scholarly journals An Unifying Replacement Approach for Caching Systems

2007 ◽  
Vol 3 (4) ◽  
pp. 256
Author(s):  
Kai-Hau Yeung ◽  
Kin-Yeung Wong

A cache replacement algorithm called probability based replacement (PBR) is proposed in this paper. The algorithm makes replacement decision based on the byte accessprobabilities of documents. This concept can be applied to both small conventional web documents and large video documents. The performance of PBR algorithm is studied by both analysis and simulation. By comparing cache hit probability, hit rate and average time spent in three systems, it is shown that the proposed algorithm outperforms the commonly used LRU and LFU algorithms. Simulation results show that, when large video documents are considered, the PBR algorithm provides up to 120% improvement in cache hit rate when comparing to that ofconventional algorithms. The uniqueness of this work is that, unlike previous studies that propose different solutions for different types of documents separately, the proposed PBR algorithm provides a simple and unified approach to serve different types of documents in a single system.

2013 ◽  
Vol 433-435 ◽  
pp. 1702-1708
Author(s):  
Guo Yin Zhang ◽  
Bin Tang ◽  
Xiang Hui Wang ◽  
Yan Xia Wu

In-network caching is one of the key aspects of content-centric networks (CCN), while the cache replacement algorithm of LRU does not consider the relation between the cache contents and its neighbor nodes in the cache replacement process, which reduced the efficiency of the cache. In this paper, a Neighbor-Referencing Cooperative Cache Policy (NRCCP) in CCN has been proposed to check whether the neighbors have cached the content. Node will cache the content while none of its neighbors has cached it, therefore reduce redundancy of cached content and increase the variety of contents. Simulation results show that NRCCP has better performance, as the network path had more caching ability and more content popularity densely distributed.


InterConf ◽  
2021 ◽  
pp. 333-346
Author(s):  
Andriy Аrtikula ◽  
Dmytro Britov ◽  
Volodymyr Dzhus ◽  
Borys Haibadulov ◽  
Anastasiia Haibadulova ◽  
...  

Modern wide development of science and technology causes the growth of information needs in all branches of human development. At present, there are all opportunities to increase information security by combining sources of information into a single system. At the same time, when merging, specific difficulties and features emerge, which together make it difficult to implement the proposed solutions. The paper considers the peculiarity of combining different types of radar stations into a single information system. Errors of measurements of separate parameters and their influence on system characteristics are considered. Options for solving the problems that have arisen are proposed.


2006 ◽  
Vol 11 (5) ◽  
pp. 1141-1146
Author(s):  
Zhu Jiang ◽  
Shen Qingguo ◽  
Tang Tang ◽  
Li Yongqiang

2019 ◽  
Vol 30 (08) ◽  
pp. 1950052
Author(s):  
Feng Hu ◽  
Jin-Li Guo ◽  
Fa-Xu Li ◽  
Hai-Xing Zhao

Hypernetworks are ubiquitous in real-world systems. They provide a powerful means of accurately depicting networks of different types of entity and will attract more attention from researchers in the future. Most previous hypernetwork research has been focused on the application and modeling of uniform hypernetworks, which are based on uniform hypergraphs. However, random hypernetworks are generally more common, therefore, it is useful to investigate the evolution mechanisms of random hypernetworks. In this paper, we construct three dynamic evolutional models of hypernetworks, namely the equal-probability random hypernetwork model, the Poisson-probability random hypernetwork model and the certain-probability random hypernetwork model. Furthermore, we analyze the hyperdegree distributions of the three models with mean-field theory, and we simulate each model numerically with different parameter values. The simulation results agree well with the results of our theoretical analysis, and the findings indicate that our models could help understand the structure and evolution mechanisms of real systems.


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