TY - GEN
T1 - A Sharing-Economy Inspired Pricing Mechanism for Multi-Access Edge Computing
AU - Siew, Marie
AU - Cai, Desmond
AU - Li, Lingxiang
AU - Quek, Tony Q.S.
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/12
Y1 - 2020/12
N2 - Multi-access Edge Computing (MEC) is an emerging paradigm which allows users to offload their computationally intensive tasks to the network edge. In this paper, we analyze resource allocation in MEC from the market and economic perspective. Due to extremely heterogeneous usage demands across users in the future IoE market, current coarse-grained pricing schemes result in partial wastage: some users would have excess un-utilized resource quota while others might have reserved insufficient resources. Therefore, we introduce a novel sharing economy-inspired business model, where a platform facilitates the sharing of resource quota among users, increasing resource efficiency. The goal is to maximize the overall welfare of users who join the sharing platform. As the platform lacks control and has imperfect knowledge of users' payoff functions and distributions, a distributed pricing mechanism is proposed. In our mechanism, the platform and users jointly arrive at an equilibrium. We prove that the equilibrium point of the mechanism is the socially optimal point. Simulations illustrate convergence, the robustness of our mechanism to changes in demand and supply, and that sharing increases the welfare of users.
AB - Multi-access Edge Computing (MEC) is an emerging paradigm which allows users to offload their computationally intensive tasks to the network edge. In this paper, we analyze resource allocation in MEC from the market and economic perspective. Due to extremely heterogeneous usage demands across users in the future IoE market, current coarse-grained pricing schemes result in partial wastage: some users would have excess un-utilized resource quota while others might have reserved insufficient resources. Therefore, we introduce a novel sharing economy-inspired business model, where a platform facilitates the sharing of resource quota among users, increasing resource efficiency. The goal is to maximize the overall welfare of users who join the sharing platform. As the platform lacks control and has imperfect knowledge of users' payoff functions and distributions, a distributed pricing mechanism is proposed. In our mechanism, the platform and users jointly arrive at an equilibrium. We prove that the equilibrium point of the mechanism is the socially optimal point. Simulations illustrate convergence, the robustness of our mechanism to changes in demand and supply, and that sharing increases the welfare of users.
UR - http://www.scopus.com/inward/record.url?scp=85100379348&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85100379348&partnerID=8YFLogxK
U2 - 10.1109/GLOBECOM42002.2020.9322554
DO - 10.1109/GLOBECOM42002.2020.9322554
M3 - Conference contribution
AN - SCOPUS:85100379348
T3 - 2020 IEEE Global Communications Conference, GLOBECOM 2020 - Proceedings
BT - 2020 IEEE Global Communications Conference, GLOBECOM 2020 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2020 IEEE Global Communications Conference, GLOBECOM 2020
Y2 - 7 December 2020 through 11 December 2020
ER -