A computational offloading algorithm for cloud-edge collaboration in smart agriculture Online publication date: Fri, 04-Oct-2024
by Feng Li; Yiyuan Li; Yuqing Pan
International Journal of Simulation and Process Modelling (IJSPM), Vol. 21, No. 2, 2024
Abstract: To solve the problem that the massive amount of information and real-time processing in the IoT system puts pressure on the computing resources of the whole system, the industry often adopts the computation offloading algorithm for cloud-edge collaboration. However, at this stage, conventional computation offloading algorithms frequently fail to account for dynamic conflicts between terminal tasks and offloaded tasks, and the results of offloading are inefficient. To that purpose, this paper introduces the task volume prediction model, the response time model and the power consumption model to represent the whole computing process of agricultural activities from various angles. On that basis, the DQN algorithm is used to solve the model's mixed-integer nonlinear optimisation issue. Experiments show that the algorithm proposed in this paper can increase the offloading accuracy and the speed and accuracy of cloud-edge collaborative computing.
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Simulation and Process Modelling (IJSPM):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email subs@inderscience.com
Our Blog 
Follow us on Twitter 
Visit us on Facebook