Editing Emerging Research Directions (section)

====Collaboration Manners====
At a high level, the collaboration manner used in an edge computing architecture will determine the system's strengths and weaknesses. The various collaboration models are among devices (things), edge servers, and cloud infrastructure. Things-edge collaboration allows smart devices (things) to offload computation to nearby edge servers, reducing latency and conserving device energy [3]. This model is commonly used in scenarios where rapid responses are crucial, such as in autonomous vehicles or mobile applications. Things-edge-cloud collaboration extends this by leveraging both edge and cloud resources—tasks are dynamically split or redirected based on resource availability and performance goals, enabling scalability for complex, data-intensive applications like AI and 3D sensing for industrial IoT.

Edge-edge and edge-cloud collaboration further enhance system flexibility and efficiency. In edge-edge collaboration, overloaded edge servers can offload tasks to other edge nodes, promoting better load balancing for QoS requirements. Meanwhile, edge-cloud collaboration enables cloud services to offload computation closer to the user. For example, video transcoding taking place on a home WiFi point instead of in the cloud layer [3].