CN111095979B

CN111095979B - Method, apparatus and computer storage medium for resource allocation

Info

Publication number: CN111095979B
Application number: CN201780094891.3A
Authority: CN
Inventors: 赵昆; 林凌峰; 吕玲; 范绍帅; 田辉; 赵鹏涛; 贾杨; 李国平; 凌刚
Original assignee: Nokia Shanghai Bell Co Ltd
Current assignee: Nokia Shanghai Bell Co Ltd
Priority date: 2017-09-15
Filing date: 2017-09-15
Publication date: 2023-06-13
Anticipated expiration: 2037-09-15
Also published as: WO2019051798A1; CN111095979A

Abstract

The present disclosure relates to methods, apparatus, and computer storage media for resource allocation. Embodiments of the present disclosure provide methods, apparatuses and computer program products for resource allocation in a communication network. The method according to one embodiment comprises: determining an amount of resources required by each of a plurality of network slices of the communication network, one network slice being associated with a set of logical network functions; calculating a remaining resource amount corresponding to each subset of network slices of the plurality of network slices based on the determined amount of resources required by each network slice, the remaining resource amount being an amount of resources remaining in a total amount of resources after allocating resources to slices of the plurality of network slices other than the subset of network slices; and allocating the total amount of resources to the plurality of network slices based on the amount of resources remaining for each of the subset of network slices of the plurality of network slices. By utilizing the embodiment of the invention, the resource allocation of the network slice level can be effectively obtained, and the resource utilization is improved.

Description

Method, apparatus and computer storage medium for resource allocation

Technical Field

Embodiments of the present disclosure relate generally to the field of communication networks and, more particularly, relate to a method, apparatus, and computer storage medium for resource allocation for network slicing in a communication network.

Background

The description of this section is intended to facilitate a better understanding of the present disclosure. The contents of this section should therefore be read on this basis and should not be understood as an admission as to which belongs to the prior art or which does not.

Internet-based services bring a pleasant experience, and with the rapid development of such services, the explosive growth of mobile traffic has caused serious impacts on the bandwidth of the mobile communication system. The internet of things, automotive networks, industrial control automation, and other new services place stringent demands on the connectivity, latency, and reliability of mobile communication systems. In the third generation partnership project (3 GPP), the concept of network slicing has been introduced to address the needs of different vertical industries. These needs of the vertical industry translate into a wide range of use cases for the next generation architecture.

An important part of the idea of the next generation network architecture is the support of network slicing. Network slicing may be considered a set of end-to-end logical network functions including access network functions, core network functions, backhaul functions, and the like. Network slicing is considered an effective scheme for providing customized services for various types of fifth generation (5G) application scenarios. Specific details regarding this can be found in the next generation mobile network (NMGN) 5G white paper, the international mobile communications-2020 (5G) Group of promotions (IMT-2020 (5G) project Group) published in month 6 of 2016 entitled "The novel design of 5G architecture", and release V14.0.0 of 3GPP technical report TR 22.891, published in month 3 of 2016, entitled Technical Specification Group Services and System Aspects; feasibility Study on New Services and Markets Technology Enablers; stage 1 (Release 14). The entire contents of the above-mentioned documents are incorporated herein by reference.

Depending on the service requirements of the scenario, the network architecture resources may be divided into multiple virtual private virtual network portions. The network functions of different network slices may differ in order to provide services for different scenarios. Network slices mainly include Core Network (CN) slices and Radio Access Network (RAN) slices. The RAN working group in 3GPP has agreed on the handling of differentiated support for different network slices that the operator has preconfigured. The relevant content may be found in 3GPP manuscript R2-164004, entitled RAN support for network slicing. The contents of this document are also incorporated herein by reference.

At present, how to support differentiated processing for different network slices remains an open problem.

Disclosure of Invention

In communication networks, RAN resources are limited and scarce, so it is desirable for network slices to be able to make efficient use of the scarce RAN resources. Thus, it is necessary to enable RAN network slices to share physical resources, including radio resources, radio Access Technology (RAT)/Radio Interface Type (RITS), RAN architecture. Different network slices may include the same functionality and share resources in the RAN, in this way resources may be allocated rationally to serve each network slice in the RAN. In an embodiment of the present disclosure, a solution is provided for allocating resources to network slices in a communication network.

In a first aspect of the present disclosure, a method in a communication network is provided. The method includes determining an amount of resources required by each of a plurality of network slices of the communication network, one network slice being associated with a set of logical network functions; calculating a remaining resource amount corresponding to each subset of the plurality of network slices based on the determined amount of resources required by each network slice, the remaining resource amount being an amount of resources remaining in the total resource amount after allocating resources to slices of the plurality of network slices other than the subset of network slices; and allocating the total amount of resources to the plurality of network slices based on the amount of resources remaining for each of the subset of network slices of the plurality of network slices.

In some embodiments, calculating the remaining amount of resources for a subset S of network slices of the plurality of network slices may include calculating a feature function for the subset S of network slices, the feature function being in the form of:

wherein M represents the total resource amount, j represents a natural number, c _j And v (S) represents the amount of resources required by the jth network slice, v (S) represents the amount of resources remaining after the resources are allocated to the network slices outside the subset S of network slices, and max represents a maximum taking function.

