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Digital Home-Monitoring of Patients after Kidney Transplantation: The MACCS Platform
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Service Migration Policy Optimization considering User Mobility for E-Healthcare Applications.

Xuhui Zhao1, Jianghui Liu1, Baofeng Ji1

  • 1Information Engineering College, Henan University of Science and Technology, Luoyang 471000, China.

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|July 12, 2021
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Summary
This summary is machine-generated.

Mobile edge computing (MEC) services face interruptions due to user mobility. This study introduces a migration solution that significantly reduces costs and improves service quality for mobile e-healthcare applications.

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Area of Science:

  • Computer Science
  • Networking
  • Distributed Systems

Background:

  • Mobile edge computing (MEC) enables critical e-healthcare applications by providing cloud resources at the network edge.
  • User mobility in MEC environments can disrupt services, degrading quality of service (QoS).
  • Service migration is a key strategy to maintain service continuity and QoS.

Purpose of the Study:

  • To propose a novel service migration solution for mobile edge computing environments.
  • To develop a comprehensive cost model for service migration considering key challenges.
  • To optimize service migration policies using Markov decision processes.

Main Methods:

  • A service migration solution based on the concept of migration zones.
  • Formulation of service migration cost using a comprehensive mathematical model.
  • Modeling the service migration problem as a Markov decision process (MDP).
  • Development of three algorithms to solve the formulated optimization problem.

Main Results:

  • The proposed service migration approach reduces total system costs by up to three times compared to no migration.
  • Experimental results demonstrate superior performance over general solutions in terms of total expected reward.
  • The solution effectively handles user mobility challenges in MEC for e-healthcare.

Conclusions:

  • The developed service migration strategy effectively mitigates service interruptions caused by user mobility in MEC.
  • The proposed algorithms provide optimal migration policies, enhancing overall system performance and user experience.
  • This research offers a practical solution for reliable e-healthcare services in mobile edge computing.