WO2022142277A1 - 一种通信架构的动态调节方法及系统 - Google Patents

一种通信架构的动态调节方法及系统 Download PDF

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WO2022142277A1
WO2022142277A1 PCT/CN2021/107035 CN2021107035W WO2022142277A1 WO 2022142277 A1 WO2022142277 A1 WO 2022142277A1 CN 2021107035 W CN2021107035 W CN 2021107035W WO 2022142277 A1 WO2022142277 A1 WO 2022142277A1
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energy consumption
partition
node
architecture
terminal
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PCT/CN2021/107035
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English (en)
French (fr)
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刘川
陶静
刘世栋
邢宁哲
郭少勇
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全球能源互联网研究院有限公司
国网冀北电力有限公司信息通信分公司
北京邮电大学
国家电网有限公司
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Publication of WO2022142277A1 publication Critical patent/WO2022142277A1/zh

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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W40/00—Communication routing or communication path finding
    • H04W40/02—Communication route or path selection, e.g. power-based or shortest path routing
    • H04W40/04—Communication route or path selection, e.g. power-based or shortest path routing based on wireless node resources
    • H04W40/10—Communication route or path selection, e.g. power-based or shortest path routing based on wireless node resources based on available power or energy
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W40/00—Communication routing or communication path finding
    • H04W40/02—Communication route or path selection, e.g. power-based or shortest path routing
    • H04W40/20—Communication route or path selection, e.g. power-based or shortest path routing based on geographic position or location
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W52/00—Power management, e.g. TPC [Transmission Power Control], power saving or power classes
    • H04W52/02—Power saving arrangements
    • H04W52/0209—Power saving arrangements in terminal devices
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W84/00—Network topologies
    • H04W84/18—Self-organising networks, e.g. ad-hoc networks or sensor networks
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L67/00—Network arrangements or protocols for supporting network services or applications
    • H04L67/01—Protocols
    • H04L67/10—Protocols in which an application is distributed across nodes in the network
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D30/00—Reducing energy consumption in communication networks
    • Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks

Definitions

  • the present application relates to the field of mobile communication technologies, and in particular, to a method and system for dynamic adjustment of a communication architecture.
  • cloud computing technology Due to the high flexibility, scalability and high performance ratio of cloud computing, cloud computing technology is widely used, but with the development of mobile Internet, such as the rise of AR, VR, high-definition video and real-time services, centralized cloud computing architecture Faced with huge challenges; cloud servers are usually deployed far away from end users, and with the increase in the number of users, cloud computing network bandwidth will be seriously insufficient, and the robustness is poor, so cloud computing network architecture is difficult to meet users' low demand. Latency and the need for high reliability services.
  • 5G, and the Internet of Things people obtain resources and services in the network through various novel wireless terminal devices, and the data of access devices increases in large quantities. With the continuous increase of various types of access devices, services The type must also be upgraded simultaneously.
  • the traditional service architecture of "intelligent terminal-Internet-cloud computing center” Difficult to adapt to the needs of latency-sensitive applications.
  • MEC Mobile Edge Computing
  • SDN Software Defined Networks
  • the MEC-SDN system deploys computing resources, storage resources and network resources to the edge of the Internet closer to users, which improves the resource acquisition speed of users and terminals.
  • the combination of the two realizes the synchronization of network resources, computing resources and storage resources;
  • users will obtain various resources from the nearby MEC-SDN system servers, including computing resources managed by mobile edge computing, storage resources and network resources managed by SDN.
  • the research of mobile edge computing mainly focuses on hardware and architecture, mobile edge computing server deployment, resource virtualization, load balancing, application layer protocols and applications in related fields.
  • the embodiments of the present application provide a method and system for dynamically adjusting a communication architecture, which overcomes the defects of high delay and high energy efficiency from a traditional mobile terminal to a cloud computing platform in the prior art.
  • an embodiment of the present application provides a method for dynamically adjusting a communication architecture, including:
  • the dynamic energy consumption adjustment of the access node path is performed according to the energy consumption of all terminal nodes in the partition;
  • the SDN-based wireless communication network constructs a data dynamic energy consumption adjustment scheme according to the distance between the terminal node and the access node and the dynamic energy consumption of the access node path.
  • the terminal nodes include: common nodes and partitioned nodes; the method further includes: with the support of the SDN architecture, dividing the terminal nodes in the network, and using a clustering mechanism to select the terminal nodes in the network. Some of the nodes are used as partition nodes, and data is forwarded through the partition nodes.
  • the partitioning of the wireless communication network based on the cloud-edge-terminal network architecture, and calculating the energy consumption of all terminal nodes in the partition includes: calculating the energy consumption between the terminal nodes and the edge computing access nodes according to the The distance and the remaining energy of the terminal node are divided into partitions, and the energy consumption of all terminal nodes in the partition is calculated.
  • the energy consumption of the terminal node transmission length 1 in the partition is calculated by the following formula:
  • l r and l f respectively represent the length of the data in the partition node aggregated by the partition node in the partition node i and the length of the data of other partitions fused and forwarded
  • l j represents the length of the data sent by the common terminal node to the partition node
  • d i represents the partition node i
  • d j represents the distance from the common terminal node to the partition node
  • ⁇ fs represents the signal fading coefficient of the signal propagating in free space
  • ⁇ fs and ⁇ mp are the free space propagation attenuation coefficient of the signal and Multipath propagation attenuation coefficient
  • P r is the energy consumption of receiving unit byte of data.
  • the forward data transmission path is not unique, and the SDN controller completes the access node path according to the size of the data volume to be forwarded by the partition node and the remaining energy of the partition node dynamic energy regulation.
  • the energy consumption of partition i is calculated by the following formula:
  • P Ai (l, d) represents the energy consumption of each partition node in partition i, Represents the sum of energy consumption of ordinary nodes in partition j to transmit data.
  • the normal communication of the wireless communication network includes: the maximum communication radius R CH of the partitioned node is not less than a preset multiple of the maximum communication radius R node of the common node.
  • an embodiment of the present application provides a dynamic adjustment system for a communication architecture, including:
  • the network architecture building module is configured to build a cloud-edge-end-based network architecture according to SDN and edge computing architecture;
  • the energy consumption calculation module is configured to partition the wireless communication network based on the cloud-edge-end network architecture, and calculate the energy consumption of all terminal nodes in the partition;
  • the dynamic energy consumption adjustment module is configured to perform dynamic energy consumption adjustment of the access node path according to the energy consumption of all terminal nodes in the partition when the wireless communication network communicates normally;
  • the adjustment scheme generation module is configured as an SDN-based wireless communication network, and constructs a data dynamic energy consumption adjustment scheme according to the distance between the terminal node and the access node and the dynamic energy consumption of the path of the access node.
  • an embodiment of the present application provides a terminal, including: at least one processor, and a memory communicatively connected to the at least one processor, wherein the memory stores a program executable by the at least one processor.
  • the instruction is executed by the at least one processor, so that the at least one processor executes the method for dynamically adjusting the communication architecture according to the first aspect of the embodiments of this application.
  • the embodiments of the present application provide a computer-readable storage medium, where the computer-readable storage medium stores computer instructions, and the computer instructions are used to cause the computer to execute the first aspect of the embodiments of the present application.
  • a dynamic adjustment method for communication architectures is used to cause the computer to execute the first aspect of the embodiments of the present application.
  • the method and system for dynamic adjustment of the communication architecture provided by the present application, according to the SDN and edge computing architecture, build a cloud-edge-terminal based network architecture;
  • the distance between the ingress nodes and the dynamic energy consumption of the access node path are used to construct a data dynamic energy consumption adjustment scheme.
