Detection Performance of Packet Arrival under Downclocking for Mobile Edge Computing

Zhimin Wang; Qinglin Zhao; Fangxin Xu; Hongning Dai; Yujun Zhang

doi:10.1155/2018/9641712

Detection Performance of Packet Arrival under Downclocking for Mobile Edge Computing

Zhimin Wang
, Qinglin Zhao^*
, Fangxin Xu
, Hongning Dai
, Yujun Zhang

^*Corresponding author for this work

Department of Computer Science

Research output: Contribution to journal › Journal article › peer-review

6 Citations (Scopus)

Abstract

Mobile edge computing (MEC) enables battery-powered mobile nodes to acquire information technology services at the network edge. These nodes desire to enjoy their service under power saving. The sampling rate invariant detection (SRID) is the first downclocking WiFi technique that can achieve this objective. With SRID, a node detects one packet arrival at a downclocked rate. Upon a successful detection, the node reverts to a full-clocked rate to receive the packet immediately. To ensure that a node acquires its service immediately, the detection performance (namely, the miss-detection probability and the false-alarm probability) of SRID is of importance. This paper is the first one to theoretically study the crucial impact of SRID attributes (e.g., tolerance threshold, correlation threshold, and energy ratio threshold) on the packet detection performance. Extensive Monte Carlo experiments show that our theoretical model is very accurate. This study can help system developers set reasonable system parameters for WiFi downclocking.

Original language	English
Article number	9641712
Number of pages	7
Journal	Wireless Communications and Mobile Computing
Volume	2018
DOIs	https://doi.org/10.1155/2018/9641712
Publication status	Published - 28 Feb 2018

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 9 Industry, Innovation, and Infrastructure

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Cite this

@article{76fd773de2764956b6447d94e7786d37,

title = "Detection Performance of Packet Arrival under Downclocking for Mobile Edge Computing",

abstract = "Mobile edge computing (MEC) enables battery-powered mobile nodes to acquire information technology services at the network edge. These nodes desire to enjoy their service under power saving. The sampling rate invariant detection (SRID) is the first downclocking WiFi technique that can achieve this objective. With SRID, a node detects one packet arrival at a downclocked rate. Upon a successful detection, the node reverts to a full-clocked rate to receive the packet immediately. To ensure that a node acquires its service immediately, the detection performance (namely, the miss-detection probability and the false-alarm probability) of SRID is of importance. This paper is the first one to theoretically study the crucial impact of SRID attributes (e.g., tolerance threshold, correlation threshold, and energy ratio threshold) on the packet detection performance. Extensive Monte Carlo experiments show that our theoretical model is very accurate. This study can help system developers set reasonable system parameters for WiFi downclocking.",

author = "Zhimin Wang and Qinglin Zhao and Fangxin Xu and Hongning Dai and Yujun Zhang",

note = "This work is supported by the Macao FDCT-MOST Grant 001/2015/AMJ, Macao FDCT Grants 056/2017/A2 and 005/2016/A1, National Science Foundation of China (61672500), and Program of International S\&T Cooperation (2016YFE0121500). Publisher Copyright: {\textcopyright} 2018 Zhimin Wang et al.",

year = "2018",

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day = "28",

doi = "10.1155/2018/9641712",

language = "English",

volume = "2018",

journal = "Wireless Communications and Mobile Computing",

issn = "1530-8669",

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TY - JOUR

T1 - Detection Performance of Packet Arrival under Downclocking for Mobile Edge Computing

AU - Wang, Zhimin

AU - Zhao, Qinglin

AU - Xu, Fangxin

AU - Dai, Hongning

AU - Zhang, Yujun

N1 - This work is supported by the Macao FDCT-MOST Grant 001/2015/AMJ, Macao FDCT Grants 056/2017/A2 and 005/2016/A1, National Science Foundation of China (61672500), and Program of International S&T Cooperation (2016YFE0121500). Publisher Copyright: © 2018 Zhimin Wang et al.

PY - 2018/2/28

Y1 - 2018/2/28

N2 - Mobile edge computing (MEC) enables battery-powered mobile nodes to acquire information technology services at the network edge. These nodes desire to enjoy their service under power saving. The sampling rate invariant detection (SRID) is the first downclocking WiFi technique that can achieve this objective. With SRID, a node detects one packet arrival at a downclocked rate. Upon a successful detection, the node reverts to a full-clocked rate to receive the packet immediately. To ensure that a node acquires its service immediately, the detection performance (namely, the miss-detection probability and the false-alarm probability) of SRID is of importance. This paper is the first one to theoretically study the crucial impact of SRID attributes (e.g., tolerance threshold, correlation threshold, and energy ratio threshold) on the packet detection performance. Extensive Monte Carlo experiments show that our theoretical model is very accurate. This study can help system developers set reasonable system parameters for WiFi downclocking.

AB - Mobile edge computing (MEC) enables battery-powered mobile nodes to acquire information technology services at the network edge. These nodes desire to enjoy their service under power saving. The sampling rate invariant detection (SRID) is the first downclocking WiFi technique that can achieve this objective. With SRID, a node detects one packet arrival at a downclocked rate. Upon a successful detection, the node reverts to a full-clocked rate to receive the packet immediately. To ensure that a node acquires its service immediately, the detection performance (namely, the miss-detection probability and the false-alarm probability) of SRID is of importance. This paper is the first one to theoretically study the crucial impact of SRID attributes (e.g., tolerance threshold, correlation threshold, and energy ratio threshold) on the packet detection performance. Extensive Monte Carlo experiments show that our theoretical model is very accurate. This study can help system developers set reasonable system parameters for WiFi downclocking.

UR - https://www.scopus.com/pages/publications/85044156378

U2 - 10.1155/2018/9641712

DO - 10.1155/2018/9641712

M3 - Journal article

AN - SCOPUS:85044156378

SN - 1530-8669

VL - 2018

JO - Wireless Communications and Mobile Computing

JF - Wireless Communications and Mobile Computing

M1 - 9641712

ER -

Detection Performance of Packet Arrival under Downclocking for Mobile Edge Computing

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