Latency-Aware Offloading for Mobile Edge Computing Networks

Feng, Wei; Líu, Hao; Yao, Yingbiao; Cao, Diqiu; Zhao, Mingxiong

doi:10.1109/lcomm.2021.3074621

Cited by 17 publications

(7 citation statements)

References 13 publications

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“…As mentioned before, literatures [2]- [5] have mainly focused on minimizing the task-completion latency. In addition to them, several studies have been performed to optimize both the communication and computing resources for minimizing energy consumption or task-completion latency under various system models.…”

Section: Related Workmentioning

confidence: 99%

“…We consider a single base station (BS) integrated with a mobile edge computing (MEC) server which plays a key role to provide high-performance computing resources to the resource-demanding edge devices (EDs) in proximity. 1,2 The BS is also equipped with multiple J antennas where j represents the antenna index at the BS. Let J denote a set of indices indicating the BS's antenna where J = {j | 1, • • • , J} and |J | = J.…”

Section: System Modelmentioning

confidence: 99%

“…Most previous studies have focused on jointly optimizing them under either energy consumption constraint or latency constraint [1]- [5]. Among them, there have been enormous studies to intensively address the task-completion latency issue [2]- [5]. Particularly, Feng et al [2] jointly optimized the computation and radio resource allocation problem to minimize overall task-completion latency.…”

Section: Introductionmentioning

confidence: 99%

“…Among them, there have been enormous studies to intensively address the task-completion latency issue [2]- [5]. Particularly, Feng et al [2] jointly optimized the computation and radio resource allocation problem to minimize overall task-completion latency. Pursuing a similar objective, Tan et al [3] considered collaborative MEC systems where the computing power of idle edge devices as well as the MEC server is also collaboratively utilized to improve the offloading performance.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

On Offloading Decision for Mobile Edge Computing Systems Considering Access Reservation Protocol

Kim

Adu

et al. 2023

IEEE Access

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For several years, mobile edge computing (MEC) has been highlighted as a promising technique to support emerging computation-intensive applications in cellular networks, e.g., 5G and 6G. Most previous studies have mainly focused on jointly optimizing communication (i.e., radio) and computation resources to improve offloading performance without considering specific communication protocols required for operating the MEC systems in practice. In this article, we newly design a contention-based access reservation protocol (ARP) for efficiently supporting simultaneous task offloading requests from a number of edge devices (EDs), and further define necessary signalings required to determine an optimal offloading factor. Thereafter, we formulate an optimization problem to find the optimal offloading factor that minimizes the task-completion latency. Through simulations, we mainly evaluate the task-completion latency performance of the MEC system incorporated with our proposed access reservation protocol under a multiple-input multiple-output (MIMO) environment. Particularly, we thoroughly investigate several practical aspects such as the effect of the number of edge devices attempting to join the task offloading, the number of antennas equipped at the edge device, and the amount of reserved radio resources required for configuring access reservation protocol on the optimal offloading decision. From the results, we verify the validity of our approach, and provide meaningful insights regarding how the network should be configured to fruitfully exploit the offloading with the MEC systems. INDEX TERMSMobile edge computing, Computation offloading, Offloading decision, Access reservation protocol, Multiple-input multiple-output VOLUME 4, 2021

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Section: Related Workmentioning

confidence: 99%

Section: System Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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On Offloading Decision for Mobile Edge Computing Systems Considering Access Reservation Protocol

Kim

Adu

et al. 2023

IEEE Access

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“…In addition, computation offloading will cause additional delay [16], such as the delay of transmitting tasks on the uplink, which does not exist in local computing. Therefore, reasonable task offloading decision and computing resource allocation are very important in satellite-terrestrial cooperation, i.e., the cooperation between the LEO satellite in the local area and the terrestrial BS in the adjacent area, which assists UEs in computing tasks.…”

Section: Introductionmentioning

confidence: 99%

Joint Offloading Decision and Resource Allocation in Mobile Edge Computing-Enabled Satellite-Terrestrial Network

Tong

Wang

et al. 2022

Symmetry

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With the development of satellite-terrestrial network (STN), mobile edge computing (MEC) servers are deployed at low orbit earth (LEO) satellites to provide computing services for user devices (UEs) in areas without terrestrial network coverage. There is symmetry between satellite networks and terrestrial networks, but there is asymmetry between their resources. Computing resources of satellites’ MEC servers may not be enough. The satellite-terrestrial cooperation is promising, where a satellite migrates tasks to a base station (BS) in an adjacent area, thus utilizing computing resources of the BS’s MEC server. Although there are some studies on computation offloading in STN, few studies consider a satellite as both a relay and a computing unit to assist UEs in computing tasks. This paper proposes a joint offloading decision and resource allocation scheme in MEC-enabled STN, which minimizes the completion delay of all UEs’ indivisible tasks. Firstly, the optimization problem is formulated and decomposed. Then, the proposed scheme based on potential game and the Lagrange multiplier method makes UEs’ task offloading decisions and allocates the satellite’s and the BS’s computing resources, thus obtaining the optimal solution through continuous iterations. Finally, the simulation results validate that the proposed scheme can obtain better gain than other baseline schemes.

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Soft computing approaches for dynamic multi-objective evaluation of computational offloading: a literature review

Khan,

Jiangbin,

Ali

2024

Cluster Comput

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Latency-Aware Offloading for Mobile Edge Computing Networks

Cited by 17 publications

References 13 publications

On Offloading Decision for Mobile Edge Computing Systems Considering Access Reservation Protocol

On Offloading Decision for Mobile Edge Computing Systems Considering Access Reservation Protocol

Joint Offloading Decision and Resource Allocation in Mobile Edge Computing-Enabled Satellite-Terrestrial Network

Soft computing approaches for dynamic multi-objective evaluation of computational offloading: a literature review

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