Mobile ad hoc network service function chain arrangement method, device and system and storage medium

Abstract

The invention relates to the technical field of wireless communication, and discloses a mobile ad hoc network service function chain arrangement method, device and system and a storage medium, and the method comprises the steps: obtaining an arrangement request and a starting node; wherein the arrangement request comprises a plurality of entities; inserting the starting node into the head of the arrangement request to obtain a preprocessed arrangement request, and dividing the preprocessed arrangement request into a plurality of node-entity anchor point pairs; capturing topology dynamics in the mobile ad hoc network based on a time-limited recursive topology discovery protocol; utilizing the topology dynamic to construct a network forest map; and based on the network forest map, determining an optimal segment corresponding to each node-entity anchor point pair by taking the sum of the communication cost and the performance cost as a target, and connecting the optimal segments to obtain an optimal service function chain. The method can be used for functional arrangement of the mobile self-organizing nodes with heterogeneous functions in an infrastructure-free environment (such as a field area without a base station).

Description

Technical Field

[0001] The present invention relates to the field of wireless communication technology, and in particular to a method, device, system and storage medium for orchestrating a mobile self-organizing network service function chain. Background Art

[0002] Mobile Ad Hoc Networks (MANETs) are often used for rescue, environmental monitoring, military activities, etc. in environments with poor communication infrastructure (such as outdoor areas without base stations). On-demand on-site orchestration of mobile self-organizing nodes (such as drones, smart cars, etc.) plays an important role in executing these complex tasks, which usually require multiple functions (camera shooting, image recognition, data transmission, target tracking, etc.) to be orchestrated into a unified service function chain (Service Function Chain) with limited human intervention and communication infrastructure support. Its component functions are called in sequence as needed to collaborate to complete the task.

[0003] The orchestration of the service function chain of a mobile self-organizing network includes several key aspects: 1. Functional aspect: The functions deployed on the nodes must be optimized and executed in the required order to meet the functional requirements of the task. 2. Communication aspect: Qualified nodes must be correctly selected to form the best communication path to provide good service quality QoS guarantee for data and command interaction. Therefore, the service function chain orchestration is more complex than pure routing (only involving communication aspects) that only includes nodes. At the same time, due to the high dynamics of mobile self-organizing networks in terms of topology, signal strength, node failure, and battery capacity, mobile orchestration in environments without infrastructure (such as outdoor areas without base stations) is more challenging, and there are still many issues that need to be studied in depth: 1) How to quickly discover sufficient topology, function, communication, and performance information of mobile self-organizing nodes in an environment without infrastructure, and manage them in a unified manner as the data foundation for the orchestration of mobile service function chains.

[0004] 2) How to automatically orchestrate a high-quality mobile service function chain consisting of mobile self-organizing nodes based on the information discovered in the topology, without (or with little) human intervention or base station assistance, to provide a series of ordered functions required for on-site tasks.

[0005] In the prior art, the orchestration schemes of the service function chain involved include: 1. Orchestration in site-based wireless networks The paper "ZHANG P, WANG C, KUMAR N, et al. Space-Air-Ground Integrated Multi-Domain Network Resource Orchestration Based on Virtual Network Architecture:A DRL Method[J / OL]. IEEE Transactions on Intelligent Transportation Systems, 2022, 23(3): 2798-2808. DOI:10.1109 / TITS.2021.3099477." focuses on the allocation of network resources in the space-ground integrated network and models it as a virtual network mapping (VNE) problem. A deep reinforcement learning (DRL) scheduling algorithm considering node heterogeneity, temporal dynamics and self-organization characteristics is proposed, and a five-layer DRL agent is constructed. The optimization goal is to maximize the profit of the service provider while serving as many virtual network requests (VNRs) as possible. This paper mainly focuses on the communication aspect, but does not deeply address the orchestration problem of heterogeneous functions.

[0006] The paper "MA L, CHENG N, WANG X, et al. On-Demand Resource Management for 6GWireless Networks Using Knowledge-Assisted Dynamic Neural Networks[C / OL] / / ICC2022 - IEEE International Conference on Communications. 2022: 1-6. DOI:10.1109 / ICC45855.2022.9882279." The paper "KHAN AA, ABOLHASAN M, NI W, et al. An End-to-End (E2E) Network Slicing Framework for 5G Vehicular Ad-Hoc Networks[J / OL]. IEEE Transactions on Vehicular Technology, 2021, 70(7): 7103-7112. DOI:10.1109 / TVT.2021.3084735." proposes a model based on dynamic neural network to allocate bandwidth resources requested by users in heterogeneous wireless networks. The model builds a knowledge base that comprehensively considers service characteristics and node computing capabilities, and dynamically adjusts the depth of the neural network model to balance bandwidth allocation accuracy and overall processing latency, thereby obtaining the optimal solution and transmission overhead. However, the model does not consider the functional orchestration of heterogeneous nodes.

[0007] The paper "KHAN AA, ABOLHASAN M, NI W, et al. An End-to-End (E2E) Network Slicing Framework for 5G Vehicular Ad-Hoc Networks[J / OL]. IEEE Transactions on Vehicular Technology, 2021, 70(7): 7103-7112. DOI:10.1109 / TVT.2021.3084735." proposed an SDN / NFV-driven end-to-end 5G vehicle network slicing framework. The orchestration of heterogeneous resources is modeled as a multi-objective optimization problem, and the service function chain is solved using a genetic algorithm to construct an end-to-end network slice. However, the mobility of nodes, the heterogeneity of functions, the self-organizing characteristics, and the interaction between mobile nodes and network infrastructure have not been effectively reflected in this framework.

[0008] The paper "THIRUVASAGAM PK, CHAKRABORTY A, MATHEW A, et al. Reliable Placement of Service Function Chains and Virtual Monitoring Functions With Minimal Cost in Softwarized 5G Networks[J / OL]. IEEE Transactions on Network and Service Management, 2021, 18(2): 1491-1507. DOI:10.1109 / TNSM.2021.3056917." proposes to reliably place service function chains and virtual monitoring functions with minimal cost in software-based 5G networks, and formulates the problem as an integer linear programming (ILP) to minimize the total deployment cost.

[0009] A common point of the above studies is that service or resource orchestration is performed in a managed wireless network, and these infrastructures provide useful information for orchestration. However, these studies do not cover the orchestration scenarios in wireless environments without infrastructure. During the orchestration and collaboration process, self-organizing nodes may not get help from base stations (because there is no base station or the base station is too far away), so their orchestration algorithms need to be redesigned.