  • the energy consumption of the communication data is calculated, and the communication path is re-planned according to the level of energy consumption, so that the wireless communication network can be implemented with low energy consumption and delay. communication.
  • FIG. 1 is a flowchart of a specific example of a method for dynamic adjustment of a communication architecture provided by an embodiment of the present application
  • FIG. 2 is a schematic diagram of an SDN-based "cloud-side-terminal" wireless communication network architecture of a specific example of a dynamic adjustment method for a communication architecture provided by an embodiment of the present application;
  • FIG. 3 is an MEC architecture diagram of a wireless communication network of a specific example of a method for dynamically adjusting a communication architecture provided by an embodiment of the present application;
  • Fig. 4 is the application scene diagram of a specific example of the dynamic adjustment method of a kind of communication architecture provided by the embodiment of this application;
  • FIG. 5 is a schematic diagram of a wireless communication network partition of a specific example of a dynamic adjustment method of a communication architecture provided by an embodiment of the present application;
  • FIG. 6 is a simulation comparison diagram of response delay of a service without the number of requests provided by the embodiment of the present application.
  • FIG. 7 is a simulation comparison diagram of system energy consumption without the number of requests provided by an embodiment of the present application.
  • FIG. 8 is a block diagram of a dynamic adjustment system of a communication architecture provided by an embodiment of the present application.
  • FIG. 9 is a composition diagram of a specific example of a terminal according to an embodiment of the present application.
  • the terms “installed”, “connected” and “connected” should be understood in a broad sense, for example, it may be a fixed connection or a detachable connection connection, or integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium, or it can be the internal connection of two components, which can be a wireless connection or a wired connection connect.
  • installed should be understood in a broad sense, for example, it may be a fixed connection or a detachable connection connection, or integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium, or it can be the internal connection of two components, which can be a wireless connection or a wired connection connect.
  • communication architecture described in the following embodiments of the present application may also be referred to as “cloud-side-terminal-based communication architecture” or “cloud-side-terminal communication architecture”. ” as an abbreviation.
  • a method for dynamic adjustment of a communication architecture provided by an embodiment of the present application, as shown in FIG. 1 includes the following steps:
  • Step S1 According to the SDN and edge computing architecture, build a cloud-edge-terminal based network architecture.
  • the switches and controllers of the SDN are integrated into the MEC architecture to realize the SDN-MEC architecture.
  • SDN architecture consists of application layer, control layer and data transmission layer;
  • the southbound interface is connected, using the OpenFlow communication protocol, and each edge element in the data transmission layer has a unified communication identifier, such as: switch, AP, this is only an example, not limited to this, in practical applications according to actual needs Select the corresponding edge element.
  • the edge cloud framework in the wireless communication network is mainly composed of MEC and edge access devices, mobile intelligent terminals and cloud data centers.
  • the deployment of MEC equipment is one of the main differences between the "cloud-edge-device" architecture and the traditional cloud computing architecture.
  • the terminal nodes in the network are divided, and then the clustering mechanism is used to select Some nodes in the terminal nodes are used as partition nodes, and data is forwarded through the partition nodes, thereby reducing the energy consumption of common terminal nodes.
  • FIG 4 it is an application scenario diagram of the SDN-based wireless cloud-edge network.
  • an SDN virtual environment composed of Floodlight and mininet is used to build a simulation environment.
  • the specific environment is a PC with a 2.6GHz CPU and 8GB RAM
  • the software environment is a 64-bit simulation tool with Floodlight, Mininet and Iperf. Ubuntu16.04 operating system.
  • Floodlight is the current mainstream SDN controller, with stable and flexible control of SDN network performance.
  • Write an application to call Floodlight's RESTful API to form the application layer use the MEC architecture to build network facilities to form the communication layer, and connect terminal devices to OpenFlow switches to form the node layer.
  • Step S2 Partition the wireless communication network based on the cloud-edge-end network architecture, and calculate the energy consumption of all terminal nodes in the partition.
  • the wireless communication network is partitioned, the nodes in the partition are clustered, and the terminal node at the appropriate point is selected as the partition node, and the other nodes are ordinary nodes.
  • energy consumption of a node The distribution of terminal nodes is uneven, and the energy consumption of different terminal nodes to transmit data is different. Therefore, in the SDN-based "cloud-edge-terminal" network architecture, the distance between the terminal nodes and the edge is calculated. The distance and the remaining energy of the terminal node are divided into partitions, and the terminal nodes in the partition are selected.
  • the wireless communication network is divided into n areas, each area contains common nodes and partition nodes, the nodes that aggregate the data of terminal nodes within its coverage area in the partition are called partition nodes, and the others collect data and forward the data to the regional nodes.
  • the terminal nodes of are called ordinary nodes.
  • the partition node aggregates the data collected by ordinary terminal nodes within the coverage area and fuses the data received and forwarded by other partitions, and then transmits it to the next-hop partition node, and transmits the data to the edge computing node and cloud computing data center through multi-hop In-depth analysis and processing.
  • the wireless communication network and the “cloud-edge” network are connected to each other through edge computing nodes, wherein the network access nodes with edge computing devices
  • the wireless communication network is divided into the first area, and the area farthest from the edge computing node is called the tail area; the data transmission process from the tail area to the first area and then to the edge computing access node is called forward transmission .
  • the energy consumption due to the forward transmission between the first area and the tail area varies with the partition; in addition, the transmission function between ordinary nodes and partition nodes and the distance between them It is related to the amount of transmitted data. Therefore, in an SDN-based wireless communication network, by changing the data transmission path in the wireless network, the energy consumption of the network can be dynamically adjusted.
  • each partition node in partition i mainly includes two parts: the energy consumption of receiving ordinary node data packets (P Rx ) and the energy consumption of fusion forwarding data packets (P Tx ).
  • l r and l f respectively represent the length of the data in the partition node aggregated by the partition node in the partition node i and the length of the data of other partitions fused and forwarded.
  • ⁇ represents the signal fading coefficient of the signal propagating in space, which is ⁇ fs or ⁇ mp ;
  • P r is the energy consumption of receiving unit byte data, which is represented by a constant;
  • d i represents the distance from the partition node i to the next hop The distance between the partition nodes;
  • ⁇ represents the node transmission energy consumption and the signal space propagation attenuation index, the value is 2 or 4, this is only an example, not limited to this, in practical applications, select the corresponding value according to the actual needs;
  • d 0 is the threshold point of the transition of the signal transmission scheme in space, usually within the range of [75, 80] meters.
  • the values of ⁇ fs and ⁇ mp are 13.5pJ/bit/m 2 and 0.0015pJ
  • Step S3 In the case of normal communication in the wireless communication network, dynamic energy consumption adjustment of the access node path is performed according to the energy consumption of all terminal nodes in the partition.
  • the SDN controller collects the terminal and link information of the network to construct a global view of the network, so as to control the network from a global perspective.
  • the maximum communication radius R CH of partitioned nodes is not less than a preset multiple of the maximum communication radius R node of ordinary nodes. Set the multiple to be selected according to actual needs.
  • the maximum communication radius R CH of a partition node is not less than twice the maximum communication radius R node of a common node, that is, R CH ⁇ 2R node .
  • the partition node transmits the aggregated data to the access node of edge computing by selecting different paths for further processing and calculation. In each partition, the larger the partition number, the farther the partition is from the access node of edge computing, and the more energy is consumed during data transmission.
  • the forward data transmission path is not unique.
