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Summary: Wireless sensor networks (WSNs) consist of nodes. Issues involved with the use of a sensor network are energy‐saving and the effective use of energy. Clustering in WSNs is a proven technique for energy optimization. The relationship between sensor nodes and cluster heads (CHs) has only been considered prior to cluster‐based routing protocols. However, most clustering algorithms have failed to address the routing overhead and the energy consumption rate between CH nodes and SINK. In this paper, a new framework named as EEC‐MA‐PSOGA ‐ an energy‐efficient (EE) intra‐cluster mobile agent (INC‐MA)‐based particle swarm optimization–genetic algorithm (PSO‐GA), has been presented to initiate the distance communication and place the SINK optimally in WSNs. The cluster members send the collected data towards their respective CHs for aggregation. To find the sink's best position, the PSO‐GA‐based location estimation algorithm is initiated based on the network structure. The limited capability of WSNs makes them more vulnerable to attackers. The prevention mechanism must be less complex to ensure the fair operations in the network. Here, the attack detection ability of the proposed solution has been tested against clone attack. With varied communication range, simulation time, and sensor nodes, the tests are conducted extensively on various scenarios of WSNs. When compared with the prior mechanisms, the framework provides better results and better prevention with less overhead by analyzing the experimental results such as energy consumption, network lifetime, and throughput. [ABSTRACT FROM AUTHOR]

Summary: Wireless sensor networks (WSN) encompasses millions of nodes that work jointly, senses environmental information, and transmits to the Base Station (BS). "Energy hole" or "hot‐spot" is a problem in which sensor nodes near to the BS deceasetoo early which creates the partitioning of the network. This is due to the reason of the difference in the consumption of energy by the nodes in WSN which reduces the lifespan of the sensor network. The distribution of the cluster heads and the load balancing are the major pitfalls. In this paper to deal with the statedpitfalls, a hybrid of fuzzy logic technique and harmony search algorithm is proposed to lengthen the lifetime of the network. Unequal clustering is a technique proposed by the researchers to handle the hot‐spot issue, hence it is also included. The proposed algorithm forms unequal clusters. To prove the efficiency of the proposed algorithm, some well‐known unequal clustering algorithms and harmony search based algorithmare used to compare the proposed algorithm under different network settings. In all the settings, better performance is achieved by the proposed protocol. It prolongs the lifespan of the network as compared to the different algorithms proposed so far. [ABSTRACT FROM AUTHOR]