The cloud offers more services across multiple infrastructures and rapidly growing areas of development in medical care. In the cloud, Network virtualization allows multiple isolated virtual networks (VNs) for flexible sharing of network resources. The virtual network mapping in Network virtualization provides the dynamic virtual node and link resources to satisfy the user needs. The major challenges of cloud computing are optimally and resourcefully responds to each user service requests with minimum time. To address these problems in distributed and hybrid cloud environments, Multicriteria Dragonfly based Graph Theory Resource Optimized Virtual Network Mapping (MD-GTROVNM) technique is introduced. The main objective of the MD-GTROVNM technique is to improve the efficiency of virtual network request mapping with less resource utilization. In the MD-GTROVNM technique, Multicriteria Dragonfly based Graph Theory performs both virtual node mapping and link mapping with reasonable resource utilization such as CPU, memory, and bandwidth. In node mapping, the Multicriteria Dragonfly optimization technique is applied to find the optimal physical node among the population that satisfies the resource constraints. The proposed Multicriteria Dragonfly optimization algorithm achieved a more optimal solution for virtual network mapping. The experimental scenario is carried out with various parameters such as mapping efficiency, computation time, Request acceptance ratio and memory consumption with a number of VN requests. The observed results confirm that the MD-GTROVNM technique effectively increases the mapping efficiency, Request acceptance ratio and minimizes the computation time as well as memory consumption when compared to the existing techniques.

云提供了跨多个基础架构和快速增长的医疗保健发展领域的更多服务。在云中，网络虚拟化允许多个隔离的虚拟网络（VN）灵活共享网络资源。网络虚拟化中的虚拟网络映射提供动态虚拟节点和链接资源，以满足用户需求。云计算的主要挑战是在最短的时间内以最佳方式充分利用资源来响应每个用户服务请求。为了解决分布式和混合云环境中的这些问题，引入了基于多准则蜻蜓的图论资源优化虚拟网络映射（MD-GTROVNM）技术。MD-GTROVNM技术的主要目标是在减少资源利用的情况下提高虚拟网络请求映射的效率。在MD-GTROVNM技术中，基于Multicriteria Dragonfly的图论以合理的资源利用率（例如CPU，内存和带宽）执行虚拟节点映射和链接映射。在节点映射中，采用多准则蜻蜓优化技术在满足资源约束的总体中找到最佳物理节点。提出的Multicriteria Dragonfly优化算法为虚拟网络映射提供了更优化的解决方案。实验方案是使用各种参数执行的，例如映射效率，计算时间，请求接受率和带有多个VN请求的内存消耗。观察到的结果证实了MD-GTROVNM技术有效地提高了映射效率，