  • the SDN controller dynamically adjusts the energy consumption of the wireless communication network according to the amount of data to be forwarded by the partitioned nodes and the remaining energy of the partitioned nodes. Therefore, The energy consumption of partition i can be expressed as:
  • the SDN controller completes the dynamic energy consumption adjustment of the access node path according to the amount of data to be forwarded by the partition node and the remaining energy of the partition node.
  • Step S4 In the SDN-based wireless communication network, a data dynamic energy consumption adjustment scheme is constructed according to the distance between the terminal node and the access node and the dynamic energy consumption of the path of the access node.
  • the controller dynamically adjusts the data transmission path, thereby adjusting the energy consumption of data transmission in the network.
  • the number of nodes in a partition of the SDN architecture is determined by the communication distance of the partition, and the network nodes with larger communication distance are relatively few; in order to reduce the energy consumption of the SDN-based cloud-edge network, it is necessary to dynamically adjust the transmission path to improve the use of energy efficiency. Therefore, when the energy consumption is high, the communication path is redeployed; when the receiving node is fixed, the sending node will choose a shorter path to realize communication, so as to complete the dynamic adjustment of the energy consumption of the partition communication distance;
  • the total energy consumption of a network of length l is:
  • the total energy consumption of the network can be further expressed as:
  • l j represents the data length sent by the common node to the partition node
  • d j represents the distance from the common node to the partition node
  • ⁇ fs represents the signal fading coefficient of the signal propagating in free space
  • P r is an energy consumption that represents the received unit byte of data, which is a constant and can be obtained by averaging multiple measurements.
  • the method further includes: calculating the transmission in the wireless communication network according to the constructed dynamic energy consumption adjustment scheme, and calculating the overall transmission delay of the data in combination with edge computing and cloud computing to ensure the service quality of the network.
  • the wireless communication network needs to transmit the data to the cloud computing center through the network access node for centralized processing, which not only increases the data processing delay but also increases the network energy consumption; expressed by the following formula Signal transmission delay:
  • T i represents the processing delay of the data packet in the transmission node, and the speed of signal propagation in space is equal to the speed of light. In order to reduce the computational complexity, the time delay of signal propagation in space is not considered; T n is each data
  • the processing delay of the packet in the terminal node can be obtained by statistical calculation.
  • the network energy reduction is mainly achieved by increasing the number of hops.
  • increasing the delay in applications sensitive to delay will greatly reduce the availability of services.
  • edge computing technology is used to process part of The data reduces the delay problem of data processing, thereby assisting the wireless communication network to reduce the energy consumption of the system. Therefore, under the SDN-MEC network architecture, the real-time problem of user services is improved; in order to reduce the delay of service response, MEC technology is introduced to handle the computing-intensive operations at the edge of the network, and SDN technology is introduced to achieve centralized Control the network and collect global information about the network.
  • MEC equipment is used for processing.
  • the preprocessing result Task pre is sent to the MEC locally or to the cloud computing service platform for decision-making. Since the business response delay in distributed computing is equal to the maximum processing delay of all subtasks, in order to ensure the performance and service quality of the network when serving users, Performance needs to be prioritized. Therefore, it is necessary to reduce the overhead of network energy consumption while meeting user requirements for transmission delay.
  • the total service response delay in the SDN-MEC network architecture is expressed as follows:
  • the service response delay based on the SDN-MEC network architecture can be expressed as:
  • ⁇ i is the best task allocation coefficient.
  • the edge nodes preprocess the service data to reduce the data transmission delay, so as to make up for the increased delay caused by the reduction of energy consumption in the wireless communication network, thereby ensuring the quality of network services. At the same time, the incremental energy consumption of the wireless communication network is reduced.
  • MEC device v1 was selected as a single MEC device.
  • the simulation results of the response delay of the service without the number of requests, when the number of user requests is less than 10, the delay of the SDN-MEC scheme is smaller than that of the cloud computing scheme and the single MEC device scheme, but the three schemes The delay difference is not large; but as the number of users increases, the processing delay in the network also increases.
  • the system energy consumption is not required under the number of requests.
  • the energy consumption in the network also increases continuously.
  • the energy consumption of wireless transmission nodes in the system for processing data also increases, especially the energy consumption of the nodes farthest from the edge computing nodes.
  • the rapidly increasing trend also illustrates this problem.
  • the dynamic adjustment method of the communication architecture provided in the embodiment of the present application, wherein, according to the SDN and the edge computing architecture, a cloud-edge-terminal-based network architecture is constructed; the wireless communication network based on the cloud-edge-terminal network architecture is partitioned, Calculate the energy consumption of all terminal nodes in the partition; in the case of normal communication in the wireless communication network, the dynamic energy consumption adjustment of the access node path is performed according to the energy consumption of all terminal nodes in the partition; SDN-based wireless communication network, according to the terminal The distance between the node and the access node and the dynamic energy consumption of the access node path are used to construct a data dynamic energy consumption adjustment scheme.
  • the energy consumption of the communication data is calculated, and the communication path is re-planned according to the level of energy consumption, so that the wireless communication network can be implemented with low energy consumption and delay. communication.
  • An embodiment of the present application provides a dynamic adjustment system of a communication architecture, as shown in FIG. 8 , including:
  • the network architecture construction module 1 is configured to construct a cloud-edge-terminal based network architecture according to the SDN and edge computing architecture; this module executes the method described in step S1 in Embodiment 1, and details are not repeated here.
  • the energy consumption calculation module 2 is configured to partition the wireless communication network based on the cloud-side-end network architecture, and calculate the energy consumption of all terminal nodes in the partition; this module executes the method described in step S2 in Embodiment 1, in This will not be repeated here.
  • the dynamic energy consumption adjustment module 3 is configured to perform dynamic energy consumption adjustment of the access node path according to the energy consumption of all terminal nodes in the partition when the wireless communication network communicates normally; this module executes step S3 in Embodiment 1 The described method is not repeated here.
  • the adjustment scheme generation module 4 configured as an SDN-based wireless communication network, constructs a data dynamic energy consumption adjustment scheme according to the distance between the terminal node and the access node and the dynamic energy consumption of the path of the access node; this module executes Embodiment 1 The method described in step S4 in the above will not be repeated here.
  • the embodiment of the present application provides a dynamic adjustment system for a communication architecture, and proposes a cloud-edge-terminal-based network architecture based on SDN and edge computing architecture; Partition, calculate the energy consumption of all terminal nodes in the partition; in the case of normal communication in the wireless communication network, according to the energy consumption of all terminal nodes in the partition, perform dynamic energy consumption adjustment of the access node path; SDN-based wireless communication network, According to the distance between the terminal node and the access node and the dynamic energy consumption of the access node path, a data dynamic energy consumption adjustment scheme is constructed.
  • the energy consumption of the communication data is calculated, and the communication path is re-planned according to the level of energy consumption, so that the wireless communication network can be implemented with low energy consumption and delay. communication.
  • An embodiment of the present application provides a terminal, as shown in FIG. 9 , comprising: at least one processor 401, such as a CPU (Central Processing Unit, central processing unit), at least one communication interface 403, a memory 404, and at least one communication bus 402.
  • the communication bus 402 is used to realize the connection and communication between these components.
  • the communication interface 403 may include a display screen (Display) and a keyboard (Keyboard), and the optional communication interface 403 may also include a standard wired interface and a wireless interface.
  • the memory 404 may be a high-speed RAM memory (Random Access Memory, volatile random access memory), or may be a non-volatile memory (non-volatile memory), such as at least one disk memory.
