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Whispering: Joint Service Offloading and Computation Reuse in Cloud-Edge Networks.

Boubakr Nour1, Spyridon Mastorakis2, Abderrahmen Mtibaa3

  • 1School of Computer Science, Beijing Institute of Technology, China.

IEEE International Conference on Communications : [Proceedings]. IEEE International Conference on Communications
|October 25, 2021
PubMed
Summary
This summary is machine-generated.

This study introduces Whispering, an edge computing model for optimizing service offloading. It significantly reduces task completion times by intelligently migrating services and reusing computations, outperforming traditional edge or cloud execution.

Keywords:
Computation ReuseEdge ComputingService Offloading

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Area of Science:

  • Computer Science
  • Distributed Systems
  • Cloud Computing

Background:

  • The proliferation of Internet of Things (IoT) devices and increasing user demands strain traditional cloud computing infrastructures.
  • Edge computing offers a solution by moving computation closer to data sources, addressing communication and computation challenges.
  • Optimizing service migration (offloading) and computation reuse is crucial for efficient edge computing.

Purpose of the Study:

  • To present Whispering, an analytical model for service offloading from cloud to edge.
  • To minimize computational task completion time for user devices.
  • To enhance resource utilization in edge computing environments.

Main Methods:

  • Developed an analytical model named Whispering for service migration.
  • Empirically investigated the impact of computation reuse for previously executed tasks.
  • Proposed an adaptive task offloading scheme between edge and cloud.

Main Results:

  • Whispering model demonstrated significant reductions in task completion time.
  • Achieved up to 35% lower task completion times compared to edge-only execution.
  • Achieved up to 97% lower task completion times when coupled with computation reuse compared to cloud-only execution.

Conclusions:

  • The Whispering model effectively minimizes task completion times in edge computing.
  • Computation reuse further amplifies the performance gains of the proposed offloading scheme.
  • The adaptive offloading scheme enhances resource utilization and efficiency in distributed computing environments.