The main goal is to find multiple node-disjoint paths that meet the multi-objective optimization problem in terms of energy consumption minimization and network lifetime improvement. Due to the battery-dependent nodes in mobile ad hoc networks, the performance of the network will degrade. Hence, it is necessary to choose multiple optimal node-disjoint paths between source and destination for data transfer. Additionally, it improves the Quality of Service (QoS) of wireless networks. Multi-objective function is used to select a path such that it gives an optimum result based on the energy consumption, hop, and traffic load. From the simulation results, it is proved that the proposed system is achieving less energy consumption and improved network lifetime compared with existing Dynamic Source Routing (DSR), Hopfield Neural Network-based Disjoint Path set Selection (HNNDPS) and Multipath DSR (MDSR).

Nowadays, most of the research focuses on the distributed algorithm to form the clusters in wireless sensor networks, in which the sensor nodes act autonomously to self‐configure themselves with the help of the local information. However, the issues in such distributed mechanisms are (i) how to assign the time division multiple access (TDMA) schedule to collect the data from the cluster member (CM), (ii) how to distribute and balance the overall energy consumption of the cluster heads (CHs) under the circumstance of node's mobility. To overcome these problems, a cluster switched data gathering protocol (CSDGP) is proposed which ensures a uniform distribution of CHs by utilising a waiting time‐based CH selection and an effective cluster switch based TDMA scheduling mechanism. The salient feature observed in the proposed CSDGP is that the migrated node has a chance to transmit the sensed data to the CH, whenever the CH has a free time slot. From the simulation results, it is proved that CSDGP provides a good performance under three different scenarios in comparison with existing protocols in terms of average energy consumption, average end‐to‐end delay, packet delivery ratio, and control overhead.

Landslides and avalanches are the two major hydro-geological hazards that affect large parts of India, especially in Himalayas, northeastern hills, Munnar, and Uttarakhand. The rock fall, cracks, muddy in river water, etc., are used to identify the occurrence of landslide. Nowadays, sensor nodes are deployed in the landslide-prone area to monitor the soil grip. The proposed method focuses on collecting the data from the landslide-prone area and reduces the human risk on physical inspection. Energy-efficient and reliable data collection protocol (EERDCP) is introduced depending on the principle of tap root growing in the tree, in which residual energy, distance, and tuning parameters are considered for selecting the SR node, FOL node (FOLN), SOL node, and FOLN head nodes. These parameters are given as input to a fuzzy inference system to choose the best relay node. Also, the head node of tap root collects the data from sensor nodes which in turn transmit to the mobile sink (MS). The performance of the proposed routing approach is tested in the network simulator-2 and the results are compared with the existing protocols cluster switched data gathering protocol, mobile sink and fuzzy-based relay node routing, fuzzy-based relay node selection and energy-efficient routing, and general self-organized tree-based energy balance. The results show that the proposed EERDCP outperforms the existing routing scheme in terms of average energy consumption, average end-to-end delay, packet delivery ratio, control overhead, and network lifetime.