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    A Computation Offloading Incentive Mechanism with Delay and Cost Constraints under 5G Satellite-Ground IoV Architecture

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    Name:
    1804.02035v1.pdf
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    2.890Mb
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    Genre
    Pre-print
    Date
    2019-08-01
    Author
    Liwang, M
    Dai, S
    Gao, Z
    Du, X
    Guizani, M
    Dai, H
    Subject
    cs.NI
    cs.NI
    Permanent link to this record
    http://hdl.handle.net/20.500.12613/4185
    
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    DOI
    10.1109/MWC.2019.1800364
    Abstract
    © 2002-2012 IEEE. The 5G Internet of Vehicles has become a new paradigm alongside the growing popularity and variety of computation-intensive applications with high requirements for computational resources and analysis capabilities. Existing network architectures and resource management mechanisms may not sufficiently guarantee satisfactory Quality of Experience and network efficiency, mainly suffering from the coverage limitation of road side units, unsatisfactory computational resources and capabilities of onboard equipment, frequently changing network topologies, and ineffective resource management schemes. To meet the demands of such applications, in this article we first establish a novel architecture by integrating the satellite network with the 5G cloud-enabled Internet of Vehicles to efficiently support seamless coverage and efficient resource management. An incentive mechanism based joint optimization problem of opportunistic computation offloading under delay and cost constraints is formulated under the proposed 5G integrated satellite-ground framework, where a vehicular user can either be a service requestor allowed to offload workload to nearby vehicles via vehicle-to-vehicle channels while effectively controlling the cost, or a service provider who provides computing services while protecting profits. As the optimization problem is non-convex and NP-hard, simulated annealing based on the Markov Chain Monte Carlo as well as the metropolis algorithm is applied which can efficaciously obtain both high-quality and cost-effective approximations of global optimal solutions. The effectiveness of the proposed mechanism is corroborated through simulation results.
    Citation to related work
    Institute of Electrical and Electronics Engineers (IEEE)
    Has part
    IEEE Wireless Communications
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    ae974a485f413a2113503eed53cd6c53
    http://dx.doi.org/10.34944/dspace/4167
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