CN109451344A - P2p流媒体系统中基于关联规则的缓存替换方法 - Google Patents
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Abstract
P2P流媒体系统中基于关联规则的缓存替换方法,属于P2P流媒体技术领域,主要是根据用户的历史播放记录,推断出用户的兴趣爱好,即用关联规则找出用户进行VCR操作时的规律,事先将热点视频存入超级节点,以提高用户要观看的视频正好存储在缓存中的概率。
Description
技术领域
本发明属于P2P流媒体技术领域,主要是根据用户的历史播放记录,推断出用户的兴趣爱好,即用关联规则找出用户进行VCR操作时的规律,事先将热点视频存入超级节点,以提高用户要观看的视频正好存储在缓存中的概率。
背景技术
流媒体是应用流式传输技术在网络上传播音频、视频或多媒体文件。流媒体应用的一个最大好处是用户不需要花费很长时间将数据全部下载到本地才能播放,而只需要将起始几秒的数据先下载到本地的缓冲区中就可以开始播放,然后边下载边播放,当网络实际连线速度小于播放所耗用资源的速度时,播放程序就会取用这一小段缓冲区的资料,避免播放中断,也使播放品质得以维持。因此,设计一种有效的缓存替换算法具有重要的意义。
在本发明提出之前,P2P流媒体缓存替换领域,最开始使用LRU、LFU、FIFO策略来替换,再到后来根据视频段的流行度来替换,用这些方法进行缓存替换的缺点有:
(1)将上一次访问时间作为决定是否缓存的唯一标准,会导致流行度较高或者系统中预先分发的视频段被删除,并且容易发生视频段刚刚被替换出去又被请求使用的状况,不适用于当前的服务需求。
(2)根据视频段的访问频率来计算缓存的价值,倾向于缓存请求量较高的视频段,存在缓存污染的问题,即访问频率较高的视频段即使不再被访问,依然占据着缓存空间。
(3)虽然在考虑视频流行度的同时提高了命中率,却增加了网络的流量,故存在副本不均匀的问题。
发明内容
本发明的目的就在于克服上述缺陷,研制P2P流媒体系统中基于关联规则的缓存替换方法。
P2P流媒体系统中基于关联规则的缓存替换方法,其主要技术特征在于如下步骤:
(1)获取用户的历史访问记录;
(2)计算每个视频段出现的频率,用关联规则找出支持度最高的3个段,即为待缓存段;
(3)进行缓存替换。本发明提出了两种缓存替换方法:基于关联规则的选择替换方法CRA-AR和基于关联规则的先进先出替换方法FIFO-AR。在CRA-AR中,首先用关联规则预测待缓存段,然后判断待缓存的视频段是否在超级节点中,得到缓存列表cache list,存在则cache(1,i)=1,不存在则cache(1,i)=0;其中i表示第i个待缓存视频段的标号。再有选择地进行缓存替换,当超级节点还有剩余空间时,直接将待缓存视频段存入超级节点,当超级节点没有剩余空间时,则将超级节点中流行度最低的视频段替换掉,如果流行度最低的视频段不止一个,则替换掉最先缓存的视频段。在FIFO-AR中,同样先用关联规则预测待缓存段,然后判断待缓存的视频段是否在超级节点中,得到缓存列表cache list,存在则cache(1,i)=1,不存在则cache(1,i)=0;其中i表示第i个待缓存视频段的标号。再按先进先出进行缓存替换,当超级节点还有剩余空间时,直接将待缓存视频段存入超级节点,当超级节点没有剩余空间时,则将超级节点中先进来的视频段先替换,后进来的视频段后替换。
(4)完成缓存替换操作后,计算请求视频段的响应时间;
(5)用户访问超级节点,计算命中率。
所述步骤(1)根据用户的历史播放记录,构建用户矩阵;通过步骤(2)推断出用户的兴趣爱好,即用关联规则找出用户进行VCR操作时的规律。
所述步骤(3)事先将热点内容存入超级节点,以提高用户要观看的视频正好在缓存中的概率;通过步骤(4)计算响应时间;通过步骤(5)计算命中率。
