With the scale of Internet of Things (IoT) continues to increase, it brings big challenges for service selection in a large-scale IoT. For solving this problem, a service selection method based on the enhanced genetic algorithm is proposed in this paper. To decrease the scale of service selection, this paper uses the lexicographic optimization approach and quality of service (QoS) constraint relaxation technique to find the candidate service with height QoS. Then, the IoT service selection problem is transformed into a single-objective optimization problem adopting a simple weighting method, and the final composite service meeting the user's QoS needs are obtained from the candidate service. The simulation results show that the proposed algorithm can efficiently and quickly achieve a composite service satisfying user's QoS needs, and is more suitable for solving the service composite problem in large-scale IoT services.

随着物联网（IoT）规模的不断增加，它给大型IoT中的服务选择带来了巨大挑战。针对这一问题，提出了一种基于改进遗传算法的服务选择方法。为了减小服务选择的规模，本文采用字典优化方法和服务质量（QoS）约束松弛技术来查找具有高度QoS的候选服务。然后，采用简单的加权方法将物联网服务选择问题转化为单目标优化问题，并从候选服务中获得满足用户QoS需求的最终复合服务。仿真结果表明，该算法能够有效，快速地实现满足用户QoS需求的复合服务，