A futuristic trust coefficient-based semi-Markov prediction model for mitigating selfish nodes in MANETs

Janakiraman Sengathir,Rajendiran Manoharan

doi:10.1186/s13638-015-0384-4

Janakiraman Sengathir, Rajendiran Manoharan

Open Access

https://doi.org/10.1186/s13638-015-0384-4

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Abstract

In mobile ad hoc networks (MANETs), network survivability is considered as a potential factor required for maintaining maximum degree of connectivity among the mobile nodes even during failures and attacks. But, the selfish mobile nodes pose devastating influence towards network survivability. Hence, a prediction model that assesses network survivability through stochastic properties derived from nodes’ behaviour becomes essential. This paper proposes a futuristic trust coefficient-based semi-Markov prediction model (FTCSPM) that investigates and quantifies the impact of selfish behaviour towards the survivability of the network. This FTCSPM approach incorporates a non birth-death process for manipulating futuristic trust coefficient since it does not consider the transition of a mobile node from the failed state to a selfish state into account. This semi-Markov prediction model also aids in framing a lower and upper bound for network survivability. Extensive simulations were carried out through ns-2 and the results indicates that FTCSPM show better performance than the existing benchmark mitigation mechanisms like correlated node behaviour model (CNBM), probabilistic behavior model (PBM) and epidemic correlated node behavioural model (ECNBM) proposed for selfish nodes. Further, FTCSPM isolates the selfish nodes rapidly at the rate of 33 % than the considered benchmark systems. Furthermore, the validation of this prediction model performed through Weibull distribution has a high degree of correlation with the simulation results and thus assures the reliability and correctness of the proposed approach. In addition, this approach computes the mean transition time incurred by a mobile node to transit from cooperative to selfish mode as 6.49 s and also identifies the minimum and maximum selfish behaviour detection time as 140 and 180 s, respectively.

Highlights

1 Introduction In mobile ad hoc networks (MANETs), network survivability is considered as an important entity for reliable data communication
“Given a wireless ad hoc network ‘N’ with possible definitions of mobile node behaviours ‘B’, the problem can be formulated as a network survivability model ‘M (N,B)’ that estimates and isolates the selfish nodes from the routing path through futuristic trust coefficient which quantifies the likelihood probability incurred by a mobile node to get transited into the non-cooperative state”
6 Conclusions This paper has presented a futuristic trust coefficientbased semi-Markov prediction model formulated through non birth-death process for mitigating selfish mobile nodes in an ad hoc network

Summary

Introduction

In mobile ad hoc networks (MANETs), network survivability is considered as an important entity for reliable data communication. This mechanism mitigates the selfish nodes which drops others nodes’ packets without forwarding it to the hop neighbour in the routing path This model incorporates 3-D Markov chain for analysing the characterization behaviour of mobile nodes towards network survivability. “Given a wireless ad hoc network ‘N’ with possible definitions of mobile node behaviours ‘B’, the problem can be formulated as a network survivability model ‘M (N,B)’ that estimates and isolates the selfish nodes from the routing path through futuristic trust coefficient which quantifies the likelihood probability incurred by a mobile node to get transited into the non-cooperative state”. A mobile node either in cooperative or selfish state may either turn into failure state This transition is confirmed based on stochastic probability λsf, which is defined through the ratio of maximum number of packets dropped by the mobile node to the maximum number of packets received by the mobile node from its neighbours as given by (6). This rehabilitation probability of a mobile ‘μfc’ depends upon the mean time required for reconfiguration as defined by (8)

Node behaviour modeling through transition probability matrix

Isolation of selfish nodes based on futuristic trust coefficient

Findings

Conclusions