DC Field | Value | Language |
---|---|---|
dc.contributor.author | Sung, Jihoon | ko |
dc.contributor.author | Kim, Kyounghye | ko |
dc.contributor.author | Kim, Junhyuk | ko |
dc.contributor.author | Rhee, June-Koo Kevin | ko |
dc.date.accessioned | 2023-07-28T06:00:28Z | - |
dc.date.available | 2023-07-28T06:00:28Z | - |
dc.date.created | 2023-07-07 | - |
dc.date.created | 2023-07-07 | - |
dc.date.issued | 2016-12 | - |
dc.identifier.citation | 15th IEEE International Conference on Machine Learning and Applications, ICMLA 2016, pp.547 - 552 | - |
dc.identifier.uri | http://hdl.handle.net/10203/310943 | - |
dc.description.abstract | Wireless content delivery networks (WCDNs) have received attention as a promising solution to reduce the network congestion caused by rapidly growing demands for mobile content. The amount of reduced congestion is intuitively proportional to the hit ratio in a WCDN. Cooperation among cache servers is strongly required to maximize the hit ratio in a WCDN where each cache server is equipped with a small-size cache storage space. In this paper, we address a content replacement problem that deals with how to manage contents in a limited cache storage space in a reactive manner to cope with a dynamic content demand over time. As a new challenge, we apply reinforcement learning, which is Q-learning, to the content replacement problem in a WCDN with coooperative caching. We model the content replacement problem as a Markov Decision Process (MDP) and finally propose an efficient content replacement strategy to maximize the hit ratio based on a multi-agent Q-learning scheme. Simulation results exhibit that the proposed strategy contributes to achieving better content delivery performance in delay due to a higher hit ratio, compared to typical existing schemes of least recently used (LRU) and least frequently used (LFU). | - |
dc.language | English | - |
dc.publisher | Institute of Electrical and Electronics Engineers Inc. | - |
dc.title | Efficient content replacement in wireless content delivery network with cooperative caching | - |
dc.type | Conference | - |
dc.identifier.wosid | 000399100100087 | - |
dc.identifier.scopusid | 2-s2.0-85015359225 | - |
dc.type.rims | CONF | - |
dc.citation.beginningpage | 547 | - |
dc.citation.endingpage | 552 | - |
dc.citation.publicationname | 15th IEEE International Conference on Machine Learning and Applications, ICMLA 2016 | - |
dc.identifier.conferencecountry | US | - |
dc.identifier.conferencelocation | Anaheim, CA | - |
dc.contributor.localauthor | Rhee, June-Koo Kevin | - |
dc.contributor.nonIdAuthor | Kim, Junhyuk | - |
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