[0010] 2. Orchestration in edge networks The paper "LAROUI M, KHEDHER HI, MOUNGLA H, et al. Service function chains multi-resource orchestration in virtual mobile edge computing[J / OL]. Computer Networks, 2023, 224: 109582. DOI:https: / / doi.org / 10.1016 / j.comnet.2023.109582." comprehensively considers various system costs such as server power consumption and wireless transmission power consumption, and combines wireless multicast to establish an optimization model to reduce system costs and provide efficient services for mobile nodes (including IoT devices, user-end systems, etc.).

[0011] The paper "LI H, KORDI M E. DSPPV: Dynamic service function chainsplacement with parallelized virtual network functions in mobile edgecomputing[J / OL]. Internet of Things, 2023, 22: 100733. DOI:https: / / doi.org / 10.1016 / j.iot.2023.100733." proposes a parallel dynamic service function chain deployment method to accelerate the computing process, minimize the length of the service function chain, and improve the ability to process future requests through parallel VNFs.

[0012] The paper "LI J, GUO D, XIE J, et al. Availability-aware provision of service function chains in mobile edge computing[J / OL]. ACM Trans. Sen. Netw., 2023,19(3). https: / / doi.org / 10.1145 / 3565483. DOI:10.1145 / 3565483." takes into account the reliability of hardware and software to maximize the reliability of service function chains in each service delivery.

[0013] The paper "NGUYEN TTL, PHAM TM, PHAM L M. Efficient redundancy allocation for reliable service function chains in edge computing[J / OL].Journal of Network and Systems Management, 2022, 31(1)" proposes a deployment scheme that perceives service availability, aiming to improve the processing speed and reliability of user requests. The scheme mainly solves the problem of effectively mapping the primary network and backup virtual network functions while reducing user access latency.

[0014] The above studies follow a server-centric perspective, which orchestrates functions and resources to serve mobile nodes, which means that mobile nodes are service consumers rather than function providers or service orchestration nodes to complete complex ad hoc tasks, which does not meet the requirements of on-demand on-site orchestration of mobile self-organizing nodes.

[0015] 3. Routing in Ad Hoc Networks The paper "CHEN X, SUN G, WU T, et al. RANCE: A Randomly Centralized and On-Demand Clustering Protocol for Mobile Ad Hoc Networks[J / OL]. IEEE Internet of Things Journal, 2022, 9(23): 23639-23658. DOI:10.1109 / JIOT.2022.3188679." proposes a random centralized on-demand clustering protocol for mobile ad hoc networks, aiming to extend the node's clustering time to support collaboration between nodes.

[0016] The paper "LAVANYA K, INDIRA R, VELMURUGAN AK, et al. Mobility-BasedOptimized Multipath Routing Protocol on Optimal Link State Routing in MANET[C / OL] / / 2023 International Conference on Applied Intelligence and SustainableComputing (ICAISC). 2023: 1-6[2024-02-16]. https: / / ieeexplore.ieee.org / document / 10199484. DOI:10.1109 / ICAISC58445.2023.10199484." proposes a mobility-based multipath routing protocol and a link state transmission algorithm for QoS perception in mobile ad hoc networks.

[0017] The paper "KUMBHAR FH, YOUNG SHIN S. CV-AODV: Compatibility BasedVehicular Ad-hoc On Demand Distance Vector Routing Protocol[C / OL] / / 2020International Conference on Information and Communication TechnologyConvergence (ICTC). 2020: 1004-1008[2024-02-16]." proposes compatibility-based on-demand distance vector routing for Internet of Vehicles to improve vehicle connectivity.

[0018] The paper "CUI Y, ZHANG Q, FENG Z, et al. Topology-Aware Resilient Routing Protocol for FANETs: An Adaptive Q-Learning Approach[J / OL]. IEEE Internet of Things Journal, 2022, 9(19): 18632-18649. DOI:10.1109 / JIOT.2022.3162849." proposes a FANET topology-aware resilient routing protocol based on Q-learning method, which captures topology changes (especially in UAV cooperative environments) with low overhead and makes routing decisions in a distributed and autonomous manner.

[0019] The above research mainly focuses on the basic routing problem, that is, the communication aspect. The orchestration problem of heterogeneous functions deployed on mobile ad hoc nodes is not well addressed. The requirement that different functions must be traversed in the order of requests on the optimal communication path composed of mobile wireless nodes makes this problem more complex than pure routing. Summary of the invention

[0020] In order to solve the above problems, the present invention provides a mobile self-organizing network service function chain orchestration method, device, system and storage medium to reasonably orchestrate functionally heterogeneous mobile self-organizing nodes in an environment without infrastructure. An environment without infrastructure means that no base station assistance is provided during the chain orchestration and collaboration process, and clusters are not pre-built through protocols such as ZigBee and LEACH. All nodes can operate equally and can freely participate in or leave collaboration based on orchestration. The present invention has good applicability to complex collaborative tasks, and is particularly suitable for remote areas with underdeveloped communication infrastructure.

[0021] In order to achieve the above object, the technical solution adopted by the present invention is as follows: According to a first solution of the present invention, a method for arranging a mobile ad hoc network service function chain is provided, the method comprising: Obtaining an orchestration request and a starting node; wherein the orchestration request includes multiple entities, and the entities are nodes or functions; Inserting the start node into the header of the orchestration request to obtain a preprocessed orchestration request, and dividing the preprocessed orchestration request into a plurality of node-entity anchor point pairs; Capturing topology dynamics in a mobile ad hoc network based on a time-constrained recursive topology discovery protocol; wherein the topology dynamics include topology information, functional information, communication information, and performance information; The network forest graph is dynamically constructed using the topology; wherein the network forest graph is represented as , For nodes, is the communication link between nodes, For function, is a functional link between a node and a function, the communication link between the nodes is weighted by a communication cost, the communication cost is determined according to the topology information and the communication information, and the functional link between the node and the function is weighted by a performance cost, the performance cost is determined according to the function information and the performance information; Based on the mesh forest graph, with the goal of minimizing the sum of communication cost and performance cost, the optimal segment corresponding to each node-entity anchor point pair is determined, and the optimal service function chain is obtained by connecting the optimal segments.

