A regional collaborative node cache collaborative sharing technology

Abstract

The present application relates to the technical field of content distribution networks. In order to solve the problem of low cache hit rate and cache efficiency of regional cache nodes, a regional collaborative node cache collaborative sharing technology, computer equipment, computer-readable storage medium and computer program product are disclosed. The technology includes obtaining the access history data and location information of all nodes; constructing a node association network model based on the access history data and location information of all nodes; dividing the nodes in the node association network model into different collaborative domains through a clustering algorithm; selecting at least one super node in each collaborative domain, and the remaining nodes in the collaborative domain are used to synchronize their cache content directories to the super node, and the super node is used to manage and schedule the cache content in the collaborative domain, as well as communicate with nodes in other collaborative domains. The use of this technology can realize the collaborative sharing of node cache content based on regional collaboration, and improve the cache hit rate and cache efficiency of the entire cache system.

Description

Technical Field

[0001] The present application relates to the technical field of content distribution networks, and more specifically, to a regional collaborative node cache collaborative sharing technology, a computer device, a computer-readable storage medium, and a computer program product. Background Art

[0002] Focusing on the distribution needs of edge / end nodes, and addressing issues such as limited computing resources and insufficient storage resources at edge / end nodes, the current approach primarily utilizes Content Delivery Networks (CDNs) to cache business content on cache nodes (also known as CDN nodes) close to users. This allows node users to access content locally, alleviating node traffic pressure to a certain extent. However, traditional single cache nodes often cannot meet the needs of high-concurrency and large-scale data access, making it difficult to fundamentally reduce regional node distribution pressure and ensure the service experience of node users.

[0003] Existing caching technology (i.e., CDN caching technology) primarily caches service content in cache service devices (i.e., cache nodes) close to the node. This technology then redirects service requests to the nearest single cache node for response, shortening service access time and alleviating node access pressure. A single cache node must cache all origin server data accessed by users to ensure user access needs.

[0004] In terms of collaborative sharing of edge / end node cache, existing cache technologies mainly perform clustering management based on network topology, network load and node location information, thereby achieving hierarchical caching.

[0005] However, existing caching technologies still have the following defects: 1) Unreasonable node clustering methods: Node clustering is usually achieved by setting the number of nodes in the collaborative domain or the content similarity threshold. Although this method takes into account node device and user information to a certain extent, excessive reliance on thresholds or pre-set numbers of nodes to divide the collaborative domain during the clustering process may lead to errors in the evaluation of the collaborative capabilities between cache devices, thereby weakening the performance of collaborative caching. In addition, although the node clustering method can improve collaborative efficiency, when the distance between nodes is too far, the network conditions are poor, or the cache information duplication rate is too high, it will reduce the collaborative benefits, increase user access latency, and have limited improvement in the overall cache hit rate. 2) Low node collaborative cache hit rate: Edge / end nodes can only communicate with the source station and cache source station data, and the cache capacity of edge / end nodes is limited, making it difficult to cache all content that users may request. Summary of the Invention

[0006] In order to solve the above problems, the present invention provides a regional collaborative node cache collaborative sharing technology, computer equipment, computer-readable storage medium and computer program product, which will realize optimal node clustering and collaborative sharing of node cache content based on regional collaboration, thereby improving the cache hit rate and cache efficiency of the entire cache system.

[0007] To achieve the above objectives, according to a first aspect of the present invention, a regional cooperative node cache collaborative sharing technology is provided, which includes:

[0008] Get access history data and location information of all nodes;

[0009] Build a node association network model based on the access history data and location information of all nodes;

[0010] By using clustering algorithms, nodes in the node association network model are divided into different collaboration domains;

[0011] At least one super node is selected in each collaboration domain, and the remaining nodes in the collaboration domain are used to synchronize their cache content directories to the super node. The super node is used to manage and schedule the cache content in the collaboration domain and communicate with nodes in other collaboration domains.

[0012] Furthermore, based on the access history data and location information of all nodes, a node association network model is constructed, including calculating the cache content similarity between nodes based on the access history data of all nodes; calculating the communication capability between nodes based on the location information of all nodes; and constructing a node association network model by taking nodes as vertices and the cache content similarity between nodes and the communication capability between nodes as the weights of edges.

[0013] Furthermore, based on the access history data of all nodes, cache content similarity between nodes is calculated, including calculating the cache content similarity between nodes based on the access history data of all nodes through cosine similarity.

[0014] Furthermore, based on the location information of all nodes, the communication capability between nodes is calculated, including calculating the location distance between nodes based on the location information of all nodes; and based on the location distance between nodes, the communication capability between nodes is calculated through Gaussian similarity.

