Aarhus Universitets segl

Qi Zhang

Revenue Maximization in Delay-aware Computation Offloading among Service Providers with Fog Federation

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Revenue Maximization in Delay-aware Computation Offloading among Service Providers with Fog Federation. / Mukherjee, Mithun; Kumar, Vikas; Lloret, Jaime et al.
I: IEEE Communications Letters, Bind 24, Nr. 8, 08.2020, s. 1799-1803.

Publikation: Bidrag til tidsskrift/Konferencebidrag i tidsskrift /Bidrag til avisTidsskriftartikelForskningpeer review

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Mukherjee M, Kumar V, Lloret J, Zhang Q. Revenue Maximization in Delay-aware Computation Offloading among Service Providers with Fog Federation. IEEE Communications Letters. 2020 aug.;24(8):1799-1803. doi: 10.1109/LCOMM.2020.2992781

Author

Mukherjee, Mithun ; Kumar, Vikas ; Lloret, Jaime et al. / Revenue Maximization in Delay-aware Computation Offloading among Service Providers with Fog Federation. I: IEEE Communications Letters. 2020 ; Bind 24, Nr. 8. s. 1799-1803.

Bibtex

@article{e8be4466a68143e3acad6cc2d78d4bb2,
title = "Revenue Maximization in Delay-aware Computation Offloading among Service Providers with Fog Federation",
abstract = "In this letter, we study the computational offloading scheme for the delay-aware tasks of the end-users in the fog computing network. We consider a fog federation of different service providers where an individual fog node allocates its computing resources to the end-user in its proximity, while a fog manager coordinates the load balancing among the fog nodes over the entire network. At first, an individual fog node aims to maximize its revenue by selling the computational resources to the end-user in a distributed manner without any global knowledge of the network. To further maximize the overall revenue considering all fog nodes in the fog federation, the fog manager utilizes the remaining computing resources of the underloaded fog nodes. The extensive simulation results show the revenue improvement leveraging fog federation over entire network while maintaining the same and even better delay-performance for the end-users.",
author = "Mithun Mukherjee and Vikas Kumar and Jaime Lloret and Qi Zhang",
year = "2020",
month = aug,
doi = "10.1109/LCOMM.2020.2992781",
language = "English",
volume = "24",
pages = "1799--1803",
journal = "I E E E Communications Letters",
issn = "1089-7798",
publisher = "The Institute of Electrical and Electronics Engineers",
number = "8",

}

RIS

TY - JOUR

T1 - Revenue Maximization in Delay-aware Computation Offloading among Service Providers with Fog Federation

AU - Mukherjee, Mithun

AU - Kumar, Vikas

AU - Lloret, Jaime

AU - Zhang, Qi

PY - 2020/8

Y1 - 2020/8

N2 - In this letter, we study the computational offloading scheme for the delay-aware tasks of the end-users in the fog computing network. We consider a fog federation of different service providers where an individual fog node allocates its computing resources to the end-user in its proximity, while a fog manager coordinates the load balancing among the fog nodes over the entire network. At first, an individual fog node aims to maximize its revenue by selling the computational resources to the end-user in a distributed manner without any global knowledge of the network. To further maximize the overall revenue considering all fog nodes in the fog federation, the fog manager utilizes the remaining computing resources of the underloaded fog nodes. The extensive simulation results show the revenue improvement leveraging fog federation over entire network while maintaining the same and even better delay-performance for the end-users.

AB - In this letter, we study the computational offloading scheme for the delay-aware tasks of the end-users in the fog computing network. We consider a fog federation of different service providers where an individual fog node allocates its computing resources to the end-user in its proximity, while a fog manager coordinates the load balancing among the fog nodes over the entire network. At first, an individual fog node aims to maximize its revenue by selling the computational resources to the end-user in a distributed manner without any global knowledge of the network. To further maximize the overall revenue considering all fog nodes in the fog federation, the fog manager utilizes the remaining computing resources of the underloaded fog nodes. The extensive simulation results show the revenue improvement leveraging fog federation over entire network while maintaining the same and even better delay-performance for the end-users.

U2 - 10.1109/LCOMM.2020.2992781

DO - 10.1109/LCOMM.2020.2992781

M3 - Journal article

VL - 24

SP - 1799

EP - 1803

JO - I E E E Communications Letters

JF - I E E E Communications Letters

SN - 1089-7798

IS - 8

ER -