains of the wireless access network, the transmission bearing network and the core network to obtain punishment functions.
5. The resource scheduling method according to claim 1, wherein obtaining the network overall resource state and the correction parameters of the input scheduling algorithm in the period based on the terminal optimization function and the penalty function comprises:
comparing the terminal optimization function with the penalty function,
if the penalty function is smaller than the terminal optimization function, indicating that the network overall resources are in a state to be expanded or optimized, and taking the terminal optimization function as a correction parameter of an input arrangement algorithm in the period;
and if the penalty function is greater than or equal to the terminal optimization function, the penalty function is used as a correction parameter of the input arrangement algorithm in the period, wherein the penalty function indicates that the overall network resources are sufficient.
6. A slice orchestrator, comprising:
the conversion module is used for converting the business requirement of the order into an end-to-end network performance index after the slicing orchestrator receives the slicing ordering order;
the acquisition module is used for acquiring a network end optimization function and a weight function of the wireless access network, the transmission bearing network and the core network in a preset period based on the end-to-end network performance index;
the computing module is arranged to obtain a punishment function according to a network end optimization function and a weight function of the wireless access network, the transmission bearing network and the core network;
the sending module is configured to send the end-to-end network performance index to a terminal, so that the terminal measures the end-to-end performance in the period to obtain a terminal optimization function and send the terminal optimization function to the slice composer;
the acquisition module is further configured to obtain a network overall resource state based on the terminal optimization function and the penalty function, and input correction parameters of an arrangement algorithm in the period;
and the resource arrangement module is set to carry out resource arrangement correction of the current period according to the correction parameters of the arrangement algorithm input in the period.
7. The slice orchestrator according to claim 6, wherein the acquisition module comprises:
a decomposition unit configured to decompose the end-to-end network performance index into a wireless network target index, a transmission network target index, and a core network target index;
the transmitting unit is configured to respectively allocate the wireless network target index, the transmission network target index and the core network target index to three subdomains of the wireless access network, the transmission bearing network and the core network through the transmitting module, so that the wireless access network, the transmission bearing network and the core network respectively monitor performance indexes in respective network segments in a preset period to obtain the monitored performance indexes in the period, respectively obtain respective corresponding network end optimization functions according to the difference between the respective monitored performance indexes and the respective target indexes, respectively evaluate the optimizable space of the respective monitored performance indexes in the period according to the performance upper limit capability of the respective network segments to respectively give respective corresponding weight functions in the period, and respectively send the respective network end optimization functions and the weight functions to the slicing orchestrator;
the receiving unit is configured to receive respective network end optimization functions and weight functions respectively sent by the radio access network, the transmission bearer network and the core network.
8. The slice orchestrator according to claim 6, wherein the end-to-end network performance metrics include one or more of: average rate, peak rate, delay and packet loss rate.
9. The slice orchestrator according to claim 6, wherein the acquisition module is specifically arranged to:
comparing the terminal optimization function with the penalty function,
if the penalty function is smaller than the terminal optimization function, indicating that the network overall resources are in a state to be expanded or optimized, and taking the terminal optimization function as a correction parameter of an input arrangement algorithm in the period;
and if the penalty function is greater than or equal to the terminal optimization function, the penalty function is used as a correction parameter of the input arrangement algorithm in the period, wherein the penalty function indicates that the overall network resources are sufficient.
10. A network slice resource orchestration system comprising a terminal, and a slice orchestrator according to any one of claims 6-9.
11. An electronic device comprising a memory and a processor, the memory having a computer program stored therein, the processor performing the network slice resource orchestration method according to any one of claims 1-5 when the processor runs the computer program stored in the memory.