[0015] Furthermore, through the clustering algorithm, the nodes in the node association network model are divided into different collaboration domains, including constructing a comprehensive similarity matrix based on the node association network model; through the community discovery FN algorithm, the nodes in the node association network model are divided into different collaboration domains based on the comprehensive similarity matrix.

[0016] Furthermore, the regional collaborative node cache collaborative sharing technology also includes selecting a new super node by designation or election when the super node leaves the collaborative domain, and synchronizing the cache content directories of the remaining nodes in the collaborative domain to the new super node.

[0017] Furthermore, the above-mentioned regional collaborative node cache collaborative sharing technology also includes monitoring the business access status and node status of nodes in each collaborative domain, and the node status includes node joining, node leaving or node failure; according to the business access status and node status of nodes in the collaborative domain, adjusting the structure of the collaborative domain and / or reselecting super nodes.

[0018] According to a second aspect of the present invention, a computer device is further provided, which includes a memory, a processor, and a computer program stored in the memory, and the processor executes the computer program to implement the steps of any one of the above technologies.

[0019] According to a third aspect of the present invention, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps of any of the above technologies are implemented.

[0020] According to a fourth aspect of the present invention, there is also provided a computer program product, comprising a computer program, which implements the steps of any of the above techniques when executed by a processor.

[0021] In general, the above technical solutions conceived by the present invention can achieve the following beneficial effects compared with the prior art:

[0022] (1) The present invention provides a regional collaborative node cache collaborative sharing technology. First, based on the access history data and location information of all nodes, a node association network model is constructed. Then, through a clustering algorithm, the nodes in the node association network model are divided into different collaborative domains to achieve optimal node clustering and collaborative sharing of node cache content based on regional collaboration, thereby maximizing the efficiency of regional collaboration. In addition, by selecting at least one super node in each collaborative domain, the cache content of the nodes in the collaborative domain is uniformly managed and scheduled, thus avoiding cache content redundancy and significantly improving the utilization efficiency of cache content, thereby achieving the purpose of improving the cache hit rate and cache efficiency of the entire cache system.

[0023] (2) By adopting the regional collaborative node cache collaborative sharing technology provided by the present invention, when receiving a user request, the most appropriate node can be selected in the collaborative domain to respond to the user request based on factors such as the cache content distribution of the node, the network status between nodes, and the user's preference for specific content. Therefore, it can also significantly reduce the user access delay and improve the user experience.

[0024] (3) Using the regional collaborative node cache sharing technology provided by this invention, if a supernode needs to leave the collaborative domain for some reason, a new supernode can be designated or re-elected, and the cache directory can be synchronized. This mechanism ensures that the collaborative domain maintains its stability and functionality even when supernodes change, avoiding the risk of cache system collapse due to a single node failure.

[0025] (4) The regional collaborative node cache collaborative sharing technology provided by this invention improves the scalability of the cache system through collaborative domain division and supernode management mechanisms. As the network scale expands and the number of nodes increases, the system's processing capacity can be easily expanded by adding collaborative domains and supernodes to meet growing user needs.

[0026] (5) The regional collaborative node cache collaborative sharing technology provided by the present invention can improve the utilization of network resources, reduce unnecessary network traffic and transmission delay, and lower network operating costs through collaborative domain division and super node management mechanism. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0028] Figure 1 A schematic diagram of a process flow of a regional cooperative node cache collaborative sharing technology provided in an embodiment of the present application;

[0029] Figure 2 A schematic diagram of the process of constructing a node association network model according to an embodiment of the present application;

[0030] Figure 3 A schematic diagram of the internal structure of a computer device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0031] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely for the purpose of explaining the present invention and are not intended to limit the present invention. In addition, the technical features involved in the various embodiments of the present invention described below may be combined with each other as long as they do not conflict with each other.

[0032] The terms "first," "second," "third," and the like in the specification and claims of this application and the accompanying drawings are used to distinguish between different objects, not to describe a particular order. Furthermore, the terms "including," "having," and any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, system, product, or apparatus comprising a series of steps or elements is not limited to the listed steps or elements, but may optionally include steps or elements not listed, or may optionally include other steps or elements inherent to the process, method, product, or apparatus.

[0033] like Figure 1 As shown, a regional collaborative node cache collaborative sharing technology is provided. This technology adopts a collaborative caching strategy based on collaborative domain division. This technology can be executed by a terminal or by a server that communicates with the terminal via a network. The terminal can be, but is not limited to, various personal computers, laptops, smartphones, tablets, etc. The server can be a standalone server or a server cluster consisting of multiple servers. Taking the application of this technology to a terminal as an example, the following steps are included:

[0034] Step 101: Obtain access history data and location information of all nodes.

