  Mobile edge computing (MEC) is a promising computing paradigm that offers
users proximity and instant computing services for various applications, and it
has become an essential component of the Internet of Things (IoT). However, as
compute-intensive services continue to emerge and the number of IoT devices
explodes, MEC servers are confronted with resource limitations. In this work,
we investigate a task-offloading framework for device-assisted edge computing,
which allows MEC servers to assign certain tasks to auxiliary IoT devices (ADs)
for processing. To facilitate efficient collaboration among task IoT devices
(TDs), the MEC server, and ADs, we propose an incentive-driven pricing and task
allocation scheme. Initially, the MEC server employs the Vickrey auction
mechanism to recruit ADs. Subsequently, based on the Stackelberg game, we
analyze the interactions between TDs and the MEC server. Finally, we establish
the optimal service pricing and task allocation strategy, guided by the
Stackelberg model and priority settings. Simulation results show that the
proposed scheme dramatically improves the utility of the MEC server while
safeguarding the interests of TDs and ADs, achieving a triple-win scenario.
