DMORA : Decentralized Multi-SP Online Resource Allocation Scheme for Mobile Edge Computing
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
Author(s)
Related Research Unit(s)
Detail(s)
Original language | English |
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Pages (from-to) | 2497-2507 |
Number of pages | 11 |
Journal / Publication | IEEE Transactions on Cloud Computing |
Volume | 10 |
Issue number | 4 |
Online published | 15 Dec 2020 |
Publication status | Published - Oct 2022 |
Link(s)
Abstract
Mobile edge computing (MEC) can significantly reduce latency by pushing resources away from remote clouds to distributed base stations (BSs) equipped with MEC servers, which are closer to users and deployed by service providers (SPs) at the edge of cellular networks. To improve user experience and increase their own revenue, SPs tend to use resources in their deployed BSs to provide services instead of using resources in BSs deployed by other SPs. We envision a densely-deployed multi-SP MEC network where a user equipment (UE) is covered by multiple BSs from different SPs. As the resource in BSs and MEC servers is limited, it is a challenging problem for SPs to reasonably allocate resources in the edge computing (EC) layer to improve the quality of service. In this paper, we propose a novel resource allocation scheme, Decentralized Multi-SP Resource Allocation (DMRA), which aims to maximize the total profit of all SPs at the EC layer and provide high-quality services. Then, we extend our design to the online scheme. The algorithm Decentralized Multi-SP Online Resource Allocation (DMORA) is proposed to fit the dynamic network environment. Simulation results indicate that our proposed schemes can effectively maximize the total profit of all SPs at the EC layer while improving user experience.
Research Area(s)
- Mobile Edge Computing, Resource Allocation, Profit Maximization
Citation Format(s)
DMORA: Decentralized Multi-SP Online Resource Allocation Scheme for Mobile Edge Computing. / Zhang, Chen; Du, Hongwei.
In: IEEE Transactions on Cloud Computing, Vol. 10, No. 4, 10.2022, p. 2497-2507.
In: IEEE Transactions on Cloud Computing, Vol. 10, No. 4, 10.2022, p. 2497-2507.
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review