[0035] Among them, access history data includes user preference data such as user access interests, access habits, download history, etc.

[0036] Exemplarily, the terminal obtains access history data and location information of all nodes.

[0037] Step 102: construct a node association network model based on the access history data and location information of all nodes.

[0038] Among them, the node association network model is composed of multiple vertices and multiple edges.

[0039] Step 103: Divide the nodes in the node association network model into different collaboration domains through a clustering algorithm.

[0040] Step 104: select at least one super node in each collaboration domain. The remaining nodes in the collaboration domain are used to synchronize their cache content directories to the super node. The super node is used to manage and schedule the cache content in the collaboration domain and communicate with nodes in other collaboration domains.

[0041] It's important to note that collaboration between nodes is central to the management mechanism of a collaborative domain. Once a collaborative domain is established, the nodes within it jointly manage their respective cached content. To more efficiently manage the cached content within the collaborative domain, one or more specific nodes are selected through election or designation as supernodes. This supernode plays a central role in the collaborative domain, responsible for receiving and synchronizing the cached content directories of all nodes within the collaborative domain. In this way, the supernode is able to uniformly manage and schedule cached content across the entire collaborative domain. Furthermore, the supernode is responsible for communicating with nodes within other collaborative domains.

[0042] The above-mentioned regional collaborative node cache collaborative sharing technology first constructs a node association network model based on the access history data and location information of all nodes; then, through a clustering algorithm, the nodes in the node association network model are divided into different collaborative domains to achieve optimal node clustering and collaborative sharing of node cache content based on regional collaboration, thereby maximizing regional collaboration efficiency.

[0043] Moreover, by selecting at least one super node in each collaborative domain, the cache contents of the nodes in the collaborative domain are uniformly managed and scheduled, thus avoiding the redundancy of cache contents and significantly improving the utilization efficiency of cache contents, thereby achieving the purpose of improving the cache hit rate and cache efficiency of the entire cache system.

[0044] In one embodiment, Figure 2 As shown, the above step 102, based on the access history data and location information of all nodes, constructs a node association network model, including:

[0045] Step 201, based on the access history data of all nodes, calculate the cache content similarity between nodes;

[0046] Step 202, calculating the communication capability between nodes based on the location information of all nodes;

[0047] In step 203 , a node association network model is constructed by taking the nodes as vertices, the cache content similarity between the nodes and the communication capability between the nodes as the weights of the edges.

[0048] It's important to note that a node's cached content plays a crucial role in the efficiency of inter-node collaboration. When considering cached content similarity between nodes, cosine similarity is often used to measure the similarity of user preferences. Nodes with similar access histories are likely to have similar local cached content. However, precisely because of this similarity, these nodes should not be grouped into the same collaborative domain when partitioning collaboration domains to avoid cache redundancy and unnecessary network traffic.

[0049] In one embodiment, the cache content similarity between nodes is calculated based on the access history data of all nodes, including calculating the cache content similarity between nodes based on the access history data of all nodes through cosine similarity.

[0050] It's important to note that location distance also plays a crucial role in the efficiency of inter-node collaboration. The higher the Gaussian similarity, the easier it is for nodes to collaborate. However, when nodes are farther apart, communication latency increases significantly, significantly reducing collaboration efficiency. Therefore, when dividing collaboration domains, it's important to fully consider the geographic location of nodes to ensure maximum collaboration efficiency.

[0051] In one embodiment, the communication capability between nodes is calculated based on the location information of all nodes, including calculating the location distance between nodes based on the location information of all nodes; and calculating the communication capability between nodes based on the location distance between nodes through Gaussian similarity.

[0052] In one embodiment, the above step 103 divides the nodes in the node association network model into different collaboration domains through a clustering algorithm, including constructing a comprehensive similarity matrix based on the node association network model; and divides the nodes in the node association network model into different collaboration domains based on the comprehensive similarity matrix through a community discovery FN algorithm.

[0053] The FN community discovery algorithm is a fast, greedy community discovery algorithm. It first attempts to partition the collaboration domain at different locations, generating multiple possible collaboration domain partitioning structures. It then evaluates the modularity of these partitioning structures, a metric that measures the modularity and collaboration of the network structure. Among all the partitioning structures, the one with the highest modularity is selected, as it represents the optimal collaboration domain partitioning method, maximizing collaboration efficiency between nodes while avoiding cache redundancy.

