[vc_empty_space][vc_empty_space]
CAPIC: Cache based on Popularity and Class in Named Data Network
Yovita L.V.a, Syambas N.R.a, Matheus Edward I.Y.a
a School of Electrical Engineering and Informatics, Bandung Institute of Technology, Bandung, 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]© 2018 IEEE.In the IP network, if there are many consumers who want the same data, the request and response process for data will be repeated and will increase the overall network load. Modifications have been made to IP networks, namely by Content Distribution Network which places a duplicate server in a place closer to the consumer. CDN managed to reduce network load but cannot accommodate changes in dynamic consumer requests. A new network paradigm was proposed. The network paradigm that was originally host-centric turned into content-centric. This scheme is known as the Named Data Network (NDN). NDN causes data communication to be carried out efficiently and minimizes network load. Content store as an important component of NDN routers is a limited resource. For this reason, certain mechanisms are needed to optimize content store usage. As far as the author’s knowledge there are no papers that discuss caching mechanisms that pay attention to popularity and at the same time also differentiate service classes. In fact, there is a variation of traffic related to the traffic requirement. That’s why it is necessary to differentiate service class treatment in NDN content store and also consider the content popularity. This paper proposed a caching algorithm namely CAPIC (CAche based on PopularIty and Class). From the simulation, concludes that CAPIC gives the greater hit rate compared to another scheme that only considers popularity and the better path stretch and appropriates with the cache proportion based on class.[/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]Caching,Class,Content store,Named data networks,Popularity[/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]Caching,Class,Content store,Named data Network,Popularity[/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]This research was supported by Ministry of Research Technology Republic of Indonesia.[/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/ICCEREC.2018.8712105[/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]