RIS-assisted Task Offloading for Wireless Dead Zone to Minimize Delay in Edge Computing

Mithun Mukherjee; Vikas Kumar; Suman Kumar; Constandinos X. Mavromoustakis; Qi Zhang; Mian Guo

doi:10.1109/GLOBECOM48099.2022.10001478

RIS-assisted Task Offloading for Wireless Dead Zone to Minimize Delay in Edge Computing

Mithun Mukherjee, Vikas Kumar, Suman Kumar, Constandinos X. Mavromoustakis, Qi Zhang, Mian Guo

Research output: Contribution to book/anthology/report/proceeding › Article in proceedings › Research › peer-review

7 Citations (Scopus)

Abstract

End-users under poor wireless network coverage generally suffer from underutilization of bandwidth. This adversely affects the overall performance of task offloading to the edge server. In this work, we study a Reconfigurable Intelligent Surface (RIS)-assisted wireless network that enables end-user's devices under weak signal reception areas to enhance their offloading opportunities for delay minimization. It becomes a challenging task to allocate uploading bandwidth allocation for the offloaded tasks from end-user devices under different signal coverage areas. We formulate the optimization problem of bandwidth allocation for the offloaded tasks in the edge server and the offloading decisions as a quadratically constrained quadratic problem. We exploit a semi-definite relaxation (SDR) method to solve the problem. Moreover, during optimization, we minimize the adverse impact of bandwidth allocation for poor end-users on good end-users performance. From extensive simulation results, we show remarkably elevated improvement in delay reduction with RIS assistance compared to other baselines, increasing the number and ratio of end-user devices under good and poor signal reception areas.

Original language	English
Title of host publication	2022 IEEE Global Communications Conference, GLOBECOM 2022 - Proceedings
Number of pages	6
Publisher	IEEE
Publication date	Dec 2022
Pages	2554-2559
ISBN (Print)	978-1-6654-3541-3
ISBN (Electronic)	978-1-6654-3540-6
DOIs	https://doi.org/10.1109/GLOBECOM48099.2022.10001478
Publication status	Published - Dec 2022
Event	IEEE Global Communications Conference 2022: Hybrid: In-Person and Virtual Conference Accelerating the Digital Transformation through Smart Communications - Rio de Janeiro, Brazil Duration: 4 Dec 2022 → 8 Dec 2022 https://globecom2022.ieee-globecom.org/

Conference

Conference	IEEE Global Communications Conference 2022
Country/Territory	Brazil
City	Rio de Janeiro
Period	04/12/2022 → 08/12/2022
Internet address	https://globecom2022.ieee-globecom.org/

Keywords

Mobile edge computing
deadline-aware task offloading
edge computing
offloading
reconfigurable intelligent surfaces

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10.1109/GLOBECOM48099.2022.10001478

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title = "RIS-assisted Task Offloading for Wireless Dead Zone to Minimize Delay in Edge Computing",

abstract = "End-users under poor wireless network coverage generally suffer from underutilization of bandwidth. This adversely affects the overall performance of task offloading to the edge server. In this work, we study a Reconfigurable Intelligent Surface (RIS)-assisted wireless network that enables end-user's devices under weak signal reception areas to enhance their offloading opportunities for delay minimization. It becomes a challenging task to allocate uploading bandwidth allocation for the offloaded tasks from end-user devices under different signal coverage areas. We formulate the optimization problem of bandwidth allocation for the offloaded tasks in the edge server and the offloading decisions as a quadratically constrained quadratic problem. We exploit a semi-definite relaxation (SDR) method to solve the problem. Moreover, during optimization, we minimize the adverse impact of bandwidth allocation for poor end-users on good end-users performance. From extensive simulation results, we show remarkably elevated improvement in delay reduction with RIS assistance compared to other baselines, increasing the number and ratio of end-user devices under good and poor signal reception areas.",

keywords = "Mobile edge computing, deadline-aware task offloading, edge computing, offloading, reconfigurable intelligent surfaces",

author = "Mithun Mukherjee and Vikas Kumar and Suman Kumar and Mavromoustakis, {Constandinos X.} and Qi Zhang and Mian Guo",