[0054] In one embodiment, when a super node leaves the collaborative domain, the above-mentioned regional collaborative node cache collaborative sharing technology also provides a flexible alternative mechanism, that is, selecting a new super node by designation or election, and synchronizing the cache content directories of the remaining nodes in the collaborative domain to the new super node.

[0055] For example, an existing node is first designated as a new supernode, and the current cache content directory is synchronized to this new supernode. This allows the new supernode to seamlessly take over management responsibilities. Alternatively, if no suitable node can be directly designated, a new supernode can be selected through elections, which will then establish and synchronize the cache content directory. This mechanism ensures that the collaboration domain maintains stability and functionality even when the supernode changes.

[0056] In one embodiment, the regional collaborative node cache collaborative sharing technology also includes monitoring the business access status and node status of nodes in each collaborative domain, where the node status includes node joining, node leaving or node failure; based on the business access status and node status of nodes in the collaborative domain, adjusting the structure of the collaborative domain and / or reselecting super nodes to maintain the stability and efficiency of the entire cache system.

[0057] In one embodiment, a regional cooperative node cache collaborative sharing technology includes the following steps:

[0058] (1) Data collection and analysis:

[0059] Collect access history data of all nodes in the area, including users' access interests, access habits, and download history.

[0060] Get the location information of all nodes.

[0061] (2) Construct a node association network model to cluster nodes:

[0062] The cosine similarity algorithm is used to analyze the access history data of each node and calculate the cache content similarity between nodes. By comparing the differences in the access history data between nodes, the cache content similarity between nodes is determined.

[0063] The Gaussian similarity algorithm is used to evaluate the communication capability between nodes based on their location distance. The impact of location distance between nodes on communication transmission delay and collaboration efficiency is determined.

[0064] Based on the cache content similarity and communication capabilities between nodes, a node association network model is constructed. The node association network model has multiple vertices and multiple edges. Specifically, each node is regarded as a network vertex, and the cache content similarity and communication capabilities between nodes are used as edge weights.

[0065] In the node association network model, clustering algorithms (such as K-means, hierarchical clustering, etc.) are applied to divide the nodes into different collaboration domains, cluster the nodes, and ensure that the nodes in each collaboration domain have high similarity in cache content and strong communication capabilities in location distance.

[0066] (3) Select a super node and synchronize the cached content to the super node:

[0067] In each collaboration domain, one or more super nodes are selected through election or designation. The super nodes are responsible for managing and scheduling cache content within the collaboration domain, as well as communicating with nodes in other collaboration domains.

[0068] The nodes in the collaboration domain synchronize their cache content directories to the super node, and the super node maintains a unified cache directory to quickly respond to requests from nodes in the collaboration domain.

[0069] (4) Dynamic adjustment and optimization:

[0070] Monitor service access and node status within the collaboration domain, such as node joining, leaving, or failure.

[0071] According to actual conditions, the structure of the collaboration domain and the selection of super nodes are dynamically adjusted to maintain the stability and efficiency of the cache system.

[0072] (5) Cache system evaluation and feedback:

[0073] Regularly evaluate the service quality of the regional cache system, such as cache hit rate, user access latency, etc. Testing has shown that the accuracy of node clustering and collaborative regional division is no less than 80%, and the cache hit rate after node collaborative sharing is increased by no less than 50%.

[0074] A regional collaborative node cache collaborative sharing technology provided in this embodiment is adopted. Based on the access history data of all nodes, the cosine similarity is used to measure the cache content similarity between nodes; based on the location distance between nodes, the Gaussian similarity is used to measure the communication capability between nodes; by constructing a node association network model, the nodes are divided into different collaborative domains, and the optimal clustering of nodes and the collaborative sharing of node cache content based on regional collaboration are achieved, thereby maximizing the regional collaboration efficiency. In addition, the cache content of the nodes in the collaborative domain is uniformly managed and scheduled by the super node, which avoids the redundancy of the cache content and significantly improves the utilization efficiency of the cache content, thereby achieving the purpose of improving the overall cache hit rate and overall cache efficiency. In addition, since the nodes in the collaborative domain can select the most appropriate node to respond to user requests based on factors such as the cache content distribution of the node, the network status between the nodes, and the user's preference for specific content, it can also significantly reduce the user access delay and improve the user experience.

[0075] The present application also provides a computer device, the internal structure of which can be as follows: Figure 3As shown. The computer device includes a processor, a memory, an input / output interface, a communication interface, a display unit and an input device. The processor, the memory and the input / output interface are connected via a system bus, and the communication interface, the display unit and the input device are connected to the system bus via the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be implemented through WIFI, a mobile cellular network, NFC (near field communication) or other technologies. When the computer program is executed by the processor, a regional collaborative node cache collaborative sharing technology is implemented. The display unit of the computer device is used to form a visually visible image, and can be a display screen, a projection device or a virtual reality imaging device. The input device of the computer device can be a touch layer covering the display screen, or a button, trackball or touchpad set on the computer device casing, or an external keyboard, touchpad or mouse, etc.

