Edge computing service detection method

Abstract

The invention discloses an edge computing service detection method. The method comprises the steps that operation and maintenance personnel configure a service detection strategy in a fixed center; the maneuvering center receives and executes the service detection strategy, and detects the edge computing service availability of each service node; and the fixed center node gathers and processes the received service information of each node. Compared with the prior art, the method has the advantages that the service state is detected by adopting different strategies, the edge computing service availability and access range of each service node can be evaluated in real time, and cross-node edge computing service unified access is provided for business. According to the method provided by the invention, the operation of service detection is simplified, and the perception and management of the edge computing service state can be more efficiently realized.

Description

Technical Field

[0001] The present invention belongs to the field of computer technology, and in particular to an edge computing service detection method. Background Art

[0002] With the rapid development of edge computing technology, more and more application scenarios, especially tactical edge environments and industrial Internet, rely on edge computing nodes to provide low-latency, high-reliability computing services. However, edge computing nodes are usually distributed at the edge of the network and often face challenges such as limited bandwidth, large network fluctuations, and frequent changes in node locations. In this complex network environment, how to ensure the high availability, reliability, and performance of edge computing services has become a technical problem that needs to be solved urgently.

[0003] Edge computing systems usually include a fixed central node and multiple mobile nodes, which are distributed in different geographical locations. How to achieve collaborative work between nodes and ensure the stability of cross-node services is a major challenge in edge computing.

[0004] Edge computing nodes usually carry important business loads, especially in tactical, military and emergency scenarios, where the reliability of nodes is directly related to the success or failure of the mission. Through real-time monitoring and status detection of edge computing nodes, service anomalies, resource bottlenecks or failures can be discovered in a timely manner, and effective emergency measures can be taken to ensure the high availability of edge computing services.

[0005] In existing edge computing systems, the access reliability of services is often affected due to the volatility of network bandwidth and the mobility of nodes. Summary of the invention

[0006] The purpose of the present invention is to propose an edge computing service detection method, which detects (monitors) each mobile node by designing different detection strategies, realizes real-time evaluation of the status of the edge computing service of each mobile node, and thus overcomes the problem of service perception in a weak network (insufficient bandwidth) environment.

[0007] The technical solution to achieve the purpose of the present invention is:

[0008] A method for detecting edge computing services includes the following steps:

[0009] Step 1: Configure the service detection strategy at the fixed central node;

[0010] Step 2: The mobile node receives and executes the service detection strategy to detect the availability of edge computing services of each service node;

[0011] Step 3: The fixed central node aggregates and processes the received service information of each node.

[0012] Furthermore, in step 1, configuring the service detection strategy includes setting the detection frequency, service items, and detection level to ensure that each mobile node can be detected in real time when the bandwidth is limited or the network is unstable.

[0013] Furthermore, when setting the service detection frequency, in the case of low bandwidth, the detection frequency is set to a low level; in the case of normal bandwidth, the detection frequency is set to a medium level; in the case of high bandwidth, the detection frequency is set to a high level.

[0014] Furthermore, the level of service detection is set, and different detection levels are set according to the importance or priority of the service; for key mobile node services, high priority detection is set.

[0015] Furthermore, when setting the detection range of the service, only the mobile node services that need to be monitored are selected according to the network topology and actual needs, so that the mobile node services that need to be monitored can be perceived at the fixed central node when the bandwidth is limited.

[0016] Further, in step 2, specifically: the mobile node receives the policy file; the mobile node parses the policy file and extracts the configured detection parameters; these parameters include detection frequency, level, monitored node range, etc.; according to the acquired detection parameter information, the service of the mobile node is detected through the detection module; the service detection module runs on each mobile node, and triggers the execution of the service status detection task according to the detection frequency;

[0017] According to the set reporting frequency, the obtained service information is reported; according to the configured reporting frequency, the mobile node reports the obtained service status information to the fixed central node.

