The emphasizes on nature-inspired meta-heuristic techniques such as cat swarm optimization (CSO) and particle swarm optimization (PSO) for identifying the election of the optimal location sector head (SH) and invoking rapid communication is studied in the paper. The aim of this study is to use the intelligence of the behaviour of cats to solve the chain-based sectoring (partitioning) problem associated with a Nondeterministic Polynomial (NP) hard block. Here, a unique chain-based energy-efficient reliable sectoring scheme (EERSS) is proposed for electing an optimal number of SHs and is implemented for increasing the reliability of a network. The uniqueness of the proposed EERSS is the consideration of factors such as the receiving signal strength identification (RSSI) value, one hop away nodes from a sink, Euclidean distance, remaining energy, neighbour table, and distance between the SH node and the sink while electing a node as an SH. The CSO algorithm is applied to the sectoring scheme for obtaining the optimal number and location of the elected SHs. The unique CSO-based sectoring scheme results are compared with those of well-known optimization technique like PSO. The simulation results show that the CSO-based EERSS provides improved reliability, by consuming less energy and time when compared to the existing chain-based clustering schemes such as the original EERSS, PEGASIS (Power-Efficient Gathering in Sensor Information System) and PSO-based EERSS.