Research on Fog Resource Scheduling based on Cloud-fog Collaboration Technology in the Electric Internet of Things

Abstract

Background: With the further development of electric Internet of things (eIoT), IoT devices in the distributed network generate data with different frequencies and types. Objective: Fog platform is located between the smart collected terminal and cloud platform, and the resources of fog computing are limited, which affects the delay of service processing time and response time. Methods: In this paper, an algorithm of fog resource scheduling and load balancing is proposed. First, the fog devices divide the tasks into high or low priority. Then, the fog management nodes cluster the fog nodes through K-mean+ algorithm and implement the earliest deadline first dynamic (EDFD) task scheduling algorithm and De-REF neural network load balancing algorithm. Results: We use tools to simulate the environment, and the results show that this method has strong advantages in -30% response time, -50% scheduling time, delay, -50% load balancing rate and energy consumption, which provides a better guarantee for eIoT. Conclusion: Resource scheduling is important factor affecting system performance. This article mainly addresses the needs of eIoT in terminal network communication delay, connection failure, and resource shortage. And the new method of resource scheduling and load balancing is proposed, The evaluation was performed and proved that our proposed algorithm has better performance than the previous method, which brings new opportunities for the realization of eIoT.

[Retracted] Optimization and Simulation of Enterprise Management Resource Scheduling Based on the Radial Basis Function (RBF) Neural Network

“…In different research stages, experts and scholars have made their own contributions to the development of marketing theory from different research perspectives. Zhu et al [ 9 ] believed that the essence of marketing management is the “creative adaptation to the dynamic environment” of the enterprise. The task of marketing is to use various means to achieve the best environmental adaptation.…”

Research on Rural Comprehensive Energy Service Operation Based on Data-driven of Electric Power Internet of Things

“…At present, the comprehensive energy service market has great potential and many participants. Platform development can promote the efficient connection of all participants, promote the organic combination of energy industry chain and digital economy, and rely on technical means to promote the high-quality development of rural comprehensive energy services [2][3]. The existing community energy system scheme of the Internet of Things can realize the intelligent management of the community power system to a certain extent, but there are still the following shortcomings in technology: it can not realize the local management of the photovoltaic system in the community, resulting in the transmission loss of photovoltaic power in the community; The fault detection of the power system in the residential area depends on the feedback of the users, and cannot be prevented in advance.…”