CN108900570B - Cache replacement method based on content value - Google Patents
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Abstract
The invention discloses a cache replacement method based on content value, which comprises the steps of counting the popularity of content, calculating the cache cost of each content, calculating the time interval between the last accessed time of the content and the current time, and calculating the value of each content in a cache space and replacing the minimum value of the value. The invention not only can cache the content with high popularity in advance, but also has good response to the content with high caching cost, thereby effectively improving the accuracy of node data replacement, being beneficial to improving the data transmission efficiency of a content center network and improving the internet experience of users.
Description
Technical Field
The invention relates to a cache replacement method, in particular to a cache replacement method based on content value, and belongs to the technical field of communication.
Background
With the rapid development of Internet technology, the number of network information and user Internet access devices has increased dramatically, resulting in exponential growth of network traffic, and this explosive traffic growth brings huge challenges and pressure to an Internet Protocol (IP) network architecture based on end-to-end interconnection between networks. In order to solve the impact caused by huge data traffic in the mobile network, researchers have proposed a Content-Centric Networking (CCN), which is a completely new network architecture with Content as the center. In the content-centric network, each node has a caching function, and popular content is cached on a node close to a user for a long time, so that the pressure of the bandwidth of a return link can be effectively relieved, and the network delay is reduced, thereby improving the experience quality of the user.
However, the cache capacity of each node is limited, and when the cache space is occupied, the less valuable contents in the cache must be cleaned out according to a certain replacement policy, and new meaningful data is stored to improve the request hit rate of the cache space, so that it can be seen that it is critical to reasonably manage and replace the cache contents to affect the overall performance of the network.
Conventional cache replacement algorithms include a First In First Out (FIFO) algorithm, a least recently used (LFU) algorithm, a Least Recently Used (LRU) algorithm, and a content SIZE replacement (SIZE) algorithm. The FIFO replaces the data which is firstly input into the cache space according to the first-in first-out rule of the queue, and the algorithm is low in complexity and easy to implement, but the request hit rate is low. The LRU algorithm always replaces the least recently accessed resource out of the cache, considers that the probability of the recently accessed data being accessed in the near future is high, only considers the replacement data from the latest request time, and reduces the adaptive performance when the content popularity distribution changes. By counting the access frequency of the cache contents in a past period of time, the LFU replacement strategy considers that the use value of the resource with high frequency is higher, so when the cache space is insufficient, the content with the lowest access frequency is always replaced, and the algorithm also has the cache pollution problem, namely the content with high access frequency in the past occupies the cache space even if the content is not accessed any more at present, so that the utilization rate of the cache space is reduced. The SIZE algorithm replaces data according to the SIZE of the content, and preferentially replaces the data with large byte number, but the algorithm does not consider factors such as access time interval, cache hit times and the like, so that small byte objects with low value can be reserved in a cache space for a long time, and the hit rate is reduced.
The design of the above algorithm shows a little bit of detail, and a single objective function is adopted to determine that the cache replacement object can not meet diversified network data requirements. The least recently used and least recently used replacement algorithm (LFRU) combines an LRU and an LFU algorithm that comprehensively considers the request frequency and the time of the most recent access of the content, but does not consider the global popularity of the content. The Greedy-Dual Size (GDS) based on Size considers the Size of the object, the caching cost and the age factor of the content comprehensively, and sets a weight for each file of the caching space, and replaces the object with the smallest weight each time, but the GDS does not consider the number of times the caching object was accessed in the past. MaT et al propose an improved Weighted Greedy Dual (WGDSF) cache replacement strategy based on size and frequency, which adds a time-based Weighted frequency parameter and a Weighted file type parameter on the basis of a GDS algorithm, although the performance is improved, the algorithm complexity is greatly increased. The Ant Colony Algorithm-based Cache Replacement Algorithm (ACACRA) Algorithm is characterized in that the size of a data object is used for representing the weight of a backpack, the average requested times of the object are used for representing the storage value, and the Replacement content is determined by using an Ant Colony Algorithm for solving a backpack problem of 0/1, but the Algorithm is high in complexity and is suitable for an application layer of a computer.
