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Proactive Caching of Mobility Prediction Prefetch and Non-Prefetch in ICN
Arifin H.N.a, Yovita L.V.b, Syambas N.R.a
a School of Electrical Engineering and Informatics, Bandung Institute of Technology, Bandung, Indonesia
b School of Electrical Engineering, Telkom University, Indonesia
[vc_row][vc_column][vc_row_inner][vc_column_inner][vc_separator css=”.vc_custom_1624529070653{padding-top: 30px !important;padding-bottom: 30px !important;}”][/vc_column_inner][/vc_row_inner][vc_row_inner layout=”boxed”][vc_column_inner width=”3/4″ css=”.vc_custom_1624695412187{border-right-width: 1px !important;border-right-color: #dddddd !important;border-right-style: solid !important;border-radius: 1px !important;}”][vc_empty_space][megatron_heading title=”Abstract” size=”size-sm” text_align=”text-left”][vc_column_text]© 2019 IEEE.Efficiently storing content on the network is a very important thing to do at this time so that consumers can access easily the content on the network. One way to do this is to store content on the available routers, which is storing content on the router that has a high probability, it’s called proactive caching. This can reduce latency because it has stored content on the selected router. Proactive caching cellular networks depend on predicting user mobility to the next location and router retrieving content files. We present a proactive caching strategy that utilizes the flexibility of data caching Information-Centric Networking (ICN) anywhere in the network. The main contribution of this paper is to make a model using the Markov model to determine the best router to be prefetched. The results of this research showed that from several times the average experiment that had been prefetched, the total cache hits generated had a percentage of 76.4% compared to those not prefetched by 34%. This shows a 42.4% increase in selected router prefetched, a very significant amount for the effectiveness of accessing content on the network.[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Author keywords” size=”size-sm” text_align=”text-left”][vc_column_text]Cellular network,Data caching,High probability,Information-centric networkings (ICN),Markov model,Mobility predictions,Proactive caching,User mobility[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Indexed keywords” size=”size-sm” text_align=”text-left”][vc_column_text]ICN,Markov Model,Named Data Networking,Proactive caching[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Funding details” size=”size-sm” text_align=”text-left”][vc_column_text][/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”DOI” size=”size-sm” text_align=”text-left”][vc_column_text]https://doi.org/10.1109/ICEEI47359.2019.8988885[/vc_column_text][/vc_column_inner][vc_column_inner width=”1/4″][vc_column_text]Widget Plumx[/vc_column_text][/vc_column_inner][/vc_row_inner][/vc_column][/vc_row][vc_row][vc_column][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][/vc_column][/vc_row]