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Top1. Introduction
MANET contains a collection of nodes interconnected through the wireless medium. A larger distance separates the nodes present in the MANET, and hence, the MANET does not possess a standard infrastructure (Gurung & Chauhan, 2018; Achankunju et al., 2013). Due to the complicated nature of the MANET model, the configuration and the routing of the nodes remain a prime challenge (Cervera et al., 2013). The topology of the MANET constantly changes from time to time, and hence, there is more chance for the link breakage in the MANET. The routing protocols discussed in the literature can be categorized as reactive, proactive and multicast (Sun et al., 2012). Two common protocols under the proactive routing are Destination-Sequenced Distance Vector (DSDV) and Optimized Link State Routing Protocol (OLSR). The reactive protocols like Dynamic Source Routing (DSR) and Ad-hoc On-Demand Distance Vector (AODV) provide the route between the node based on the demand (Soni & Nayak, 2013; Schweitzer et al., 2016). The routing protocols discussed in the literature concentrate on the QoS parameters, such as throughput, bandwidth, jitter, and delay (Wang et al., 2014). The better of the routing protocols can be achieved through the inclusion of the security-based features along with the QoS parameters. The routing with the secured features allows better network traffic, replay transmissions, control packet headers, and redirect routing messages and thus, reduces the attacks occurring in the node (Borkar & Mahajan, 2017).
The routing protocols need to overcome the network attacks (Marimuthu & Krishnamurthi, 2013) for improving the MANET factors, such as authentication, non-repudiation, resource availability, integrity, confidentiality, and privacy. The attacks occurring in the MANET can be classified as 1) external and 2) internal attacks. The external attacks occur in the nodes not included in the MANET, and the black hole and gray hole attacks can be categorized under the internal attacks (Mohanapriya & Krishnamurthi, 2014). The presence of the gray hole attacks in the node poses greater instability to the network since these attacks cannot be predicted earlier. This accounts for the introduction of the secured routing algorithms (Chang et al., 2015; Marimuthu & Krishnamurthi, 2013). Introducing the optimization-based strategies (Binu et al., 2013; Ratre & Pankajakshan, 2017; Dhumane & Prasad, 2017; Nipanikar et al., 2017; Shelke & Prasad, 2018; Krishnamoorthy & Asokan, 2014; Menaga & Revathi, 2018) in the secured routing provides the real time solution to the problems (Biswas et al., 2014). Optimization strategies discussed in the literature comprise of both the single or multiple objective functions. The multi-objective optimization technique balances the load in the network, congestion avoidance, and provides better QoS than the single objective functions (Rajan & Shanthi, 2015; Achankunju et al., 2013).
This paper incorporates the trust between the nodes within an optimization strategy for the secured routing in the MANET. This paper introduces the Trust based Whale optimization algorithm (T-Whale) for the secured routing in the MANET. The optimization through the T-Whale algorithm requires a fitness function. The fitness function is developed based on the trust and the distance between the neighbor nodes. The steps involved in the selection of the best optimal route with the use of the T-Whale are: 1) Calculation of the trust and the distance factors between the neighbor nodes; 2) Find the disjoint paths in the MANET; and 3) Finding the secured path based on the fitness function. The evaluation of the T-Whale algorithm requires the metrics, energy, throughput, and packet delivery rate (PDR).