In another embodiment, assigning the total amount of resources to the plurality of network slices based on the amount of resources remaining for each of the subset of network slices of the plurality of network slices may include: determining an allocation amount of resources available for the network slices in the subset of network slices based on the amount of remaining resources corresponding to the subset of network slices of the plurality of network slices; and allocating a total amount of resources to the plurality of network slices based on the determined amount of resource allocation. In a further embodiment, determining the resource allocation amount available to the network slices of the subset of network slices may include: establishing a bankruptcy game model, wherein a plurality of network slices are modeled as creditors in the bankruptcy game, and the total resource quantity is modeled as bankruptcy property in the bankruptcy game; and determining an allocation amount of resources available to the network slice of the subset of network slices using a bankruptcy gaming algorithm.

In yet another embodiment, determining the resource allocation amount available to a network slice of the subset of network slices may include: the amount of resource allocation available to an i-th network slice is determined by calculating the saprolimus value of the i-th network slice by the following equation:

Where v (S- { i }) represents the amount of remaining resources corresponding to the subset of network slices obtained after removal of the ith network slice in the subset of network slices S,

is a normalization factor, andand |S| represents the number of members in the subset S of network slices, N is the total set of all network slices, N is the total number of the plurality of network slices, N-! Representing the factorial of n. In a further embodiment, allocating the total amount of resources to the plurality of network slices based on the determined amount of resource allocation comprises: the determined resource allocation amount is quantized to a non-negative integer and the sum of the non-negative integers is made equal to the total resource amount.

In some embodiments, the determined amount of resources may be a number of physical resource blocks.

In other embodiments, the determining, calculating, and assigning operations of the method may be performed at predetermined cycles. In a further embodiment, the predetermined period may depend on at least one of: the validity time of the plurality of network slices, the fluctuation characteristics of the required amount of resources of the plurality of network slices, and the processing power of the means for performing the method in the communication network.

In a second aspect of the present disclosure, an apparatus is provided that operates in a communication network. The apparatus includes a determination unit, a calculation unit, and an allocation unit. The determining unit is configured to determine an amount of resources required by each of a plurality of network slices of the communication network, wherein one network slice is associated with a set of logical network functions; the computing unit is configured to calculate, based on the determined amount of resources required by each network slice, a remaining amount of resources corresponding to each subset of network slices of the plurality of network slices, the remaining amount of resources being an amount of resources remaining in a total amount of resources after allocating resources to slices of the plurality of network slices other than the subset of network slices; the allocation unit is configured to allocate the total amount of resources to the plurality of network slices based on the amount of resources remaining for each of the subset of network slices of the plurality of network slices.

In a third aspect of the present disclosure, an apparatus is provided. The apparatus comprises a processor and a memory containing instructions executable by the processor, whereby the apparatus is operative to perform any one of the methods described in the first aspect of the present disclosure.

In a fourth aspect of the present disclosure, there is provided a computer program product comprising instructions which, when executed on one or more processors, cause the one or more processors to perform any of the methods according to the first aspect of the present disclosure.

In a fifth aspect of the present disclosure, a computer-readable storage medium having a computer program product embodied thereon is provided. The computer program product comprises instructions which, when executed on at least one processor, cause the at least one processor to perform any of the methods according to the first aspect of the present disclosure.

It should be appreciated that although some embodiments of the present disclosure are described with reference to a 5G communication network, embodiments of the present disclosure are not limited to use in this scenario, but may be more broadly applied to any communication network, system, and scenario where similar problems exist.

Drawings

The above and other aspects, features and benefits of the various embodiments of the present disclosure will become more apparent from the following detailed description with reference to the accompanying drawings. Like reference symbols in the drawings indicate like or equivalent elements. The figures are only used to facilitate a better understanding of embodiments of the present disclosure and are not necessarily drawn to scale, in which:

FIG. 1 illustrates an example communication network in which embodiments of the present disclosure may be implemented;

2A-2B schematically illustrate a flow chart of a method for resource allocation according to an embodiment of the present disclosure;

FIG. 3 illustrates a flow chart of another method for resource allocation according to an embodiment of the present disclosure;

FIG. 4 illustrates a schematic diagram of the operation between modules 10 of an apparatus for resource allocation according to an embodiment of the present disclosure; and

fig. 5 is a simplified block diagram schematically illustrating an apparatus according to an embodiment of the present disclosure.

Detailed Description

Hereinafter, the principles and spirit of the present disclosure will be described with reference to exemplary embodiments. It should be understood that all of these embodiments are presented merely to provide those skilled in the art with a better understanding and further practice of the disclosure, and are not intended to limit the scope of the disclosure. For example, features illustrated or described as part of one embodiment can be used with another embodiment to yield still a further embodiment. For clarity, some features of an actual implementation described in this specification may be omitted.

References in the specification to "one embodiment," "an example embodiment," etc., indicate that the embodiment described may include a particular feature, structure, or characteristic, but every embodiment may not necessarily include the particular feature, structure, or characteristic. Moreover, such phrases are not necessarily referring to the same embodiment. Furthermore, when a particular feature, structure, or characteristic is described in connection with an embodiment, it is submitted that it is within the knowledge of one skilled in the art to effect such feature, structure, or characteristic in connection with other embodiments whether or not explicitly described.

