Intelligent cache replacement method and system based on application awareness

Abstract

The invention relates to the technical field of data processing, and particularly discloses an intelligent cache replacement method and system based on application awareness, and the method comprises the steps: sensing a cache state of an application scene, and determining a candidate cache replacement strategy according to a cache replacement strategy matching rule; the method comprises the following steps: collecting data of a storage node data access mode, a cache access state, a capacity state and a power consumption state of an application scene, and preprocessing the data to generate historical data; according to historical data, training a GRU model to predict future cache hit information, and determining a cache hit rate of the application scene; calculating strategy benefits according to the cache hit rate and the evaluation index of the cache hit rate, and comparing the candidate cache replacement strategy with the current cache replacement strategy; and when the cache hit rate is lower than a preset threshold value and a strategy benefit comparison result exceeds a set value, configuring the candidate cache replacement strategy as a current cache replacement strategy.

Description

Technical Field

[0001] The present invention relates to the field of data processing technology, and in particular to a cache intelligent replacement method and system based on application perception. Background Art

[0002] Cache replacement can improve cache hit rates, enhance system performance, and improve resource utilization efficiency. Intelligent replacement can predict future data access trends and combine it with benefit analysis of different cache replacement strategies to achieve intelligent configuration of cache replacement strategies, thereby supporting diverse application scenarios.

[0003] Existing technologies lack comprehensive understanding of data access patterns, write operation ratios, and other conditions specific to different application scenarios. Their single-rule configuration of cache replacement policies is inadequate for practical application in complex scenarios. Furthermore, existing technologies primarily select replacement policies based on historical data, lacking reference to predictive information and thus unable to effectively implement early warnings. Furthermore, existing technologies lack evaluation and comparison of policy effectiveness, leading to ineffective configuration of policy changes.

[0004] Therefore, how to solve the technical problems in the prior art is a technical problem that needs to be solved urgently by those skilled in the art. Summary of the Invention

[0005] To achieve the purpose of the present invention, the present application provides an application-aware intelligent cache replacement method, comprising:

[0006] Step S1: Sense the cache status of the application scenario and determine a candidate cache replacement strategy based on a cache replacement strategy matching rule;

[0007] Step S2: collecting data access mode, cache access status, capacity status, and power consumption status data of the storage node of the application scenario, and performing data preprocessing to generate historical data;

[0008] Step S3: Based on the historical data, a GRU model is trained to predict future cache hit information and determine the cache hit rate of the application scenario;

[0009] Step S4: calculating the policy benefit according to the cache hit rate and the cache hit rate evaluation index, and comparing the candidate cache replacement policy with the current cache replacement policy;

[0010] Step S5: When the cache hit rate is lower than a preset threshold and the strategy benefit comparison result exceeds a set value, the candidate cache replacement strategy is configured as the current cache replacement strategy.

[0011] In some specific embodiments, including: in step S1, the cache status of the application scenario includes: data access mode, cache capacity, system overhead, write operation ratio and cache hit status.

[0012] In some specific embodiments, the method includes: in step S3, combining historical cache hit conditions with predicted future cache hit conditions, and determining according to the following formula:

[0013]

[0014] Where H represents the historical value of cache hit counts, H P Represents the predicted value of the number of cache hits. M represents the historical value of the number of cache misses, M P represents the predicted number of cache misses, and α is the adjustment factor.

[0015] In some specific embodiments, the cache hit rate evaluation index includes:

[0016] One or more of cache hit rate, effective throughput, AMAT, power consumption, number of replacements, and average number of transmission hops.

[0017] In some specific embodiments, including: in step S4, the strategy benefit is determined according to the following formula:

[0018]

[0019] Where α, β, and γ are adjustment factors for power consumption, number of replacements, and average number of transmission hops, respectively; AMAT is the average access time; Throughout is the effective throughput; and P total is the total power consumption, N placement is the number of replacements, AverageHops is the average number of transmission hops;

[0020] The strategic benefit comparison results are determined according to the following formula:

[0021]

[0022] Where, StrategyBenefits candidate StrategyBenefits current For the current strategic benefits.

