Mobile ad hoc networks (MANETs) routing is a very challenging task because of the dynamic nature of the network. The linking of provisional communication assures based on the infrastructure of MANET, however, there is no centralised monitoring process for making the routing in MANETs in terms of trust and security. Therefore, the stability routing is not considered, which may break easily in dynamic MANETs. Thus, this paper introduces a trust-based secure routing protocol using the proposed atom whale optimisation algorithm (AWOA), which is the trust-aware routing protocol. The developed atom whale optimisation is utilised to select the optimal route with respect to the trust factors, like average encounter rate (AER), and successful cooperation frequency (SCF), integrity factor, and the forwarding rate. Moreover, secure routing is performed between the nodes using the proposed AWOA. The AWOA is the integration of atom search optimisation (ASO), and whale optimisation algorithm (WOA) that inherits the faster global convergence. The fitness function is newly modelled considering mobility, and trust factors. The proposed AWOA outperformed other methods with a minimal end-to-end delay of 0.0083 sec, maximal packet delivery ratio (PDR) of 97.73%, and the maximal throughput of 85.05% respectively.

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Handover algorithms based on different performance metric are used to provide seamless handover and need to be evaluated in terms of unnecessary handover and missing handovers. Wrong decision probability (WDP) is one such performance metric used to measure the efficiency of handover algorithms and is measured based on Unnecessary handover probability (UHP) and Missing handover probability (MHP) for handover evaluation. In this work handover probability (HP), UHP, MHP and WDP are computed for a five node network model. The handoff algorithm for the five node network model is designed based on combination of Received signal strength (RSS) and Bandwidth (BW), and is evaluated using Wrong Decision Probability model considering the four states of mobile node, namely Cooperative state, failed state, selfish state and malicious state. Analytical and simulation results are presented to validate the vertical handover. Results are compared with the results of single state five node network model. KeywordsMissing handover probability (MHP), Unnecessary handover probability (UHP), Wrong decision probability (WDP), Bandwidth (BW), Received Signal strength (RSS),

Mobility management enables the Mobile Terminal to switch between networks for better resource management and is still a hot research topic. Handoff management is one such challenge for maintaining active connections for roaming mobile terminals, as they change their network point of attachment. In heterogeneous networks, it is critical to evaluate and select the best algorithm out of the different algorithms, available for vertical handoff. Wrong decision probability (WDP) is one of the performances metric which is used to measure the efficiency of handover algorithms in providing such seamless service. In this work, probability equations are derived for five network models and probabilities are computed for unnecessary handover, missing handover and wrong decisions. The handoff algorithm for the five network model is designed to evaluate the performance of algorithms designed based on combination of received signal strength and bandwidth using Wrong Decision Probability model. Presentation of analytical and simulation results is made to validate the vertical handover and is compared with the results of handoff algorithm for the five network model designed considering bandwidth alone. Keywords-Bandwidth (BW), Missing handover probability (MHP), Received signal strength (RSS), Unnecessary handover probability (UHP), Wrong decision probability (WDP).I.

In this work, handover probability, unnecessary handover probability, missing handover probability and wrong decision probability are computed for a five node network model. The four states of mobile node, namely Cooperative state, failed state, selfish state and malicious state are also modeled. The simulation results are presented for a case of bandwidths up to 20. Decision time has been varied from 11ms to 15ms. Finally important conclusions are drawn and future work is defined.