It will be understood that, although the terms "first" and "second," etc. may be used herein to describe various elements, these elements should not be limited by these terms. These terms are only used to distinguish one element from another element. For example, a first element could be termed a second element, and, similarly, a second element could be termed a first element, without departing from the scope of example embodiments. The term "and/or" as used herein includes any and all combinations of one or more of the associated listed items.

The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of example embodiments. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms "comprises," "comprising," "includes," "including," "having," and/or "having," when used herein, specify the presence of stated features, elements, and/or components, but does not preclude the presence or addition of one or more other features, elements, components, and/or groups thereof. The term "optional" means that the described embodiments or implementations are not mandatory and may be omitted in some cases.

Generally, terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the present disclosure pertains, unless explicitly defined otherwise.

As used herein, the term "communication network" refers to a network that conforms to any suitable communication standard, such as New Radio (NR), long term evolution (LTE-a), wideband Code Division Multiple Access (WCDMA), high Speed Packet Access (HSPA), CDMA2000, time division synchronous code division multiple access (TD-CDMA), etc. Furthermore, communication between devices in a communication network may be performed according to any suitable communication protocol including, but not limited to, global system for mobile communications (GSM), universal Mobile Telecommunications System (UMTS), long Term Evolution (LTE), and/or other suitable communication protocols, such as first generation (1G), second generation (2G), 2.5G, 2.75G, 3G, 4G, 4.5G, 5G communication protocols, wireless Local Area Network (WLAN) standards (such as IEEE 802.11 standards); and/or any other suitable wireless communication standard, and/or any other presently known or future developed protocol.

As used herein, the term "network device" refers to a device in a communication network via which a terminal device accesses the network and receives services from it. Depending on the terminology and technology used, a network device may refer to a Base Station (BS), an Access Point (AP), etc.

The term "communication device" refers to any device having communication capabilities. By way of example and not limitation, a communication device may also be referred to as a terminal device, user Equipment (UE), subscriber Station (SS), portable subscriber station, mobile Station (MS), or Access Terminal (AT). The communication devices may include, but are not limited to, mobile phones, cellular phones, smart phones, voice over IP (VoIP) phones, tablet computers, wearable terminals, personal Digital Assistants (PDAs), portable computers, desktop computers, image capture terminals such as digital cameras, gaming terminals, music storage and playback appliances, car wireless terminals, wireless endpoints, mobile stations, laptop embedded devices (LEEs), laptop mounted devices (LMEs), USB dongles, smart devices, wireless Customer Premise Equipment (CPE), D2D devices, machine-to-machine (M2M) devices, V2X devices, and the like. In the following description, the terms "communication device", "terminal", "user equipment" and "UE" may be used interchangeably.

A schematic diagram of an example wireless communication network 100 in which embodiments of the present disclosure can be implemented is shown in fig. 1. The wireless communication network 100 may include one or more network devices 101. For example, in this example, network device 101 may be embodied as a base station, e.g., a gNB. It should be understood that the network device 101 may also be embodied in other forms, such as NB, eNB, BTS, BS, or BSS, repeater, etc. The network device 101 provides wireless connectivity for a plurality of communication devices 111-1, 111-2 (hereinafter collectively referred to as communication devices 111) that are within its coverage area. It should be understood that the arrangement in the figures is merely an example and that the wireless communication network 100 may include more or fewer communication devices or network devices. In addition, communication devices in the wireless communication network 100 may be of different types and capabilities and use different services.

In a conventional 4G network, a unified communication system is employed to serve all users. The entire physical resource is directly allocated to the user according to traffic and load. This is because the access devices in the previous network were almost entirely smartphones, and there was no need for network slicing. However, in 5G or other future communication systems, there may be many kinds of access devices and their traffic demands are quite different, which makes the conventional system model unsuitable for at least the following reasons.

First, the integrally applicable solution does not only not reflect the characteristics of 5G network slices, but also results in low resource utilization. Second, models with man-in-the-middle have not been fully studied, mainly due to the difficulty in designing appropriate mechanisms. Furthermore, previous networking technologies have not taken 5G networking scenarios into account. For example, enhanced mobile broadband (emmbb) scenarios require consideration of massive multiple-input multiple-output (MIMO) technology, while massive and its type of communication (mctc) requires consideration of narrowband internet of things (NB-IoT) technology. These technologies are key contributors to 5G networks.

For the above reasons, the concept of network slicing is proposed for different application scenarios. That is, there may be multiple network slices in the wireless communication network 100 of fig. 1. The network functions of different network slices may differ to provide services for different scenarios. In addition, different network slices may have different performance requirements and bandwidth requirements, and thus differentiated processing should be supported for different network slices to increase the utilization efficiency of scarce RAN resources. Multiple communication devices in fig. 1 may be associated with different network slices.

Embodiments of the present disclosure propose a resource allocation algorithm in a communication system that can be used for resource allocation in network slice services in, for example, but not limited to, 5G networks, and that can allocate resources reasonably and efficiently in a variety of scenarios.