12. A computer-readable storage medium, comprising: computer program which, when run on a computer, causes the computer to perform the network slice resource orchestration method according to any one of claims 1-5.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110659280.7A CN113473498B (en) | 2021-06-15 | 2021-06-15 | Network slice resource arrangement method, slice arrangement device and arrangement system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110659280.7A CN113473498B (en) | 2021-06-15 | 2021-06-15 | Network slice resource arrangement method, slice arrangement device and arrangement system |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN113473498A CN113473498A (en) | 2021-10-01 |
| CN113473498B true CN113473498B (en) | 2023-05-19 |
Family
ID=77869872
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110659280.7A Active CN113473498B (en) | 2021-06-15 | 2021-06-15 | Network slice resource arrangement method, slice arrangement device and arrangement system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113473498B (en) |
Citations (17)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2014168225A2 (en) * | 2013-04-10 | 2014-10-16 | Nec Corporation | Communication system |
| CN108601087A (en) * | 2018-04-27 | 2018-09-28 | 哈尔滨工业大学深圳研究生院 | A kind of wireless communication resources allocation algorithm based on network slice |
| CN109600262A (en) * | 2018-12-17 | 2019-04-09 | 东南大学 | Resource self-configuring and self-organization method and device in URLLC transmission network slice |
| CN110301143A (en) * | 2016-12-30 | 2019-10-01 | 英特尔公司 | Method and apparatus for radio communication |
| CN110505101A (en) * | 2019-09-05 | 2019-11-26 | 无锡北邮感知技术产业研究院有限公司 | A kind of network slice method of combination and device |
| CN110519783A (en) * | 2019-09-26 | 2019-11-29 | 东华大学 | 5G network based on enhancing study is sliced resource allocation methods |
| CN111182637A (en) * | 2019-12-24 | 2020-05-19 | 浙江大学 | Wireless network resource allocation method based on generation countermeasure reinforcement learning |
| CN111556518A (en) * | 2020-06-12 | 2020-08-18 | 国网经济技术研究院有限公司 | Resource allocation method and system for improving network quality in multi-slice network |
| CN111629390A (en) * | 2020-04-30 | 2020-09-04 | 北京邮电大学 | Network slice arranging method and device |
| CN111865681A (en) * | 2020-07-14 | 2020-10-30 | 中国电力科学研究院有限公司 | Core network slice end-to-end time delay optimization method, system and storage medium |
| CN112152855A (en) * | 2020-09-25 | 2020-12-29 | 广州爱浦路网络技术有限公司 | Method for dynamically adjusting network slice instance resources |
| CN112369103A (en) * | 2018-05-08 | 2021-02-12 | Idac控股公司 | Method for logical channel prioritization and traffic shaping in a wireless system |
| CN112437449A (en) * | 2020-09-30 | 2021-03-02 | 国网安徽省电力有限公司信息通信分公司 | Joint resource allocation method and area organizer |
| CN112801125A (en) * | 2019-11-13 | 2021-05-14 | 辉达公司 | Synthesizing data for training one or more neural networks |
| CN112887142A (en) * | 2021-01-26 | 2021-06-01 | 贵州大学 | Method for generating web application slice in virtualized wireless access edge cloud |
| CN112911715A (en) * | 2021-02-03 | 2021-06-04 | 南京南瑞信息通信科技有限公司 | Power distribution method and device for maximizing throughput in virtual wireless network |
| CN112954742A (en) * | 2021-02-08 | 2021-06-11 | 中国科学院计算技术研究所 | Resource allocation method for mobile communication network slice |
-
2021
- 2021-06-15 CN CN202110659280.7A patent/CN113473498B/en active Active
Patent Citations (18)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP2984889A2 (en) * | 2013-04-10 | 2016-02-17 | NEC Corporation | Communication system |
| WO2014168225A2 (en) * | 2013-04-10 | 2014-10-16 | Nec Corporation | Communication system |
| CN110301143A (en) * | 2016-12-30 | 2019-10-01 | 英特尔公司 | Method and apparatus for radio communication |
| CN108601087A (en) * | 2018-04-27 | 2018-09-28 | 哈尔滨工业大学深圳研究生院 | A kind of wireless communication resources allocation algorithm based on network slice |
| CN112369103A (en) * | 2018-05-08 | 2021-02-12 | Idac控股公司 | Method for logical channel prioritization and traffic shaping in a wireless system |
| CN109600262A (en) * | 2018-12-17 | 2019-04-09 | 东南大学 | Resource self-configuring and self-organization method and device in URLLC transmission network slice |
| CN110505101A (en) * | 2019-09-05 | 2019-11-26 | 无锡北邮感知技术产业研究院有限公司 | A kind of network slice method of combination and device |
| CN110519783A (en) * | 2019-09-26 | 2019-11-29 | 东华大学 | 5G network based on enhancing study is sliced resource allocation methods |
