DDAPSO: Hybrid Discrete Dragonfly Algorithm and Particle Swarm Algorithm to Service Selection and Composition for the Internet of Things Applications

Recently, the Internet of Things (IoT) has quickly risen as one most essential technologies this century. IoT allows users to connect a vast network smart devices, services, and data. An important challenging research problem in applications is how select an appropriate service selection (SS). In SS problem, can combine several services from diverse sources (things or devices) satisfy their needs. On other hand, known for its complexity categorized NP-hard problem; such problems are typically solved utilizing heuristics like bio-inspired algorithms. new algorithm called DDAPSO created solve where strategy proposed maintain balance between exploration exploitation abilities. This hybrid result coupling Discrete Dragonfly Algorithm (DDA) with particle swarm optimization (PSO). The suggested was properly tested using variety scenarios different numbers concrete per each set task. compared main recent well-known algorithms, i.e. GA, PSO, DDA, ABC MVO selection. large-scale setting, results clearly show that outperforms algorithms reported literature terms optimally well execution time.