In addition, in some embodiments of the present disclosure, the resource allocation problem in the communication network may be solved with a cooperative gaming algorithm. For example, a bankruptcy gaming model may be used to simulate multiple scenarios in a 5G network (e.g., emmbb, mctc, etc.). Bankruptcy gaming is a special type of multi-player collaborative gaming. In the bankruptcy gaming model, the total amount of liabilities of a bankruptcy company to each creditor is greater than the bankruptcy property owned by the company. To distribute the remaining property of a bankrupter, creditors operate by forming a coalition to obtain the maximum benefit of the coalition, and then members within the coalition will fairly distribute the benefit. In this way, creditors are free to form coalitions in order to obtain maximum benefit for specific situations in different environments. From this point of view, the bankruptcy game model has great flexibility and from the point of view of creditor it can produce optimal results according to different requirements.

In 5G networks, resources (e.g., physical Resource Blocks (PRBs), codewords, etc.) owned by a Base Station (BS) are limited and scarce. Thus, in some embodiments, it may be reasonably assumed that the total amount of resources required by all network slices is always no less than the total amount of resources owned by the BS. This is similar to the case in bankruptcy gaming. Accordingly, the inventors of the present disclosure propose to model the resource allocation of network slices in a communication network as property allocation in bankruptcy gaming.

In 1953, l.s. saproli (Shapley) proposed a mathematical approach that uses the concept of feature functions and saproli values to solve the allocation problem in bankruptcy gaming. In some embodiments of the present disclosure, the mathematical model may be used to solve the resource allocation problem in a communication network and to design appropriate parameters for the context of the communication network to obtain reasonable resource allocation results at the network slice level.

By way of example, embodiments of the present disclosure will be described in certain sections below in connection with a bankruptcy gaming model. In the description of these embodiments, terms such as "bankruptcy", "player (creditor)", "gaming" and the like are no longer intended in their original model. Rather, these terms are to be used to refer to the corresponding features. For example, a bankruptcy property in "bankruptcy" is referred to herein as a total resource in a communication network, an asset allocation in "bankruptcy" is referred to herein as a resource allocation in a communication network, players in "bankruptcy" are used to refer to network slices in a communication network, and a coalition of players is used to refer to a subset of network slices made up of one or more network slices in a communication network.

Thus, the inventors of the present disclosure propose to model base stations and network slices associated with different scenarios as a bankruptcy company and player (creditor) in a bankruptcy game, respectively. Finally, based on the separated reasonable requirements, the bankruptcy gaming model may enable network slices (modeled as creditors) to obtain stable resource allocations, and each network slice is satisfied with the allocation relationship. That is, the bankruptcy gaming model may be utilized in some embodiments to ensure relatively fair allocation of resources among network slices. A method 200 for resource allocation in a communication network according to an embodiment of the present disclosure is described below in conjunction with fig. 2A-2B. The communication network may be, for example, the wireless communication network 100 of fig. 1, and the method may be implemented by, for example, the network device 101 of fig. 1. However, the present disclosure is not limited thereto. In some embodiments, the method 200 may also be implemented by a plurality of network elements distributed in a network. For ease of discussion, the method 200 will be described below with reference to the network device 101 and the wireless communication network 100 described in fig. 1.

As shown in fig. 2A, at block 210, network device 101 determines an amount of resources required for each of a plurality of network slices of wireless communication network 100. In one embodiment, the wireless communication network 100 may be a 5G network and include a plurality of network slices corresponding to different application scenarios (e.g., emmbb, emtc). Each network slice is associated with a set of logical network functions. In addition, each network slice may have typical services, and different services may have relatively differentiated rate requirements. Thus, in some embodiments, the total rate required by the network slice may be obtained based on the rate requirements of the service and the number of users in the network slice, thereby determining the amount of resources required by the network slice. For example, for simplicity, fading issues may not be considered so that the number of PRBs required for a network slice may be roughly estimated based on the rate support that a single PRB can provide. It should be appreciated that in some embodiments, the amount of resources required for each of the plurality of network slices may also be alternatively or additionally determined based on other factors (e.g., qoS requirements, latency requirements, etc.).

At block 220, the network device 101 calculates a remaining amount of resources corresponding to each subset of network slices of the plurality of network slices based on the determined amount of resources required for each network slice. The remaining resource amount corresponding to each subset of network slices is an amount of resources remaining in a total resource amount after allocating resources to network slices other than the subset of network slices. Thus, the amount of remaining resources corresponding to each subset of network slices may be indicative of the amount of resources available to the subset of network slices.

In one embodiment, consider 1..n total N network slices, then the total set of network slices may be represented as n= {1, …, N }, while the subset of network slices has 2 ⁿ And each. In this case, at block 220, for 2 ⁿ Each subset of network slices in the subset calculates its corresponding amount of remaining resources.

In one embodiment, the amount of remaining resources corresponding to a subset of network slices S may be calculated by calculating a feature function for the subset of network slices S. As an example, the feature function form may be expressed as:

where M represents the total amount of resources, e.g. the total number of PRBs, j represents a natural number,

representing network slices j, c outside of the subset of network slices S _j The j-th network slice is represented by the required resource amount, and the result v (S) is represented by the remaining resource amount after the resource is allocated to the network slices outside the subset S of network slices, and max is represented by the maximum function. The feature functions of other subsets of network slices may be calculated in the same manner.