| CN112801125A (en) * | 2019-11-13 | 2021-05-14 | 辉达公司 | Synthesizing data for training one or more neural networks |
| CN111182637A (en) * | 2019-12-24 | 2020-05-19 | 浙江大学 | Wireless network resource allocation method based on generation countermeasure reinforcement learning |
| CN111629390A (en) * | 2020-04-30 | 2020-09-04 | 北京邮电大学 | Network slice arranging method and device |
| CN111556518A (en) * | 2020-06-12 | 2020-08-18 | 国网经济技术研究院有限公司 | Resource allocation method and system for improving network quality in multi-slice network |
| CN111865681A (en) * | 2020-07-14 | 2020-10-30 | 中国电力科学研究院有限公司 | Core network slice end-to-end time delay optimization method, system and storage medium |
| CN112152855A (en) * | 2020-09-25 | 2020-12-29 | 广州爱浦路网络技术有限公司 | Method for dynamically adjusting network slice instance resources |
| CN112437449A (en) * | 2020-09-30 | 2021-03-02 | 国网安徽省电力有限公司信息通信分公司 | Joint resource allocation method and area organizer |
| CN112887142A (en) * | 2021-01-26 | 2021-06-01 | 贵州大学 | Method for generating web application slice in virtualized wireless access edge cloud |
| CN112911715A (en) * | 2021-02-03 | 2021-06-04 | 南京南瑞信息通信科技有限公司 | Power distribution method and device for maximizing throughput in virtual wireless network |
| CN112954742A (en) * | 2021-02-08 | 2021-06-11 | 中国科学院计算技术研究所 | Resource allocation method for mobile communication network slice |
Non-Patent Citations (3)
| Title |
|---|
| 5G车联网资源分配技术研究与评估;李杏;《中国优秀硕士学位论文全文数据库（电子期刊）信息科技辑》;全文 * |
| Advanced_Dynamic_Channel_Access_Strategy_in_Spectrum_Sharing_5G_Systems;Siyu Lin;《IEEE XPLORE》;全文 * |
| Ericsson.R2-2007645 "Methods for serving slices on different frequencies".3GPP tsg_ran\wg2_rl2.2020,(第tsgr2_111-e期),全文. * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN113473498A (en) | 2021-10-01 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN102422701B (en) | Load estimation to meet a defined quality of service | |
| KR101265031B1 (en) | Method and apparatus for transmitting management information in wireless local area network system | |
| Galeana-Zapién et al. | Design and evaluation of a backhaul-aware base station assignment algorithm for OFDMA-based cellular networks | |
| US20150063144A1 (en) | Method and apparatus for software defined flow control in wireless systems | |
| RU2480944C2 (en) | Determining load measure for network element using weighted method | |
| Tian et al. | QoS-constrained medium access probability optimization in wireless interference-limited networks | |
| KR20130132525A (en) | Method and apparatus for transmitting management information frame in wireless local area network system | |
| WO2019230659A1 (en) | Communication system | |
| JP4990279B2 (en) | Allocation of radio resources to reduce terminal transmission power | |
| JP2009534973A (en) | Radio resource management method in radio communication network | |
| KR100932787B1 (en) | Channel State Information Transmission Method in User Terminal of Broadband Mobile Communication System and Radio Resource Allocation Method in Base Station | |
| US8385930B2 (en) | Reduced resource allocation parameter signalling | |
| Kim et al. | Edge computing assisted adaptive streaming scheme for mobile networks | |
| CN107666467B (en) | Resource allocation method, equipment and system | |
| Elmosilhy et al. | User association with mode selection in LWA-based multi-RAT HetNet | |
| Zarin et al. | Hybrid radio resource management for time-varying 5G heterogeneous wireless access network | |
| CN113473498B (en) | Network slice resource arrangement method, slice arrangement device and arrangement system | |
| Ho et al. | Mobile data offloading system for video streaming services over SDN-enabled wireless networks | |
| Kim et al. | Super-MAC design for tightly coupled multi-RAT networks | |
| US20130303158A1 (en) | Key Performance Indicator for Operator Performance Evaluation in Communication Network Resource Sharing | |
| Baynat et al. | An efficient analytical model for the dimensioning of wimax networks | |
| Braga Jr et al. | A semi-distributed approach for uplink max-min energy efficiency optimization with minimum user satisfaction and adjacency constraints | |
| WO2023010359A1 (en) | Data transmission method and apparatus, device, and storage medium | |
| Sachs et al. | Generic abstraction of access performance and resources for multi-radio access management | |
| CN115334525B (en) | Network utilization rate calculation method and device |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |