GDL

Journal from gdlhub / 2017-08-15 10:12:00
Oleh : R. Manoharan, J. Sengathir, King Saud University
Dibuat : 2016-07-15, dengan 1 file

Keyword : Selfish nodes Reputation Genuineness factor Conditional Probabilistic Coefficient Erlang coefficient Network resilience
Url : http://www.sciencedirect.com/science/article/pii/S1319157815000932
Sumber pengambilan dokumen : web

In MANETs, reputation plays a significant role in reliable dissemination of data for establishing maximum degree of cooperation among the mobile nodes in the network. But, the presence of selfish nodes drastically reduces the level of cooperation between the nodes and further reduces the life time of the network. Moreover, when the number of selfish nodes increases in the network, the packet delivery ratio and throughput decreases which in turn increases the number of retransmissions. Hence, an effective mechanism for isolating selfish nodes in order to increase the packet delivery rate and the throughput for reliable dissemination of data becomes vital. This paper proposes an Erlang coefficient based conditional probabilistic model (ECCPM) which makes the decision of isolating selfish nodes through the manipulation of Conditional Probabilistic Coefficient (CPC) factor. This Conditional Probabilistic Coefficient acts as the reputation factor for estimating the level of negative impact produced by selfish nodes toward the resilience of the network. The proposed work is simulated in ns-2 and from the results, it is obvious that ECCPM showed better performance in terms of packet delivery ratio, throughput, control overhead and total overhead than existing mitigation mechanisms like RCSBMM, RFBMM, SHRCM and PCMA proposed for selfish nodes.

Beri Komentar ?#(0) | Bookmark

Properti	Nilai Properti
ID Publisher	gdlhub
Organisasi	King Saud University
Nama Kontak	Herti Yani, S.Kom
Alamat	Jln. Jenderal Sudirman
Kota	Jambi
Daerah	Jambi
Negara	Indonesia
Telepon	0741-35095
Fax	0741-35093
E-mail Administrator	elibrarystikom@gmail.com
E-mail CKO	elibrarystikom@gmail.com