In summary, those skilled in the art need to solve the above-mentioned problems in order to reasonably replace the cache contents when the cache space is limited.
Disclosure of Invention
The invention aims to solve the defects of the prior art, and provides a cache replacement method based on content value. The scheme can effectively improve the cache hit rate and reduce the average hop count of the data acquired by the user.
The technical solution of the invention is as follows:
a cache replacement method based on content value is characterized by comprising the following steps:
s1: counting and updating the popularity of the content in each period, and calculating the popularity of the content in the current period according to the popularity of the content in the last period and the hit rate of the content in the period;
s2: calculating the caching cost of each content according to the node, wherein the caching cost comprises transmission cost and caching cost, and the transmission cost of the content is greater than the caching cost; the calculation formula of the cache cost is as follows:
wherein, HoprRepresenting the number of hops the content r is from the origin server,
representing transmission of content r in single hopThe cost of the transportation is reduced,
represents the caching cost of the content r;
s3: designing a time tag in a cache space, recording the latest access time of the content by using the time tag, and then calculating the time interval between the latest access time of the content and the current time;
s4: according to the popularity in the step S1, the caching cost in the step S2 and the latest access time interval in the step S3, the value of each content in the caching space is calculated, and when the caching space is insufficient, the node replaces the minimum value of the value.
Preferably, the calculation formula of the popularity in the step S1 is:
pr(t)＝αpr(t-1)+(1-α)hr(t)
where r is the number of the content in the cache space, pr(t) denotes the popularity of the content r in the current period, pr(t-1) represents the popularity of the content r in the previous period, alpha is an attenuation factor, and is the proportion of the popularity of the previous period in the current period, 0 < alpha < 1, hr(t) represents the hit rate of the content r in the current cycle, Nr(t) represents the number of hits on the content r in the current cycle, NQAnd (t) represents the total number of requests received by the node in the current period.
Preferably, the calculation formula of the time interval in step S3 is:
tinter＝tcur-told
wherein, tinterTime interval, t, representing the time at which the content was last accessed and the current timecurRepresenting the current time, toldIndicating the time at which the content was last requested.
Preferably, the calculation formula of the value in step S4 is:
Preferably, the packet types of the contents in the step S1, the step S2, the step S3 and the step S4 include interest packets and data packets.
Preferably, the interest package includes a name of the requested content, is issued by the requesting client, is transmitted to a neighboring node or an origin server having the requested resource, and generates a corresponding data package;
the data package includes the data object, the content name, and the publisher's signature information and is transmitted to the user along the reverse path of the interest package.
Preferably, the nodes in the steps S2 and S4 include a content storage, a forwarding information base and a pending request table.
Preferably, the content store stores data arriving on the node, the cached content satisfying future requests for the data; the target field of the forwarding information base is a prefix of the content name; the pending request table records the routing state information being transmitted.
The invention provides a cache replacement method based on content value, which can dynamically update the popularity of content according to the access behavior of a user, and adjust the popularity of the content and the proportion of cache cost in a value function in real time by utilizing the request time interval of the content, thereby not only caching the content with high popularity in advance, but also having good response to the content with high cache cost, thereby effectively improving the accuracy of node data replacement, being beneficial to improving the data transmission efficiency of a content center network and improving the internet experience of the user.
The following detailed description of the embodiments of the present invention is provided in connection with the accompanying drawings for the purpose of facilitating understanding and understanding of the technical solutions of the present invention.
Drawings
FIG. 1 is a flow chart of an embodiment of the present invention;
FIG. 2 is a flow chart of the process of interest package in the present invention;
fig. 3 is a flow chart of the packet processing in the present invention.
