Energy conservation in Wireless Sensor Networks (WSNs) is essential for improving the stability of sensor nodes and network lifetime. An energyproficient clustering-based routing protocol is necessary for efficient cluster formation and Cluster Head (CH) selection to sustain Quality of Service (QoS). In this paper, an Improved Bkd-Tree-Inspired Energy-eFficient Clusteringbased Routing Protocol (IBkd-Tree-IEFCRP) is propounded as a potential strategy for guaranteeing significant cluster formation and management. It is proposed as an effective strategy in CH node allocation that handles the impacts of QoS during the process of data dissemination. This IBkd-Tree-IEFCRP is proposed to deal with energy saving with respect to data traffic by including a strategy of cluster formation which incorporates the benefits of partition data structure that incorporates animprovedBkd-treealgorithm.Italsoconcentrates ontheprocessofCHselection by integrating a reactive approach that enhances throughput with minimized energy, delay and jitter. The simulation experiments of the proposed IBkd-Tree-IEFCRP confirm a better performance in improving the average throughput by 13.21%, reducing the energy consumptions by 12.96%, minimizing the delay by 11.98% and reducing the jitter by 14.24% when compared to the baseline kdimensional tree algorithm (kd-tree algorithm), Weighting and Parameter Optimization-based Energy-Efficient Clustering Routing Protocol (WPO-EECRP), Improved Clustering by Fast Search and Finding of Density Peaks (ICFSFDP), and Energy-based Cluster Centered Routing Protocol (ECCRP) taken for comparison. The proposed IBkd-Tree-IEFCRP is also identified to reduce delay by 8.42% and jitter by 7.18% and increase throughput by 6.84% when compared to the benchmarked protocols for different number of rounds.
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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