[0018] Furthermore, in step 3, specifically: the fixed central node deduplicates the received service information; the fixed central node parses and classifies the deduplicated service information, and the classification includes: normal service, abnormal service, and faulty service; the fixed central node aggregates the service information of each node to generate a global view; the global view displays the availability, load status and network status of each mobile node in real time.

[0019] Furthermore, a service detection system includes: a service detection module, which is responsible for real-time monitoring and evaluation of the operating status of each edge computing node; a service policy configuration module, which is responsible for configuring the service detection strategy according to different network environments, task requirements and bandwidth conditions to ensure the execution of the detection work while adapting to changes in network bandwidth; a service aggregation processing module, which is responsible for collecting and integrating the detection results of each edge computing node, aggregating and processing the data, and finally providing comprehensive status information to the operation and maintenance personnel or the central node.

[0020] Compared with the prior art, the present invention has the following significant advantages:

[0021] (1) The present invention is based on a distributed edge computing architecture. By flexibly configuring the detection cycle and detection level in the detection strategy, the service detection module of the mobile node can still maintain efficient status monitoring and data reporting under limited bandwidth.

[0022] (2) Through the global service status view, the service status information of each mobile node is clearly displayed, so that the operation and maintenance personnel of the fixed central node can quickly identify the status of each mobile node, thereby solving the reliability problem of service access. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 is a schematic diagram of service detection of the method of the present invention;

[0024] Figure 2 It is a schematic diagram of a service detection module of the method described in the present invention. DETAILED DESCRIPTION

[0025] The following will be combined with the attached Figure 1-2 The embodiments of the present invention are described in more detail. According to the specific description of the following embodiments, the purpose, technical solutions and advantages of the present application can be made clearer. It should be understood that the mode of implementing the present invention is not limited to the specific embodiments described below. Based on the embodiments provided in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work belong to the scope of protection of this application.

[0026] This embodiment takes into account the tactical edge environment, based on the construction requirements of the distributed task system, and focuses on the issue of secure access to tactical edge network computing resources. It studies the edge computing service operation status detection technology, detects the service status through different strategies, and realizes real-time evaluation of the edge computing service availability and access scope of each service node, providing unified access to cross-node edge computing services for the business.

[0027] Aiming at the demand for service detection of edge cloud center, the present invention proposes an edge computing service detection method. By configuring different service detection strategies, based on a general cloud platform, in an environment with high mobility and weak connection between edge service mobile nodes, the fixed central node can realize real-time perception of the mobile nodes. At the same time, the fixed central node aggregates and processes the service information reported by each node and aggregates it into a global view. The service status of each mobile node is displayed in real time on the view, thereby solving the problem of service access reliability.

[0028] In the edge computing service detection method of the present invention, the core is the service detection module system. The service detection system is to ensure that in the tactical edge environment, efficient detection, status evaluation and data aggregation of edge computing service nodes can be achieved to ensure the availability and reliability of the service. The service detection system includes three parts: service detection, service policy configuration and service aggregation. Specifically:

[0029] (1) The service detection module of the mobile node obtains the service status of each mobile node in real time by calling the service information deployed by the cloud platform;

[0030] The service detection module is the core module of the entire edge computing service detection method, which is responsible for real-time monitoring and evaluation of the operating status of each edge computing mobile node. Specifically, this module will periodically or according to the specified trigger frequency, detect various services of the edge computing mobile nodes and evaluate their operating status.

[0031] (2) Central fixed central node service policy configuration module (fixed)

[0032] The service policy configuration module is responsible for flexibly configuring the service detection strategy according to different network environments, task requirements and bandwidth conditions to ensure that the detection work can be performed efficiently while adapting to changes in network bandwidth. The specific functions are as follows:

[0033] 1) Detection strategy configuration: According to actual needs, flexibly configure the detection frequency, priority, detection range and trigger conditions. For example, for high-bandwidth environments, you can configure frequent high-precision detection; while in low-bandwidth environments, you can configure low-frequency and efficient detection methods to avoid excessive data transmission consuming bandwidth.