At block 230, the network device 101 allocates a total amount of resources to the plurality of network slices based on the amount of resources remaining for each of the subset of network slices of the plurality of network slices.

In one embodiment, at block 230, a resource allocation amount available for a network slice of the subset of network slices S may be determined based on an amount of remaining resources corresponding to the subset of network slices S of the plurality of network slices, and the total resource amount may be allocated to the plurality of network slices based on the determined resource allocation amount. Embodiments of the present disclosure are not limited to determining the amount of resource allocation available to network slices in the subset S of network slices in any particular manner.

By way of example and not limitation, in some embodiments, the network device 101 may determine the resource allocation amount based on a cooperative gaming algorithm (e.g., bankruptcy gaming algorithm).

An example implementation of block 230 is shown in fig. 2B. In this example, at block 231, the network device 101 builds a bankruptcy gaming model for resource allocation, wherein a plurality of network slices are modeled as creditors in the bankruptcy game and the total amount of resources are modeled as bankruptcy properties in the banuptcy game. Thus, the allocation of resources to network slices translates into the allocation of bankruptcy property among creditors. With respect to this allocation, there are bankruptcy gaming algorithms.

At block 232, the network device 101 determines an allocation amount of resources available to the network slice of the subset of network slices using a bankruptcy gaming algorithm; and at block 233, the total amount of resources is allocated to the plurality of network slices based on the determined amount of resource allocation.

In some embodiments, the resource allocation amount of network slice i may be determined by calculating a saproliferation value of an i-th network slice (also referred to as network slice i) of the plurality of network slices. For example, the saproli value for the ith network slice may be obtained by the following equation (2):

wherein v (S) represents the amount of remaining resources corresponding to the network slice itself S, and v (S- { i }) represents the amount of remaining resources corresponding to the subset of network slices obtained after the removal of the network slice i from the subset of network slices S. Thus, v (S) -v (S- { i }) may represent the contribution of network slice i to the subset of network slices. In addition, in the case of the optical fiber,

is a normalization factor, where |S| represents the number of members in the subset S of network slices, N is the total set of all network slices, N is the total number of the plurality of network slices, N-! Representing the factorial of n.

An example of resource allocation using method 200 in a 5G network is described below for purposes of example and not limitation. It should be understood, however, that embodiments of the present disclosure may be used with any other communication network where similar problems exist.

In this example, 3 network slices corresponding to three typical application scenarios in a 5G network are considered to build a bankruptcy game model. Each network slice corresponds to one creditor in the bankruptcy gaming model. With bankruptcy gaming algorithms, network slices form a coalition to achieve better debt settlement, i.e., resource allocation. Suppose the BS (modeled as bankruptcy in bankruptcy gaming)Company) is represented as a positive integer M, the total set of considered network slices is represented as n= {1, …, N }, then the union of network slices can be represented as S, S being a subset of N, i.e.

In the case where the total number of network slices is n, 2 is taken in total ⁿ Possibly in alliances. S may be 1/2 of the probability ⁿ Representing all possible federations.

Based on the above definition, a feature function v (S) for each federation (i.e., a subset of network slices) S may be obtained according to equation (1) above, which represents the amount of resources remaining after allocation of resources to network slices outside of the subset of network slices S, and thus may be indicative of the resources available to the subset of network slices S.

In one example embodiment, a saproli value may be calculated for each member i therein based on the feature function calculated for each federation S. In the bankruptcy game model, the saprolite value represents the average compensation available to members in the coalition, reflecting the coalition's contribution to the coalition. In resource allocation, the saprolipram value is used to represent the average contribution of each network slice to a subset of network slices, which indicates the amount of resources, e.g. the number of PRBs, that each network slice should be allocated. The saproli value of network slice i may be calculated, for example, as shown in equation (2) above.

In resource allocation, the amount of resources for each network slice may be fairly assigned based on the average contribution of each network slice. This is equivalent to equitably assigning properties for each member based on its contribution to the league in bankruptcy gaming.

The process of determining resource allocation for network slices according to embodiments of the present disclosure is described below in connection with a more specific example.

In this example, it is assumed that there are 5 network slices involved in resource allocation, i.e., n=5, and the 5 network slices may be denoted as a, B, C, D, E, respectively. Thus, taking network slice A as an example, there are 16 subsets of network slices containing network slice A, or, in other words, there are associations containing member A16, and can be expressed as: { A }, { A, B }, { A, C }, { A, D }, { A, E }, { A, B, C }, { A, B, D }, { A, B, E }, { A, C, D }, { A, C, E }, { A, B, C, D }, { A, B, C, E }, { A, B, D, E }, { A, C, D, E }, { A, B, C, D, E }. The 16 federations may be divided into 5 parts according to membership. Taking the three member federation { A, B, C }, { A, B, D }, { A, B, E }, { A, C, D }, { A, C, E }, { A, D, E }, as an example, in which case the normalization factor can be calculated as

Wherein->

Indicating that the federation is divided into 5 parts, +.>

The number of alliances representing this part is 6. The contribution of member a to the portion can be expressed as:

in some embodiments, when allocating the total amount of resources to the plurality of network slices based on the determined amount of resource allocation, the network device 101 may first quantize the determined amount of resource allocation to a non-negative integer and make the sum of the quantized non-negative integers for the plurality of network slices equal to the total amount of resources. For example, the contribution of member a to all possible coalitions in the above example may be quantified to obtain a remuneration of member a in bankruptcy gaming, i.e., the amount of resources that network slice a is allocated in the resource allocation.

