  A method for optimizing encryption mechanism and resource allocation based on
edge computing environment is proposed. A local differential privacy algorithm
based on a histogram algorithm is used to protect user information during task
offloading, which allows accurate preservation of user contextual information
while reducing interference with the playback decision. To efficiently offload
tasks and improve offloading performance, a joint optimization algorithm for
task offloading and resource allocation is proposed that optimizes overall
latency. A balance will be found between privacy protection and task offloading
accuracy. The impact of contextual data interference on task offloading
decisions is minimized while ensuring a predefined level of privacy protection.
In the concrete connected vehicle example, the method distributes tasks among
roadside devices and neighboring vehicles with sufficient computational
resources.
