  Mobile edge computing (MEC) is a promising technology that provides cloud and
IT services within the proximity of the mobile user. With the increasing number
of mobile applications, mobile devices (MD) encounter limitations of their
resources, such as battery life and computation capacity. The computation
offloading in MEC can help mobile users to reduce battery usage and speed up
task execution. Although there are many solutions for offloading in MEC, most
usually only employ one MEC server for improving mobile device energy
consumption and execution time. Instead of conventional centralized
optimization methods, the current paper considers a decentralized optimization
mechanism between MEC servers and users. In particular, an assignment mechanism
called school choice is employed to assist heterogeneous users to select
different MEC operators in a distributed environment. With this mechanism, each
user can benefit from minimizing the price and energy consumption of executing
tasks while also meeting the specified deadline. The present research has
designed an efficient mechanism for a computation offloading scheme that
achieves minimal price and energy consumption under latency constraints.
Numerical results demonstrate that the proposed algorithm can attain efficient
and successful computation offloading.
