CN109032969A - A kind of caching method of the LRU-K algorithm based on K value dynamic monitoring - Google Patents
A kind of caching method of the LRU-K algorithm based on K value dynamic monitoring Download PDFInfo
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- CN109032969A CN109032969A CN201810684735.9A CN201810684735A CN109032969A CN 109032969 A CN109032969 A CN 109032969A CN 201810684735 A CN201810684735 A CN 201810684735A CN 109032969 A CN109032969 A CN 109032969A
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- 238000000034 method Methods 0.000 title claims abstract description 18
- 238000012544 monitoring process Methods 0.000 title claims abstract description 17
- 238000012163 sequencing technique Methods 0.000 claims description 3
- 238000013500 data storage Methods 0.000 abstract description 2
- 230000006870 function Effects 0.000 description 2
- 238000007726 management method Methods 0.000 description 2
- 230000006386 memory function Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F12/00—Accessing, addressing or allocating within memory systems or architectures
- G06F12/02—Addressing or allocation; Relocation
- G06F12/08—Addressing or allocation; Relocation in hierarchically structured memory systems, e.g. virtual memory systems
- G06F12/12—Replacement control
- G06F12/121—Replacement control using replacement algorithms
- G06F12/123—Replacement control using replacement algorithms with age lists, e.g. queue, most recently used [MRU] list or least recently used [LRU] list
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Abstract
The invention discloses a kind of caching methods of LRU-K algorithm based on K value dynamic monitoring, are related to Data cache technology field.The present invention includes judging whether K access data block frequency is lower than lower threshold Ldown；If so, setting K-1 access list LinkSeqK- of data block；Judge whether K access data block frequency is more than upper limit threshold Lup；If so, setting K+1 access list LinkSeqK+ of data block.Present invention K access data block frequency monitoring and judge whether K access data block frequency exceeds lower threshold Ldown or upper limit threshold Lup and then uses K-1 access list LinkSeqK- and K+1 access list LinkSeqK+ in LRU-K algorithm, improve the performance of existing LRU-K algorithm, guarantee system handles high efficiency when different data, improves space utilisation and data storage efficiency.
Description
Technical field
The invention belongs to Data cache technology fields, more particularly to a kind of LRU-K algorithm based on K value dynamic monitoring
Caching method.
Background technique
The virtual memory management of memory is mode generally used now -- in the case where limited memory, it is outer to extend a part
It deposits as virtual memory, real memory is used when only storing current operation to obtain information.This has undoubtedly greatly expanded memory
Function, greatly improve the concurrency of computer.Virtual paged memory management, then be space needed for process is divided into it is more
A page only stores the current desired page in memory, remaining page is put into the way to manage of external memory.
The superiority and inferiority of LRU-K page replacement algorithm and K value are provided with much relations, in different data handling procedures, phase
The number difference bring system treatment effeciency being accessed with data block is different, often the LRU-K page replacement algorithm of identical K value
As soon as the efficiency showed in operation processing is higher, but efficiency may not be quite reasonable when handling another operation.
This invention address that a kind of caching method of LRU-K algorithm based on K value dynamic monitoring is studied, for solving LRU-
K page replacement algorithm system effectiveness shows the uncontrollable problem of efficiency because of different work.
Summary of the invention
The purpose of the present invention is to provide a kind of caching methods of LRU-K algorithm based on K value dynamic monitoring, by right
K access data block frequency monitoring and judge whether K access data block frequency exceeds lower threshold Ldown in LRU-K algorithm
Or upper limit threshold Lup uses K-1 access list LinkSeqK- and K+1 access list LinkSeqK+ in turn, realizes root
According to the K value in real system processing result dynamic adjustment LRU-K algorithm, solves existing LRU-K page replacement algorithm system effect
Rate shows the uncontrollable problem of efficiency because of different work.
In order to solve the above technical problems, the present invention is achieved by the following technical solutions:
The present invention is a kind of caching method of LRU-K algorithm based on K value dynamic monitoring, is included the following steps:
S000: setting data block access list LinkSeq；
S001: setting K access list LinkSeqK of data block；
S002: judge to access whether data block reaches K times；If so, executing S003；S006 is executed if not；
S003: judge whether access list LinkSeqK is full；If so, executing S005；If it is not, then executing S004；
S004: judge whether K access data block frequency is lower than lower threshold Ldown；If so, setting data block K-1
Secondary access list LinkSeqK-；If it is not, then executing S006；
S005: judge whether K access data block frequency is more than upper limit threshold Lup；If so, setting data block K+1 times
Access list LinkSeqK+；If it is not, then executing S006；
S006: the data block in S002 is entered in list LinkSeqK and executes S002；
Wherein, K-1 is more than or equal to 2.