[0076] Those skilled in the art will understand that Figure 3 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0077] like Figure 3 As shown, the present application also provides a computer device, which includes a memory, a processor and a computer program stored in the memory, and the processor executes the computer program to implement the steps in the above-mentioned technical embodiments.

[0078] The present application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps in the above-mentioned technical embodiments. The computer-readable storage medium may include, but is not limited to, any type of disk, including a floppy disk, an optical disk, a DVD, a CD-ROM, a microdrive, a magneto-optical disk, a ROM, a RAM, an EPROM, an EEPROM, a DRAM, a VRAM, a flash memory device, a magnetic card or an optical card, a nanosystem (including a molecular memory IC), or any type of medium or device suitable for storing instructions and / or data.

[0079] The present application also provides a computer program product, including a computer program, which implements the steps in the above-mentioned technical embodiments when executed by a processor.

[0080] It should be noted that for the aforementioned technical embodiments, for the sake of simplicity, they are all expressed as a series of action combinations, but those skilled in the art should be aware that this application is not limited by the order of the actions described, because according to this application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required by this application.

[0081] In the above embodiments, the description of each embodiment has its own focus. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0082] The above description is merely an exemplary embodiment of the present disclosure and is not intended to limit the scope of the present disclosure. That is, any equivalent changes and modifications made in accordance with the teachings of the present disclosure are still within the scope of the present disclosure. After considering the specification and practicing the disclosure herein, those skilled in the art will easily think of the implementation scheme of the present disclosure. This application is intended to cover any variations, uses or adaptations of the present disclosure, which follow the general principles of the present disclosure and include common knowledge or customary technical means in the art that are not recorded in the present disclosure. The description and examples are to be regarded as exemplary only, and the scope and spirit of the present disclosure are defined by the claims.

[0083] The technical features of the above embodiments can be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0084] It will be easily understood by those skilled in the art that the above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A regional cooperative node cache collaborative sharing technology, characterized in that: include: Get access history data and location information of all nodes; Build a node association network model based on the access history data and location information of all nodes; Dividing the nodes in the node association network model into different collaboration domains by a clustering algorithm, including: constructing a comprehensive similarity matrix based on the node association network model; Using a community discovery FN algorithm, nodes in a node association network model are divided into different collaboration domains based on the comprehensive similarity matrix; At least one super node is selected in each collaboration domain, and the remaining nodes in the collaboration domain are used to synchronize their cache content directories to the super node. The super node is used to manage and schedule the cache content in the collaboration domain and communicate with nodes in other collaboration domains.

2. The technology of claim 1, wherein: The node association network model is constructed based on the access history data and location information of all nodes, including: Based on the access history data of all nodes, calculate the cache content similarity between nodes; Based on the location information of all nodes, calculate the communication capacity between nodes; The nodes are taken as vertices, and the cache content similarity between the nodes and the communication capability between the nodes are taken as the weights of the edges to construct a node association network model.

3. The technology of claim 2, wherein: The calculation of cache content similarity between nodes based on access history data of all nodes includes: Through cosine similarity, the cache content similarity between nodes is calculated based on the access history data of all nodes.

4. The technology of claim 2, wherein: The communication capability between nodes is calculated based on the location information of all nodes, including: Based on the location information of all nodes, calculate the location distance between nodes; The communication capability between nodes is calculated based on the location distance between nodes through Gaussian similarity.

5. The technology of claim 1, wherein: The technology also includes: When a super node leaves the collaboration domain, a new super node is selected by designation or election, and the cache content directories of the remaining nodes in the collaboration domain are synchronized to the new super node.

6. The technology of claim 1, wherein: The technology also includes: Monitor the service access and node status of nodes in each collaboration domain, including node joining, node leaving, or node failure; According to the service access conditions and node states of the nodes in the collaboration domain, the structure of the collaboration domain is adjusted and / or the super node is reselected.

7. A computer device, characterized in that: The invention comprises a memory, a processor and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the technology according to any one of claims 1 to 6.

8. A computer-readable storage medium, characterized in that A computer program is stored thereon, and when the computer program is executed by a processor, the steps of the technology described in any one of claims 1 to 6 are implemented.

9. A computer program product, characterized in that The invention comprises a computer program, which implements the steps of any one of claims 1 to 6 when the computer program is executed by a processor.

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