[0023] To achieve the same invention objective, the present application also provides an application-aware intelligent cache replacement system, comprising:

[0024] Application perception module: used to perceive the cache status of the application scenario and determine the candidate cache replacement strategy based on the cache replacement strategy matching rules;

[0025] Data collection and processing module: used to collect storage node data access mode, cache access status, capacity status, power consumption status data of the application scenario, and perform data preprocessing to generate historical data;

[0026] Prediction module: used to train the GRU model based on the historical data to predict future cache hit information and determine the cache hit rate of the application scenario;

[0027] A policy evaluation module is configured to calculate the policy benefit based on the cache hit rate and the cache hit rate evaluation index, and compare the candidate cache replacement policy with the current cache replacement policy;

[0028] The strategy configuration module is configured to configure the candidate cache replacement strategy as the current cache replacement strategy when the cache hit rate is lower than a preset threshold and the strategy benefit comparison result exceeds a set value.

[0029] In some specific embodiments, including: in the application perception module, the cache status of the application scenario includes: data access mode, cache capacity, system overhead, write operation ratio and cache hit status.

[0030] In some specific embodiments, the prediction module combines historical cache hits with predicted future cache hits and determines the following formula:

[0031]

[0032] Where H represents the historical value of cache hit counts, H P Represents the predicted value of the number of cache hits. M represents the historical value of the number of cache misses, M P represents the predicted number of cache misses, and α is the adjustment factor.

[0033] In some specific embodiments, the cache hit rate indicator includes:

[0034] Cache hit rate, effective throughput, AMAT, power consumption, number of replacements, and average number of transmission hops.

[0035] In some specific embodiments, including: in the strategy evaluation module, the strategy benefit is determined according to the following formula:

[0036]

[0037] Where α, β, and γ are adjustment factors for power consumption, number of replacements, and average number of transmission hops, respectively; AMAT is the average access time; Throughout is the effective throughput; and P total is the total power consumption, N placementis the number of replacements, AverageHops is the average number of transmission hops;

[0038] The strategic benefit comparison results are determined according to the following formula:

[0039]

[0040] Where, StrategyBenefits candidate StrategyBenefits current For the current strategic benefits.

[0041] Beneficial effects of the above technical solution:

[0042] (1) The present invention achieves comprehensive perception of complex conditions in application scenarios, such as data access patterns, cache capacity, system overhead, write operation ratio, and cache hit status, thereby determining candidate cache replacement strategies based on the characteristics of different application scenarios. This addresses the problem that existing technologies have a single rule for configuring cache replacement strategies and cannot guide practical operations in complex application scenarios.

[0043] (2) The present invention combines historical cache data and future cache hit information to calculate indicators such as cache hit rate, effective throughput, AMAT, power consumption, number of replacements, and average number of transmission hops, thereby achieving comprehensive strategy benefit analysis and further supporting the benefit comparison between candidate strategies and current strategies, thereby quantifying the feasibility of strategy changes. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] 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 description of the embodiments. Obviously, the drawings described below are only some embodiments of the present application. For those skilled in the art, other drawings can be obtained based on these drawings without creative work.

[0045] Figure 1 A schematic diagram of a process flow of an application-aware cache intelligent replacement method provided by an embodiment of the present invention;

[0046] Figure 2 A schematic structural diagram of an application-aware cache intelligent replacement system provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0047] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments.

[0048] Examples of the embodiments are shown in the accompanying drawings, wherein the same or similar symbols throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present invention, and should not be construed as limiting the present invention.

[0049] Example 1

[0050] An embodiment of the present invention provides a cache intelligent replacement method based on application awareness, referring to Figure 1 As shown, including:

[0051] Step S1: Sense the cache status of the application scenario and determine a candidate cache replacement strategy based on a cache replacement strategy matching rule.

