摘要
针对命名数据网络(NDN)中典型LRU和FIFO缓存替换策略只考虑单一影响因素时间新进度,无法区分内容的请求频率是高是低,存在流行内容被非流行内容驱逐的问题,为实现高效的NDN缓存替换,提出了一种基于熵的概率缓存替换策略(EPR)。该策略在数据包原有格式基础上进行拓展,增加3个字段分别记录缓存内容大小、内容流行度和请求代价;然后使每个路由节点在需要替换数据包时,统计该节点所有数据包携带的这3个字段的信息,根据属性值和分配的属性权重计算每个数据包的熵权重值和替换概率;最后基于计算的替换概率进行缓存内容的替换。实验结果表明,相较于常见的NDN缓存替换策略,该策略能有效提高平均缓存命中率,降低平均请求时延。
In the named data network(NDN),the typical LRU and FIFO cache replacement strategy only considers the time and progress of a single influencing factor,and cannot distinguish whether the frequency of content requests is high or low,and there is a problem that popular content is expelled by non-popular content.In order to achieve efficient NDN cache replacement,an entropy-based probabilistic cache replacement strategy(EPR)was proposed.This strategy was expanded on the basis of the original format of the data packet,adding 3 fields to record the size of the cached content,content popularity and request cost,and making each routing node count the data carried by all the data packets of the node when it needs to replace the data packet.Based on the information of these three fields,the entropy weight value and replacement probability of each data packet were calculated according to the attribute value and the assigned attribute weight,and finally the cache content was replaced based on the calculated replacement probability.Experimental results show that compared with some common NDN cache replacement strategies,this strategy can effectively increase the average cache hit rate and reduce the average request latency.
作者
高全力
李庆敏
高岭
王西汉
胡发丽
GAO Quanli;LI Qingmin;GAO Ling;WANG Xihan;HU Fali(School of Computer Science,Xi’an Polytechnic University,Xi’an 710048,China;National and Local Joint Engineering Center for New Network Intelligent InformationService,Xi’an Polytechnic University, Xi’an 710048,China)
出处
《西安工程大学学报》
CAS
2022年第2期87-93,共7页
Journal of Xi’an Polytechnic University
基金
国家自然科学基金青年科学基金(61902300)
陕西省重点产业创新链(群)项目(2020ZDLGY07-05)
山东省重点研发计划重大科技创新工程(厅市联合)项目(2019TSLH0209)。
关键词
命名数据网络
缓存替换
信息熵
缓存命中率
named data network
cache replacement
information entropy
cache hit rate
