UCL Discovery
UCL home » Library Services » Electronic resources » UCL Discovery

Media Query Processing For The Internet-of-Things: Coupling Of Device Energy Consumption And Cloud Infrastructure Billing

Renna, F; Doyle, J; Giotsas, V; Andreopoulos, I; (2016) Media Query Processing For The Internet-of-Things: Coupling Of Device Energy Consumption And Cloud Infrastructure Billing. IEEE Transactions on Multimedia , 18 (12) pp. 2537-2552. 10.1109/TMM.2016.2600438. Green open access

[thumbnail of Journal_SecondRevision_v4_2col_1space.pdf]
Preview
Text
Journal_SecondRevision_v4_2col_1space.pdf - Accepted Version

Download (802kB) | Preview

Abstract

Audio/visual recognition and retrieval applications have recently garnered significant attention within Internet-of- Things (IoT) oriented services, given that video cameras and audio processing chipsets are now ubiquitous even in low-end embedded systems. In the most typical scenario for such services, each device extracts audio/visual features and compacts them into feature descriptors, which comprise media queries. These queries are uploaded to a remote cloud computing service that performs content matching for classification or retrieval applications. Two of the most crucial aspects for such services are: (i) controlling the device energy consumption when using the service; (ii) reducing the billing cost incurred from the cloud infrastructure provider. In this paper we derive analytic conditions for the optimal coupling between the device energy consumption and the incurred cloud infrastructure billing. Our framework encapsulates: the energy consumption to produce and transmit audio/visual queries, the billing rates of the cloud infrastructure, the number of devices concurrently connected to the same cloud server, the query volume constraint of each cluster of devices, and the statistics of the query data production volume per device. Our analytic results are validated via a deployment with: (i) the device side comprising compact image descriptors (queries) computed on Beaglebone Linux embedded platforms and transmitted to Amazon Web Services (AWS) Simple Storage Service; (ii) the cloud side carrying out image similarity detection via AWS Elastic Compute Cloud (EC2) instances, with the AWS Auto Scaling being used to control the number of instances according to the demand.

Type: Article
Title: Media Query Processing For The Internet-of-Things: Coupling Of Device Energy Consumption And Cloud Infrastructure Billing
Open access status: An open access version is available from UCL Discovery
DOI: 10.1109/TMM.2016.2600438
Publisher version: http://dx.doi.org/10.1109/TMM.2016.2600438
Language: English
Additional information: Copyright © 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Keywords: Visual search, internet-of-things, cloud computing, analytic modeling
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Electronic and Electrical Eng
URI: https://discovery.ucl.ac.uk/id/eprint/1507819
Downloads since deposit
112Downloads
Download activity - last month
Download activity - last 12 months
Downloads by country - last 12 months

Archive Staff Only

View Item View Item