year = "2022",

month = dec,

doi = "10.1109/GLOBECOM48099.2022.10001478",

language = "English",

isbn = "978-1-6654-3541-3",

pages = "2554--2559",

booktitle = "2022 IEEE Global Communications Conference, GLOBECOM 2022 - Proceedings",

publisher = "IEEE",

note = "IEEE Global Communications Conference 2022 ; Conference date: 04-12-2022 Through 08-12-2022",

url = "https://globecom2022.ieee-globecom.org/",

}

Mukherjee, M, Kumar, V, Kumar, S, Mavromoustakis, CX, Zhang, Q & Guo, M 2022, RIS-assisted Task Offloading for Wireless Dead Zone to Minimize Delay in Edge Computing. in 2022 IEEE Global Communications Conference, GLOBECOM 2022 - Proceedings. IEEE, pp. 2554-2559, IEEE Global Communications Conference 2022, Rio de Janeiro, Brazil, 04/12/2022. https://doi.org/10.1109/GLOBECOM48099.2022.10001478

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T1 - RIS-assisted Task Offloading for Wireless Dead Zone to Minimize Delay in Edge Computing

AU - Mukherjee, Mithun

AU - Kumar, Vikas

AU - Kumar, Suman

AU - Mavromoustakis, Constandinos X.

AU - Zhang, Qi

AU - Guo, Mian

PY - 2022/12

Y1 - 2022/12

N2 - End-users under poor wireless network coverage generally suffer from underutilization of bandwidth. This adversely affects the overall performance of task offloading to the edge server. In this work, we study a Reconfigurable Intelligent Surface (RIS)-assisted wireless network that enables end-user's devices under weak signal reception areas to enhance their offloading opportunities for delay minimization. It becomes a challenging task to allocate uploading bandwidth allocation for the offloaded tasks from end-user devices under different signal coverage areas. We formulate the optimization problem of bandwidth allocation for the offloaded tasks in the edge server and the offloading decisions as a quadratically constrained quadratic problem. We exploit a semi-definite relaxation (SDR) method to solve the problem. Moreover, during optimization, we minimize the adverse impact of bandwidth allocation for poor end-users on good end-users performance. From extensive simulation results, we show remarkably elevated improvement in delay reduction with RIS assistance compared to other baselines, increasing the number and ratio of end-user devices under good and poor signal reception areas.

AB - End-users under poor wireless network coverage generally suffer from underutilization of bandwidth. This adversely affects the overall performance of task offloading to the edge server. In this work, we study a Reconfigurable Intelligent Surface (RIS)-assisted wireless network that enables end-user's devices under weak signal reception areas to enhance their offloading opportunities for delay minimization. It becomes a challenging task to allocate uploading bandwidth allocation for the offloaded tasks from end-user devices under different signal coverage areas. We formulate the optimization problem of bandwidth allocation for the offloaded tasks in the edge server and the offloading decisions as a quadratically constrained quadratic problem. We exploit a semi-definite relaxation (SDR) method to solve the problem. Moreover, during optimization, we minimize the adverse impact of bandwidth allocation for poor end-users on good end-users performance. From extensive simulation results, we show remarkably elevated improvement in delay reduction with RIS assistance compared to other baselines, increasing the number and ratio of end-user devices under good and poor signal reception areas.

KW - Mobile edge computing

KW - deadline-aware task offloading

KW - edge computing

KW - offloading

KW - reconfigurable intelligent surfaces

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U2 - 10.1109/GLOBECOM48099.2022.10001478

DO - 10.1109/GLOBECOM48099.2022.10001478

M3 - Article in proceedings

SN - 978-1-6654-3541-3

SP - 2554

EP - 2559

BT - 2022 IEEE Global Communications Conference, GLOBECOM 2022 - Proceedings

PB - IEEE

T2 - IEEE Global Communications Conference 2022

Y2 - 4 December 2022 through 8 December 2022

ER -

RIS-assisted Task Offloading for Wireless Dead Zone to Minimize Delay in Edge Computing

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