As an example, in the case where the resource amount is an integer, for example, in the case where the resource amount is the number of PRBs, the saprolitic value calculated by the expression (2) may be subjected to an upward or downward rounding operation to obtain a quantized value. In the case where the result of the expression (2) is not a non-negative integer, the quantization operation may be performed.

Non-negative integer vectors can be utilized

Representing the number of resources obtained by the resource allocation method proposed by the embodiments of the present disclosure for each network slice, wherein +.>

Representing the number of resources obtained by the ith network slice. In the case of computing resource allocation by the expression (2), the elements of the vector X satisfy the following expressions (4) to (6):

Wherein N and M represent the aggregate and total resource amount of the network slice, respectively, (5) represents that

Adjusting (e.g. quantizing, or rounding) to obtain a non-negative integer +.>

Although in some embodiments, the amount of resources may represent the number of PRBs, it should be understood that embodiments of the present disclosure are not limited thereto. In some embodiments, the amount of resources may also represent, for example, the number of time resources, or the number of code resources, etc.

In some embodiments, the resource allocation problem of network slices may be addressed at layer 2 or layer 3 (L2/L3) of a communication network (e.g., wireless communication network 100 of fig. 1). For example, the methods of FIGS. 2A-2B may be implemented at L2/L3 of network device 101.

Alternatively or additionally, in some embodiments, the determining, calculating, and assigning operations in blocks 210-230 may be performed at a predetermined period T, as shown in FIG. 2A. For example, the active time period T of a network slice may be defined. At the end of period T, resource allocation for the network slice may be re-performed. The number of multiple network slices in the communication network may be different in each execution. Thus, when using a bankruptcy gaming algorithm, the bankruptcy gaming model established in the new resource allocation cycle will also change (e.g., the number of players (creditors) changes).

This periodic operation allows for the use of semi-dynamic programming algorithms (e.g., in conjunction with bankruptcy game models) to address resource allocation issues. The semi-dynamic programming algorithm can visually reflect the characteristic requirements of different types of users. By way of example and not limitation, the predetermined period T may depend on at least one of a fluctuation characteristic of an amount of resources required by the plurality of network slices, a processing power of a device performing the resource allocation method, and an effective time of the network slices.

An example method 300 of periodically performing resource allocation according to one embodiment of this disclosure is shown in fig. 3. The method 300 may be implemented, for example, but not limited to, by the network device 101 of fig. 1. For ease of discussion, the method 300 will be described below with reference to the network device 101.

As shown in FIG. 3, at block 310, network device 101 builds a bankruptcy gaming model that includes modeling total resource amounts and network slices as bankruptcy property and players, respectively. At block 320, the network device 101 obtains the number Ci of PRBs required for each network slice i. At block 330, a federation (i.e., a subset of network slices) is formed using the network slices to obtain a better allocation. At block 340, feature function values for all possible federations are obtained, e.g., based on equation (1). At block 350, a saprolidinous value for a member in the federation (i.e., a network slice) is determined, for example, based on equation (2), and resource allocation to the network slice is performed based thereon. At block 360, the network device determines whether an update period T has arrived, upon which a new round of resource allocation is initiated, i.e., returns to block 310.

After obtaining the network slice level resource allocation using embodiments of the present disclosure (e.g., methods 200 or 300), the resource allocation within the network slice may be further performed. The allocation of resources within the network slice may be performed, for example, but not limited to, using any known method. For example, scheduling policies such as Round Robin (RR) allocation, proportional Fair (PF) allocation, etc. may be used for resource allocation within a network slice.

An aspect of the present disclosure also provides an apparatus for allocating resources in a communication network. The apparatus may be, for example, the network device 101 shown in fig. 1. In one embodiment, the network device 101 comprises a determination unit, a calculation unit and an allocation unit. The determining unit is configured to determine an amount of resources required for each of a plurality of network slices of the wireless communication network 100. The computing unit is configured to compute, based on the determined amount of resources required for each network slice, a remaining amount of resources corresponding to each subset of network slices of the plurality of network slices, the remaining amount of resources being an amount of resources remaining in a total amount of resources after allocating resources to slices of the plurality of network slices other than the subset of network slices. The allocation unit is configured to allocate a total amount of resources to the plurality of network slices based on an amount of resources remaining for each of the subset of network slices of the plurality of network slices.

In one embodiment, the determination unit, calculation unit, and allocation unit of the network device 101 may perform the operations of blocks 210-230, respectively, in FIG. 2A, or may perform the operations of blocks 310-320, 330-340, and 350, respectively, in FIG. 3. Accordingly, the operations described above in connection with

methods

200 and 300 are equally applicable here and are not repeated here.