  • the memory 404 can optionally also be at least one storage device located away from the aforementioned processor 401 .
  • the processor 401 may execute the dynamic adjustment method of the communication architecture in Embodiment 1.
  • a set of program codes are stored in the memory 404, and the processor 401 calls the program codes stored in the memory 404 for executing the dynamic adjustment method of the communication architecture in Embodiment 1.
  • the communication bus 402 may be a peripheral component interconnect (PCI for short) bus or an extended industry standard architecture (EISA for short) bus or the like.
  • the communication bus 402 can be divided into an address bus, a data bus, a control bus, and the like. For ease of presentation, only one line is shown in FIG. 9, but it does not mean that there is only one bus or one type of bus.
  • the memory 404 may include volatile memory (English: volatile memory), such as random-access memory (English: random-access memory, abbreviation: RAM); the memory may also include non-volatile memory (English: non-volatile memory) memory), such as flash memory (English: flash memory), hard disk (English: hard disk drive, abbreviation: HDD) or solid-state drive (English: solid-state drive, abbreviation: SSD); the memory 404 may also include the above types combination of memory.
  • the processor 401 may be a central processing unit (English: central processing unit, abbreviation: CPU), a network processor (English: network processor, abbreviation: NP), or a combination of CPU and NP.
  • the memory 404 may include volatile memory (English: volatile memory), such as random-access memory (English: random-access memory, abbreviation: RAM); the memory may also include non-volatile memory (English: non-volatile memory) memory), such as flash memory (English: flash memory), hard disk (English: hard disk drive, abbreviation: HDD) or solid-state drive (English: solid-state drive, abbreviation: SSD); the memory 404 may also include the above types of combination of memory.
  • volatile memory English: volatile memory
  • RAM random-access memory
  • non-volatile memory English: non-volatile memory
  • flash memory English: flash memory
  • hard disk English: hard disk drive, abbreviation: HDD
  • SSD solid-state drive
  • the memory 404 may also include the above types of combination of memory.
  • the processor 401 may be a central processing unit (English: central processing unit, abbreviation: CPU), a network processor (English: network processor, abbreviation: NP), or a combination of CPU and NP.
  • CPU central processing unit
  • NP network processor
  • the processor 401 may further include a hardware chip.
  • the above-mentioned hardware chip may be an application-specific integrated circuit (English: application-specific integrated circuit, abbreviation: ASIC), a programmable logic device (English: programmable logic device, abbreviation: PLD) or a combination thereof.
  • the above-mentioned PLD can be a complex programmable logic device (English: complex programmable logic device, abbreviation: CPLD), field programmable logic gate array (English: field-programmable gate array, abbreviation: FPGA), general array logic (English: generic array logic, abbreviation: GAL) or any combination thereof.
  • memory 404 is also used to store program instructions.
  • the processor 401 can invoke the program instructions to implement the dynamic adjustment method of the communication architecture as in the implementation embodiment 1 of the present application.
  • Embodiments of the present application further provide a computer-readable storage medium, where computer-executable instructions are stored on the computer-readable storage medium, and the computer-executable instructions can execute the dynamic adjustment method of the communication architecture in Embodiment 1.
