Two-steps QoS-aware services composition algorithm for Internet of Things

Abstract

The Internet of Things (IoT) is a global infrastructure that provides services having similar functionality but with different quality of service (QoS). The fast growing of these services leads to a difficulty of selecting the most appropriate services to fulfill a complex user's requirement. It is therefore necessary to automate the mechanism for selecting the appropriate services in order to satisfy both functional and non-functional user's requirements. In this paper, a two-steps QoS-aware services composition algorithm (TS-QCA) based on clustering and shuffled frog leaping algorithm (SFLA) is proposed in the context of large-scale IoT environments. This approach aims at minimizing the composition time through accelerating the algorithm convergence by using the clustering technique and the exploitation of the parallel aspect of the SFLA algorithm. The simulation results demonstrate that the proposed algorithm is scalable and achieves a near-to-optimal composition in a reduced amount of composition in comparison to other services composition approaches proposed in the literature.