Current Issue : July-September Volume : 2022 Issue Number : 3 Articles : 5 Articles
With the widespread use of industrial Internet technology in intelligent production lines, the number of task requests generated by smart terminals is growing exponentially. Achieving rapid response to these massive tasks becomes crucial. In this paper we focus on the multi-objective task scheduling problem of intelligent production lines and propose a task scheduling strategy based on task priority. First, we set up a cloud-fog computing architecture for intelligent production lines and built the multi-objective function for task scheduling, which minimizes the service delay and energy consumption of the tasks. In addition, the improved hybrid monarch butterfly optimization and improved ant colony optimization algorithm (HMA) are used to search for the optimal task scheduling scheme. Finally, HMA is evaluated by rigorous simulation experiments, showing that HMA outperformed other algorithms in terms of task completion rate. When the number of nodes exceeds 10, the completion rate of all tasks is greater than 90%, which well meets the real-time requirements of the corresponding tasks in the intelligent production lines. In addition, the algorithm outperforms other algorithms in terms of maximum completion rate and power consumption....
Aiming at the problems of high computing energy consumption and long time in traditional UAV-assisted edge computing research work, a computing resource allocation strategy using biological evolutionary algorithms in UAV-assisted mobile edge computing is proposed by introducing UAV swarms and genetic algorithms. Firstly, it analyzes the communication model for uplink transmission, the calculation model for local computing tasks, and UAV to perform computing tasks. Secondly, the objective function and overall model of system are constructed by comprehensively considering multiple constraints. Then, improved genetic algorithm is introduced into the model. On the basis of data encoding, crossover, mutation, and termination operations, the optimization performance of algorithm is greatly improved by multiple iterations of fitness function. Finally, the energy consumption of proposed algorithm and other two algorithms under the same number of iterations are compared and analyzed by simulation experiments. The experimental results show that the optimal solution, average, and variance of proposed algorithm for energy consumption are 52.354, 50.326, and 0.224, respectively, and its performance is better than other two comparison algorithms....
Mobile edge computing (MEC) has become a more and more popular technology, which plays a very important role in various fields. In view of the task of offloading of multiple users, most of the existing studies do not take into account data sharing and cooperation among users, which can easily lead to less generalization of the model trained by a single user, and some data sharing may also cause privacy leakage. Then, this paper uses the method of federated reinforcement learning to solve this problem in order to insure privacy. Besides, considering the poor quality of local models, which leads to the poor versatility of the overall parameters, this paper proposes a federated reinforcement learning method based on Attention mechanism to aggregate the parameter weights, which makes the new model more generalized.Theexperimental results show that the federated reinforcement learning task offloading model with Attention mechanism can reduce the processing delay of the task....
The study of how to construct the integration mode of water conservancy information resources for water conservancy applications is extremely practical. This paper discusses the history of cloud computing and data centers, as well as the development paths of related technologies, and proposes the use of cloud computing to integrate and share water conservation data resources. The current state of water conservation informatization, as well as its characteristics and future development trends, is investigated. The regional water conservancy integrated management system is analyzed in detail according to the process and ideas of software project design and development, and the overall architecture model based on cloud computing is determined by analyzing relevant regulations of water conservancy informatization infrastructure and the actual situation of water conservancy informatization construction in sample areas. And the system’s specific functions are designed and presented. This method has changed the traditional concept and mode of water conservation business management, and it can achieve service value-added and efficient and low-cost development and utilization of information resources, according to practice....
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