[0052] In a specific embodiment of the present invention, it includes: in step S1, the cache status of the application scenario includes: data access mode, cache capacity, system overhead, write operation ratio and cache hit status.

[0053] Specifically, data access pattern awareness is determined through the following steps:

[0054] 1) Call the interface to pass in the application scenario ID and return the detailed configuration of the application scenario, including parameters such as data access mode, trigger conditions, and data block size.

[0055] 2) The analysis model quantifies data access locality through temporal distance, i.e., the total number of accesses between two accesses to the same data.

[0056] 3) Data access frequency: Use a hash table to count data access frequency, using the data as the key and the number of accesses as the value. The count is updated with each access. Set an access frequency threshold based on the application scenario, and mark it as a hotspot if it exceeds the threshold.

[0057] Cache capacity awareness is determined through the following steps: The cache capacity is obtained through hardware information detection. If the cache capacity is less than the set value, a cache replacement strategy needs to be carefully selected.

[0058] System overhead awareness is determined through the following steps: Use performance analysis tools to obtain the CPU, memory and other resource consumption status.

[0059] The write operation ratio perception is determined by the following steps: obtaining the read and write operation counts of the process through a counter, and the write operation ratio = the number of write operations / (the number of read operations+the number of write operations)*100%.

[0060] Cache hit status awareness is determined through the following steps: obtaining the number of cache hits through a counter, obtaining the cache read speed and the underlying storage device read speed through a test tool.

[0061] Based on the above state perception results, candidate cache replacement strategies are determined, taking into account the following factors:

[0062] Scenarios with strong temporal locality: LRU can be selected as the candidate strategy.

[0063] For data with high access frequency and long-term hot spots, the candidate strategy can be LFU.

[0064] Cache space is limited and low overhead is required: FIFO is a candidate strategy.

[0065] Write-intensive applications: Candidate strategies can be combined with write strategies.

[0066] Systems requiring high predictability: Candidate strategies include pseudo-random or round-robin.

[0067] Step S2: Collect cache status data of the application scenario, perform data preprocessing, and generate historical cache data.

[0068] Specifically, data collection includes: configuring data collection tools and testing tools on each storage system node to collect data such as data access mode, data block size, timestamp, data access times, cache capacity, read and write operation counts, cache hit times, hit time, miss times, hop count, data load times in the first cycle, read times, write times, single operation energy consumption, cache active time, cache read speed, and underlying storage device read speed.

[0069] Data processing includes: deduplication, missing value processing, format unification, anomaly detection and other operations to eliminate noise, fill in missing values, correct errors and ensure data quality.

[0070] Step S3: Based on the historical cache data, a GRU model is trained to predict future cache hit information and determine the cache hit rate of the application scenario.

[0071] In a specific embodiment of the present invention, the method includes: in step S3, combining historical cache hit conditions with predicted future cache hit conditions, and determining according to the following formula:

[0072]

[0073] Where H represents the historical value of cache hit counts, H P Represents the predicted value of the number of cache hits. M represents the historical value of the number of cache misses, M P represents the predicted number of cache misses, and α is the adjustment factor.

[0074] Effective throughput calculation: Effective throughput refers to the amount of data read from the cache or the underlying storage device per unit time. It is calculated as follows: cache hit ratio * cache read rate + cache miss ratio * underlying storage device read rate.

[0075] Throughout=HR*S cache +MR*S sd , where S cache is the cache read speed, S sd The read speed of the underlying storage device. The cache read speed and the read speed of the underlying storage device are obtained through testing tools.

[0076] AMAT (Average Access Time) calculation: It is calculated by combining hit time, miss rate and miss penalty to reflect the overall access efficiency. The formula is as follows: AMAT = T hit +MR*AP,MR=1-HR. Where, T hit stands for hit time, MR stands for miss rate, and AP stands for miss penalty.

[0077] Power consumption calculation: including dynamic power consumption and static power consumption. The calculation formula is as follows:

[0078] P total =(N read *E read +N wrire *E write )*f+P idle *(1-U active )

[0079] Among them, N read / N wrire is the number of read / write times, E read / E write is the energy consumption of a single read / write operation, f is the operating frequency, U active The percentage of cache active time.

