Offloading Frameworks
Offloading frameworks can be divided into three categories:
-
Computation offloading frameworks
Communication offloading frameworks
Energy offloading frameworks
Data offloading framework
Computation Offloading
Binary Offloading: Tries to determine if a device has the correct resources available, if they don’t,
then a request is made to neighbouring devices, if that is also not available, then a request is made
to the MEC server. If the MEC server is not available, a request is made to the cloudlet.
Partial offloading:
A computation task is partitioned in multiple parts that are then offloaded to different devices. It is
possible to partition a task into two parts, one for a local computing source and the other one for a
neighbour. This is good for delay-sensitive tasks.
Another case would be to offload to a “higher level” drone, which means that the task is offloaded
to a drone with more computational power, however this also increases the latency.
Energy Offloading Framework
Energy offloading frameworks try to create algorithms that can either decrease the energy
consumption of battery-powered MEC devices, or try to create a framework that can interchange
the
Lyapunov optimization-based dynamic computation offloading (LODCO) algorithm