Cloud computing is an important technology to offer consumer appliances a wide pool of elastic resources. The heterogeneous network faces collision while making communication, which reduces the entire network performance. The future cloud-edge networks will deal with a vast amount of clients and servers, such as the Internet of Things (IoT) and the 6G networks, which require flexible solutions. From these points, Multiple Machine Access Learning with Collision Carrier Avoidance (MMALCCA) protocol is proposed in the environment of 6G Internet of Things for creating an effective communication process. This protocol employs the Media Access Control (MAC) protocol for the sync of high-speed wireless communication networks in the Terahertz (THz) band. MMALCCA performs multiple machine access and collision control for improving the resource utilization and latency-less services of the users. The decisions of the protocol are made using the output of the classification and regression learning method for improving the efficiency of MAC sync. The performance of the proposed protocol is verified using the metrics latency, collision probability, service failure, and resource utilization by varying channels and user equipment density.

云计算是一项重要技术，可为消费类设备提供大量弹性资源。异构网络在进行通信时会遇到冲突，这会降低整个网络的性能。未来的云边缘网络将处理大量需要灵活解决方案的客户端和服务器，例如物联网（IoT）和6G网络。从这些角度出发，在6G物联网环境中提出了具有避免冲突载体的多机访问学习（MMALCCA）协议，以创建有效的通信过程。该协议采用媒体访问控制（MAC）协议来同步太赫兹（THz）频带中的高速无线通信网络。MMALCCA执行多机器访问和冲突控制，以提高用户的资源利用率和无延迟服务。使用分类和回归学习方法的输出来制定协议的决策，以提高MAC同步的效率。通过改变信道和用户设备密度，使用度量等待时间，冲突概率，服务故障和资源利用率来验证所提出协议的性能。