The Empirical Discovery of Near-Optimal Offline Cache Replacement Policies for Nonuniform Objects

Author(s):  
Thepparit Banditwattanawong
Author(s):  
Stefani S. Pires ◽  
Adriana V. Ribeiro ◽  
Antonio M. de Sousa ◽  
Allan E. S. Freitas ◽  
Leobino N. Sampaio

2019 ◽  
Vol 14 (1) ◽  
pp. 1-87
Author(s):  
Akanksha Jain ◽  
Calvin Lin

2021 ◽  
Vol 11 (3) ◽  
pp. 250-255
Author(s):  
Yinyin Wang ◽  
◽  
Yuwang Yang ◽  
Qingguang Wang

An efficient intelligent cache replacement policy suitable for picture archiving and communication systems (PACS) was proposed in this work. By combining the Support vector machine (SVM) with the classic least recently used (LRU) cache replacement policy, we have created a new intelligent cache replacement policy called SVM-LRU. The SVM-LRU policy is unlike conventional cache replacement policies, which are solely dependent on the intrinsic properties of the cached items. Our PACS-oriented SVM-LRU algorithm identifies the variables that affect file access probabilities by mining medical data. The SVM algorithm is then used to model the future access probabilities of the cached items, thus improving cache performance. Finally, a simulation experiment was performed using the trace-driven simulation method. It was shown that the SVM-LRU cache algorithm significantly improves PACS cache performance when compared to conventional cache replacement policies like LRU, LFU, SIZE and GDS.


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