In this paper, we have proposed different deployment strategies and have applied area-wise
clustering along with modified Ant Colony Optimization to minimize energy consumption.
Background: Previously, some deployment strategies were used to enhance the lifetime of WSN. In our
research, we have applied some novel deployment strategies like random, spiral, and S-pattern along
with a novel area-wise clustering process to get better results than the existing literature, as shown in
Objective: The main objective of the research article is to enhance the lifetime of Wireless Sensor
Network with the help of different deployment strategies like random, spiral, and S-pattern). A novel
clustering process (i.e., area-wise clustering), and a Meta-heuristic algorithm (modified ACO) are applied.
Method: We have applied different methods for deployment strategies (random, spiral, and S-pattern).
A novel clustering process (i.e., area-wise clustering), and a Meta-heuristic algorithm (modified ACO)
are applied to get the desired results.
Results: Random Deployment: 11.15 days to 15.09 days. Spiral Deployment: 11.25 days to 15.23 days.
S-Pattern Deployment: 11.33 days to 15.33 days.
Conclusion: In this paper, efficient Wireless Sensor Networks have been configured considering energy
minimization as the prime concern. To minimize the energy consumption, a modified ACO algorithm
has been proposed. In our work, the minimization of energy consumption leads to an increment of the
lifetime of WSN to a significant margin theoretically. The obtained result has been compared with the
existing literature and it has been found that the proposed algorithm produced a better result than the