Song, Y, Jiao, L, Yang, R orcid.org/0000-0001-6334-4925 et al. (2 more authors) (2022) Incentivizing Online Edge Caching via Auction-Based Subsidization. In: SECON 2022 Participants' Proceedings. 19th Annual IEEE International Conference on Sensing, Communication, and Networking (SECON), 20-23 Sep 2022, Virtual. IEEE , pp. 253-261. ISBN 978-1-6654-8643-9
Abstract
There exists a practical need for incentivizing content providers to cache contents at distributed network edges closer to users. However, this is a particularly challenging problem due to system environments that are uncertain, content placements that couple adjacent time slots, and economic properties that are desired but hard to ensure. In this paper, we present our design of an auction-based incentive mechanism for online edge caching. We formulate the long-term social cost minimization problem as a nonlinear mixed-integer program that addresses bid selections, user request dispatching, content placements, and payment determination in repetitive auctions. To solve this problem online, we devise a greedy approximation algorithm for solving each auction individually, and a lazy-replacement-based online algorithm that ties the series of auctions over time while dynamically pursuing the balance between downloading contents to new cache locations and keeping them at existing locations. We formally prove the approximation ratio for each single auction, the competitive ratio for the long-term social cost, as well as the truthfulness, the individual rationality, and the computational efficiency of our approach. Evaluations with real-world data have also validated and confirmed the practical superiority of our approach over multiple alternative algorithms.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | This item is protected by copyright, all rights reserved. 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. |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Computing (Leeds) |
Funding Information: | Funder Grant number EPSRC (Engineering and Physical Sciences Research Council) EP/T01461X/1 |
Depositing User: | Symplectic Publications |
Date Deposited: | 04 Aug 2022 11:31 |
Last Modified: | 27 Nov 2024 16:51 |
Status: | Published |
Publisher: | IEEE |
Identification Number: | 10.1109/SECON55815.2022.9918618 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:189707 |