research-article

An LSH-based Offloading Method for IoMT Services in Integrated Cloud-Edge Environment

Authors:

Wanchun DouAuthors Info & Claims

ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM), Volume 16, Issue 3s

Article No.: 94, Pages 1 - 19

https://doi.org/10.1145/3408319

Published: 08 January 2021 Publication History

Abstract

Benefiting from the massive available data provided by Internet of multimedia things (IoMT), enormous intelligent services requiring information of various types to make decisions are emerging. Generally, the IoMT devices are equipped with limited computing power, interfering with the process of computation-intensive services. Currently, to satisfy a wide range of service requirements, the novel computing paradigms, i.e., cloud computing and edge computing, can potentially be integrated for service accommodation. Nevertheless, the private information (i.e., location, service type, etc.) in the services is prone to spilling out during service offloading in the cloud-edge computing. To avoid privacy leakage while improving service utility, including the service response time and energy consumption for service executions, a <underline>L</underline>ocality-sensitive-hash (LSH)-based <underline>o</underline>ffloading <underline>m</underline>ethod, named LOM, is devised. Specifically, LSH is leveraged to encrypt the feature information for the services offloaded to the edge servers with the intention of privacy preservation. Eventually, comparative experiments are conducted to verify the effectiveness of LOM with respect to promoting service utility.

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An LSH-based Offloading Method for IoMT Services in Integrated Cloud-Edge Environment

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Published In

cover image ACM Transactions on Multimedia Computing, Communications, and Applications

ACM Transactions on Multimedia Computing, Communications, and Applications Volume 16, Issue 3s

Special Issue on Privacy and Security in Evolving Internet of Multimedia Things and Regular Papers

October 2020

190 pages

ISSN:1551-6857

EISSN:1551-6865

DOI:10.1145/3444536

Editor:
Alberto Del Bimbo
University of Firenze, Italy

Issue’s Table of Contents

Copyright © 2021 ACM.

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Association for Computing Machinery

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Publication History

Published: 08 January 2021

Accepted: 01 May 2020

Revised: 01 May 2020

Received: 01 February 2020

Published in TOMM Volume 16, Issue 3s

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Priority Academic Program Development of Jiangsu Higher Education Institutions fund
Financial and Science Technology Plan Project of Xinjiang Production and Construction Corps
National Natural Science Foundation of China

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https://doi.org/10.23887/jfi.v7i2.72435
Luo LLi XYang KWei MChen JYang JYao L(2023)Intelligent Identification over Power Big Data: Opportunities, Solutions, and ChallengesComputer Modeling in Engineering & Sciences10.32604/cmes.2022.021198134:3(1565-1595)Online publication date: 2023
https://doi.org/10.32604/cmes.2022.021198
Jiang JGuo JKhan MCui YLin W(2023)Energy-saving Service Offloading for the Internet of Medical Things Using Deep Reinforcement LearningACM Transactions on Sensor Networks10.1145/356026519:3(1-20)Online publication date: 1-Mar-2023
https://dl.acm.org/doi/10.1145/3560265
Zhou HYang GXiang YBai YWang W(2023)A Lightweight Matrix Factorization for Recommendation With Local Differential Privacy in Big DataIEEE Transactions on Big Data10.1109/TBDATA.2021.31391259:1(160-173)Online publication date: 1-Feb-2023
https://doi.org/10.1109/TBDATA.2021.3139125
Gao ALiu XMiao Y(2023)LSH-based missing value prediction for abnormal traffic sensors with privacy protection in edge computingComplex & Intelligent Systems10.1007/s40747-023-00992-x9:5(5081-5091)Online publication date: 2-Mar-2023
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Yang CXu XZhou XQi L(2022)Deep Q Network–Driven Task Offloading for Efficient Multimedia Data Analysis in Edge Computing–Assisted IoVACM Transactions on Multimedia Computing, Communications, and Applications10.1145/354868718:2s(1-24)Online publication date: 21-Jul-2022
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Rasool RAhmad HRafique WQayyum AQadir J(2022)Security and privacy of internet of medical things: A contemporary review in the age of surveillance, botnets, and adversarial MLJournal of Network and Computer Applications10.1016/j.jnca.2022.103332201(103332)Online publication date: May-2022
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