  • the storage medium may be a magnetic disk, an optical disk, a read-only memory (Read-Only Memory, ROM), a random access memory (Random Access Memory, RAM), a flash memory (Flash Memory), a hard disk (Hard) Disk Drive, abbreviation: HDD) or solid-state drive (Solid-State Drive, SSD), etc.; the storage medium may also include a combination of the above-mentioned types of memories.

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Abstract

本申请公开了一种通信架构的动态调节方法及系统，方法包括: 根据SDN和边缘计算体系结构，构建基于云-边-端的网络架构; 对基于云-边-端的网络架构的无线通信网络进行分区，计算分区内所有终端节点的能耗; 在无线通信网络正常通信的情况下，根据分区内所有终端节点的能耗，进行接入节点路径的动态能耗调节; 基于SDN的无线通信网络，根据终端节点到接入节点之间的距离、接入节点路径的动态能耗，构建数据动态能耗调节方案。通过考虑终端节点到接入节点之间的距离、接入节点路径的动态能耗，计算通信数据能量消耗，并根据能耗高低重新规划通信路径，实现无线通信网络以较低能耗及时延进行通信。

Description

一种通信架构的动态调节方法及系统
相关申请的交叉引用
本申请基于申请号为202011613339.0、申请日为2020年12月30日的中国专利申请提出，并要求该中国专利申请的优先权，该中国专利申请的全部内容在此引入本申请作为参考。
技术领域
本申请涉及移动通信技术领域，具体涉及一种通信架构的动态调节方法及系统。
背景技术
由于云计算的高灵活性、可扩展性及高性比，使得云计算技术被广泛应用，但随着移动互联网的发展，例如AR、VR、高清视频及实时服务的兴起，集中式云计算架构面临着巨大的挑战；云服务器通常部署在远离最终用户的位置，并且随着用户数量的增加，云计算网络带宽将严重不足，并且健壮性较差，因此，云计算网络架构难以满足用户对低延迟和高可靠性服务的需求。随着移动互联网、5G、物联网的不断发展，人们通过各种新颖的无线终端设备获取网络中的资源和服务，接入设备数据海量增加，随着各种接入设备种类的不断增加，服务类型也必须与之同步升级，在物联网“深度感知、互通互联、智慧处理”、即时定位与地图构建、增强现实等应用需求下，传统的“智能终端-互联网-云计算中心”的服务架构难以适应延迟敏感的应用的需求。
因此，移动边缘计算(Mobile Edge Computing，MEC)技术提供在邻近移动终端的无线接入网络基站提供信息服务和云计算资源的技术；软件定义网络(Software Defined Networks，SDN)则提供了网络可编程性，通 过网络功能抽象实现了弹性和动态的网络资源管理，实现了网络可测可控。MEC-SDN系统将计算资源、存储资源和网络资源部署到离用户更近的互联网边缘，提高了用户和终端的资源获取速度，两者的结合实现网络资源与计算资源、存储资源的同步；在未来的移动互联网络中，用户从位置上邻近的MEC-SDN系统服务器获得各种资源，包括移动边缘计算管理的计算资源、存储资源和SDN管理的网络资源。移动边缘计算的研究主要集中于硬件与体系结构、移动边缘计算服务器部署、资源虚拟化、负载均衡、应用层协议与相关领域应用。
MEC系统的研究目前存在以下不足：很多研究给出的特定领域的能效评估方案，但只局限于MEC服务器的能效评估，没有将SDN网络与云计算中心考虑在内。这种局限方案无法针对同时应用MEC服务和云计算服务的跨层应用进行建模和分析；没有提出基于移动终端、边缘计算、云计算架构下具备“完备性、一致性、高效性”的系统能效评估体系；现有的研究工作大部分都简化了终端移动过程中能效动态变化的问题，仅考虑在某一时刻静态条件下的移动终端与边缘计算服务器之间数据传输的能耗。对于基于云计算的无线通信网络及上述不足，存在传统移动终端到云计算平台的高延迟和高能效问题。
发明内容
鉴于此，本申请实施例提供了一种通信架构的动态调节方法及系统，克服了现有技术中传统移动终端到云计算平台的高延迟和高能效的缺陷。
为达到上述目的，本申请实施例提供如下技术方案：
第一方面，本申请实施例提供一种通信架构的动态调节方法，包括：
根据SDN和边缘计算体系结构，构建基于云-边-端的网络架构；
对基于云-边-端的网络架构的无线通信网络进行分区，计算分区内所有终端节点的能耗；
在无线通信网络正常通信的情况下，根据分区内所有终端节点的能耗，进行接入节点路径的动态能耗调节；
基于SDN的无线通信网络，根据终端节点到接入节点之间的距离、接入节点路径的动态能耗，构建数据动态能耗调节方案。
在一些可选实施方式中，所述终端节点包括：普通节点、分区节点；所述方法还包括：在SDN架构的支持下，对网络中的终端节点进行划分，利用分簇机制选择终端节点中的部分节点作为分区节点，数据通过分区节点进行转发数据。
在一些可选实施方式中，所述对基于云-边-端的网络架构的无线通信网络进行分区，计算分区内所有终端节点的能耗，包括：根据终端节点与边缘计算接入节点之间的距离、终端节点的剩余能量进行分区划分，计算分区内所有终端节点的能耗。
在一些可选实施方式中，通过以下公式计算分区内终端节点传输长度为l的能耗：
Figure PCTCN2021107035-appb-000001
其中，l r、l f分别表示分区节点i中分区节点汇聚分区内数据的长度和融合转发其它分区数据的长度，l j表示普通终端节点发送给分区节点的数据长度，d i表示分区节点i距离下一跳的分区节点距离，d j表示普通终端节点到分区节点的距离，ε fs分别表示信号在自由空间传播的信号衰落系数，ε fs和ε mp分别是信号的自由空间传播衰减系数和多径传播衰减系数，P r为接收单位字节数据的能耗。
在一些可选实施方式中，在基于SDN架构的无线通信网络中，数据前向传输路径不唯一，SDN控制器根据分区节点需要转发数据量的大小及分 区节点的剩余能量，完成接入节点路径的动态能耗调节。
在一些可选实施方式中，通过以下公式计算分区i的能耗：
Figure PCTCN2021107035-appb-000002
其中，P Ai(l，d)表示分区i中每个分区节点的能耗，
Figure PCTCN2021107035-appb-000003
表示分区j中普通节点传输数据的能耗和。
在一些可选实施方式中，无线通信网络正常通信，包括：分区节点的最大通信半径R CH不小于普通节点最大通信半径R node的预设倍数。
第二方面，本申请实施例提供一种通信架构的动态调节系统，包括：
网络架构构建模块，配置为根据SDN和边缘计算体系结构，构建基于云-边-端的网络架构；
能耗计算模块，配置为对基于云-边-端的网络架构的无线通信网络进行分区，计算分区内所有终端节点的能耗；
动态能耗调节模块，配置为在无线通信网络正常通信的情况下，根据分区内所有终端节点的能耗，进行接入节点路径的动态能耗调节；
调节方案生成模块，配置为基于SDN的无线通信网络，根据终端节点到接入节点之间的距离、接入节点路径的动态能耗，构建数据动态能耗调节方案。
第三方面，本申请实施例提供一种终端，包括：至少一个处理器，以及与所述至少一个处理器通信连接的存储器，其中，所述存储器存储有可被所述至少一个处理器执行的指令，所述指令被所述至少一个处理器执行，以使所述至少一个处理器执行本申请实施例第一方面所述的通信架构的动态调节方法。
第四方面，本申请实施例提供一种计算机可读存储介质，所述计算机可读存储介质存储有计算机指令，所述计算机指令用于使所述计算机执行本申请实施例第一方面所述的通信架构的动态调节方法。
本申请技术方案，至少具有如下优点：
本申请提供的通信架构的动态调节方法及系统，根据SDN和边缘计算体系结构，构建基于云-边-端的网络架构；对基于云-边-端的网络架构的无线通信网络进行分区，计算分区内所有终端节点的能耗；在无线通信网络正常通信的情况下，根据分区内所有终端节点的能耗，进行接入节点路径的动态能耗调节；基于SDN的无线通信网络，根据终端节点到接入节点之间的距离、接入节点路径的动态能耗，构建数据动态能耗调节方案。通过考虑终端节点到接入节点之间的距离、接入节点路径的动态能耗，计算通信数据能量消耗，并根据能耗高低重新规划通信路径，实现无线通信网络以较低能耗及时延进行通信。
