A Hybrid Algorithm for Q-coverage Problem in Under Provisioned Directional Sensor Networks

In the context of emerging technologies like the Internet of Things (IoT) and home automation, researchers are increasingly exploring the use of Wireless Sensor Networks (WSNs). One of the primary functions of these sensors is coverage, which refers to how effectively they can monitor targets within a given environment. In many applications, it is essential that each target is covered by at least one sensor; this is known as "Simple Coverage." In other cases, multiple sensors may be required to cover a single target, a situation referred to as "Multiple Coverage." When the number of sensors covering a target can vary, it is termed "Q-coverage." When there are not enough sensors in an environment, achieving balanced coverage becomes critical. To address this challenge, current research presents a hybrid algorithm that combines genetic algorithms and Tabu Search as a promising solution for monitoring targets in such under-provisioned environments. To evaluate the effectiveness of this proposed algorithm, several experiments were conducted, and the results were compared with those obtained from a genetic algorithm introduced in recent studies.