Reliability factor-based mathematical model for isolating selfish nodes in MANETs

Sengathir, J.; Manoharan, R.

doi:10.1504/ijict.2014.063223

Cited by 11 publications

(10 citation statements)

References 11 publications

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“…The simulation experiments of the proposed HHOA‐NLOS‐LS are conducted using EstiNet 8.1 network simulator in order to investigate its predominance over the benchmarked schemes used for comparison 27‐33 . The network simulator EstiNet 8.1 is used for simulating the proposed HHOA‐NLOS‐LS, since it is the world‐renowned tool that is a commercial version of the NCTUns network simulator and acts as an emulator.…”

Section: Simulation Results and Discussionmentioning

confidence: 99%

“…The simulation experiments of the proposed HHOA-NLOS-LS are conducted using EstiNet 8.1 network simulator in order to investigate its predominance over the benchmarked schemes used for comparison. [27][28][29][30][31][32][33] The network simulator EstiNet 8.1 is used for simulating the proposed HHOA-NLOS-LS, since it is the world-renowned tool that is a commercial version of the NCTUns network simulator and acts as an emulator. EstiNet simulator facilitates vital capabilities that include realistic distance based vehicle movement and optimally enhanced IEEE 802.11p/1609 VANET network simulation of the road for VANET.…”

Section: Computational Complexitymentioning

confidence: 99%

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Harris Hawk Optimization Algorithm‐based Effective Localization of Non‐Line‐of‐Sight Nodes for Reliable Data Dissemination in Vehicular Ad hoc Networks

Malar¹,

Priya²,

Janakiraman³

2020

Int J Communication

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SummaryVehicular Ad hoc NETwork (VANET) is considered as the appropriate candidate for provisioning risk‐free environment that confirms secure cooperation and very minimal congestion among the vehicular nodes in the network. The establishment and maintenance of connectivity between vehicular nodes are determined to be influenced by the existence of Non‐Line‐of‐Sight (NLOS) nodes that introduce channel congestion and broadcasting storm into the network during emergency message delivery. Thus, NLOS nodes need to be localized with optimality for enhancing the emergency data delivery rate with minimized latency degree and energy consumption in the network. In this paper, Harris Hawk Optimization Algorithm (HHOA)‐based NLOS nodes Localization Scheme (NLOS‐LS) (HHOA‐NLOS‐LS) is proposed for facilitating reliable data dissemination among vehicular nodes under emergency situations. HHOA utilizes chasing styles and cooperative behavior of Harris hawks termed as surprise pounce for efficient localization based on reference nodes. In particular, the intelligent strategy of Harris hawks' behavior in attacking the prey in all directions is included for localizing the NLOS nodes from the reference nodes positioned in all directions of the network. It is capable of localizing the NLOS nodes based on adaptive localizing (chasing) styles attained through reference nodes dependingon the dynamic nature of NLOS nodes. The simulation results prove that the mean localization rate is improved by 23.21%, mean neighborhood awareness rate by 19.82%, mean emergency message delivery rate by 18.32% and mean channel utilization by 17.28% when compared to the baseline Weighted Inertia‐based Dynamic Virtual Bat Algorithm (WIDVBA)‐based NLOS‐LS (WIDVBA‐NLOS‐LS), Cooperative Volunteer Vehicular Nodes (CVVN)‐based NLOS‐LS (CVVN‐NLOS‐LS), Vote Selection Mechanisms and Probabilistic Data Association (VSMPDA)‐based NLOS‐LS (VSMPDA‐NLOS‐LS), and Weighted Distance Hyperbolic Prediction (WDHP)‐based NLOS‐LS (WDHP‐NLOS‐LS) for a varying number of vehicular nodes in the network.

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Section: Simulation Results and Discussionmentioning

confidence: 99%

Section: Computational Complexitymentioning

confidence: 99%

Harris Hawk Optimization Algorithm‐based Effective Localization of Non‐Line‐of‐Sight Nodes for Reliable Data Dissemination in Vehicular Ad hoc Networks

Malar¹,

Priya²,

Janakiraman³

2020

Int J Communication

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“…CoCoWa greatly reduces the cost of transmission by accurately predicting the selfish behaviour of nodes. Authors of this paper also has proposed a Reliability Factor Based Mitigation Mechanism (RFBMM) [18] that estimates the reliability of the mobile nodes through a packet deficiency parameter. This reliability parameter is computed based on the weighted sum of product of the estimated normalized deficiency factor which has been collected for some session period.…”

Section: Literature Reviewmentioning

confidence: 99%

An Erlang factor-based conditional reliability mechanism for enforcing co-operation in MANETs

Janakiraman¹,

Manoharan²

2016

Serb J Electr Eng

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Reputation is considered to be one of the vital entities for maintaining collaboration among wireless mobile nodes present in an ad hoc environment. The nodes in MANET are dynamic and could change its behaviour drastically, but establishing maximum level of cooperation between these nodes is highly crucial. Moreover, the presence of selfish nodes has a greater impact on the resilience of the network. Hence, a need arises for formulating a mechanism that deals with these selfish nodes. In this paper, we contribute an Erlang distribution based Conditional Reliability Mechanism (ECRCM) that aids in detecting and isolating the selfish nodes present in an ad hoc environment. This mathematical model makes the routing decision with the help of a parameter called Erlang factor based Conditional Reliability Coefficient (ECRC) determined for each and every mobile node present in the ad hoc network. Extensive simulations were carried out through ns-2 simulator and the analysis was based on performance metrics such as packet delivery ratio, throughput, control overhead and total overhead. ECRCM also helps in framing an optimal threshold range for selfish node detection. From the results, it is obvious that the threshold range derived in our study remarkably identifies maximum number of selfish nodes when compared to the selfishness detecting parameters available in the literature.

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“…In this experiment, the FTCSPM is analysed based on varying CBR traffic flows viz., low (2-4), medium (6), high (8)(9)(10). Figure 5a-e presents the comparative analysis plots of packet delivery ratio, energy consumption rate, average end-to-end delay, packet drop rate and throughput derived for comparing the selfish mitigation mechanisms like FTCSPM, CNBM, PBM and ECNBM.…”

Section: Performance Evaluation Of Ftcspm By Varying the Cbr Traffic mentioning

confidence: 99%

“…In the literature, various mitigation mechanisms proposed for selfish nodes either concentrates on the past history of mobile nodes or estimates conditional probabilistic factor based on both the past and present behaviour of the mobile node into account [9,10]. However, these approaches lack to detect selfish nodes by forecasting the probability of transition between the behavioural states of the mobile nodes based on its present characteristics.…”

Section: Introductionmentioning

confidence: 99%

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

Janakiraman

Manoharan

2015

J Wireless Com Network

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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.

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Reliability factor-based mathematical model for isolating selfish nodes in MANETs

Cited by 11 publications

References 11 publications

Harris Hawk Optimization Algorithm‐based Effective Localization of Non‐Line‐of‐Sight Nodes for Reliable Data Dissemination in Vehicular Ad hoc Networks

Harris Hawk Optimization Algorithm‐based Effective Localization of Non‐Line‐of‐Sight Nodes for Reliable Data Dissemination in Vehicular Ad hoc Networks

An Erlang factor-based conditional reliability mechanism for enforcing co-operation in MANETs

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

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