Volume 11, Issue 3 (9-2019)                   itrc 2019, 11(3): 9-16 | Back to browse issues page

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Karimi S, Darmani Y. Multi-Objective P- Epidemic Forwarding Method in Heterogeneous DTNs Using NSGA-II. itrc. 2019; 11 (3) :9-16
URL: http://ijict.itrc.ac.ir/article-1-371-en.html
1- K.Faculty of Electrical Engineering, K. N. Toosi University of Technology
2- Faculty of Electrical Engineering, K. N. Toosi University of Technology , darmani@kntu.ac.ir
Abstract:   (334 Views)
Due to the increasing use of wireless communications, infrastructure-less networks should be highly considered. Delay Tolerant Network (DTN) as such networks does not have the end to end path between the source and destination nodes. Consequently, routing in DTN as an open issue needs to be studied. Many replication protocols such as epidemic routing are proposed in these challenging wireless environments. The main idea of epidemic routing is to send a copied message to each node without that message. The replication process consumes a high amount of network resources such as energy.
In this work, a probabilistic epidemic (p-epidemic) forwarding scheme is suggested that minimizes the energy consumption and maximizes the message delivery probability within the heterogeneous sets of nodes using Non-dominated Sorting Genetic Algorithm II (NSGA-II). Current research considers all the nodes of the network with the equal transmission radii and the network is assumed homogeneous. In our work, the nodes have two different amounts of available energies and two different transmission radii. The radius of each node is chosen according to the current energy of that node. The node energy has a significant role in successfully delivering the messages. Regarding the node energy, the lower transmission radius the node has, the lower its chance to send the message with the lower probability. The node with the higher transmission radius sends the message with a higher probability. The optimal transmission probabilities are obtained by NSGA-II. The front of optimal solutions according to these probabilities for delivery probability and energy consumption are observed.
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Type of Study: Research | Subject: Network

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