Detailed Description
A cache replacement method based on content value comprises the following steps:
s1: counting and updating the popularity of the content in each period, and calculating the popularity of the content in the current period according to the popularity of the content in the last period and the hit rate of the cache content in the period;
the popularity calculation formula is as follows: p is a radical ofr(t)＝αpr(t-1)+(1-α)hr(t)
Where r is the number of the content in the cache space, pr(t) popularity of the content r in the current period, pr(t-1) is the popularity of the content r in the previous period, alpha is an attenuation factor, and is the proportion of the popularity of the previous period in the current period, alpha is more than 0 and less than 1, hr(t) represents the hit rate of the content r in the current cycle, Nr(t) represents the number of hits on the content r in the current cycle, NQAnd (t) represents the total number of requests received by the node in the current period.
S2: calculating the caching cost of each content according to the nodes; the caching cost comprises transmission cost and caching cost, and the transmission cost of the content is greater than the caching cost; the calculation formula of the cache cost is as follows:
wherein, HoprIndicating Hop count, Hop, of content r from the origin serverrThe larger, the higher the transmission cost, the greater the storage value of the content,
representing the transmission cost of a single hop of the content r,
representing the caching cost of the content r.
S3: designing a time tag in a cache space, recording the latest access time of the content by using the time tag, and then calculating the time interval between the latest access time of the content and the current time; the calculation formula of the time interval is as follows: t is tinter＝tcur-toldWherein, tinterTime interval, t, representing the time at which the content was last accessed and the current timecurRepresenting the current time, toldIndicating the time at which the content was last requested.
S4: according to the popularity in the step S1, the caching cost in the step S2 and the latest access time interval in the step S3, the value of each content in the caching space is calculated, and when the caching space is insufficient, the node replaces the minimum value of the value. The value is calculated as:
In the technical solution of the present invention, the packet types of the contents in the step S1, the step S2, the step S3, and the step S4 include an interest packet (interest packet) and a data packet (data packet), the interest packet includes a name of the requested content, is sent by the requesting client, is transmitted to a neighboring node or an origin server having the requested resource, and generates a corresponding data packet; the data package includes the data object, the content name, and the publisher's signature information and is transmitted to the user along the reverse path of the interest package.
The nodes in the steps S2 and S4 include a Content Store (CS), a Forwarding Information Base (FIB), and a Pending request Table (PIT), where the Content Store stores data arriving at the node, and the cached Content satisfies a future request for the data; the target field of the forwarding information base is a prefix of the content name; the pending request table records the routing state information being transmitted.
In order to better explain the technical scheme of the invention, the following detailed description of the specific embodiments of the invention is provided in conjunction with the accompanying drawings.
The CCN is no longer concerned with where the content is stored, but only with the data itself, the data packet in this structure is identified by the content name rather than the traditional IP address, and the CCN includes two packet types: interest packets and data packets. The interest packet is sent by the requesting client, wherein the name of the requested content is carried, but the destination address is not contained, after the interest packet is routed to the adjacent node or the source server with the requested resource, a corresponding data packet is generated, the data packet carries the data object, the content name and the signature information of the publisher, and the data packet is transmitted to the user along the reverse path of the interest packet.
The nodes of the CCN include CS, FIB and PIT. The CS stores data objects arriving on the node and the cached content can be used to satisfy future requests for the data, thereby reducing duplicate transfers of content. FIB is similar to an IP routing table in a conventional Transmission Control Protocol/Internet Protocol (TCP/IP) network architecture, but the target field is a prefix of a content name. The PIT records the routing state information being transmitted. As shown in fig. 1, when an interest packet arrives at a node, it is first queried whether the CS stores content corresponding to the interest packet, and if so, the content is directly sent to a requester along the arrival path of the interest packet, and the interest packet is discarded. If the cache does not have the content, the node continuously inquires whether an entry corresponding to the content name exists in the PIT, if so, the request interface is added into a corresponding interface list, then the request interest packet is discarded, otherwise, a new PIT entry is created and the FIB is inquired, the interest packet is forwarded to the adjacent CCN node according to the matched port, and if the FIB does not have the matched entry, the interest packet is discarded or forwarded to the default port.