[0022] Furthermore, a time-constrained recursive topology discovery protocol is used to capture the topology dynamics in mobile ad hoc networks, including: Based on a time-constrained recursive topology discovery protocol, on-demand mode, periodic mode and / or hybrid mode are utilized to capture the topology dynamics in mobile ad hoc networks; In on-demand mode, each node starts the recursive topology discovery process only when an orchestration request arrives to capture topology dynamics. The process is as follows: (1) When any node When receiving an orchestration request, it becomes an orchestration node, starts the topology discovery process, generates and broadcasts a topology discovery request ,in Is the global topology discovery timer , the orchestration node is During this period, wait for other nodes to reply to the discovered topology. Request signal for topology discovery; (2) When any node Receive a topology discovery request hour: Immediately reply the node that sent the topology discovery request with its own node information and the currently known topology dynamics ,in, , Indicates functional information, representing The functionality provided is represented by , Indicates whether the corresponding function can be provided; Indicates communication information, representing The various communication quality QoS indicators are expressed as , For the The value of the QoS indicator; Indicates performance information, representing The various performance indicators during function calls are expressed as , For the The value of the performance indicator; Set the local topology discovery timer , Used to characterize the time allowed for wireless round trip and processing, During this period, it waits for other nodes to reply to the discovered topology and broadcasts the forwarding topology discovery request. ; (3) When any node Topology discovery timer time out: If the node Is the arrangement node, in the current mesh forest graph Start the arrangement on the If the node Not an orchestration node, go up one node again Reply to newly found topology dynamics ; (4) When any node Received from other nodes Topological dynamics of reply When , it merges it with its own topology dynamically, and calculates the communication cost and performance cost to weight the communication link and functional link respectively; In periodic mode, any node sets a topology exchange timer , used for periodic exchange, the process is as follows: (2) When any node Topology discovery timer Timeout, broadcast node Topology , and reset the topology discovery timer ; (2) When any node Received from other nodes Topological dynamics of reply When With Node The topologies are dynamically merged, and the communication cost and performance cost are calculated to weight the communication links and functional links respectively; (3) When any node When receiving an orchestration request, it becomes an orchestration node and Start the arrangement on the In hybrid mode, both on-demand mode and periodic mode are integrated and work in a concurrent thread mode, including the following multiple concurrently running threads: The thread that processes the orchestration request is a code shared by the on-demand mode and the periodic mode. It processes the received orchestration request in real time. In the on-demand mode, the on-demand topology discovery process is triggered, and in the periodic mode, the service function chain orchestration is directly triggered. The thread that processes the topology graph arrival is the code shared by the on-demand mode and the periodic mode. It processes the topology graph transmitted by other nodes in real time and calculates the communication cost and performance cost to weight the communication link and functional link respectively. The periodic topology discovery thread is used only for periodic topology discovery and starts the periodic topology map broadcast exchange process in periodic mode.

[0023] Further, the starting node is inserted into the header of the orchestration request to obtain a preprocessed orchestration request, and the preprocessed orchestration request is divided into a plurality of node-entity anchor point pairs, including: The starting node Insert into the header of the orchestration request to obtain the pre-processed orchestration request , the current pointer points to the first element of the arrangement request, take the pointer ,in Indicates entities, Indicates entities, is the total number of entities; when When the starting node As starting anchor point ; when When , according to the optimal segmentation found previously ,by The second-to-last element of is used as the starting anchor point; Determine the end anchor point ; Form a branch node-entity anchor pair, .

[0024] Furthermore, based on the mesh forest graph, the optimal segmentation corresponding to each node-entity anchor point pair is determined with the goal of minimizing the sum of the communication cost and the performance cost, including: Based on the mesh forest graph, a mesh tree graph is dynamically generated according to the functions included in the node-entity anchor point pairs; wherein the mesh tree graph only retains the functions included in the node-entity anchor point pairs and the functional links related to the functions, as well as all nodes and communication links in the mesh forest graph.

[0025] Further, based on the mesh forest graph, with the goal of minimizing the sum of communication cost and performance cost, the optimal segment corresponding to each node-entity anchor point pair is determined, and the optimal service function chain is obtained by connecting the optimal segments, including: use The algorithm determines the optimal segmentation between the starting anchor point and the ending anchor point in the current node-entity anchor point on the network tree diagram; Connect the optimal segment between the starting anchor point and the ending anchor point in the current node-entity anchor point with the determined optimal segment, and extend the service function chain segment by segment; The currently determined optimal segmentation is used as the starting point of the next segmentation until all node-entity anchor point pairs are determined and connected in sequence to obtain the optimal service function chain.

[0026] Furthermore, the communication cost is calculated by the following method: Get Node No. QoS indicators The corresponding communication cost; Different QoS indicators are converted using the following formula: Delay cost: ; Packet loss rate cost: ; Jitter cost: ; Bandwidth cost: ,in It is the bandwidth reference value, which can be set according to the actual situation; Normalize the converted cost: ; In the formula, represents the normalized communication cost, Indicates the node number, Indicates the total number of nodes; The nodes are calculated by the following formula Aggregate communication cost : ; In the formula, is the weight of each single communication cost, N is the total number of QoS indicators; node To Node Communication Link The communication cost The authority is granted as follows: .

[0027] Furthermore, the performance cost is calculated by the following method: Get Node No. Performance indicators The corresponding performance cost; Different performance indicators are converted using the following formula: CPU cost: ; RAM cost: ; Battery price: ,in It is the battery reference value, which can be set according to the actual situation; Reliability cost: ; The performance cost of the conversion Normalize: ;

[0028] In the formula, represents the normalized performance cost; The nodes are calculated by the following formula Aggregation performance cost: ;

[0029] In the formula, is the weight of each single performance cost, is the total number of performance indicators; node To function Functional Link Performance cost The authority is granted as follows: .

[0030] According to a second technical solution of the present invention, a mobile self-organizing network service function chain arrangement device is provided, the device comprising: A request acquisition module is configured to acquire an orchestration request and a starting node; wherein the orchestration request includes multiple entities, and the entities are nodes or functions; a request partitioning module configured to insert the start node into the header of the orchestration request to obtain a preprocessed orchestration request, and to partition the preprocessed orchestration request into a plurality of node-entity anchor point pairs; A topology discovery module, configured to capture topology dynamics in a mobile ad hoc network based on a time-constrained recursive topology discovery protocol; wherein the topology dynamics include topology information, functional information, communication information, and performance information; A forest graph construction module is configured to dynamically construct a network forest graph using the topology; wherein the network forest graph is represented as , For nodes, is the communication link between nodes, For function, is a functional link between a node and a function, the communication link between the nodes is weighted by a communication cost, the communication cost is determined according to the topology information and the communication information, and the functional link between the node and the function is weighted by a performance cost, the performance cost is determined according to the function information and the performance information; The orchestration module is configured to determine the optimal segment corresponding to each node-entity anchor point pair based on the mesh forest graph with the goal of minimizing the sum of communication cost and performance cost, and connect the optimal segments to obtain the optimal service function chain.

[0031] According to the third technical solution of the present invention, a mobile self-organizing network service function chain orchestration system is provided, the system comprising: a memory for storing a computer program; a processor for executing the computer program to implement the method as described above.

[0032] According to a fourth technical solution of the present invention, a non-transitory computer-readable storage medium storing instructions is provided. When the instructions are executed by a processor, the method described above is executed.