In fig. 4, an example operational diagram 400 between a determination unit 410, a calculation unit 420, and an allocation unit 430 of a network device according to one embodiment of the present disclosure is shown. As shown in fig. 4, the determining unit 410 may comprise sub-units 411-413 for determining the amount of resources required for different network slices, respectively. For example, each of the sub-units 411-413 may estimate the resource amount requirement Ci based on the number of users Ni associated with network slice i and the corresponding rate Vi of typical traffic. The resource amount demand Ci is reported (401, 402, 403) to a calculation unit 420 for calculating a characteristic function v (S) of the federation S, the saproli values of the network slices i in the federation S

And a final resource allocation result xi obtained by the rounding operation. The calculation unit 420 reports 404 the final resource allocation result xi to the allocation unit 430 to perform resource allocation 405-407.

Fig. 5 illustrates a simplified block diagram of an apparatus 500 for resource allocation according to another embodiment of the present disclosure. The device may be implemented in/as a network device (e.g., network device 101 shown in fig. 1).

The device 500 may include one or more processors 510 (such as a data processor) and one or more memories 520 coupled to the processors 510. The device 500 may also include one or more transmitters/receivers 540 coupled to the processor 510. Memory 520 may be a non-transitory machine-readable storage medium and it may store a program or computer program product 530. The computer program (product) 530 may include instructions that, when executed on an associated processor 510, enable the apparatus 500 to operate in accordance with embodiments of the present disclosure (e.g., perform the method 200 or 300). The combination of the one or more processors 510 and the one or more memories 520 may form a processing component 550 suitable for implementing various embodiments of the present disclosure.

Various embodiments of the present disclosure may be implemented by a computer program or computer program product executable by processor 510, software, firmware, hardware, or a combination thereof.

Memory 520 may be of any type suitable to the local technical environment and may be implemented using any suitable data storage technology, such as semiconductor-based memory terminal devices, magnetic memory terminal devices and systems, optical memory terminal devices and systems, fixed memory, and removable memory, as non-limiting examples.

Processor 510 may be of any type suitable to the local technical environment and may include, as non-limiting examples, one or more general purpose computers, special purpose computers, microprocessors, digital Signal Processors (DSPs), and processors based on a multi-core processor architecture.

Although some of the above description is made in the context of the communication network shown in fig. 1, this should not be construed as limiting the spirit and scope of the present disclosure. The principles and concepts of the present disclosure may be more generally applied to other scenarios.

Furthermore, the present disclosure may also provide a computer-readable storage medium, such as a memory containing a computer program or a computer program product as described above, including a machine-readable medium and a machine-readable transmission medium. The machine-readable medium may also be referred to as a computer-readable medium and may include machine-readable storage media, such as magnetic disks, magnetic tapes, optical disks, phase change memories, or electronic memory terminal devices, such as Random Access Memories (RAMs), read Only Memories (ROMs), flash memory devices, CD-ROMs, DVDs, blu-ray discs, etc. A machine-readable transmission medium may also be referred to as a carrier and may include, for example, electrical, optical, radio, acoustical or other form of propagated signals, such as carrier waves, infrared signals, etc.

The techniques described herein may be implemented by various means such that an apparatus implementing one or more functions of a corresponding apparatus described with an embodiment includes not only the prior art means but also means for implementing one or more functions of a corresponding apparatus described with respect to an embodiment, and may include separate means for each separate function or means that may be configured to perform two or more functions. For example, the techniques may be implemented in hardware (one or more devices), firmware (one or more devices), software (one or more modules), or a combination thereof. For firmware or software, implementation can be through modules (e.g., procedures, functions, and so on) that perform the functions described herein.

Example embodiments herein are described above with reference to block diagrams and flowcharts of methods and apparatus. It will be understood that each block of the block diagrams and flowchart illustrations, and combinations of blocks in the block diagrams and flowchart illustrations, respectively, can be implemented by various means including hardware, software, firmware, and combinations thereof. For example, in one embodiment, each block of the block diagrams and flowchart illustrations, and combinations of blocks in the block diagrams and flowchart illustrations, can be implemented by a computer program or computer program product comprising computer program instructions. These computer program instructions may be loaded onto a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions which execute on the computer or other programmable data processing apparatus create means for implementing the functions specified in the flowchart block or blocks.

Moreover, although operations are depicted in a particular order, this should not be understood as requiring that such operations be performed in the particular order shown or in sequential order, or that all illustrated operations be performed, to achieve desirable results. In some cases, multitasking and parallel processing may be advantageous. Likewise, while the above discussion contains several specific implementation details, these should not be construed as limitations on the scope of the subject matter described herein, but rather as descriptions of features specific to particular embodiments. Certain features that are described in this specification in the context of separate embodiments can also be implemented in combination in a single embodiment. Conversely, various features that are described 20 in the context of a single embodiment can also be implemented in multiple embodiments separately or in any suitable subcombination. Furthermore, although features may be described above as acting in certain combinations and even initially claimed as such, one or more features of a claimed combination can in some cases be excised from the combination, and the claimed combination may be directed to a subcombination or variation of a subcombination.

