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Overlay network for low churn environment

Sitepu H.I.a, Machbub C.a, Langi A.Z.R.a, Supangkat S.H.a

a School of Electrical Engineering and Informatics, Institut Teknologi 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]Distributed Hash Tables (DHTs) are the important algorithms for building structured peer-to-peer overlay networks. There are two approaches that used by the DHT’s designers for choosing the number of states maintained by each peer. With the first approach, each peer stores minimal information about other peers, typically increase logarithmically with the number of peers in the network. The DHT protocols need to minimize the communication cost for updating the overlay states with the dynamics of peers that join and leave the network arbitrarily (also called as churn). Maintaining minimal states under churn condition will minimize network updates. With the second approach, each peer stores complete information about all peers in the network. Key lookup messages can be resolved by contacting one peer, thus decreasing the hop countforforwarding key lookup messages to single hop. The DHTprotocol performance come with higher bandwidth consumption for updating routing states under churn condition. In this paper we evaluate and compare both approaches and show that the second approach performs better in low churn environment, thus can be used for application with less dynamic peers behavior. © 2008 IEEE.[/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]Bandwidth consumptions,Communication costs,Complete informations,Distributed hash tables,Minimal informations,Minimal states,Number of states,Overlay Networks,Peer to peers,Single hops[/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][/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/ITSIM.2008.4631961[/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]