命中率是衡量缓存替换算法性能的标准,命中率越高,替换策略就越好。本发明的命中率是指超级节点在进行缓存替换后,用户即将要看的视频段存储在超级节点中的概率。使用命中率矩阵(MZ)存储超级节点中视频段的命中情况,如果命中,则置1;如果没有命中,则置0。其中i表示第i个用户节点(Userpeer),j表示用户节点中即将要观看的第j个视频段。假设有M个用户节点,每个用户节点有N个预选视频段。则命中率为:
本发明的优点和有益效果在于根据视频的流行度,结合数据挖掘中的关联规则对用户的喜好进行预测,具有较高的命中率。
在P2P流媒体点播系统中,用户可进行VCR操作,即可随时进行快进、快退等跳转。本发明在综合现有P2P视频点播系统的基础上进行了改进。因为要想能够很好地实现VCR交互式操作,最好将视频段预先取到缓存中。然而,用户的带宽是有限的,在保证视频正常播放的情况下,不能另外下载过多的数据,而且用户也不愿意自己的缓存空间被过多占用,因此需要采用关联规则找出用户进行VCR操作时的规律,有选择地预取。本发明给出节点的播放记录,超级节点通过这些播放记录,根据关联规则得出待缓存的段。再结合流行度进行段缓存和段替换,结果表明该技术可以提高视频段的命中率,降低响应时延,使用户得到更好的体验,扩展了该技术在流媒体领域的应用范围和实用性。
附图说明
图1——本发明中步骤(2)中支持度曲线;
图2——本发明方法的系统流程示意图;
图3(a)、图3(b)——本发明与其他方法在用户正常访问时的命中率比较图;
图4(a)、图4(b)——本发明与其他方法在用户非正常访问时的命中率比较图;
图5——本发明与其他方法的用户响应时间比较图。
具体实施方式
本发明的技术思路是:
P2P流媒体点播系统主要由3个部分组成:源服务器(Source server)、超级节点(Super node)、用户节点(User node)。设置参数模型如下:
(1)节点的播放记录Playback record:节点在播放视频段时,会将记录保存下来,即用户过去一段时间内所访问的段序号,形成一个记录列表,通过关联规则找出用户进行VCR操作时的规律,有选择地预取待缓存的视频段。
(2)用户节点User node:部分用户在观看视频时,会进行前进、倒退、暂停等VCR操作,他们通常只观看自己感兴趣的视频段或热点视频段。用户节点里存储着用户即将要访问的视频段序号。
(3)超级节点Super node:超级节点用来存储预先缓存的视频段。在获取待缓存段后,若超级节点的空间足够,则直接存储待缓存的视频段;若超级节点的空间不够,则将流行度最低的视频段替换出去,腾出一段缓存空间,用来存待缓存的视频段。如果流行度最低的视频段不止一个,则替换掉最先缓存的视频段。
如图2所示,根据用户的历史播放记录,推断出用户的兴趣爱好,即用关联规则找出用户进行VCR操作时的规律,事先将热点视频存入超级节点。以提高用户要观看的视频正好存储在缓存中的概率。当用户请求视频段时,若视频在缓存中,则向用户返回视频段。在提高命中率的同时,还能保证数据传输的实时性。若出现视频不在缓存中的情况,则超级节点优先从邻居节点获取即将观看的视频。若邻居节点里没有该视频,则从其他超级节点或者服务器获取,然后根据流行度进行缓存替换。最后用户访问超级节点并计算命中率。
在关联规则中,根据以往的用户访问记录,提取待缓存段,本发明提出的改进的关联规则如下表所示:
首先根据用户的历史访问记录,提取流行度最高的视频段,有时流行度最高的视频段有一个或多个。再从所有提取出的视频段中,找出支持度最高即出现频率最高的一个或多个视频段,如上表所示视频段8的支持度为4/7,视频段9的支持度为2/7,视频段10的支持度为1/7,所以选择视频段8进行缓存。
实施例:
