  In mobile Internet ecosystem, Mobile Users (MUs) purchase wireless data
services from Internet Service Provider (ISP) to access to Internet and acquire
the interested content services (e.g., online game) from Content Provider (CP).
The popularity of intelligent functions (e.g., AI and 3D modeling) increases
the computation-intensity of the content services, leading to a growing
computation pressure for the MUs' resource-limited devices. To this end, edge
computing service is emerging as a promising approach to alleviate the MUs'
computation pressure while keeping their quality-of-service, via offloading
some computation tasks of MUs to edge (computing) servers deployed at the local
network edge. Thus, Edge Service Provider (ESP), who deploys the edge servers
and offers the edge computing service, becomes an upcoming new stakeholder in
the ecosystem. In this work, we study the economic interactions of MUs, ISP,
CP, and ESP in the new ecosystem with edge computing service, where MUs can
acquire the computation-intensive content services (offered by CP) and offload
some computation tasks, together with the necessary raw input data, to edge
servers (deployed by ESP) through ISP. We first study the MU's Joint Content
Acquisition and Task Offloading (J-CATO) problem, which aims to maximize his
long-term payoff. We derive the off-line solution with crucial insights, based
on which we design an online strategy with provable performance. Then, we study
the ESP's edge service monetization problem. We propose a pricing policy that
can achieve a constant fraction of the ex-post optimal revenue with an extra
constant loss for the ESP. Numerical results show that the edge computing
service can stimulate the MUs' content acquisition and improve the payoffs of
MUs, ISP, and CP.