[0080] Calculation of replacement times: Frequent replacements may increase computational overhead, so fewer replacements represent a more stable strategy.

[0081] The formula is as follows: Number of replacements = Number of misses when the cache is full - Number of data loads in the first loop. N placement =N m_cachefull -N cacheload_firstcycle

[0082] If the cache is initially empty, the number of misses in the first cycle is equal to the number of data loads, and replacement is triggered only when a miss occurs after the cache is full.

[0083] Average Hops Calculation: The average hop count represents the number of relays required for a data packet to reach the requester. Fewer hops indicate better cache distribution. The formula is as follows:

[0084] Hopquest represents the number of hops from the user to the cache node. data Indicates the number of hops from the cache node to the user, N totalquests Indicates the total number of requests.

[0085] Step S4: Calculate the policy benefit according to the cache hit rate and the cache hit rate evaluation index, and compare the candidate cache replacement policy with the current cache replacement policy.

[0086] In a specific embodiment of the present invention, the evaluation index of the cache hit rate includes:

[0087] One or more of cache hit rate, effective throughput, AMAT, power consumption, number of replacements, and average number of transmission hops.

[0088] In a specific embodiment of the present invention, the method includes: in step S4, the strategy benefit is determined according to the following formula:

[0089]

[0090] Where α, β, and γ are adjustment factors for power consumption, number of replacements, and average number of transmission hops, respectively; AMAT is the average access time; Throughout is the effective throughput; and P total is the total power consumption, N placement is the number of replacements, AverageHops is the average number of transmission hops, and all variables need to be normalized to unitless quantities to ensure the balance of the formula;

[0091] Based on the strategy benefits, the strategy benefits of the candidate strategy and the current strategy are compared, and the strategy benefit comparison result is determined according to the following formula:

[0092]

[0093] Where, StrategyBenefits candidate StrategyBenefits current For the current strategic benefits.

[0094] Step S5: When the cache hit rate is lower than a preset threshold and the strategy benefit comparison result exceeds a set value, the candidate cache replacement strategy is configured as the current cache replacement strategy.

[0095] The present invention achieves comprehensive perception of complex conditions in application scenarios, such as data access patterns, cache capacity, system overhead, write operation ratio, and cache hit status, thereby determining candidate cache replacement strategies based on the characteristics of different application scenarios. This addresses the problem that existing technologies have single rules for configuring cache replacement strategies and are unable to guide practical operation in complex application scenarios.

[0096] The present invention combines historical cache data and future cache hit information to calculate indicators such as cache hit rate, effective throughput, AMAT, power consumption, number of replacements, and average number of transmission hops, achieving comprehensive strategy benefit analysis and further supporting the benefit comparison between candidate strategies and current strategies, thereby quantifying the feasibility of strategy changes.

[0097] Example 2

[0098] An embodiment of the present invention provides a cache intelligent replacement system based on application awareness, referring to Figure 2 As shown, including:

[0099] Application perception module 10: used to perceive the cache status of the application scenario and determine the candidate cache replacement strategy according to the cache replacement strategy matching rule;

[0100] Data collection and processing module 20: collects data such as storage node data access mode, cache capacity, cache hit count, hit time, read and write count, read speed, power consumption, etc. driven by the application scenario, and performs data preprocessing to generate historical data;

[0101] Prediction module 30: used to train a GRU model based on the historical data to predict future cache hit information and determine the cache hit rate of the application scenario;

[0102] A policy evaluation module 40 is configured to calculate the policy benefit based on the cache hit rate and the cache hit rate evaluation index, and compare the candidate cache replacement policy with the current cache replacement policy;

[0103] The strategy configuration module 50 is configured to configure the candidate cache replacement strategy as the current cache replacement strategy when the cache hit rate is lower than a preset threshold and the strategy benefit comparison result exceeds a set value.