Preferably, the data block access list LinkSeq accesses data block according to LEU algorithm.
Preferably, in the K access list LinkSeqK storing data block meet system access data block number be greater than
Equal to K times；Storing data block meets system access data block number and is more than or equal in the K-1 access list LinkSeqK-
K-1 times；Storing data block meets system access data block number and is more than or equal to K+1 in the K+1 access list LinkSeqK+
It is secondary.
Preferably, the lower threshold Ldown is that the preset data block for meeting K access times of system accounts for total access time
The minimum value of several ratio；The upper limit threshold Lup is that the preset data block for meeting K access times of system accounts for total access time
The maximum value of several ratio；
Preferably, K-1 access list LinkSeqK- of data block is arranged in S004 to include the following steps:
A000: K-1 access list LinkSeqK- is judged whether there is；If so, executing A002；If it is not, then executing
A001；
A001: setting K-1 access list LinkSeqK- of data block simultaneously executes A002；
A002: judge whether K access list LinkSeqK has data block；If so, executing A003；If it is not, then executing
A004；
A003: data block in K access list LinkSeqK is stored according to enqueue time sequencing to K-1 Access Column
In table LinkSeqK-；
A004: the data block in S002 is entered in list LinkSeqK- and executes S002.
The invention has the following advantages:
The present invention is by K access data block frequency monitoring in LRU-K algorithm and judging that K access data block frequency is
It is no to use K-1 access list LinkSeqK- and K+1 access list in turn beyond lower threshold Ldown or upper limit threshold Lup
LinkSeqK+ realizes according to the K value in real system processing result dynamic adjustment LRU-K algorithm, improves existing LRU-K
The performance of algorithm guarantees high efficiency when system processing different data, improves space utilisation and data storage efficiency.
Certainly, it implements any of the products of the present invention and does not necessarily require achieving all the advantages described above at the same time.
Detailed description of the invention
In order to illustrate the technical solution of the embodiments of the present invention more clearly, will be described below to embodiment required
Attached drawing is briefly described, it should be apparent that, drawings in the following description are only some embodiments of the invention, for ability
For the those of ordinary skill of domain, without creative efforts, it can also be obtained according to these attached drawings other attached
Figure.
Fig. 1 is a kind of flow chart of the caching method of LRU-K algorithm based on K value dynamic monitoring of the invention；
Fig. 2 is the flow chart that K-1 access list LinkSeqK- of data block is arranged in S004.
Specific embodiment
Following will be combined with the drawings in the embodiments of the present invention, and technical solution in the embodiment of the present invention carries out clear, complete
Site preparation description, it is clear that described embodiments are only a part of the embodiments of the present invention, instead of all the embodiments.It is based on
Embodiment in the present invention, it is obtained by those of ordinary skill in the art without making creative efforts all other
Embodiment shall fall within the protection scope of the present invention.
Refering to Figure 1, the present invention is a kind of caching method of LRU-K algorithm based on K value dynamic monitoring, including such as
Lower step:
S000: setting data block access list LinkSeq；
S001: setting K access list LinkSeqK of data block；
S002: judge to access whether data block reaches K times；If so, executing S003；S006 is executed if not；
S003: judge whether access list LinkSeqK is full；If so, executing S005；If it is not, then executing S004；
S004: judge whether K access data block frequency is lower than lower threshold Ldown；If so, setting data block K-1
Secondary access list LinkSeqK-；If it is not, then executing S006；
S005: judge whether K access data block frequency is more than upper limit threshold Lup；If so, setting data block K+1 times
Access list LinkSeqK+；If it is not, then executing S006；
S006: the data block in S002 is entered in list LinkSeqK and executes S002；
Wherein, K-1 is more than or equal to 2.
Wherein, data block access list LinkSeq accesses data block according to LEU algorithm.
Wherein, storing data block meets system access data block number and is more than or equal to K in K access list LinkSeqK
It is secondary；Storing data block meets system access data block number and is more than or equal to K-1 times in K-1 access list LinkSeqK-；K+1
Storing data block meets system access data block number and is more than or equal to K+1 times in secondary access list LinkSeqK+.