本发明重点在于使用关联规则(AR)进行预取,为了验证本发明所提出的算法的性能,特地将本发明提出的基于关联规则的选择替换方法(CRA-AR)和基于关联规则的先进先出替换方法(FIFO-AR)分两种情况(用户正常访问和非正常访问)与基于流行度的先进先出替换方法(FIFO-P)和基于流行度的视频点播方法(VOVOP)进行比较。
从图3(a)中可看出,当用户正常访问时,用户访问满足泊松分布,流行度较高的段用户访问的概率就越大。CRA-AR将流行度较低的段替换成value列表中的段,可以有效提高超级节点中视频段的命中率。FIFO-AR将排在最前面的视频段替换出去,排在最前面的视频段也有可能是流行度较高的段,导致命中率略微下降。所以相比于FIFO-P,本发明提出的CRA-AR和FIFO-AR的命中率是有较大提升的。
在图3(b)中,VOVOP算法根据用户的访问记录,提取出现次数最多的段,但访问记录中的段出现频率与段全局出现频率有所差距,所以会影响到命中率。也可说明融入了关联规则的方法,相比于VOVOP有明显优势。
由图4(a)可知,当用户非正常访问时,用户访问随机性较高,波动较大,CRA-AR,FIFO-AR以及FIFO-P的命中率都有较大下降,低于0.67。其中CRA-AR的命中率略低于FIFO-AR,但是仍高于FIFO-P。
在图4(b)中,由于VOVOP算法对段流行度的依赖程度不高,所以命中率几乎维持不变,但仍低于本发明所提CRA-AR和FIFO-AR的命中率。由此可见,基于关联规则的缓存替换策略比传统的基于流行度的缓存替换策略性能更为优越。
图5为100个用户节点从超级节点中请求视频段时的总响应时间。从图5中可以看出,CRA-AR和FIFO-AR的响应时间基本持平,FIFO-P和VOVOP的响应时间偏高,所以本发明提出的融入了关联规则的缓存替换方法具有较低的响应时延和较高的命中率。
Claims (4)
1.P2P流媒体系统中基于关联规则的缓存替换方法,其特征在于,包括如下步骤:
(1)获取用户的历史访问记录;
(2)计算每个视频段出现的频率,用关联规则找出支持度最高的3个段,即为待缓存段;
(3)采用两种缓存替换方法进行缓存替换:
①基于关联规则的选择替换方法CRA-AR:首先用关联规则预测待缓存段,然后判断待缓存的视频段是否在超级节点中,得到缓存列表cache list,存在则cache(1,i)=1,不存在则cache(1,i)=0;其中i表示第i个待缓存视频段的标号;
再有选择地进行缓存替换,当超级节点还有剩余空间时,直接将待缓存视频段存入超级节点,当超级节点没有剩余空间时,则将超级节点中流行度最低的视频段替换掉,如果流行度最低的视频段不止一个,则替换掉最先缓存的视频段;
②基于关联规则的先进先出替换方法FIFO-AR:先用关联规则预测待缓存段,然后判断待缓存的视频段是否在超级节点中,得到缓存列表cache list,存在则cache(1,i)=1,不存在则cache(1,i)=0;其中i表示第i个待缓存视频段的标号;
再按先进先出进行缓存替换,当超级节点还有剩余空间时,直接将待缓存视频段存入超级节点,当超级节点没有剩余空间时,则将超级节点中先进来的视频段先替换,后进来的视频段后替换;
(4)完成缓存替换操作后,计算请求视频段的响应时间;
(5)用户访问超级节点,计算命中率。
2.根据权利要求1所述的P2P流媒体系统中基于关联规则的缓存替换方法,其特征在于,所述步骤(1)根据用户的历史播放记录,构建用户矩阵。
3.根据权利要求2所述的P2P流媒体系统中基于关联规则的缓存替换方法,其特征在于,通过步骤(2)推断出用户的兴趣爱好,即用关联规则找出用户进行VCR操作时的规律。
4.根据权利要求1所述的P2P流媒体系统中基于关联规则的缓存替换方法,其特征在于,所述步骤(3)事先将热点内容存入超级节点,以提高用户要观看的视频正好在缓存中的概率。
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