附图说明
此处的附图被并入说明书中并构成本说明书的一部分，示出了符合本公开的实施例，并与说明书一起用于解释本公开的原理。
为了更清楚地说明本申请具体实施方式或现有技术中的技术方案，下面将对具体实施方式或现有技术描述中所需要使用的附图作简单地介绍，显而易见地，下面描述中的附图是本申请的一些实施方式，对于本领域普通技术人员来讲，在不付出创造性劳动的前提下，还可以根据这些附图获得其他的附图。
图1为本申请实施例提供的一种通信架构的动态调节方法的一个具体示例的流程图；
图2为本申请实施例提供的一种通信架构的动态调节方法的一个具体示例的基于SDN的“云-边-端”无线通信网络体系架构图；
图3为本申请实施例提供的一种通信架构的动态调节方法的一个具体示例的无线通信网络的MEC体系架构图；
图4为本申请实施例提供的一种通信架构的动态调节方法的一个具体 示例的应用场景图；
图5为本申请实施例提供的一种通信架构的动态调节方法的一个具体示例的无线通信网络分区示意图；
图6为本申请实施例提供的不用请求数量下服务的响应时延仿真对比图；
图7为本申请实施例提供的不用请求数量下的系统能耗仿真对比图；
图8为本申请实施例提供的一种通信架构的动态调节系统的模块组成图；
图9为本申请实施例提供的一种终端一个具体示例的组成图。
具体实施方式
下面将结合附图对本申请的技术方案进行清楚、完整地描述，显然，所描述的实施例是本申请一部分实施例，而不是全部的实施例。基于本申请中的实施例，本领域普通技术人员在没有做出创造性劳动前提下所获得的所有其他实施例，都属于本申请保护的范围。
在本申请的描述中，需要说明的是，术语“中心”、“上”、“下”、“左”、“右”、“竖直”、“水平”、“内”、“外”等指示的方位或位置关系为基于附图所示的方位或位置关系，仅是为了便于描述本申请和简化描述，而不是指示或暗示所指的装置或元件必须具有特定的方位、以特定的方位构造和操作，因此不能理解为对本申请的限制。此外，术语“第一”、“第二”、“第三”仅用于描述目的，而不能理解为指示或暗示相对重要性。
在本申请的描述中，需要说明的是，除非另有明确的规定和限定，术语“安装”、“相连”、“连接”应做广义理解，例如，可以是固定连接，也可以是可拆卸连接，或一体地连接；可以是机械连接，也可以是电连接；可以是直接相连，也可以通过中间媒介间接相连，还可以是两个元件内部的连通，可以是无线连接，也可以是有线连接。对于本领域的普通技术人员而 言，可以具体情况理解上述术语在本申请中的具体含义。
此外，下面所描述的本申请不同实施方式中所涉及的技术特征只要彼此之间未构成冲突就可以相互结合。
需要说明的是，本申请以下实施例中描述的“通信架构”也可以称为“基于云-边-端的通信架构”或者“云-边-端通信架构”，为便于描述，以“通信架构”作为简称进行说明。
实施例1
本申请实施例提供的一种通信架构的动态调节方法，如图1所示，包括如下步骤：
步骤S1：根据SDN和边缘计算体系结构，构建基于云-边-端的网络架构。
在本申请实施例中，根据移动边缘计算(Mobile Edge Computing，MEC)体系架构和SDN体系结构特点，将SDN的交换机和控制器融入MEC架构中，实现SDN-MEC体系结构。如图2所示，构建基于SDN的“云-边-端”无线通信网络架构体系，具体过程如下：SDN体系结构由应用层、控制层和数据传输层组成；控制层和数据传输层通过SDN南向接口相连，采用OpenFlow通信协议，在数据传输层中每个边缘元素都具有统一的通信标识，如：交换机、AP，仅以此举例，不以此为限，在实际应用中根据实际需求选择相应的边缘元素。如图3所示，无线通信网络中的边缘云框架主要由MEC及边缘接入设备、移动智能终端和云数据中心组成。MEC设备的部署是“云-边-端”体系结构与传统云计算体系结构之间的主要区别之一，在SDN架构的支持下，对网络中的终端节点进行划分，然后利用分簇机制选择终端节点中的部分节点作为分区节点，数据通过分区节点进行转发数据，从而减少普通终端节点的能耗。如图4所示，为基于SDN的无线云边网络应用场景图。
在一具体实施例中，使用Floodlight和mininet组成的SDN虚拟环境搭 建仿真环境，具体环境是一台具有2.6GHz CPU和8GB RAM的PC，该软件环境是具有Floodlight，Mininet和Iperf仿真工具的64位ubuntu16.04操作系统。其中，Floodlight是当前主流的SDN控制器，具有稳定且易于灵活控制SDN网络的性能。编写应用程序调用Floodlight的RESTfulAPI组成应用层，使用MEC架构搭建网络设施组成通信层，终端设备接入OpenFlow交换机组成节点层。
步骤S2：对基于云-边-端的网络架构的无线通信网络进行分区，计算分区内所有终端节点的能耗。
在本申请实施例中，如图5所示，对无线通信网络进行分区，对分区内的节点进行分簇并选择合适点的终端节点作为分区节点，其他节点则为普通节点，计算分区内各种节点的能耗。终端节点的分布是不均匀的，且不同终端节点传输数据的能耗是不相同的，因此，在基于SDN的“云-边-端”网络架构中，根据终端节点距离边缘计算接入节点的距离、终端节点的剩余能量进行分区划分，并对分区内的终端节点进行选择。将无线通信网划分成n个区域，每个区域中都包含有普通节点和分区节点，分区内汇聚其覆盖范围内终端节点数据的节点称为分区节点，其它采集数据并将数据转发给区域节点的终端节点被称为普通节点。分区节点汇聚覆盖范围内普通终端节点采集的数据与接收到其它分区转发的数据进行融合，然后再传输给下一跳分区节点，通过多跳方式将数据传输到边缘计算节点和云计算数据中心进行深入的分析和处理。
在本申请实施例中，基于SDN架构的“云-边-端”网络架构，无线通信网络与“云-边”网络通过边缘计算节点进行相互连接，其中带有边缘计算设备的网络接入节点所在的无线通信网络分区为第1区域，而离边缘计算节点最远的区域被称为尾部区域；从尾部区域到第1区域再到边缘计算接入节点的数据传输过程被称为前向传输。在分布式的无线通信网络中，由于第1区域和尾部区域之间前向传输的能耗随着分区的变化而变化；另 外，普通节点和分区节点之间的传输功能与它们之间的距离以及传输数据量的大小有关，因此，在基于SDN的无线通信网络中，通过改变无线网络中数据的传输路径，可以动态调节网络的能耗。
无线通信网络经过区域划分和分簇以后，分区节点将汇聚区域范围内其它终端节点的数据并将它们转发到其它分区的分区节点进程前向传输。在分区i中每个分区节点的能耗主要包括两部分：接收普通节点数据包的能耗(P Rx)和融合转发数据包的能耗(P Tx)。
Figure PCTCN2021107035-appb-000004
其中，l r、l f分别表示分区节点i中分区节点汇聚分区内数据的长度和融合转发其它分区数据的长度。ε表示信号在空间中传播的信号衰落系数，取值为ε fs或者ε mp；P r是一个表示接收单位字节数据的能耗，用一个常数表示；d i表示分区节点i距离下一跳的分区节点距离；δ表示节点传输能耗与信号空间传播衰减指数，取值为2或4，仅以此举例，不以此为限，在实际应用中，根据实际需求选择相应的数值；d 0为信号在空间中传输方案转折的阈值点，通常取值在[75,80]米的区间范围内。ε fs和ε mp的取值分别为13.5pJ/bit/m 2和0.0015pJ/bit/m 4。
普通节点传输数据的能耗表示为：
Figure PCTCN2021107035-appb-000005
其中，l j表示普通节点发送给分区节点的数据长度；d j表示普通节点到分区节点的距离；ε fs分别表示信号在自由空间传播的信号衰落系数；ε fs和ε mp分别是信号的自由空间传播衰减系数和多径传播衰减系数。
步骤S3：在无线通信网络正常通信的情况下，根据分区内所有终端节点的能耗，进行接入节点路径的动态能耗调节。
在本申请实施例中，在每个区域内，无论无线网络的终端节点通过哪条无线前向传输链路将数据发送到边缘计算网络，边缘计算网络的接入节点接收到的数据总量都是一样的。在基于SDN体系结构的无线通信网络中，SDN控制器采集网络的终端和链路信息构建网络的全局视图，从而从全局的角度实现对网络的控制。在每个区域内，为了确保无线网络中的所有终端节点都能够稳定的接入到边缘计算网络中，分区节点的最大通信半径R CH不小于普通节点最大通信半径R node的预设倍数，预设倍数根据实际需求进行相应选择，例如，分区节点的最大通信半径R CH不小于普通节点最大通信半径R node的2倍，即考虑R CH≥2R node。在保证网络能够正常通信的情况下，分区节点通过选择不同的路径将汇聚数据传输到边缘计算的接入节点中，进行进一步的处理和计算。在每个分区中，分区号越大表示分区离边缘计算的接入节点的距离越远，在数据传输过程中消耗的能量也就越多。
