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首页> 外文期刊>Mobile networks & applications >Three-Tier Architecture Supporting QoS Multimedia Routing in Cloud-Assisted MANET with 5G Communication (TCM5G)
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Three-Tier Architecture Supporting QoS Multimedia Routing in Cloud-Assisted MANET with 5G Communication (TCM5G)

机译：支持QoS多媒体路由的三层架构在云辅助疯狂的船长中，具有5G通信（TCM5G）

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摘要

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%.
机译：最近，5G和云计算等演变的技术在移动临时网络（船只）中提供了新的前景。然而，由于移动设备的动态性质，在MANED-Cloud中实现高质量的服务（QoS）在Manet-Cloud上使用5G网络仍然具有挑战性。本研究通过提出具有5G（TCM5G）通信的云辅助舰队中的三层架构来解决这个问题。该网络包括MANET，CLOORLET和云层。在所提出的方案中，执行分区和群集以优化簇大小。具体地，首先通过改进的Monarch蝶形优化算法执行分区。这里，首先通过计算重要性速率来选择簇头（CH）。然后，所选的CH通过广播其选择消息来形成围绕自身的集群。使用Kuhn-Munkres算法建立设备到设备（D2D）通信，该算法确定网络中的每个D2D通信的最佳设备以增加数据传输效率。网络性能取决于有效路由;因此，我们考虑了两个路由类型：群集间和Cloudlet。前者通过混沌花授粉进行，通过使用改进的2型Takagi Sugeno模糊算法来实现后者。为了提高多媒体路由中的QoS，我们采用了一种用于有效多媒体数据编码的全插值，可伸缩的视频编码算法。 Cloudlet之间的任务卸载是基于负载标准来执行的，以平衡Cloudlet负载。使用五个度量评估所提出的系统的性能：吞吐量，分组传递比（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，所提出的TCM5G方案增强了吞吐量和PDR的30％，并减少了最终延迟，任务完成时间和带宽消耗最多40个％。

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