[0034] 2) Bandwidth adaptation: The service policy configuration module can adjust the detection parameters according to the real-time network bandwidth situation, ensuring effective service monitoring and reporting efficiency of detection data under limited bandwidth conditions. This module supports adaptive configuration of multiple bandwidth environments to ensure the reliability of edge computing services.

[0035] (3) Service aggregation processing module of fixed central node

[0036] The service aggregation module is mainly responsible for collecting and integrating the detection results of each edge computing node, summarizing and processing the data, and finally providing comprehensive status information to the operation and maintenance personnel or the central node. The specific functions are as follows:

[0037] 1) Status data aggregation: This module aggregates the service status data from each edge node and generates a unified view to provide a basis for subsequent decision-making.

[0038] 2) Data reporting: According to the policy configuration, data is reported to the central node or operation and maintenance personnel. When the system detects an abnormal state, the module will trigger the alarm mechanism and report the problem to the relevant personnel in time to facilitate emergency measures.

[0039] The present invention discloses an edge computing service detection method, wherein the present invention is based on the transmission of service information based on a common cloud platform network in which both the mobile node and the fixed central node are based;

[0040] An edge computing service detection method, the specific steps are:

[0041] Step 1, configure the service detection strategy; configure the service detection strategy through the fixed central node, and the mobile node reports the service information of the mobile node according to different bandwidths and different requirements by receiving the service detection strategy of the fixed central node;

[0042] Configuring the service detection strategy includes setting parameters such as detection frequency (cycle), service items (scope), and detection level to ensure that the service monitoring method can be flexibly adjusted when bandwidth is limited or the network is unstable.

[0043] Step 1.1, set the service detection frequency, according to the actual network conditions and business needs, set the service detection frequency. For example, in the case of low bandwidth, the detection frequency can be set to a lower level to reduce bandwidth pressure.

[0044] In the case of normal bandwidth, the detection frequency can be set to medium; in the case of high bandwidth, the detection frequency can be set to high, so that the service information of the mobile node and the fixed central node can be fully synchronized;

[0045] Step 1.2, set the service detection level, and set different detection levels according to the importance or priority of the service.

[0046] For example, for key mobile node services, high-priority detection can be set to ensure real-time monitoring of the service status of key nodes at any bandwidth.

[0047] Step 1.3, set the detection range of the service, and select only the mobile node services that need to be monitored according to the network topology and actual needs. Then, when the bandwidth is limited, the mobile node services that need to be monitored can be sensed at the fixed central node.

[0048] Step 2: After the service detection strategy is configured, the mobile center will receive and execute the corresponding service detection strategy to detect the availability of edge computing services of each service node.

[0049] Step 2.1: The mobile node receives the policy file: The mobile node receives the configured detection policy file from the fixed central node. The file contains information such as the detection frequency, level, and range of each service node, ensuring that the mobile center can perform service monitoring tasks according to the specified policy.

[0050] Step 2.2: Parse the policy file to obtain the detection frequency, detection level and detection range. The service detection module of the mobile node parses the policy file and extracts the configured detection parameters, including the detection frequency, level, and monitored node range.

[0051] Step 2.3, based on the acquired detection parameter information, the service of the mobile node is detected (monitored) through the detection module;

[0052] The service detection module runs on each mobile node and triggers the execution of service status detection tasks according to the detection frequency.

[0053] Step 2.4, reporting the obtained service information according to the set reporting frequency; according to the configured reporting frequency, the mobile node reports the obtained service status information to the fixed central node.

[0054] The reporting frequency may be consistent with the detection frequency, or may be dynamically adjusted according to the actual network conditions of the mobile node.

[0055] Step 3: The fixed central node aggregates the service information received from each node and processes the service information.

[0056] Step 3.1: The fixed central node performs deduplication processing on the received service information. In the process of multiple reports, duplicate data packets may appear. The fixed central node needs to perform deduplication processing on the received service information to ensure that the final aggregated data does not contain redundant information.

