Abstract
With the rapid development of Internet of Things (IoT) technology, the energy consumption of service composition in the IoT environment is a key problem to be studied. At present, the problems of service composition in the IoT environment mostly focus on the evaluation research based on quality of service (QoS), ignoring the overall energy consumption in the process of dynamic configuration of service composition. Therefore, we construct the service composition structure for the IoT and propose the QoS evaluation model and energy evaluation model for the service composition in the IoT environment. Considering that the service composition in the Internet of things environment is NP hard, moth algorithm (MFO) is successfully applied to the QoS evaluation model and energy evaluation model. The simulation results reveal that MFO has good optimization effect in the abovementioned models, and the optimization effect of MFO is improved by 8% and 6% compared with the genetic algorithm and particle swarm optimization, so as to realize the green energy strategic management of QoS composition in the environment of IoT.
Highlights
In recent years, the development of embedded devices has been rapid along with the growth of Internet of ings (IoT) [1,2,3]. e service-based information system connects the physical reality world and the network virtual world, making the boundary between them gradually blurred [4]
When a single service cannot meet the complex needs of users, it is necessary to combine a large number of services with simple functions to form a powerful service that can meet the needs of users. erefore, scholars hope to create new and more powerful service functions by combining the existing service integration, so as to make full use of the previous resources, expand and extend the original services, fully tap the potential of Web services, and make them play a greater role [9]
To solve the abovementioned problems, this paper models the quality of service (QoS) evaluation and energy consumption of the QoS-based composition problem in the IoT environment and applies MFO algorithm to the abovementioned model successfully
Summary
The development of embedded devices has been rapid along with the growth of Internet of ings (IoT) [1,2,3]. e service-based information system connects the physical reality world and the network virtual world, making the boundary between them gradually blurred [4]. Considering the quality of service composition and energy consumption, this paper puts forward the QoS evaluation model and energy evaluation model in the IoT environment and applies MFO (month flame optimization) algorithm to the QoS evaluation model and energy evaluation model successfully. E experimental results show that compared with PSO (particle swarm optimization) and GA (genetic algorithm), MFO can obtain the best QoS and effectively reduce energy consumption, so as to realize the green energy strategic management of service composition quality in the Internet of ings environment. E service quality evaluation model and energy evaluation model of service composition in the Internet of ings environment are proposed to solve the abovementioned problems; (2) the month algorithm (MFO) is successfully applied to the QoS evaluation model and energy evaluation model.
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