期刊文献+
共找到6篇文章
< 1 >
每页显示 20 50 100
Content Popularity Prediction via Federated Learning in Cache-Enabled Wireless Networks
1
作者 YAN Yuna LIU Ying +2 位作者 NI Tao LIN Wensheng LI Lixin 《ZTE Communications》 2023年第2期18-24,共7页
With the rapid development of networks,users are increasingly seeking richer and high-quality content experience,and there is an urgent need to develop efficient content caching strategies to improve the content distr... With the rapid development of networks,users are increasingly seeking richer and high-quality content experience,and there is an urgent need to develop efficient content caching strategies to improve the content distribution efficiency of caching.Therefore,it will be an effective solution to combine content popularity prediction based on machine learning(ML)and content caching to enable the network to predict and analyze popular content.However,the data sets which contain users’private data cause the risk of privacy leakage.In this paper,to address this challenge,we propose a privacy-preserving algorithm based on federated learning(FL)and long short-term memory(LSTM),which is referred to as FL-LSTM,to predict content popularity.Simulation results demonstrate that the performance of the proposed algorithm is close to the centralized LSTM and better than other benchmark algorithms in terms of privacy protection.Meanwhile,the caching policy in this paper raises about 14.3%of the content hit rate. 展开更多
关键词 content popularity prediction privacy protection federated learning long short-term memory
下载PDF
Analysis and Prediction of Content Popularity for Online Video Service:A Youku Case Study 被引量:4
2
作者 Chenyu Li Jun Liu Shuxin Ouyang 《China Communications》 SCIE CSCD 2016年第12期216-233,共18页
Understanding the characteristics and predicting the popularity of the newly published online videos can provide direct implications in various contexts such as service design, advertisement planning, network manageme... Understanding the characteristics and predicting the popularity of the newly published online videos can provide direct implications in various contexts such as service design, advertisement planning, network management and etc. In this paper, we collect a real-world large-scale dataset from a leading online video service provider in China, namely Youku. We first analyze the dynamics of content publication and content popularity for the online video service. Then, we propose a rich set of features and exploit various effective classification methods to estimate the future popularity level of an individual video in various scenarios. We show that the future popularity level of a video can be predicted even before the video's release, and by introducing the historical popularity information the prediction performance can be improved dramatically. In addition, we investigate the importance of each feature group and each feature in the popularity prediction, and further reveal the factors that may impact the video popularity. We also discuss how the early monitoring period influences the popularity level prediction. Our work provides an insight into the popularity of the newly published online videos, and demonstrates promising practical applications for content publishers,service providers, online advisers and network operators. 展开更多
关键词 online content popularity online video service popularity characterization popularity prediction
下载PDF
Exploring Content Popularity in Information-Centric Networks 被引量:1
3
作者 Andriana Ioannou Stefan Weber 《China Communications》 SCIE CSCD 2015年第7期13-22,共10页
Information-Centric Networking(ICN), an alternative architecture to the current Internet infrastructure, focuses on the distribution and retrieval of content by employing caches in a network to reduce network traffic.... Information-Centric Networking(ICN), an alternative architecture to the current Internet infrastructure, focuses on the distribution and retrieval of content by employing caches in a network to reduce network traffic. The employment of caches may be accomplished using graph-based and content-based criteria such as the position of a node in a network and content popularity. The contribution of this paper lies on the characterization of content popularity for on-path in-network caching. To this end, four dynamic approaches for identifying content popularity are evaluated via simulations. Content popularity may be determined per chunk or per object, calculated by the number of requests for a content against the sum of requests or the maximum number of requests. Based on the results, chunk-based approaches provide 23% more accurate content popularity calculations than object-based approaches. In addition, approaches that are based on the comparison of a content against the maximum number of requests have been shown to be more accurate than the alternatives. 展开更多
关键词 network distributed architectures future internet information-centric networks caching technologies on-path caching content popularity
下载PDF
A Cache Replacement Policy Based on Multi-Factors for Named Data Networking 被引量:1
4
作者 Meiju Yu Ru Li Yuwen Chen 《Computers, Materials & Continua》 SCIE EI 2020年第10期321-336,共16页