在基于SDN架构的无线通信网络中，数据前向传输路径并不是唯一的，SDN控制器根据分区节点需要转发数据量的大小及分区节点的剩余能量，动态调整无线通信网络的能耗，因此，分区i的能耗可以表示为：
Figure PCTCN2021107035-appb-000006
SDN控制器根据分区节点需要转发数据量的大小及分区节点的剩余能量，完成接入节点路径的动态能耗调节。
步骤S4：基于SDN的无线通信网络，根据终端节点到接入节点之间的距离、接入节点路径的动态能耗，构建数据动态能耗调节方案。
在本申请实施例中，基于SDN的无线通信网络，控制器动态调整数据的传输路径，从而调整网络中数据传输的能耗。SDN体系结构分区中的节点数由分区的通信距离决定，通信距离较大的网络节点相对较少；为了减 少基于SDN的云边网络能耗，需要对传输路径进行动态调整，从而提高能量的使用效率。因此，当能耗较高时，重新部署通信路径；当接收节点固定时，发送节点将选择一条较短的路径来实现通信，从而完成分区通信距离能耗的动态调整；无线通信网络中传输总长度为l的网络总能耗为：
Figure PCTCN2021107035-appb-000007
网络的总能耗可以近一步表示为：
Figure PCTCN2021107035-appb-000008
其中，l j表示普通节点发送给分区节点的数据长度；d j表示普通节点到分区节点的距离；ε fs分别表示信号在自由空间传播的信号衰落系数；ε fs和ε mp分别是信号的自由空间传播衰减系数和多径传播衰减系数；P r是一个表示接收单位字节数据的能耗，它是一个常数，可以通过多次测量求平均值获得。
在本申请实施例中，还包括：根据构建的动态能耗调节方案，计算无线通信网络中的传输，并结合边缘计算和云计算，计算数据整体的传输时延，来保障网络的服务质量。
在传统的云计算网络中，无线通信网络需要通过网络接入节点将数据传输到云计算中心进行集中处理，处理中不仅增加了处理数据的时延同时还将增加网络能耗；通过以下公式表示信号的传输时延：
Figure PCTCN2021107035-appb-000009
其中，T i表示数据包在传输节点中的处理时延，信号在空间中传播的速度等于光速，为了降低计算的复杂度，不考虑信号在空间中传播的时延；T n为每个数据包在终端节点中的处理时延，可以通过统计计算获得。
在不考虑时延的情况下，网络降低能耗主要通过增加跳数来实现，但是对时延敏感的应用增加时延将会极大降低服务的可用性，为此，通过使用边缘计算技术处理部分数据减少数据处理的时延问题，从而协助无线通信网络来降低系统的能耗。因此，在SDN-MEC网络体系架构下，对用户服务实时性的问题进行改善；为了减少业务响应的延迟，引入了MEC技术来处理网络边缘的计算密集型操作，同时，引入SDN技术来实现集中控制网络，并收集网络的全局信息。在应用场景中，考虑由k个MEC设备组成的软件定义的云边缘计算体系结构，其网络拓扑使用G＝(V,E)进行表示，V是节点集，E是边缘集。因此V＝{v 1,v 2,...,v k,S,C}，其中，v i是MEC设备，k为设备数量，S为SDN控制器，C为云计算服务平台；边缘集可用
Figure PCTCN2021107035-appb-000010
表示；
Figure PCTCN2021107035-appb-000011
表示节点v i和v j之间的通信链接；
Figure PCTCN2021107035-appb-000012
表示节点v i和v j的延迟。
在业务执行过程中，MEC设备接收到的业务首先被划分为多个子任务，并满足Task i＝δ iTask，其中δ i为子任务在总Task中所占的比例，然后将任务卸载到每个子任务中，利用MEC设备进行处理。将预处理结果Task pre在MEC本地或者发送到云计算服务平台进行决策，由于分布式计算中的业务响应延迟等于所有子任务的最大处理延迟，为了保证网络在服务用户时的性能以及服务质量，需要优先考虑性能，因此，需要在满足用户对传输时延的需求下，减少网络能耗的开销，SDN-MEC网络体系结构中的总业务响应延迟表示如下：
Figure PCTCN2021107035-appb-000013
其中，
Figure PCTCN2021107035-appb-000014
为MEC设备v i中子任务Task i的计算时间，δ i为最佳的任务分配系数，
Figure PCTCN2021107035-appb-000015
表示节点v i与v j的延迟，
Figure PCTCN2021107035-appb-000016
表示节点v i与v j的子任务分配 关系；当m＝1时，子任务分配关系存在，当m＝0时，子任务分配关系不存在；
Figure PCTCN2021107035-appb-000017
表示在云上匹配和识别预处理结果的延迟；
Figure PCTCN2021107035-appb-000018
表示将预处理结果发送到云服务器时的通信延迟。
为了优化业务响应的延迟并实现使业务响应的延迟最小化的目的，需要一组最佳的任务分配系数δ i，基于SDN-MEC网络架构的业务响应时延可以表示为：
Figure PCTCN2021107035-appb-000019
Figure PCTCN2021107035-appb-000020
Figure PCTCN2021107035-appb-000021
Figure PCTCN2021107035-appb-000022
其中，δ i为最佳的任务分配系数。
Figure PCTCN2021107035-appb-000023
表示节点v i与v j的子任务分配关系。在SDN-MEC架构中，通过边缘节点对业务数据进行预处理来降低数据的传输时延，从而来弥补无线通信网络中降低能耗所带来的时延增加问题，从而在保证网络服务质量的同时降低无线通信网络增体能耗。
通过比较：SDN-MEC方案，传统云计算方案和无边缘调节的MEC方案的网络能耗以及时延等指标。在仿真中，将MEC设备v1选择为单个MEC设备。如图6所示，不用请求数量下服务的响应时延仿真结果，当用户请求数小于10时，SDN-MEC方案的时延小于云计算方案和单个MEC设备方案的时延，但三种方案的时延差不大；但是随着用户数量的增加，网络中的处理时延也随之增加。
在一具体实施例中，如图7所示，不用请求数量下的系统能耗，在仿真模拟环境中，随着用户数量的增加，网络中的能耗也不断的增加。随着用户数量增加，系统中的无线传输节点处理数据的能耗也不断增加，尤其 是距离边缘计算节点最远的节点能耗也随着攀升，图中随着用户请求数量的增加，能耗快速增加的变化趋势也说明了此问题。通过对比三种不同传输方案，结合图6可以得出以下结论，本申请实施例所提的方案能够在调节传输时延的同时降低无线通信网络的整体能耗，同时也表明了本申请实施例的有效性。
本申请实施例中提供的通信架构的动态调节方法，其中，根据SDN和边缘计算体系结构，构建基于云-边-端的网络架构；对基于云-边-端的网络架构的无线通信网络进行分区，计算分区内所有终端节点的能耗；在无线通信网络正常通信的情况下，根据分区内所有终端节点的能耗，进行接入节点路径的动态能耗调节；基于SDN的无线通信网络，根据终端节点到接入节点之间的距离、接入节点路径的动态能耗，构建数据动态能耗调节方案。通过考虑终端节点到接入节点之间的距离、接入节点路径的动态能耗，计算通信数据能量消耗，并根据能耗高低重新规划通信路径，实现无线通信网络以较低能耗及时延进行通信。
实施例2
本申请实施例提供一种通信架构的动态调节系统，如图8所示，包括：
网络架构构建模块1，配置为根据SDN和边缘计算体系结构，构建基于云-边-端的网络架构；此模块执行实施例1中的步骤S1所描述的方法，在此不再赘述。
能耗计算模块2，配置为对基于云-边-端的网络架构的无线通信网络进行分区，计算分区内所有终端节点的能耗；此模块执行实施例1中的步骤S2所描述的方法，在此不再赘述。
动态能耗调节模块3，配置为在无线通信网络正常通信的情况下，根据分区内所有终端节点的能耗，进行接入节点路径的动态能耗调节；此模块执行实施例1中的步骤S3所描述的方法，在此不再赘述。
调节方案生成模块4，配置为基于SDN的无线通信网络，根据终端节 点到接入节点之间的距离、接入节点路径的动态能耗，构建数据动态能耗调节方案；此模块执行实施例1中的步骤S4所描述的方法，在此不再赘述。
本申请实施例提供一种通信架构的动态调节系统，提出了一种根据SDN和边缘计算体系结构，构建基于云-边-端的网络架构；对基于云-边-端的网络架构的无线通信网络进行分区，计算分区内所有终端节点的能耗；在无线通信网络正常通信的情况下，根据分区内所有终端节点的能耗，进行接入节点路径的动态能耗调节；基于SDN的无线通信网络，根据终端节点到接入节点之间的距离、接入节点路径的动态能耗，构建数据动态能耗调节方案。通过考虑终端节点到接入节点之间的距离、接入节点路径的动态能耗，计算通信数据能量消耗，并根据能耗高低重新规划通信路径，实现无线通信网络以较低能耗及时延进行通信。
