Data, User and Power Allocations for Caching in Multi-Access Edge Computing

Abstract

In the multi-access edge computing (MEC) environment, app vendors’ data can be cached on edge servers to ensure low-latency data retrieval. Massive users can simultaneously access edge servers with high data rates through flexible allocations of transmit power. The ability to manage networking resources offers unique opportunities to app vendors but also raises unprecedented challenges. To ensure fast data retrieval for users in the MEC environment, edge data caching must take into account the allocations of data, users, and transmit power jointly. We make the first attempt to study the Data, User, and Power Allocation (DUPA <inline-formula><tex-math notation="LaTeX">$^3$</tex-math></inline-formula> ) problem, aiming to serve the most users and maximize their overall data rate. First, we formulate the DUPA <inline-formula><tex-math notation="LaTeX">$^3$</tex-math></inline-formula> problem and prove its <inline-formula><tex-math notation="LaTeX">$\mathcal {NP}$</tex-math></inline-formula> -completeness. Then, we model the DUPA <inline-formula><tex-math notation="LaTeX">$^3$</tex-math></inline-formula> problem as a potential DUPA <inline-formula><tex-math notation="LaTeX">$^3$</tex-math></inline-formula> game admitting at least one Nash equilibrium and propose a two-phase game-theoretic decentralized algorithm named DUPA <inline-formula><tex-math notation="LaTeX">$^3$</tex-math></inline-formula> Game to achieve the Nash equilibrium as the solution to the DUPA <inline-formula><tex-math notation="LaTeX">$^3$</tex-math></inline-formula> problem. To evaluate DUPA <inline-formula><tex-math notation="LaTeX">$^3$</tex-math></inline-formula> Game, we analyze its theoretical performance and conduct extensive experiments to demonstrate its effectiveness and efficiency.