Wherein, which is characterized in that lower threshold Ldown is that the preset data block for meeting K access times of system accounts for always
The minimum value of the ratio of access times；Upper limit threshold Lup is that the preset data block for meeting K access times of system accounts for total access
The maximum value of the ratio of number；
It please refers to shown in Fig. 2, K-1 access list LinkSeqK- of data block is set in S004 and is included the following steps:
A000: K-1 access list LinkSeqK- is judged whether there is；If so, executing A002；If it is not, then executing
A001；
A001: setting K-1 access list LinkSeqK- of data block simultaneously executes A002；
A002: judge whether K access list LinkSeqK has data block；If so, executing A003；If it is not, then executing
A004；
A003: data block in K access list LinkSeqK is stored according to enqueue time sequencing to K-1 Access Column
In table LinkSeqK-；
A004: the data block in S002 is entered in list LinkSeqK- and executes S002.
It is worth noting that, included each unit is only drawn according to function logic in the above system embodiment
Point, but be not limited to the above division, as long as corresponding functions can be realized；In addition, each functional unit is specific
Title is also only for convenience of distinguishing each other, the protection scope being not intended to restrict the invention.
In addition, those of ordinary skill in the art will appreciate that realizing all or part of the steps in the various embodiments described above method
It is that relevant hardware can be instructed to complete by program.
Present invention disclosed above preferred embodiment is only intended to help to illustrate the present invention.There is no detailed for preferred embodiment
All details are described, are not limited the invention to the specific embodiments described.Obviously, according to the content of this specification,
It can make many modifications and variations.These embodiments are chosen and specifically described to this specification, is in order to better explain the present invention
Principle and practical application, so that skilled artisan be enable to better understand and utilize the present invention.The present invention is only
It is limited by claims and its full scope and equivalent.
Claims (5)
1. a kind of caching method of the LRU-K algorithm based on K value dynamic monitoring, which comprises the steps of:
S000: setting data block access list LinkSeq；
S001: setting K access list LinkSeqK of data block；
S002: judge to access whether data block reaches K times；If so, executing S003；S006 is executed if not；
S003: judge whether access list LinkSeqK is full；If so, executing S005；If it is not, then executing S004；
S004: judge whether K access data block frequency is lower than lower threshold Ldown；If so, data block K-1 times visit of setting
Ask list LinkSeqK-；If it is not, then executing S006；
S005: judge whether K access data block frequency is more than upper limit threshold Lup；If so, data block K+1 times access of setting
List LinkSeqK+；If it is not, then executing S006；
S006: the data block in S002 is entered in list LinkSeqK and executes S002；
Wherein, K-1 is more than or equal to 2.
2. a kind of caching method of LRU-K algorithm based on K value dynamic monitoring according to claim 1, which is characterized in that
The data block access list LinkSeq accesses data block according to LEU algorithm.
3. a kind of caching method of LRU-K algorithm based on K value dynamic monitoring according to claim 1, which is characterized in that
Storing data block meets system access data block number and is more than or equal to K times in the K access list LinkSeqK；
Storing data block meets system access data block number and is more than or equal to K-1 in the K-1 access list LinkSeqK-
It is secondary；
Storing data block meets system access data block number and is more than or equal to K+1 in the K+1 access list LinkSeqK+
It is secondary.
4. a kind of caching method of LRU-K algorithm based on K value dynamic monitoring according to claim 1, which is characterized in that
The lower threshold Ldown is the ratio that the preset data block for meeting K access times of system accounts for total access times
Minimum value；
The upper limit threshold Lup is that the preset data block for meeting K access times of system accounts for the ratio of total access times most
Big value.
5. a kind of caching method of LRU-K algorithm based on K value dynamic monitoring according to claim 1, which is characterized in that
K-1 access list LinkSeqK- of data block is arranged in S004 to include the following steps:
A000: K-1 access list LinkSeqK- is judged whether there is；If so, executing A002；If it is not, then executing A001；
A001: setting K-1 access list LinkSeqK- of data block simultaneously executes A002；
A002: judge whether K access list LinkSeqK has data block；If so, executing A003；If it is not, then executing A004；
A003: data block in K access list LinkSeqK is stored according to enqueue time sequencing to K-1 access list
In LinkSeqK-；
A004: the data block in S002 is entered in list LinkSeqK- and executes S002.
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Application publication date: 20181218 |