As shown in fig. 2, when a packet arrives, a node queries whether an entry corresponding to the content exists in the PIT, and if so, forwards the data content from an interface list of the entry, deletes the corresponding PIT entry, and then stores the data in the CS according to a corresponding cache replacement policy.
In the CCN, the popularity of the content can well reflect the demand condition of the user on the content. The popularity of file content in the network always changes continuously due to the time-varying data requests of users, for example, some content in the cache is highly concerned by the users in the current time period, the popularity is high, but as time passes, the content is likely to become objects which are less accessed by the users, and the popularity is reduced. Therefore, the popularity of the content stored on the nodes in the network is dynamically changed under the influence of the access behavior of the user, i.e. the popularity of the content needs to be updated statistically in each period. In order to accurately predict the change of the content, a counter is designed for each item of content in the cache space in each router node, and is used for counting the number of times the content is hit in each period, and a total counter is designed for counting the total number of requests received by the node. Then based on an exponential weighted moving average algorithm (EWMA), calculating the popularity of the content in the current period according to the popularity of the content in the last period and the hit rate of the content in the current period, wherein the calculation formula of the popularity is as follows: p is a radical ofr(t)＝αpr(t-1)+(1-α)hr(t)
Where r is the number of the content in the cache space, pr(t) denotes the popularity of the content r in the current period, pr(t-1) represents the popularity of the content r in the previous period, alpha is an attenuation factor, 0 < alpha < 1 and represents the proportion of the popularity of the previous period in the current period, hr(t) represents the hit rate of the content r in the current cycle, Nr(t) represents the number of hits on the content r in the current cycle, NQAnd (t) represents the total number of requests received by the node in the current period.
The larger the hop count of the node where the content is located from the content source server is, the lower the hop count of the request for obtaining the content by the user can be, so that the content farther from the source server is prevented from being replaced as much as possible in the cache replacement process. The cache cost mainly comprises two parts of transmission cost and cache cost, and the calculation formula is as follows:
wherein, HoprIndicating Hop count, Hop, of content r from the origin serverrThe larger, the higher the transmission cost, the greater the storage value of the content,
representing the transmission cost of a single hop of the content r,
representing the caching cost of the content r, the transmission cost of the content is much larger than its caching cost.
The invention designs a time label for each content in the node on the basis of the least recently used replacement algorithm to record the time when the content is accessed last time, and supposing that the current time is tcurThe time of the last request for content is toldAnd then: t is tinter＝tcur-toldTime interval tinterThe shorter the duration, the higher the frequency of requesting the content during the current time period, the storage value of the content depends mainly on the popularity of the content, and when the interval t is shorterinterThe longer the content is, the main factor affecting the value of the content is the caching cost of the content, and the popularity of the content is taken as a secondary factor. Based on the above analysis, the value formula of the content is:
it can be seen from the value formula of the content that if the data is frequently requested for a short time, the time interval tinterThe user has high attention to the content, which means that the popularity of the data object is high at the moment, and the data object is taken as a main factor influencing the value of the cached content, otherwiseSeparate tinterWhen the number of the content requested is large, the content is requested less frequently, the popularity of the content is reduced, and at this time, the caching cost of the content is taken as a main factor influencing the value function, and the popularity of the content is taken as a secondary influence factor. The cache replacement method utilizes the time interval of the requested content as the weight factor, and can adjust the popularity of the data and the proportion of the cache cost in the value function in real time, so that the content with high popularity can be cached in the nodes, the data with high request cost also has good response, and the data stored in the network is more reasonable.
Fig. 3 shows a specific algorithm flow in the present invention, when a node receives a request from a user, it first determines whether the requested object is in the CS, if so, it adds 1 to both the number of hits of the content and the total number of requests of the node, updates the request time of the content, and then directly sends the content to the user. If the content is not cached on the node, the interest packet is forwarded, the content is acquired from the adjacent node or the source server, and the content is sent to the user. Judging whether the node has enough space to cache the data object, if so, storing the content in the CS, initializing the hit times and request time of the content, and recording the hop number of the data packet arriving at the node. If the cache space is insufficient, the value of each content is calculated according to the popularity, the cache cost and the request time interval of the content in the current period, and the content is replaced from small to large according to the value until enough space is reserved for storing new content.
