Tasks classification across edge servers nodes using K-means with multi-objective constraints Chebyshev distance

Imene Ayat, Djamila Mechta, Saad Harous

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Edge computing provides benefits such as reduced latency by processing data closer to its source, but it faces challenges due to limited processing power, memory, and storage capacity. To address these limitations and enhance system efficiency, task classification becomes crucial in edge computing. By categorizing tasks, resources can be allocated effectively. This paper presents a novel approach for classifying tasks and edge servers based on CPU and memory capacities. The proposed model treats tasks and edge servers as points and applies the K-means method by adding multi-objective constraints Chebyshev distance. The distance metric considers two objectives: The distance between points and the number of tasks and edge servers. Unlike traditional K-means algorithms that often result in clusters with either one server or clusters without servers, our model ensures that nearly every cluster contains at least one server. Simulation results demonstrate the fast convergence of the proposed model, evaluated through clustering using inertia and silhouette coefficient. It is important to note that this classification does not directly influence task scheduling or resource allocation processes. Instead, it serves as a preliminary step to improve the effectiveness of these subsequent processes. By strategically placing more powerful tasks on higher-capacity servers, and vice versa, our approach aims to reduce the workload of the scheduler and enhance resource allocation or task scheduling. This classification framework has the potential to achieve efficient task and resource management in edge computing environments.

Original languageEnglish
Title of host publication2023 15th International Conference on Innovations in Information Technology, IIT 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages162-167
Number of pages6
ISBN (Electronic)9798350382396
DOIs
Publication statusPublished - 2023
Event15th International Conference on Innovations in Information Technology, IIT 2023 - Al Ain, United Arab Emirates
Duration: Nov 14 2023Nov 15 2023

Publication series

Name2023 15th International Conference on Innovations in Information Technology, IIT 2023

Conference

Conference15th International Conference on Innovations in Information Technology, IIT 2023
Country/TerritoryUnited Arab Emirates
CityAl Ain
Period11/14/2311/15/23

Keywords

  • Chebyshev distance
  • dge computing
  • K-means

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Science Applications
  • Information Systems

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