System Model and Problem Formulation to Address Performance Issues in Edge Intelligence

Authors

  • Brinda Parekh, Kiran Amin

Keywords:

Edge-cloud computing, Edge intelligence, edge orchestrator, offload task, fuzzy logic

Abstract

When data processing is implemented in close proximity to end devices with intelligence and ample capabilities, it not only improves real time processing but also increases the effectiveness of generated results and reduces a significant burden on the overall network. Various metrics, such as computational speed, reaction time, CPU demand, network demand, and delay sensitivity, play a crucial role in enabling edge devices to execute complex tasks within time constraints. This paper presents an approach by adopting fuzzy logic to transmit the incoming tasks from the edge devices to one of the edge-cloud servers, which is decided by the edge orchestrator, taking into account various application characteristics. The primary aim of the proposed approach is to enhance task offloading by reducing service time and boosting the efficiency of edge devices. A system model and problem formulation have been designed with the help of which QoS parameters are improved in an edge-cloud environment by taking into consideration the balancing workload among the resources in the network.

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Published

20.06.2024

How to Cite

Brinda Parekh. (2024). System Model and Problem Formulation to Address Performance Issues in Edge Intelligence. International Journal of Intelligent Systems and Applications in Engineering, 12(4), 759 –. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/6282

Issue

Vol. 12 No. 4 (2024)

Section

Research Article

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