实施例3
本申请实施例提供一种终端，如图9所示，包括：至少一个处理器401，例如CPU(Central Processing Unit，中央处理器)，至少一个通信接口403，存储器404，至少一个通信总线402。其中，通信总线402用于实现这些组件之间的连接通信。其中，通信接口403可以包括显示屏(Display)、键盘(Keyboard)，可选通信接口403还可以包括标准的有线接口、无线接口。存储器404可以是高速RAM存储器(Random Access Memory，易挥发性随机存取存储器)，也可以是非易失性存储器(non-volatile memory)，例如至少一个磁盘存储器。存储器404可选的还可以是至少一个位于远离前述处理器401的存储装置。其中处理器401可以执行实施例1中的通信架构的动态调节方法。存储器404中存储一组程序代码，且处理器401调用存储器404中存储的程序代码，以用于执行实施例1中的通信架构的动态调节方法。其中，通信总线402可以是外设部件互连标准(peripheral component interconnect，简称PCI)总线或扩展工业标准结构(extended industry standard architecture，简称EISA)总线等。通信总线402可以分为地址总线、数据 总线、控制总线等。为便于表示，图9中仅用一条线表示，但并不表示仅有一根总线或一种类型的总线。其中，存储器404可以包括易失性存储器(英文：volatile memory)，例如随机存取存储器(英文：random-access memory，缩写：RAM)；存储器也可以包括非易失性存储器(英文：non-volatile memory)，例如快闪存储器(英文：flash memory)，硬盘(英文：hard disk drive，缩写：HDD)或固降硬盘(英文：solid-state drive，缩写：SSD)；存储器404还可以包括上述种类的存储器的组合。其中，处理器401可以是中央处理器(英文：central processing unit，缩写：CPU)，网络处理器(英文：network processor，缩写：NP)或者CPU和NP的组合。
其中，存储器404可以包括易失性存储器(英文：volatile memory)，例如随机存取存储器(英文：random-access memory，缩写：RAM)；存储器也可以包括非易失性存储器(英文：non-volatile memory)，例如快闪存储器(英文：flash memory)，硬盘(英文：hard disk drive，缩写：HDD)或固态硬盘(英文：solid-state drive，缩写：SSD)；存储器404还可以包括上述种类的存储器的组合。
其中，处理器401可以是中央处理器(英文：central processing unit，缩写：CPU)，网络处理器(英文：network processor，缩写：NP)或者CPU和NP的组合。
其中，处理器401还可以进一步包括硬件芯片。上述硬件芯片可以是专用集成电路(英文：application-specific integrated circuit，缩写：ASIC)，可编程逻辑器件(英文：programmable logic device，缩写：PLD)或其组合。上述PLD可以是复杂可编程逻辑器件(英文：complex programmable logic device，缩写：CPLD)，现场可编程逻辑门阵列(英文：field-programmable gate array，缩写：FPGA)，通用阵列逻辑(英文：generic array logic,缩写：GAL)或其任意组合。
可选地，存储器404还用于存储程序指令。处理器401可以调用程序 指令，实现如本申请执行实施例1中的通信架构的动态调节方法。
本申请实施例还提供一种计算机可读存储介质，计算机可读存储介质上存储有计算机可执行指令，该计算机可执行指令可执行实施例1中的通信架构的动态调节方法。其中，所述存储介质可为磁碟、光盘、只读存储记忆体(Read-Only Memory，ROM)、随机存储记忆体(Random Access Memory，RAM)、快闪存储器(Flash Memory)、硬盘(Hard Disk Drive，缩写：HDD)或固态硬盘(Solid-State Drive，SSD)等；所述存储介质还可以包括上述种类的存储器的组合。
显然，上述实施例仅仅是为清楚地说明所作的举例，而并非对实施方式的限定。对于所属领域的普通技术人员来说，在上述说明的基础上还可以做出其它不同形式的变化或变动。这里无需也无法对所有的实施方式予以穷举。而由此所引申出的显而易见的变化或变动仍处于本申请创造的保护范围之中。

Claims (10)

  1. 一种通信架构的动态调节方法，包括：
    根据软件定义网络SDN和边缘计算体系结构，构建基于云-边-端的网络架构；
    对基于云-边-端的网络架构的无线通信网络进行分区，计算分区内所有终端节点的能耗；
    在无线通信网络正常通信的情况下，根据分区内所有终端节点的能耗，进行接入节点路径的动态能耗调节；
    基于SDN的无线通信网络，根据终端节点到接入节点之间的距离、接入节点路径的动态能耗，构建数据动态能耗调节方案。
  2. 根据权利要求1所述的通信架构的动态调节方法，其中，所述终端节点包括：普通节点、分区节点；所述方法还包括：
    在SDN架构的支持下，对网络中的终端节点进行划分，利用分簇机制选择终端节点中的部分节点作为分区节点，数据通过分区节点进行转发数据。
  3. 根据权利要求1所述的通信架构的动态调节方法，其中，所述对基于云-边-端的网络架构的无线通信网络进行分区，计算分区内所有终端节点的能耗，包括：
    根据终端节点与边缘计算接入节点之间的距离、终端节点的剩余能量进行分区划分，计算分区内所有终端节点的能耗。
  4. 根据权利要求3所述的通信架构的动态调节方法，其中，通过以下公式计算分区内终端节点传输长度为l的能耗：
    Figure PCTCN2021107035-appb-100001
    其中，l r、l f分别表示分区节点i中分区节点汇聚分区内数据的长度和融合转发其它分区数据的长度，l j表示普通终端节点发送给分区节点的数据长度，d i表示分区节点i距离下一跳的分区节点距离，d j表示普通终端节点到分区节点的距离，ε fs分别表示信号在自由空间传播的信号衰落系数，ε fs和ε mp分别是信号的自由空间传播衰减系数和多径传播衰减系数，P r为接收单位字节数据的能耗。
  5. 根据权利要求1所述的通信架构的动态调节方法，其中，在基于SDN架构的无线通信网络中，数据前向传输路径不唯一，SDN控制器根据分区节点需要转发数据量的大小及分区节点的剩余能量，完成接入节点路径的动态能耗调节。
  6. 根据权利要求5所述的通信架构的动态调节方法，其中，通过以下公式计算分区i的能耗：
    Figure PCTCN2021107035-appb-100002
    其中，P Ai(l，d)表示分区i中每个分区节点的能耗，
    Figure PCTCN2021107035-appb-100003
    表示分区j中普通节点传输数据的能耗和。
  7. 根据权利要求1所述的通信架构的动态调节方法，其中，无线通信网络正常通信，包括：分区节点的最大通信半径R CH不小于普通节点最大通信半径R node的预设倍数。
  8. 一种通信架构的动态调节系统，包括：
    网络架构构建模块，配置为根据SDN和边缘计算体系结构，构建基于云-边-端的网络架构；
    能耗计算模块，配置为对基于云-边-端的网络架构的无线通信网络进行分区，计算分区内所有终端节点的能耗；
    动态能耗调节模块，配置为在无线通信网络正常通信的情况下，根 据分区内所有终端节点的能耗，进行接入节点路径的动态能耗调节；
    调节方案生成模块，配置为基于SDN的无线通信网络，根据终端节点到接入节点之间的距离、接入节点路径的动态能耗，构建数据动态能耗调节方案。
  9. 一种终端，包括：至少一个处理器，以及与所述至少一个处理器通信连接的存储器，其中，所述存储器存储有可被所述至少一个处理器执行的指令，所述指令被所述至少一个处理器执行，以使所述至少一个处理器执行权利要求1-7任一所述的通信架构的动态调节方法。
  10. 一种计算机可读存储介质，所述计算机可读存储介质存储有计算机指令，所述计算机指令用于使所述计算机执行权利要求1-7任一所述的通信架构的动态调节方法。
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