The cache replacement method based on the content value comprehensively considers the dynamic popularity, the cache cost and the recently requested time of the content, constructs a more actual content value function, and designs an effective content storage and replacement scheme according to the content value function. Specifically, when the updated cache content does not match the existing content, the existing cache content is replaced from small to large according to the value. Compared with the traditional algorithm, the method effectively improves the cache content hit rate of the network node and reduces the average hop count of the user for obtaining the content.
It should be noted that the above-mentioned embodiments illustrate rather than limit the invention, and that those skilled in the art will be able to design alternative embodiments without departing from the scope of the appended claims.
Claims (8)
1. A cache replacement method based on content value is characterized by comprising the following steps:
s1: counting and updating the popularity of the content in each period, and calculating the popularity of the content in the current period according to the popularity of the content in the last period and the hit rate of the content in the period;
s2: calculating the caching cost of each content according to the node, wherein the caching cost comprises transmission cost and caching cost, and the transmission cost of the content is greater than the caching cost; the calculation formula of the cache cost is as follows:
wherein, HoprRepresenting the number of hops the content r is from the origin server,
representing the transmission cost of a single hop of the content r,
represents the caching cost of the content r;
s3: designing a time tag in a cache space, recording the latest access time of the content by using the time tag, and then calculating the time interval between the latest access time of the content and the current time;
s4: according to the popularity in the step S1, the caching cost in the step S2 and the latest access time interval in the step S3, the value of each content in the caching space is calculated, and when the caching space is insufficient, the node replaces the minimum value of the value.
2. A content value-based cache replacement method according to claim 1, wherein: the calculation formula of the popularity in the step S1 is:
pr(t)＝αpr(t-1)+(1-α)hr(t)
where r is the number of the content in the cache space, pr(t) denotes the popularity of the content r in the current period, pr(t-1) represents the popularity of the content r in the previous period, alpha is an attenuation factor, and is the proportion of the popularity of the previous period in the current period, 0 < alpha < 1, hr(t) represents the hit rate of the content r in the current cycle, Nr(t) represents the number of hits on the content r in the current cycle, NQAnd (t) represents the total number of requests received by the node in the current period.
3. A content value-based cache replacement method according to claim 1, wherein: the calculation formula of the time interval in step S3 is:
tinter＝tcur-told
wherein, tinterTime interval, t, representing the time at which the content was last accessed and the current timecurRepresenting the current time, toldIndicating the time at which the content was last requested.
4. A content value-based cache replacement method according to claim 1, wherein: the calculation formula of the value in step S4 is:
5. A content value-based cache replacement method according to claim 1, wherein: the packet types of the content in the step S1, the step S2, the step S3, and the step S4 include interest packets and data packets.
6. A content value-based cache replacement method according to claim 5, wherein: the interest packet comprises the name of the requested content, is sent by the requesting client, is transmitted to a neighboring node or an origin server with the requested resource, and generates a corresponding data packet;
the data package includes the data object, the content name, and the publisher's signature information and is transmitted to the user along the reverse path of the interest package.
7. A content value-based cache replacement method according to claim 1, wherein: the nodes in steps S2, S4 include a content store, a forwarding information base, and a pending request table.
8. A content value-based cache replacement method according to claim 7, wherein: the content memory stores data arriving at the node, and the cached content satisfies future requests for the data; the target field of the forwarding information base is a prefix of the content name; the pending request table records the routing state information being transmitted.
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| CN110519394B (en) * | 2019-09-12 | 2022-02-15 | 广东工业大学 | Information cache replacement method, device, terminal and storage medium |
| CN111124298B (en) * | 2019-12-17 | 2021-05-11 | 河海大学 | Mist computing network content cache replacement method based on value function |
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