A Service Discovery Approach for IoT-Based Application

The rapid growth of Internet of Things (IoT) devices has presented challenges for efficiently discovering and delivering services to users. Scalability becomes a crucial concern as the number of IoT devices exponentially increases. Service discovery mechanisms struggle to identify and deliver services in a timely manner due to the sheer volume of devices, resulting in longer response times and delays in real-time service delivery. The expanding service pool leads to a larger search space, further increasing the time required for accurate service discovery. This poses a significant challenge in applications where timely delivery is crucial. Additionally, to enhance user satisfaction, personalized service recommendations based on individual needs and preferences are essential. Understanding user inclination enables the recommendation of relevant services that increases acceptance and engagement. To address these challenges, we propose a solution that formulates the problem using a bipartite graph model and utilizes a heuristic-based approach.