Named Data Networking(NDN)is one of the most excellent future Internet architectures and every router in NDN has the capacity of caching contents passing by.It greatly reduces network traffic and improves the speed of... Named Data Networking(NDN)is one of the most excellent future Internet architectures and every router in NDN has the capacity of caching contents passing by.It greatly reduces network traffic and improves the speed of content distribution and retrieval.In order to make full use of the limited caching space in routers,it is an urgent challenge to make an efficient cache replacement policy.However,the existing cache replacement policies only consider very few factors that affect the cache performance.In this paper,we present a cache replacement policy based on multi-factors for NDN(CRPM),in which the content with the least cache value is evicted from the caching space.CRPM fully analyzes multi-factors that affect the caching performance,puts forward the corresponding calculation methods,and utilize the multi-factors to measure the cache value of contents.Furthermore,a new cache value function is constructed,which makes the content with high value be stored in the router as long as possible,so as to ensure the efficient use of cache resources.The simulation results show that CPRM can effectively improve cache hit ratio,enhance cache resource utilization,reduce energy consumption and decrease hit distance of content acquisition. 展开更多
关键词 Cache replacement policy named data networking content popularity FRESHNESS energy consumption
下载PDF
Analyzing the dynamics of online video popularity 被引量:2
5
作者 Ouyang Shuxin Li Chenyu Li Xueming 《The Journal of China Universities of Posts and Telecommunications》 EI CSCD 2017年第3期58-69,共12页
Given the large volume of video content and the diversity of user attention, it is of great importance to understand the characteristics of online video popularity for technological, economic and social reasons. In th... Given the large volume of video content and the diversity of user attention, it is of great importance to understand the characteristics of online video popularity for technological, economic and social reasons. In this paper, based on the data collected from a leading online video service provider in China, namely Youku, the dynamics of online video popularity are analyzed in-depth from four key aspects: overall popularity distribution, individual popularity distribution, popularity evolution pattern and early-future popularity relationship. How the popularity of a set of newly upload videos distributes throughout the observation period is first studied. Then the notion popularity distributions of individual videos are carefully studied. of active days is proposed, and the per-day and per-hour Next, how the popularity of an individual video evolves over time is investigated. The evolution patterns are further defined according to the number and temporal locations of popularity bursts, in order to describe the popularity growth trend. At last, the linear relationship between early video popularity and future video popularity are examined on a log-log scale. The relationship is found to be largely impacted by the popularity evolution patterns. Therefore, the specialized models are proposed to describe the correlation according to the popularity evolution patterns. Experiment results show that specialized models can better fit the correlation than a general model. Above all, the analysis results in our work can provide direct help in practical for the interested parties of online video service such as service providers, online advisers, and network operators. 展开更多
关键词 online video service online content popularity popularity evolution pattern early-future popularity relationship
原文传递
Joint model of user check-in activities for point-of-interest recommendation
6
作者 Ren Xingyi Song Meina +1 位作者 E Haihong Song Junde 《The Journal of China Universities of Posts and Telecommunications》 EI CSCD 2016年第4期25-36,共12页
With the rapid development of location-based networks, point-of-interest(POI) recommendation has become an important means to help people discover interesting and attractive locations, especially when users travel o... With the rapid development of location-based networks, point-of-interest(POI) recommendation has become an important means to help people discover interesting and attractive locations, especially when users travel out of town. However, because users only check-in interaction is highly sparse, which creates a big challenge for POI recommendation. To tackle this challenge, we propose a joint probabilistic generative model called geographical temporal social content popularity(GTSCP) to imitate user check-in activities in a process of decision making, which effectively integrates the geographical influence, temporal effect, social correlation, content information and popularity impact factors to overcome the data sparsity, especially for out-of-town users. Our proposed the GTSCP supports two recommendation scenarios in a joint model, i.e., home-town recommendation and out-of-town recommendation. Experimental results show that GTSCP achieves significantly superior recommendation quality compared to other state-of-the-art POI recommendation techniques. 展开更多
关键词 POI recommendation user check-in activities joint probabilistic generative model geographical influence social influence temporal effect content information popularity information
原文传递
上一页 1 下一页 到第
使用帮助 返回顶部