[0033] The present invention can be used for the functional orchestration of heterogeneous mobile self-organizing nodes in an environment without infrastructure (such as a field area without a base station), where all nodes operate equally and can freely participate in or exit the collaboration based on the orchestration. The main technical effects are: (1) A time-constrained recursive topology discovery mechanism is proposed to quickly discover partial topologies in mobile ad hoc networks.

[0034] (2) A mesh-forest graph is proposed, which is a graph-compatible data structure that can comprehensively accommodate topology, function, communication, and performance information, and dynamically customize the mesh-tree graph according to each required function of the orchestration request to ensure the consistency of the orchestrated service function chain with the actual topology structure.

[0035] (3) An efficient orchestration method is proposed to perform iterative segmented orchestration and splicing, thereby obtaining a service function chain that efficiently traverses the required functions. This method is also highly consistent with the actual topology structure. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 A network forest diagram according to an embodiment of the present invention is shown.

[0037] Figure 2 A schematic diagram of a false link problem of a network forest graph according to an embodiment of the present invention is shown.

[0038] Figure 3 A partial mesh forest diagram of the node itself discovered according to an embodiment of the present invention is shown.

[0039] Figure 4 A partial mesh forest diagram of node merging neighbor discovery according to an embodiment of the present invention is shown.

[0040] Figure 5 A partial mesh forest diagram of node merging secondary neighbor discovery according to an embodiment of the present invention is shown.

[0041] Figure 6 A network tree diagram of f2 according to an embodiment of the present invention is shown.

[0042] Figure 7 A network tree diagram of f5 according to an embodiment of the present invention is shown.

[0043] Figure 8 A network tree diagram of f4 according to an embodiment of the present invention is shown.

[0044] Fig. 9 A structural diagram of a mobile self-organizing network service function chain orchestration device according to an embodiment of the present invention is shown. DETAILED DESCRIPTION

[0045] The following describes the embodiments of the present invention by specific examples, and those skilled in the art can easily understand other advantages and effects of the present invention from the contents disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that the following embodiments and features in the embodiments can be combined with each other without conflict.

[0046] The specific implementation of the present invention is further described in detail below in conjunction with the drawings and examples.

[0047] On-demand on-site orchestration of mobile self-organizing network nodes plays an important role in environments where communication infrastructure is lacking, such as rescue and environmental monitoring. It requires the orchestration of various function combinations into a service function chain (Service Function Chain), whose constituent functions are called in the required order. Service function chain orchestration excludes optimal communication path planning and also involves optimal function selection, so it is a complex dual problem, and it also faces problems such as dynamically changing topological structures under mobile self-organizing networks. In response to the above problems, an embodiment of the present invention provides a mobile self-organizing network service function chain orchestration method for service function chain orchestration of functionally heterogeneous mobile self-organizing nodes in an environment without infrastructure (such as a wild area without a base station). The implementation of this method relies on the time-constrained recursive topology discovery protocol constructed in this embodiment.

[0048] Service function chain orchestration relies heavily on the topology, function, communication, and performance information held by the orchestration node. If the orchestration node only knows the neighbor nodes within its wireless coverage, but does not know the topological connection of more other nodes, the orchestration will be extremely difficult. Therefore, topology discovery is necessary for successful orchestration. The "topology discovery" mentioned in this article will discover the topology, communication, function, and performance information at the same time in the process, the same below. In an environment without heterogeneous infrastructure and protocols, unlike the topology discovery that serves routing purposes, it is neither easy nor necessary to discover the complete topology for mobile self-organizing networks that require agile collaboration. Our goal is to timely orchestrate service function chains that meet functional and performance requirements. The process of quickly discovering partial topologies and efficient orchestration is more practical, especially in a large mobile self-organizing network. To this end, a time-constrained recursive topology discovery protocol (TIRE) is proposed. TIRE has the following characteristics: First, TIRE gradually reduces the time of topology discovery of each downstream node, so that the downstream nodes can feedback the results of topology discovery as early as possible, adapt to the time-varying topology characteristics of mobile self-organizing networks, and ensure the efficiency of topology discovery.

[0049] Second, TIRE can capture the topological dynamics in mobile ad hoc networks in multiple ways (on-demand mode, periodic mode, and hybrid).

[0050] Third, TIRE is designed as an application layer protocol that works according to its topological logic without considering the heterogeneity of network layer protocols.

[0051] Fourth, TIRE designs a two-layer graph data structure so that the discovered topology, functions, communications, performance information, etc. can be accommodated in a unified graph with quantized links, providing a numerical and data structure foundation for the service function chain in mobile ad hoc networks.

[0052] TIRE includes on-demand topology discovery, periodic topology discovery, and hybrid topology discovery.

[0053] In on-demand topology discovery, each node does not obtain network topology information in advance. It only starts the recursive topology discovery process when an orchestration request arrives to capture topology dynamics. The process is as follows: (1) When any node When receiving an orchestration request, it becomes an orchestration node, starts the topology discovery process, generates and broadcasts a topology discovery request ,in Is the global topology discovery timer , the orchestration node is During this period, wait for other nodes to reply to the discovered topology. Request signal for topology discovery; (2) When any node Receive a topology discovery request hour: Immediately reply the node that sent the topology discovery request (called the "previous node") with its own node information and the currently known topology dynamics to improve the timeliness of topology discovery. , contains the key information for constructing a mesh-forest graph: Indicates functional information, representing What functions can be provided? , Indicates whether corresponding functions can be provided, such as camera shooting, image recognition, target tracking, etc. Indicates communication information, representing The various communication quality QoS indicators are recorded as , For the The values ​​of QoS indicators, such as latency, packet loss rate, jitter, bandwidth, etc. Indicates performance information, representing The various performance indicators during function call are recorded as , For the The values ​​of performance indicators such as CPU, RAM, power, reliability, etc. All this information will be used to calculate the communication cost and performance cost to weight the communication link and functional link respectively, and used for the orchestration of the mobile service function chain.

[0054] Set the local topology discovery timer , is a smaller than The amount of time used to characterize the time allowed for wireless round trips and processing, During this period, it waits for other nodes to reply to the discovered topology and broadcasts the forwarding topology discovery request. , transmitted to more possible nodes beyond the signal coverage of the original orchestration node. This ensures that the downstream node always times out with the upstream node first, feeds back the topology discovery result as early as possible, adapts to the time-varying topology characteristics of the mobile ad hoc network, and ensures the efficiency of topology discovery.

