Computation offloading for object-oriented applications in a UAV-based edge-cloud environment

The high mobility and maneuverability of unmanned aerial vehicles (UAVs) enable them to act as temporary base stations (BSs) in extreme environments, expanding the computing capacities of terminals for intelligent applications, most of which are object-oriented ones. Computation offloading in a UAV-...

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Published in:	The Journal of supercomputing Vol. 78; no. 8; pp. 10829 - 10853
Main Authors:	Zhang, Jianshan, Li, Ming, Chen, Zheyi, Lin, Bing
Format:	Journal Article
Language:	English
Published:	New York Springer US 01.05.2022 Springer Nature B.V
Subjects:	Cloud computing Compilers Computation offloading Computer Science Extreme environments Genetic algorithms Interpreters Maneuverability Object oriented programming Particle swarm optimization Processor Architectures Programming Languages Task scheduling Terminals Unmanned aerial vehicles Task scheduling UAV Object-oriented applications Computation offloading Mobile edge computing
ISSN:	0920-8542, 1573-0484
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Abstract	The high mobility and maneuverability of unmanned aerial vehicles (UAVs) enable them to act as temporary base stations (BSs) in extreme environments, expanding the computing capacities of terminals for intelligent applications, most of which are object-oriented ones. Computation offloading in a UAV-based edge-cloud environment is an excellent way to improve the performance of these object-oriented intelligent applications. In contrast, the computation-intensive tasks are offloaded to the cloud, and the data-intensive ones are offloaded to the edge. Though computation offloading over the cloud, edge, and terminals has been broadly studied, existing researches primarily establish scheduling algorithms on program high-level abstraction without consideration of challenges from program structures. We focus on task scheduling for offloading object-oriented applications while considering the ’encapsulation’ characteristic. We proposed a time-driven offloading strategy based on a particle swarm optimization algorithm employing the genetic algorithm operators with floating encoding (PGFE). This strategy introduces a genetic algorithm’s randomly two-point crossover and mutation operator to avoid converging on local optima effectively. The simulation results show that our strategy can reduce the average execution time of object-oriented applications by 11.78–48.02%, compared with other classic algorithms in a UAV-based edge-cloud environment.
AbstractList	The high mobility and maneuverability of unmanned aerial vehicles (UAVs) enable them to act as temporary base stations (BSs) in extreme environments, expanding the computing capacities of terminals for intelligent applications, most of which are object-oriented ones. Computation offloading in a UAV-based edge-cloud environment is an excellent way to improve the performance of these object-oriented intelligent applications. In contrast, the computation-intensive tasks are offloaded to the cloud, and the data-intensive ones are offloaded to the edge. Though computation offloading over the cloud, edge, and terminals has been broadly studied, existing researches primarily establish scheduling algorithms on program high-level abstraction without consideration of challenges from program structures. We focus on task scheduling for offloading object-oriented applications while considering the ’encapsulation’ characteristic. We proposed a time-driven offloading strategy based on a particle swarm optimization algorithm employing the genetic algorithm operators with floating encoding (PGFE). This strategy introduces a genetic algorithm’s randomly two-point crossover and mutation operator to avoid converging on local optima effectively. The simulation results show that our strategy can reduce the average execution time of object-oriented applications by 11.78–48.02%, compared with other classic algorithms in a UAV-based edge-cloud environment.
Author	Chen, Zheyi Li, Ming Lin, Bing Zhang, Jianshan
Author_xml	– sequence: 1 givenname: Jianshan surname: Zhang fullname: Zhang, Jianshan organization: College of Mathematics and Computer Science, Fuzhou University, Fujian Provincial Key Laboratory of Network Computing and Intelligent Information Processing – sequence: 2 givenname: Ming surname: Li fullname: Li, Ming organization: College of Mathematics and Computer Science, Fuzhou University, Fujian Provincial Key Laboratory of Network Computing and Intelligent Information Processing – sequence: 3 givenname: Zheyi surname: Chen fullname: Chen, Zheyi organization: Department of Computer Science, College of Engineering, Mathematics and Physical Sciences, University of Exeter – sequence: 4 givenname: Bing orcidid: 0000-0001-5874-4748 surname: Lin fullname: Lin, Bing email: wheellx@163.com organization: College of Physics and Energy, Fujian Normal University
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Snippet	The high mobility and maneuverability of unmanned aerial vehicles (UAVs) enable them to act as temporary base stations (BSs) in extreme environments, expanding...
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SubjectTerms	Cloud computing Compilers Computation offloading Computer Science Extreme environments Genetic algorithms Interpreters Maneuverability Object oriented programming Particle swarm optimization Processor Architectures Programming Languages Task scheduling Terminals Unmanned aerial vehicles
Title	Computation offloading for object-oriented applications in a UAV-based edge-cloud environment
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