Abstract
Most vendors of e-commerce applications deploy the cache memory to deliver the web objects to clients faster. However, they face many problems in dealing with the cache memory due to limited resources and dynamic access patterns. As a result, we need to efficiently manage the cache memory by evicting the unused data. The performance of cache manager depends upon the efficiency of delete determination. In this paper, we propose ERF, a cache eviction policy using natural exponential function on time with frequency in order to cope with dynamic nature of e-commerce business with limited memory. It sorts the caches in the order of result value which come from coordination between frequency and recency and evicts the caches according to it. We evaluate the performance of ERF by using the workload which reflects the real-world applications and compare it with conventional algorithms. By increasing the cache hit ratio with ERF, we can expect the decrease of copy and delete operations of cache with improving the overall system performance.
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Acknowledgement
This research was supported by the MISP(Ministry of Science, ICT & Future Planning), Korea, under the National Program for Excellence in SW) supervised by the IITP(Institute for Information & communications Technology Promotion) (2015-0-00908)
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Lee, J.H., Kwon, S.J., Chung, TS. (2018). ERF: Efficient Cache Eviction Strategy for E-commerce Applications. In: Kim, K., Joukov, N. (eds) Mobile and Wireless Technologies 2017. ICMWT 2017. Lecture Notes in Electrical Engineering, vol 425. Springer, Singapore. https://doi.org/10.1007/978-981-10-5281-1_33
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DOI: https://doi.org/10.1007/978-981-10-5281-1_33
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