Recently, evolving technologies such as 5G and cloud computing have offered new prospects in mobile ad hoc networks (MANETs). However, achieving a high quality of service (QoS) in multimedia routing over MANET–cloud using 5G networks remains challenging owing to the dynamic nature of mobile devices. The present study addresses this problem by proposing a three-tier architecture in cloud-assisted MANETs with 5G (TCM5G) communication. The network comprises the MANET, cloudlet, and cloud tiers. In the proposed scheme, partitioning and clustering are performed to optimize the cluster size. Specifically, partitioning is first performed by the improved monarch butterfly optimization algorithm. Here, the cluster head (CH) is first selected by computing the importance rate. The selected CH then forms a cluster around itself by broadcasting its selection message. Device-to-device (D2D) communication is established using the Kuhn–Munkres algorithm, which determines the optimal device for each D2D communication in the network in order to increase data transmission efficiency. Network performance depends on effective routing; hence, we considered two routing types: inter-cluster and cloudlet. The former is performed through chaotic flower pollination, and the latter is achieved by using the improved Type-2 Takagi Sugeno fuzzy algorithm. To improve the QoS in multimedia routing, we employ a full-interpolation, scalable video-coding algorithm for effective multimedia data encoding. Task offloading among cloudlets is performed based on a load criterion to balance the cloudlet load. The performance of the proposed system is evaluated using five metrics: throughput, packet delivery ratio (PDR), end-to-end delay, task-completion time, and bandwidth consumption. The results demonstrate that in comparison with the existing DCRM, PCA, and HRM methods, the proposed TCM5G scheme enhances throughput and PDR by 30%, and reduces end-to-end delay, task-completion time, and bandwidth consumption by up to 40%.

最近，诸如5G和云计算等不断发展的技术为移动自组网（MANET）提供了新的前景。但是，由于移动设备的动态特性，使用5G网络在MANET-cloud上的多媒体路由中实现高质量服务（QoS）仍然具有挑战性。本研究通过提出具有5G（TCM5G）通信的云辅助MANET中的三层体系结构来解决此问题。该网络包括MANET，cloudlet和云层。在提出的方案中，执行分区和聚类以优化聚类大小。具体来说，首先通过改进的君主蝶形优化算法执行分区。在此，首先通过计算重要度来选择簇头（CH）。然后，选定的CH通过广播其选择消息在其周围形成一个簇。使用Kuhn–Munkres算法建立设备到设备（D2D）通信，该算法确定网络中每种D2D通信的最佳设备，以提高数据传输效率。网络性能取决于有效的路由；因此，我们考虑了两种路由类型：集群间和cloudlet。前者是通过混沌花授粉来实现的，后者是通过使用改进的Type-2 Takagi Sugeno模糊算法来实现的。为了提高多媒体路由选择中的QoS，我们采用了全插值，可扩展的视频编码算法来进行有效的多媒体数据编码。基于负载标准执行小云之间的任务卸载，以平衡小云负载。所提出的系统的性能使用五个指标进行评估：吞吐量，数据包传送率（PDR），端到端延迟，任务完成时间和带宽消耗。结果表明，与现有的DCRM，PCA和HRM方法相比，提出的TCM5G方案将吞吐量和PDR提高了30％，并减少了多达40的端到端延迟，任务完成时间和带宽消耗％。