[0055] (3) When any node Topology discovery timer time out: If the node It is an orchestration node that starts orchestration on the current topology; If the node Not an orchestration node, go up one node again Reply to newly found topology dynamics To improve the richness of topology discovery; (4) When any node Received from other nodes Topological dynamics of reply When , it merges it with its own topology dynamically, and calculates the communication cost and performance cost to weight the communication link and functional link respectively; It should be noted that according to the above process, the receiving node Restore its topology at the beginning and end Figure 1 The first reply is to ensure the timeliness of topology discovery, and the second reply is to improve the richness of topology discovery. The first reply is optional.

[0056] In periodic topology discovery, any node sets a topology exchange timer regardless of whether it receives an orchestration request. , used for periodic exchange, the process is as follows: (3) When any node Topology discovery timer Timeout, broadcast your own topology , and reset the topology discovery timer ; (2) When any node Received from other nodes Topological dynamics of reply When , it merges it with its own topology dynamically and calculates the communication cost and performance cost; (3) When any node When receiving an orchestration request, it becomes an orchestration node and starts the orchestration on the current topology, because the topology has been discovered periodically in advance; Hybrid topology discovery combines on-demand topology discovery and periodic topology discovery to overcome the shortcomings of running the two modes separately. On-demand topology discovery reflects the real-time status of the current wireless network because the information is obtained in real time. However, it will cause more orchestration delays because the topology discovery is initiated after receiving the orchestration request. On the other hand, periodic topology discovery can shorten the delay before orchestration because the topology discovery is always in progress periodically. However, due to the frequent periodic sending of the topology map, additional bandwidth overhead may be incurred. In addition, it may provide non-real-time or outdated node and link status. Therefore, in addition to on-demand and periodic, TIRE can also be configured as a hybrid, which is also the main loop of TIRE. The TIRE main loop works in a concurrent threaded manner and contains multiple concurrently running threads: Routine on_orchestration_request( ): This is the thread that processes orchestration requests. It is the code shared by on-demand mode and periodic mode. It processes received orchestration requests in real time. In the on-demand mode, the on-demand topology discovery process (including discovery initialization, timer setting, etc.) is triggered. In the periodic mode, the service function chain orchestration is directly triggered.

[0057] Routine on_topo_graph_arrival( , ): This is the thread that processes the arrival of the topology map. It is the code shared by the on-demand mode and the periodic mode. It processes the topology maps transmitted by other nodes in real time, performs the above-mentioned dynamic merging of topologies, and calculates the communication cost and performance cost to weight the communication links and functional links respectively.

[0058] Routine on_topo_exchange_timer( ): This is a thread used only for periodic topology discovery, which starts the periodic topology map broadcast exchange process in the above periodic mode.

[0059] According to TIRE, collect node communication information , calculate the communication cost between nodes, the steps are as follows: Step 101, Representation Node No. QoS indicators Corresponding communication cost. Different conversion methods are used for different QoS indicators, and their goal is to convert QoS indicators into additive costs (i.e., cost, the larger the value, the worse the performance), as shown below: Delay cost: ; Packet loss cost: ; Jitter cost: ; Bandwidth cost: .

[0060] In order to fairly compare different QoS indicators, each single cost Normalize it, that is , to eliminate the impact of different scales and units used by different QoS indicators.

[0061] Step 102, according to the conversion step of step 101, the node is obtained by weighted summation Aggregate communication cost ,in is the weighted value.

[0062] ;

[0063] Step 103: Aggregate communication cost Assigned to the node All egress wireless links are therefore connected through the node The data communication will experience its communication cost .

[0064] For slave nodes To Node Egress wireless link The communication cost Assigned in the following way, .

[0065] Node performance information collected based on TIRE and functional information ,The performance cost of computing nodes and function keys is as follows.

[0066] Step 201, Representation Node No. Performance indicators Corresponding performance cost. Different conversion methods are used for different performance indicators, and their goal is to convert performance indicators into additive costs (i.e., costs, where larger values ​​represent worse performance), as shown below: CPU cost: ; RAM cost: ; Battery cost: ; Availability cost: .

[0067] In order to compare different performance indicators fairly, Normalize it, that is , to eliminate the impact of different scales and units used by different performance indicators.

[0068] Step 202: According to the previous conversion step, the node is obtained by weighted summation. Aggregation performance cost ,in is the weighted value.

[0069] ;

[0070] Step 203, The performance cost is assigned to all its functional links, namely , so through the node Call a function , will experience its performance cost .

[0071] The difference between TIRE and other topology discovery protocols is that it constructs a graph data structure containing topology, function, communication, and performance information. Figure 1 The two-layer mesh forest graph (mesh-forest) shown is denoted by , where the upper white vertices are functions, forming a function tier (in this case, it contains 5 functions), denoted as , the black vertices at the bottom are mobile self-organizing nodes, forming a network tier (in this case, it contains 6 nodes), denoted as Function links (solid lines) between functions and nodes use performance costs To empower, record it as , while the communication links (dashed lines) between mobile ad hoc nodes use the communication cost To empower, record it as . Figure 1 Contains enough information to perform service function chaining. Figure 1 As can be seen in the figure, several nodes providing the same function form a two-layer tree, where the function is the root (white vertices) and the nodes are leaves (black vertices). Obviously, multiple such trees can be found in a mobile ad hoc network, forming a forest. At the same time, the nodes themselves form a flat mesh. Therefore, the discovered topology is a mesh-forest, where the forest provides function and performance information, and the mesh provides topology and communication information.

[0072] The network forest graph contains rich topology, function, communication, and performance information, which is suitable for the orchestration of service function chains. Intuitively, for an orchestration request , the two required functions are described in sections one by one Using the two starting and ending anchor points as the starting and ending anchor points, we find the optimal segments with the lowest communication and performance costs, and then connect these segments together to form the optimal service function chain. This idea is called "function-function segmentation", but there are loopholes in this algorithm logic.

[0073] Since the network forest graph contains communication links , Functional Link If the network forest graph is not properly processed for the two types of links, the functional links may be mistakenly identified as communication links, resulting in the problem of false communication links. Figure 2 As shown, due to the long distance, and However, using the "function-function segmentation" logic and When looking for the optimal segment, the orchestration node intuitively thinks and pass reachable, that is, the functional link is mistaken for a communication link, and then find the two segments separately , , and finally spliced ​​into an incorrect service function chain ,because and It is not physically reachable at all. Therefore, “function-function segmentation” cannot be used for the orchestration of mobile service function chains.

[0074] Logically, since functions are provided by nodes and communication is done between nodes, the service function must provide orchestration requests. A function in , we should find Topological segmentation, that is, a number of consecutive nodes Provides a communication link, where the last node provides a functional link to the . It can be seen that the starting anchor point of such a segment is a node and the ending anchor point is a function, so it is called "node-function segmentation". This requires that each time the shortest path search of "node-function segmentation" is performed, the graph should only contain one function, and other irrelevant functions and their function links should be temporarily deleted to avoid the above-mentioned communication false link problem caused by irrelevant functions and their function links. After processing, such a graph is called a mesh-tree graph, denoted as , the function layer contains only one function and its related functional links , used to find node-function segmentation , so that the service function chain provides functions . And so on, when you need to find When , another network tree diagram is generated , and is used to find topological segments .

