Research On Performance Optimization Of Internet Of Things Based On Evolutionary Algorithm

Recently,the Internet of Things technology is widely popularized in people's real life,and the components of Io T system are gradually being replaced by smart devices.Meanwhile,as the scale of the system changes from a small to a large,the internal components of the system have also increased exponentially,and the system architecture has shown diversified characteristics.The performance of Io T system largely depends on its own organizational structure,so its organizational structure is particularly important.In addition,the services provided by a single component device in the traditional Io T system cannot meet the user's complex needs.Service composition technology can integrate services provided by different components in the system into a composite service to meet specific requirements.Therefore,the efficiency and quality of Io T service composition and the organizational structure of the Io T system affect the overall performance of the system.In the Io T environment,this article optimizes the overall performance of the Io T from the following three aspects.(1)Taking the service quality(Qo S)of the composite service as the optimization goals,transform the Io T service composition problem based on the Qo S into a singleobjective optimization problem.Combining lexicographic optimization technology,constraint relaxation technology and elite strategy,an improved genetic algorithm is proposed to solve the complex service selection problem in Io T.Simulation experiments show that the algorithm proposed in this paper performs better in terms of convergence rate and service utility.(2)The life cycle of Io T devices is one of the criteria for the performance of Io T.Energy consumption is an important factor affecting the life of equipment.Therefore,taking the Qo S and energy consumption of composite services as the optimization goals,the service composite problem based on Qo S and energy consumption in Io T is transformed into a multi-objective optimization problem.Using an ideal of hierarchical optimization,combining the compromise ratio method and the relative dominance theory,a fast service composition algorithm is proposed.Experimental results show that this algorithm performs better in terms of energy consumption,selection time,and relative domaince of composite services.(3)In order to optimize the architecture of Io T system,an algorithm based on immune evolution is proposed.this algorithm adopts a hierarchical coding method to transform the system organization structure into an integer coding form,and designs an adaptive hierarchical crossover operator.a small disturbance mutation operator also applied in this algorithm.meanwhile,algorithm uses individual incentives to guide the search direction of the algorithm,and search for solution that meet the performance requirements of Io T system.The experimental results show that the algorithm can obtain a system organization scheme with high performance value,and it performs better in success rate,relative error rate and convergence speed.