[0104] In a specific embodiment of the present invention, it includes: in the application perception module 10, the cache status of the application scenario includes: data access mode, cache capacity, system overhead, write operation ratio and cache hit status.

[0105] In a specific embodiment of the present invention, the cache hit rate HR is calculated by dividing the number of cache hits by the total number of requests in the prediction module 30, and is determined according to the following formula:

[0106]

[0107] Where H represents the historical value of cache hit counts, H P Represents the predicted value of the number of cache hits. M represents the historical value of the number of cache misses, M P represents the predicted number of cache misses, and α is the adjustment factor.

[0108] In a specific embodiment of the present invention, the evaluation index of the cache hit rate includes:

[0109] One or more of cache hit rate, effective throughput, AMAT, power consumption, number of replacements, and average number of transmission hops.

[0110] In a specific embodiment of the present invention, the strategy evaluation module 40 includes: the strategy benefit is determined according to the following formula:

[0111]

[0112] Where α, β, and γ are adjustment factors for power consumption, number of replacements, and average number of transmission hops, respectively; AMAT is the average access time; Throughout is the effective throughput; and P total is the total power consumption, N placement is the number of replacements, AverageHops is the average number of transmission hops, and all variables need to be normalized to unitless quantities to ensure the balance of the formula;

[0113] Based on the strategy benefits, the strategy benefits of the candidate strategy and the current strategy are compared, and the strategy benefit comparison result is determined according to the following formula:

[0114]

[0115] Where, StrategyBenefits candidate StrategyBenefits current For the current strategic benefits.

[0116] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any modifications or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be based on the scope of protection of the claims.

[0117] The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same and similar parts between the various embodiments can be referred to each other. The embodiments of the present invention are described with reference to the flowcharts and / or block diagrams of the methods, terminal devices (systems), and computer program products according to the embodiments of the present invention. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing terminal device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing terminal device generate instructions for implementing the functions in the process. Figure 1 a process or multiple processes and / or boxes Figure 1 These computer program instructions can also be stored in a computer-readable memory that can guide a computer or other programmable data processing terminal device to work in a specific way, so that the instructions stored in the computer-readable memory produce a product including an instruction device, which implements the functions specified in the process. Figure 1 a process or multiple processes and / or boxes Figure 1 These computer program instructions can also be loaded onto a computer or other programmable data processing terminal device, so that a series of operation steps are executed on the computer or other programmable terminal device to produce a computer-implemented process, thereby providing instructions for implementing the process in the process. Figure 1 a process or multiple processes and / or boxes Figure 1The steps of the functions specified in one or more blocks. Although preferred embodiments of the present invention have been described, those skilled in the art may make additional changes and modifications to these embodiments once they are aware of the basic inventive concepts. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the embodiments of the present invention. Finally, it should be noted that, in this document, relational terms such as first and second, etc. are merely used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article, or terminal device that includes a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article, or terminal device. Without further limitation, an element defined by the phrase "comprising a..." does not exclude the presence of other identical elements in the process, method, article, or terminal device that includes the element.

[0118] The method and apparatus provided by the present invention are introduced in detail above. Specific examples are used herein to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method and core ideas of the present invention. At the same time, for those skilled in the art, according to the ideas of the present invention, there may be changes in the specific implementation methods and application scopes. In summary, the contents of this specification should not be understood as limiting the present invention.

[0119] Throughout this specification, reference to terms such as "one embodiment," "some embodiments," "example," "specific example," "a specific embodiment," or "some examples" means that the specific features, structures, materials, or characteristics described in conjunction with that embodiment or example are included in at least one embodiment or example of the present invention. In this specification, schematic representations of terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.

