With the rapid development of the communication and computer industries, computational capability has become an important metric for assessing Quality of Service (QoS). Distributed computing within computational architectures is widely applied in mobile communications, satellite communications, and the Internet of Things (IoT). Edge computing and cloud computing are typical paradigms of distributed computing. Although cloud computing has its inherent advantages, it requires continually increasing deployment costs to maintain computational effectiveness in the face of large computational requests and transmission delays. Based on this, we propose a new paradigm where initial processing is conducted on data, followed by synchronous computations in both the cloud and edge devices. This effectively addresses complex problems while ensuring timely and efficient handling of simpler issues. We aim to minimize delays within acceptable energy consumption limits, thereby enhancing communication timeliness.