TITLE:
Classification of Selfish and Regular Nodes Based on Reputation Values in MANET Using Adaptive Decision Boundary
AUTHORS:
Amir Khusru Akhtar, G. Sahoo
KEYWORDS:
MANETs; Regular Node; Selfish Node; Adaptive Decision Boundary; Feature Value; Noncooperation
JOURNAL NAME:
Communications and Network,
Vol.5 No.3,
July
26,
2013
ABSTRACT: A MANET is a cooperative network in which
each node has dual responsibilities of forwarding and routing thus node
strength is a major factor because a lesser number of nodes reduces network
performance. The existing reputation based methods have limitation due to their
stricter punishment strategy because they isolate nodes from network participation
having lesser reputation value and thus reduce the total strength of nodes in a
network. In this paper we have proposed a mathematical model for the
classification of nodes in MANETs using adaptive decision boundary. This model
classifies nodes in two classes: selfish and regular node as well as it assigns the grade to individual nodes. The grade is computed by counting how many passes
are required to classify a node and it is used to define the punishment strategy
as well as enhances the reputation definition of traditional reputation based
mechanisms. Our work provides the extent of noncooperation that a network can
allow depending on the current strength of nodes for the given scenario and
thus includes selfish nodes in network participation with warning messages. We
have taken a leader node for reputation calculation and classification which
saves energy of other nodes as energy is a major challenge of MANET. The leader
node finally sends the warning message to low grade nodes and broadcasts the
classification list in the MANET that is considered in the routing activity.