[0120] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A cache intelligent replacement method based on application awareness, characterized in that: include: Step S1: Sense the cache status of the application scenario and determine a candidate cache replacement strategy based on a cache replacement strategy matching rule; Step S2: collecting data access mode, cache access status, capacity status, and power consumption status data of the storage node of the application scenario, and performing data preprocessing to generate historical data; Step S3: Based on the historical data, a GRU model is trained to predict future cache hit information and determine the cache hit rate of the application scenario; Step S4: calculating the policy benefit according to the cache hit rate and the cache hit rate evaluation index, and comparing the candidate cache replacement policy with the current cache replacement policy; Step S5: When the cache hit rate is lower than a preset threshold and the strategy benefit comparison result exceeds a set value, the candidate cache replacement strategy is configured as the current cache replacement strategy.

2. The application-aware cache intelligent replacement method according to claim 1, characterized in that: include: In step S1, the cache status of the application scenario includes: data access mode, cache capacity, system overhead, write operation ratio and cache hit status.

3. The application-aware cache intelligent replacement method according to claim 1, characterized in that: include: In step S3, the cache hit rate HR is calculated by dividing the number of cache hits by the total number of requests and is determined according to the following formula: Where H represents the historical value of cache hit counts, H P Represents the predicted value of the number of cache hits. M represents the historical value of the number of cache misses, M P represents the predicted number of cache misses, and α is the adjustment factor.

4. The application-aware cache intelligent replacement method according to claim 1, characterized in that: The evaluation indicators of the cache hit rate include: One or more of cache hit rate, effective throughput, AMAT, power consumption, number of replacements, and average number of transmission hops.

5. The cache intelligent replacement method based on application awareness according to claim 1, characterized in that: include: In step S4, the strategy benefit is determined according to the following formula: Where α, β, and γ are power consumption, number of replacements, and average number of transmission hops, respectively; AMAT is the average access time; Throughout is the effective throughput; and P total is the total power consumption, N placement is the number of replacements, AverageHops is the average number of transmission hops; The strategic benefit comparison results are determined according to the following formula: Where, StrategyBenefits candidate StrategyBenefits current For the current strategic benefits.

6. A cache intelligent replacement system based on application awareness, characterized in that: include: Application perception module: used to perceive the cache status of the application scenario and determine the candidate cache replacement strategy based on the cache replacement strategy matching rules; Data collection and processing module: used to collect storage node data access mode, cache access status, capacity status, power consumption status data of the application scenario, and perform data preprocessing to generate historical data; Prediction module: used to train the GRU model based on the historical data to predict future cache hit information and determine the cache hit rate of the application scenario; A policy evaluation module is configured to calculate the policy benefit based on the cache hit rate and the cache hit rate evaluation index, and compare the candidate cache replacement policy with the current cache replacement policy; The strategy configuration module is configured to configure the candidate cache replacement strategy as the current cache replacement strategy when the cache hit rate is lower than a preset threshold and the strategy benefit comparison result exceeds a set value.

7. The application-aware cache intelligent replacement system according to claim 6, characterized in that: The cache status of the application scenario includes: data access mode perception, cache capacity perception, system overhead perception, write operation ratio perception and cache hit status perception.

8. The application-aware cache intelligent replacement system according to claim 6, characterized in that: The prediction module combines historical cache hits with predicted future cache hits and determines the value according to the following formula: Where H represents the historical value of cache hit counts, H P Represents the predicted value of the number of cache hits. M represents the historical value of the number of cache misses, M P represents the predicted number of cache misses, and α is the adjustment factor.

9. The application-aware cache intelligent replacement system according to claim 6, characterized in that: The evaluation indicators of the cache hit rate include: One or more of cache hit rate, effective throughput, AMAT, power consumption, number of replacements, and average number of transmission hops.

10. The application-aware cache intelligent replacement system according to claim 6, characterized in that: include: The strategy evaluation module determines the strategy benefit according to the following formula: Where α, β, and γ are adjustment factors for power consumption, number of replacements, and average number of transmission hops, respectively; AMAT is the average access time; Throughout is the effective throughput; and P total is the total power consumption, N placement is the number of replacements, AverageHops is the average number of transmission hops; The strategic benefit comparison results are determined according to the following formula: Where, StrategyBenefits candidate StrategyBenefits current For the current strategic benefits.

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