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Self-Adaptation Resource Allocation for Continuous Offloading Tasks in Pervasive Computing.

Aiman Ehsan1, Khurram Zeeshan Haider1,2, Shahla Faisal2,3

  • 1Department of Software Engineering, Government College University, Faisalabad, Pakistan.

Computational and Mathematical Methods in Medicine
|July 8, 2022
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Summary
This summary is machine-generated.

Optimizing mobile device tasks with cloud computing and metaheuristic algorithms, like Particle Swarm Optimization (PSO), significantly reduces battery consumption and processing time, enhancing device efficiency and user experience.

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Area of Science:

  • Computer Science
  • Artificial Intelligence
  • Mobile Computing

Background:

  • Technological advancements increase data volume and user expectations for sophisticated device features.
  • High-definition displays and sensor usage rapidly deplete device battery power.
  • Low latency requirements can exacerbate power consumption in smart devices.

Purpose of the Study:

  • To investigate the effectiveness of cloud computing and metaheuristic algorithms in optimizing task offloading for mobile devices.
  • To reduce energy consumption and improve the efficiency of smart devices.
  • To compare the performance of different metaheuristic algorithms for task offloading.

Main Methods:

  • Offloading computational tasks from smart devices to cloud servers.
  • Simulating tasks in a virtual environment on cloud servers to analyze resource parameters.
  • Utilizing metaheuristic algorithms, including First-Come, First-Served (FCFS), Ant Colony Optimization (ACO), and Particle Swarm Optimization (PSO), for task offloading decisions.
  • Comparing battery consumption and makespan time across different algorithms.

Main Results:

  • Particle Swarm Optimization (PSO) demonstrated lower battery consumption and makespan time compared to FCFS and ACO.
  • Offloading device resources to the cloud effectively reduces overall energy consumption.
  • PSO enhances device battery life and system efficiency.

Conclusions:

  • Cloud computing, combined with optimized metaheuristic algorithms like PSO, offers a viable solution for managing computational load and conserving energy on mobile devices.
  • PSO is a superior algorithm for task offloading, leading to significant improvements in device battery life and system performance.
  • The study highlights the potential of intelligent offloading strategies to meet the demands of modern, data-intensive applications.