Background and Objectives: The quick response time and the Coverage range are the crucial factors by which the quality service of a wireless sensor network can be acknowledged. In some cases, even networks possess sufficient available bandwidth but due to Coverage tribulations, the customer satisfaction gets down suddenly. The increasing number of nodes directly is neither a canny solution to overcome the Coverage problem nor a cost-effective. In fact, by changing the positions of the deployed node sagaciously can resolve the Coverage issue and seems a cost-effective solution. Therefore, keeping all circumstances, a Depuration based Efficient Coverage Mechanism (DECM) has been developed. This algorithm suggests the new shifting positions for previously deployed sensor nodes to fill the Coverage gap. Methods: It is a redeployment process and accomplished in two rounds. The first round avails the Dissimilitude Enhancement Scheme (DES), which searches the node to be shifted at new positions. The second round controls the unnecessary movement of the sensor nodes by the Depuration mechanism thereby the distance between previous and new positions is reduced. Results: The factors like loudness, pulse emission rate, maximum frequency, and sensing radius are meticulously explored during simulation rounds conducted by MATLAB. The performance of DECM has been compared with superlative algorithms i. e., Fruit Fly Optimization Algorithm (FOA), Particle Swarm Optimization (PSO), and Ant Colony Optimization (ACO) in terms of mean Coverage range, computation time, standard deviation, and network energy diminution. Conclusion: According to the simulation results, the DECM has achieved more than 98% Coverage range, with a trivial computation time of nearly 0. 016 seconds as compared to FOA, PSO, and ACO.