  As novel applications spring up in future network scenarios, the requirements
on network service capabilities for differentiated services or burst services
are diverse. Aiming at the research of collaborative computing and resource
allocation in edge scenarios, migrating computing tasks to the edge and cloud
for computing requires a comprehensive consideration of energy consumption,
bandwidth, and delay. Our paper proposes a collaboration mechanism based on
computation offloading, which is flexible and customizable to meet the
diversified requirements of differentiated networks. This mechanism handles the
terminal's differentiated computing tasks by establishing a collaborative
computation offloading model between the cloud server and edge server.
Experiments show that our method has more significant improvements over regular
optimization algorithms, including reducing the execution time of computing
tasks, improving the utilization of server resources, and decreasing the
terminal's energy consumption.
