Increase the Efficiency of the Offloading Algorithm in Fog Computing by Particle Swarm Optimization Algorithm

Subject Areas : Metaphorical algorithms

Seyed Ebrahim Dashti ^{1 *} , Hoasain Zare ²

1 - Department of Computer Engineering- Jahrom Branch, Islamic Azad University, Jahrom, Iran
2 - Department of Computer Engineering- Zahedshar, Branch, Islamic Azad University, Zahedshar, Iran

Received: 2022-07-31 Accepted : 2022-11-22 Published : 2022-11-22

Keywords: particle swarm optimization algorithm, Evolutionary Algorithm, Fog computing, Offloading, cloud processing,

Abstract :

Edge computing is a computing paradigm that extends cloud services to devices at the edge. This processing model refers to technologies that allow computing and storage to be performed on devices at the edge of the network. In this architecture, computing and storage operations take place close to objects and data sources. In order to reduce latency and network traffic between end devices and cloud centers, groups at the edge have processing capabilities, perform a large number of processing and computing tasks, including data processing, temporary storage, device management, decision making, and privacy protection. Since the number of edge devices is large, there must be a mechanism to select these tasks and offload them to the cloud. The problem to be decided is that which one of the available edge devices should be selected for unloading and then unloaded. This problem is classified as one of the hard non-polynomial problems and by using deterministic algorithms simply and in polynomial time, it is not possible to find a suitable and efficient solution for it found.

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