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A Methodology for Capturing Joint Visual Attention Using Mobile Eye-Trackers
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A Distributed and Context-Aware Task Assignment Mechanism for Collaborative Mobile Edge Computing.

Bo Gu1,2, Yapeng Chen3, Haijun Liao4

  • 1School of Electrical and Electronic Engineering, North China Electric Power University, Beijing 102206, China. bo.gu@cc.kogakuin.ac.jp.

Sensors (Basel, Switzerland)
|July 27, 2018
PubMed
Summary
This summary is machine-generated.

This study introduces a new task assignment mechanism for mobile edge computing (MEC). It efficiently decides where to offload tasks to minimize energy consumption while meeting user delay needs.

Keywords:
MECQoScloud computingedge computingenergy efficientfog computingintelligent computationmatchingpreference.stabilitytask assignmentutilityvehicle

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Area of Science:

  • Computer Science
  • Electrical Engineering
  • Telecommunications

Background:

  • Mobile edge computing (MEC) enhances performance by bringing computation closer to users.
  • Offloading tasks from mobile devices to edge resources presents challenges in energy consumption and latency.
  • Deciding whether to offload and to which edge node are critical for efficient MEC operation.

Purpose of the Study:

  • To design a task assignment mechanism for mobile edge computing.
  • To minimize overall energy consumption in MEC systems.
  • To satisfy diverse delay requirements of task owners and ensure scalability.

Main Methods:

  • Formulating the task assignment problem as a one-to-many matching game.
  • Developing a mechanism for efficient task offloading decisions.
  • Conducting intensive simulations to evaluate the proposed mechanism's performance.

Main Results:

  • The proposed mechanism effectively reduces energy consumption.
  • It successfully meets the heterogeneous delay requirements of users.
  • The approach demonstrates good scalability for managing multiple tasks and edge resources.

Conclusions:

  • The developed task assignment mechanism is efficient for mobile edge computing.
  • The matching game formulation provides a robust framework for MEC task offloading.
  • The study highlights the importance of intelligent task assignment for optimizing MEC performance.