It is obvious to a person skilled in the art that as technology advances, the inventive concept can be implemented in various ways. The above-described embodiments are presented for purposes of illustration and not limitation, and it is to be understood that modifications and variations may be made without departing from the spirit and scope of the disclosure as those skilled in the art will readily understand. Such modifications and variations are considered to be within the purview of this disclosure and the appended claims. The scope of the present disclosure is defined by the appended claims.

Claims

1. A method implemented in a communication network, comprising:

determining an amount of resources required by each of a plurality of network slices of the communication network, one network slice being associated with a set of logical network functions;

calculating a remaining resource amount corresponding to each subset of network slices of the plurality of network slices based on the determined amount of resources required by each network slice, the remaining resource amount being an amount of resources remaining in a total amount of resources after allocating resources to slices of the plurality of network slices other than the subset of network slices; and

allocating the total amount of resources to the plurality of network slices based on the remaining amounts of resources respectively corresponding to subsets of network slices of the plurality of network slices, and

Wherein the determining, the calculating, and the assigning are performed at predetermined periods, the predetermined periods being dependent on at least one of:

the effective time of the plurality of network slices;

a fluctuation characteristic of a required amount of resources of the plurality of network slices; and

processing power of an apparatus for performing the method in the communication network.

2. The method of claim 1, wherein calculating the remaining amount of resources for a subset S of network slices of the plurality of network slices comprises calculating a feature function for the subset S of network slices, the feature function being in the form of:

wherein M represents the total resource amount, j represents a natural number, c _j And v (S) represents the amount of resources required by the j-th network slice, v (S) represents the amount of resources remaining after the resources are allocated to the network slices outside the subset S of network slices, and max represents a maximum taking function.

3. The method of claim 1 or 2, wherein assigning the total amount of resources to the plurality of network slices based on the remaining amounts of resources to which each of a subset of network slices of the plurality of network slices corresponds comprises:

determining an allocation amount of resources available to network slices in the subset of network slices based on the remaining amounts of resources corresponding to the subset of network slices of the plurality of network slices; and

The total amount of resources is allocated to the plurality of network slices based on the determined amount of resource allocation.

4. The method of claim 3, wherein determining an amount of resource allocation available to network slices of the subset of network slices comprises:

establishing a bankruptcy game model, wherein the plurality of network slices are modeled as creditors in the bankruptcy game, and the total resource amount is modeled as bankruptcy property in the bankruptcy game; and

utilizing a bankruptcy gaming algorithm, a resource allocation amount available to a network slice of the subset of network slices is determined.

5. The method of claim 4, wherein determining the resource allocation amount available to network slices of the subset of network slices comprises:

determining the resource allocation amount available for an i-th network slice by calculating the saprolimus value of the i-th network slice by the following equation:

is a normalization factor, and |S| represents the number of members in the subset S of network slices, NFor the total set of all of the network slices, n is the total number of the plurality of network slices, n ≡! Representing the factorial of n.

6. The method of claim 5, wherein allocating the total amount of resources to the plurality of network slices based on the determined amount of resource allocation comprises:

the determined resource allocation amount is quantized to a non-negative integer, and the sum of the non-negative integers is made equal to the total resource amount.

7. The method according to claim 1 or 2, wherein the determined amount of resources is the number of physical resource blocks.

8. An apparatus in a communication network, comprising a processor and a memory, the memory containing instructions executable by the processor, whereby the apparatus operates to:

allocating the total resource amount to the plurality of network slices based on the remaining resource amounts corresponding to each of the network slice subsets of the plurality of network slices;

The apparatus is further operative to perform the determining, the calculating, and the assigning at predetermined periods, the predetermined periods being dependent on at least one of:

the effective time of the plurality of network slices;

processing power of an apparatus for performing a method in the communication network.

9. The device of claim 8, wherein the memory contains instructions executable by the processor, whereby the device is further operative to calculate the remaining amount of resources for a subset S of network slices by calculating a feature function for the subset S of network slices in the plurality of network slices, the feature function being in the form of:

10. The apparatus of claim 8 or 9, wherein the memory contains instructions executable by the processor, whereby the apparatus is further operative to allocate the total amount of resources to the plurality of network slices by:

11. The device of claim 10, wherein the memory contains instructions executable by the processor, whereby the device is further operative to determine an amount of resource allocation available to a network slice of the subset of network slices by:

12. The device of claim 11, wherein the memory includes instructions executable by the processor, whereby the device is further operative to:

is a normalization factor, and |S| represents the number of members in the subset S of network slices, N is the total set of all of the network slices, N is the total number of the plurality of network slices, N-! Representing the factorial of n.

13. The device of claim 12, wherein the memory contains instructions executable by the processor, whereby the device is further operative to:

the total amount of resources is allocated to the plurality of network slices by quantizing the determined amount of resource allocation to a non-negative integer and such that the sum of the non-negative integers is equal to the total amount of resources.

14. The apparatus according to claim 8 or 9, wherein the determined amount of resources is a number of physical resource blocks.

15. A computer-readable storage medium having embodied thereon a computer program product comprising instructions which, when executed on at least one processor, cause the at least one processor to perform the method of any of claims 1 to 7.