[0075] Based on the above description of the basic principles of the method for orchestrating a service function chain in a mobile ad hoc network, the following embodiment will introduce specific steps for orchestrating a service function chain in response to different orchestration requests.

[0076] In one embodiment, when an orchestration request is received When , the service function chain with the following topological configuration is found (where each row represents a node-function segment): ;

[0077] Minimize the total cost of the service function chain, that is, .

[0078] In the case where the received orchestration request only includes functions, the specific steps of the mobile self-organizing network service function chain orchestration method include: Step 301, input parameter preprocessing: Step 3011, obtain input parameters: The algorithm takes two parameters as input, a) the arrangement request , contains multiple functions that must be traversed ; b) The starting node of the service function chain .

[0079] Step 3012, input preprocessing: In order to facilitate node-function segmentation, Insert into the orchestration request The head, that is , and the current pointer points to the first element of the arrangement request, that is, take the pointer .

[0080] Step 302, determine the segment anchor point: Step 3021, determine the starting anchor point.

[0081] when When , the starting anchor point is determined for the first optimal segment to be found, that is, , start choreographing the service function chain from scratch.

[0082] when When , it indicates that the first optimal segment has been found, and it is necessary to find the subsequent optimal segments and connect them one by one to finally form a service function chain. To do this, it is necessary to find the optimal segment based on the previous one. , to determine the starting anchor point for the optimal segment to be found later, and to search for the optimal segment. According to the node-function segmentation rule, The last element is a function (it does not have the ability to forward data in the network), and the second-to-last element is a node (because only nodes can provide functions, so the second-to-last element must be a node, and it has the ability to forward data in the network and can connect different segments). , the starting anchor point of this segment is The second to last element of , obviously is a node.

[0083] Determine the ending anchor point. ,according to The structure, obviously is a function.

[0084] Form segment anchor pairs, .

[0085] Step 303, construct a mesh-tree graph: For the current function Dynamically generate a network tree diagram ,Right now , to avoid other functions and functional links from forming false communication links and other problems, and to ensure the consistency between the orchestration results and the actual topology. The operation will be the current function Keep in In the function layer, other functions are all intersected. Temporarily delete so that , but also makes The irrelevant functional links in the are temporarily deleted.

[0086] Step 304, find the optimal segment and connect: Step 3041, using Dijkstra algorithm in the network tree diagram Found on and The optimal segmentation between .

[0087] Step 3042, splice with the previously found segments to iteratively form a service function chain, that is, .

[0088] Step 3043, use the currently found segment as the start of the next segmentation, that is, .

[0089] Step 3044, start the next iteration, that is ,exist In the case of, jump to step 302, find the next segment and splice it.

[0090] In the above steps, in step 301, the input arrangement request is a list of functions, and this list of functions is divided into node-function anchor pairs through node-function segmentation, that is, arranged by function constraints. However, anchors are not limited to ordered node-function pairs, nodes can also be mixed with functions as input to the algorithm In each iteration of step 302, Segmentation is performed to generate "node-entity" anchors, where "entity" can be a function or a node. This is called "node-entity segmentation", which has multiple variants to meet the diverse requirements of service function chain orchestration for nodes and functions.

[0091] In some embodiments, the orchestration is performed with node constraints, and the input orchestration request is , where each is a node, only the required nodes are specified. This makes the anchor points continuous node-node pairs. The intersection operation in step 303 above No functionality is retained at all, i.e. in the tree diagram , without any functions and function links. Therefore, each iteration of the orchestration process is limited to traversing Each consecutive node in the segment that is the anchor point at the end of the segment , just adjust the corresponding code in step 3021 to , because the last entity of the previous segment It is a node itself and can be used as the starting anchor point of a new segment This variant is suitable for pure routing that does not require traversing any functions, which reflects the applicability of the method proposed in the present invention, and can be used for both service function chain orchestration and traditional routing.

[0092] In some embodiments, the link is orchestrated by constraining both the function and the node, and the input orchestration request is , where each Can be a node or a function. is a node, it forms a node-node pair; when the currently traversed When is a function, it forms a node-function pair. In this way, it limits the traversal of nodes and functions at the same time, and is suitable for complex tasks with the requirement of traversing certain functions and nodes at the same time. Since this algorithm variant needs to traverse certain nodes, it is suitable for tasks that report status to one or more specific nodes (such as the master control node) to implement fine control, which reflects the polymorphism of the method proposed in the present invention.

[0093] In some embodiments, considering that in some application scenarios, due to security vulnerabilities, poor performance, heavy load, etc. of nodes, it is necessary to avoid them during the orchestration process of the service function chain, and it is necessary to mark the nodes to be avoided in the orchestration request. Node avoidance has different granularities. (1) Chain-level avoidance: Nodes are Marked as , so that it can be dynamically removed from the mesh forest during the orchestration process of the entire service function chain, that is, permanently avoided, and restored after the orchestration is completed. (2) Segment-level avoidance: Nodes in Marked as , so that it can be dynamically deleted when searching for the current optimal segment, i.e., temporarily avoided. Since the segment-level avoidance granularity is fine, if some nodes no longer need to be avoided, they can be restored in the iterative search for the next optimal segment.

[0094] The implementation of the above variants benefits from the flexible and fast generation of the network forest graph and the corresponding network tree graph proposed by the present invention.

[0095] The feasibility and advancement of the present invention will be fully illustrated below with reference to specific examples.

[0096] Figures 3 to 5 An example of the topology discovery process using on-demand TIRE is shown. The node that initiates topology discovery. Figure 3 yes The original part of the topology discovered by itself. Due to its wireless coverage, the scale of the topology discovered by itself is small, which is not conducive to the arrangement of the service function chain. Set a timer , multicast a topology discovery request. Neighbor and After receiving the request for topology discovery, recursively perform topology discovery by first sending its existing topology map to , ensure timeliness and set timers for each , forward the topology discovery request and try to discover more topology structures. Timeout, if a new topology is discovered, and Send your topology map to , The newly discovered topology forms a larger topological graph. Figure 4 is the partial topology after merging. And so on, Figure 5 is a partial topology obtained by further merging the topology discovered recursively by the secondary neighbors. Timer If the timeout is exceeded, the recursive topology discovery ends. Figure 5 This is the discovered mesh forest diagram, which will be used for the orchestration of the service function chain later.