[0057] Step 3.2: The fixed central node parses and classifies the deduplicated service information. The fixed central node parses the deduplicated JSON information, obtains the service status, and classifies the service status; the classification includes: normal service, abnormal service, faulty service, etc.

[0058] Step 3.3: The fixed central node aggregates the service information of each node to generate a global view. After receiving and processing the data reported by all mobile nodes, the fixed central node aggregates this information and generates a global service status view. The view shows the availability, load status and network status of each mobile node in real time; this view provides a clear overview of the service status for operation and maintenance personnel, helping them to quickly identify potential problems.

[0059] The present invention discloses an edge computing service detection method, which is oriented to the tactical edge service operation status detection strategy. It is to formulate an adaptive service status detection strategy by adapting to factors such as tactical communication network conditions, resource requirements, and service dependencies, so as to improve battlefield combat efficiency and provide support for auxiliary decision-making in the combat process. The service status aggregation technology solves the problem of asynchronous service status information of multiple nodes, performs hierarchical aggregation, and realizes the synchronization of service status information, thereby improving the speed and accuracy of service guarantee.

[0060] The above-described embodiment is only an applicable mode of the present invention, but the protection scope of the present invention is not limited thereto. The mode and optimization algorithm of the present invention have been explained and demonstrated in detail in the embodiment. Without violating the technical principle, the present invention allows any changes or modifications, which should be covered within the protection scope of the claims of the present invention.

Claims

1. A method for detecting edge computing services, characterized in that: The method comprises the following steps: Step 1: Configure the service detection strategy at the fixed central node; Step 2: The mobile node receives and executes the service detection strategy to detect the availability of edge computing services of each service node; Step 3: The fixed central node aggregates and processes the received service information of each node.

2. The edge computing service detection method according to claim 1, characterized in that: In the step 1, configuring the service detection strategy includes setting the detection frequency, service items, and detection level to ensure that each mobile node can be detected in real time when the bandwidth is limited or the network is unstable.

3. The edge computing service detection method according to claim 2, characterized in that: When setting the service detection frequency, in low bandwidth conditions, the detection frequency is set to low; in normal bandwidth conditions, the detection frequency is set to medium; in high bandwidth conditions, the detection frequency is set to high.

4. The edge computing service detection method according to claim 2, characterized in that: Set the level of service detection. Set different detection levels according to the importance or priority of the service. For key mobile node services, set high-priority detection.

5. The edge computing service detection method according to claim 2, characterized in that: When setting the detection range of the service, only the mobile node services that need to be monitored are selected according to the network topology and actual needs. This is used to perceive the mobile node services that need to be monitored at the fixed central node when the bandwidth is limited.

6. The edge computing service detection method according to claim 1, characterized in that: In the step 2, specifically: The mobile node receives the policy file; The mobile node parses the policy file and extracts the configured detection parameters; these parameters include detection frequency, level, and monitored node range; According to the acquired detection parameter information, the service of the mobile node is detected through the detection module; the service detection module runs on each mobile node and triggers the execution of the service status detection task according to the detection frequency; According to the set reporting frequency, the obtained service information is reported; according to the configured reporting frequency, the mobile node reports the obtained service status information to the fixed central node.

7. The edge computing service detection method according to claim 1, characterized in that: In the step 3, specifically: The fixed central node performs deduplication processing on the received service information; The fixed central node parses and classifies the deduplicated service information, including normal service, abnormal service, and faulty service; The fixed central node aggregates the service information of each node to generate a global view; the global view displays the availability, load status and network status of each mobile node in real time.

8. A service detection system, characterized in that: The service detection system includes: The service detection module is responsible for real-time monitoring and evaluation of the operating status of each edge computing node; The service policy configuration module is responsible for configuring the service detection strategy according to different network environments, task requirements and bandwidth conditions to ensure the execution of detection work and adapt to changes in network bandwidth; The service aggregation processing module is responsible for collecting and integrating the detection results of each edge computing node, aggregating and processing the data, and finally providing comprehensive status information to the operation and maintenance personnel or the central node.

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