[0097] Example 1: Functional Constraint Orchestration is the orchestration node, and receives the orchestration request as , according to the found network forest diagram (such as Figure 5 as shown).

[0098] Step 401, input parameter preprocessing: To facilitate node-function segmentation, Insert into the orchestration request The head, that is , and the current pointer points to the first element of the arrangement request, that is, .

[0099] Step 402, determine the segment anchor point: Step 4021, determine the starting anchor point.

[0100] when When , the starting anchor point is determined for the first optimal segment to be found, that is, , start choreographing the service function chain from scratch.

[0101] Step 4022, determine the end anchor point,

[0102] Step 4023, forming segment anchor point pairs, .

[0103] Step 403, constructing a mesh-tree graph: For the current function Dynamically generate a network tree diagram ,Right now , avoiding the problem of false links formed by other functions and functional links, ensuring the consistency of the orchestration results with the actual topology, and also making The irrelevant functional links in are temporarily deleted, and the resulting network tree diagram is as follows Figure 6 shown.

[0104] Step 404, find the optimal segment and connect: Step 4041, using Dijkstra algorithm in the network tree diagram Found on and The optimal segment between ,like Figure 6 Shown by the dashed line.

[0105] Step 4042, splicing with the previously found segments to iteratively form a service function chain, that is, .

[0106] Step 4043, use the currently found segment as the start of the next segmentation, that is, .

[0107] Step 4044, start the next iteration, i.e. ,exist In the case of, jump to step 4042, find the next segment and splice it. , The corresponding network tree diagram (such as Figures 7 and 8 As shown), find the segment , , and finally spliced ​​into a service function chain: .

[0108] Example 2: Node Constraint Orchestration is the orchestration node, and receives the orchestration request as , according to the found network forest diagram (such as Figure 5 The basic principle and operation process are similar to those in Example 1, so we will not go into details. Finally, we get the service function chain: .

[0109] Example 3: Function and Node Constraint Links is the orchestration node, and receives the orchestration request as , according to the found network forest diagram (such as Figure 5The basic principle and operation process are similar to those in Example 1, so we will not go into details. Finally, we get the service function chain: .

[0110] Example 4: is the orchestration node, and receives the orchestration request as , according to the found network forest diagram (such as Figure 5 The basic principle and operation process are similar to those in Example 1, so we will not go into details. Finally, we get the service function chain: .

[0111] Fig. 9 The structure diagram of a mobile self-organizing network service function chain arrangement device according to an embodiment of the present invention is shown. The embodiment of the present invention also provides a mobile self-organizing network service function chain arrangement device, such as Fig. 9 As shown, the device comprises: The request acquisition module 901 is configured to acquire an orchestration request and a starting node; wherein the orchestration request includes multiple entities, and the entities are nodes or functions; The request partitioning module 902 is configured to insert the start node into the header of the orchestration request to obtain a pre-processed orchestration request, and partition the pre-processed orchestration request into a plurality of node-entity anchor point pairs; A topology discovery module 903 is configured to capture topology dynamics in a mobile ad hoc network based on a time-constrained recursive topology discovery protocol; wherein the topology dynamics include topology information, function information, communication information, and performance information; The forest graph construction module 904 is configured to dynamically construct a network forest graph using the topology; wherein the network forest graph is represented as , For nodes, is the communication link between nodes, For function, is a functional link between a node and a function, the communication link between the nodes is weighted by a communication cost, the communication cost is determined according to the topology information and the communication information, and the functional link between the node and the function is weighted by a performance cost, the performance cost is determined according to the function information and the performance information; The orchestration module 905 is configured to determine the optimal segment corresponding to each node-entity anchor point pair based on the mesh forest graph with the goal of minimizing the sum of communication cost and performance cost, and connect the optimal segments to obtain the optimal service function chain.

[0112] It should be noted that the device described in this embodiment and the method described previously belong to the same technical concept, have the same technical principles, and can achieve the same beneficial effects, so they will not be repeated here.

[0113] An embodiment of the present invention further provides a mobile self-organizing network service function chain orchestration system, the system comprising: a memory for storing a computer program; a processor for executing the computer program to implement the method described in any of the above embodiments.

[0114] An embodiment of the present invention further provides a non-transitory computer-readable storage medium storing instructions, and when the instructions are executed by a processor, the method described in any of the above embodiments is executed.

[0115] The above implementation modes are only used to illustrate the present invention, but not to limit the present invention. Ordinary technicians in the relevant technical field can make various changes and modifications without departing from the spirit and scope of the present invention. Therefore, all equivalent technical solutions also belong to the scope of the present invention.

Claims

1. A method for arranging a mobile self-organizing network service function chain, characterized in that: The method comprises: Obtaining an orchestration request and a starting node; wherein the orchestration request includes multiple entities, and the entities are nodes or functions; Inserting the start node into the header of the orchestration request to obtain a preprocessed orchestration request, and dividing the preprocessed orchestration request into a plurality of node-entity anchor point pairs; Capturing topology dynamics in a mobile ad hoc network based on a time-constrained recursive topology discovery protocol; wherein the topology dynamics include topology information, functional information, communication information, and performance information; The network forest graph is dynamically constructed using the topology; wherein the network forest graph is represented as , For nodes, is the communication link between nodes, For function, is a functional link between a node and a function, the communication link between the nodes is weighted by a communication cost, the communication cost is determined according to the topology information and the communication information, and the functional link between the node and the function is weighted by a performance cost, the performance cost is determined according to the function information and the performance information; Based on the mesh forest graph, with the goal of minimizing the sum of communication cost and performance cost, the optimal segment corresponding to each node-entity anchor point pair is determined, and the optimal service function chain is obtained by connecting the optimal segments.

2. The method for arranging a mobile ad hoc network service function chain according to claim 1, characterized in that: A time-constrained recursive topology discovery protocol is used to capture topology dynamics in mobile ad hoc networks, including: Based on a time-constrained recursive topology discovery protocol, on-demand mode, periodic mode and / or hybrid mode are utilized to capture the topology dynamics in mobile ad hoc networks; In on-demand mode, each node starts the recursive topology discovery process only when an orchestration request arrives to capture topology dynamics. The process is as follows: (1) When any node When receiving an orchestration request, it becomes an orchestration node, starts the topology discovery process, generates and broadcasts a topology discovery request ,in Is the global topology discovery timer , the orchestration node is During this period, wait for other nodes to reply to the discovered topology. Request signal for topology discovery; (2) When any node Receive a topology discovery request hour: Immediately reply the node that sent the topology discovery request with its own node information and the currently known topology dynamics ,in, , Indicates functional information, representing The functionality provided is represented by , Indicates whether the corresponding function can be provided; Indicates communication information, representing The various communication quality QoS indicators are expressed as , For the The value of the QoS indicator; Indicates performance information, representing The various performance indicators during function calls are expressed as , For the The value of the performance indicator; Set the local topology discovery timer , Used to characterize the time allowed for wireless round trip and processing, During this period, it waits for other nodes to reply to the discovered topology and broadcasts the forwarding topology discovery request. ; (3) When any node Topology discovery timer time out: If the node Is the arrangement node, in the current mesh forest graph Start the arrangement on the If the node Not an orchestration node, go up one node again Reply to newly found topology dynamics ; (4) When any node Received from other nodes Topological dynamics of reply When , it merges it with its own topology dynamically, and calculates the communication cost and performance cost to weight the communication link and functional link respectively; In periodic mode, any node sets a topology exchange timer , used for periodic exchange, the process is as follows: (1) When any node Topology discovery timer Timeout, broadcast node Topology , and reset the topology discovery timer ; (2) When any node Received from other nodes Topological dynamics of reply When With Node The topologies are dynamically merged, and the communication cost and performance cost are calculated to weight the communication links and functional links respectively; (3) When any node When receiving an orchestration request, it becomes an orchestration node and Start the arrangement on the In hybrid mode, both on-demand mode and periodic mode are integrated and work in a concurrent thread mode, including the following multiple concurrently running threads: The thread that processes the orchestration request is a code shared by the on-demand mode and the periodic mode. It processes the received orchestration request in real time. In the on-demand mode, the on-demand topology discovery process is triggered, and in the periodic mode, the service function chain orchestration is directly triggered. The thread that processes the topology graph arrival is the code shared by the on-demand mode and the periodic mode. It processes the topology graph transmitted by other nodes in real time and calculates the communication cost and performance cost to weight the communication link and functional link respectively. The periodic topology discovery thread is used only for periodic topology discovery and starts the periodic topology map broadcast exchange process in periodic mode.

3. The method for arranging a mobile ad hoc network service function chain according to claim 2, characterized in that: Inserting the start node into the header of the orchestration request to obtain a preprocessed orchestration request, dividing the preprocessed orchestration request into a plurality of node-entity anchor point pairs, including: The starting node Insert into the header of the orchestration request to obtain the pre-processed orchestration request , the current pointer points to the first element of the arrangement request, take the pointer ,in Indicates entities, Indicates entities, is the total number of entities; when When the starting node As starting anchor point ; when When , according to the previously found optimal segmentation ,by The second-to-last element of is used as the starting anchor point; Determine the end anchor point ; Form a branch node-entity anchor pair, .

4. The method for arranging a mobile ad hoc network service function chain according to claim 3, characterized in that: Based on the mesh forest graph, the optimal segmentation corresponding to each node-entity anchor point pair is determined with the goal of minimizing the sum of the communication cost and the performance cost, including: Based on the mesh forest graph, a mesh tree graph is dynamically generated according to the functions included in the node-entity anchor point pairs; wherein the mesh tree graph only retains the functions included in the node-entity anchor point pairs and the functional links related to the functions, as well as all nodes and communication links in the mesh forest graph.

5. The method for arranging a mobile ad hoc network service function chain according to claim 4, characterized in that: Based on the mesh forest graph, with the goal of minimizing the sum of communication cost and performance cost, the optimal segment corresponding to each node-entity anchor point pair is determined, and the optimal service function chain is obtained by connecting the optimal segments, including: use The algorithm determines the optimal segmentation between the starting anchor point and the ending anchor point in the current node-entity anchor point on the network tree diagram; Connect the optimal segment between the starting anchor point and the ending anchor point in the current node-entity anchor point with the determined optimal segment, and extend the service function chain segment by segment; The currently determined optimal segmentation is used as the starting point of the next segmentation until all node-entity anchor point pairs are determined and connected in sequence to obtain the optimal service function chain.

6. The method for arranging a mobile ad hoc network service function chain according to claim 1, characterized in that: The communication cost is calculated as follows: Get Node No. QoS indicators The corresponding communication cost; Different QoS indicators are converted using the following formula: Delay cost: ; Packet loss rate cost: ; Jitter cost: ; Bandwidth cost: ,in It is the bandwidth reference value, which can be set according to the actual situation; Normalize the converted cost: ； In the formula, represents the normalized communication cost, Indicates the node number, Indicates the total number of nodes; The nodes are calculated by the following formula Aggregate communication cost : ； In the formula, is the weight of each single communication cost, N is the total number of QoS indicators; node To Node Communication Link The communication cost The authority is granted as follows: .

7. The method for arranging a mobile ad hoc network service function chain according to claim 1, characterized in that: The performance cost is calculated as follows: Get Node No. Performance indicators The corresponding performance cost; Different performance indicators are converted using the following formula: CPU cost: ; RAM cost: ; Battery price: ,in It is the battery reference value, which can be set according to the actual situation; Reliability cost: ; The performance cost of the conversion Normalize: ； In the formula, represents the normalized performance cost; The nodes are calculated by the following formula Aggregation performance cost: ； In the formula, is the weight of each single performance cost, is the total number of performance indicators; node To function Functional Link Performance cost The authority is granted as follows: .

8. A mobile self-organizing network service function chain arrangement device, characterized in that: The device: A request acquisition module is configured to acquire an orchestration request and a starting node; wherein the orchestration request includes multiple entities, and the entities are nodes or functions; a request partitioning module configured to insert the start node into the header of the orchestration request to obtain a preprocessed orchestration request, and to partition the preprocessed orchestration request into a plurality of node-entity anchor point pairs; A topology discovery module, configured to capture topology dynamics in a mobile ad hoc network based on a time-constrained recursive topology discovery protocol; wherein the topology dynamics include topology information, functional information, communication information, and performance information; A forest graph construction module is configured to dynamically construct a network forest graph using the topology; wherein the network forest graph is represented as , For nodes, is the communication link between nodes, For function, is a functional link between a function and a node, the communication link between the nodes is weighted by a communication cost, the communication cost is determined according to the topology information and the communication information, and the functional link between the node and the function is weighted by a performance cost, the performance cost is determined according to the function information and the performance information; The orchestration module is configured to determine the optimal segment corresponding to each node-entity anchor point pair based on the mesh forest graph with the goal of minimizing the sum of communication cost and performance cost, and connect the optimal segments to obtain the optimal service function chain.

9. A mobile self-organizing network service function chain arrangement system, characterized by: The system comprises: Memory for storing computer programs; A processor, configured to execute the computer program to implement the method according to any one of claims 1 to 7. 10 . A non-transitory computer-readable storage medium storing instructions, which, when executed by a processor, perform the method according to claim 1 .

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