Bio inspired optimization techniques for virtual network mapping in a cloud environment

Abstract

Cloud computing is a Computational model that adapts available resources to provide on-demand services. Among the several services available, medical care is a critical one for obtaining prompt treatment. Various data centers are accessible in the cloud to process multiple user requests made via the internet. Virtual network mapping is used to map user requests to the various data centers. Virtual network mapping is a critical component of network virtualization. It is used to route requests for virtual networks to many resource-efficient data centers. Numerous optimization research papers have been published recently to address the issue of virtual network mapping. However, the efficiency of mapping with limited resources is not significantly enhanced. As a result, three unique and efficient recommended strategies are implemented to improve the efficiency of virtual network mapping while consuming less resource for cloud-based medical service providing. newlineThe Annealed Glowworm Optimization Graph Theory-based Virtual Network Mapping (AGOGT-VNM) technique is used to map virtual networks in order to provide cloud-based home medical care services. The AGOGT-VNM approach tries to maximize mapping efficiency while minimizing computing time. AGOGT-VNM supports two types of mapping: node mapping and link mapping. The mapping method is carried out using Annealed Glowworm Optimization Graph Theory (AGOGT). The AGOGT-VNM approach takes the number of patient data queries as an input. Taking into account the input request, node mapping is initially performed using AGOGT to identify the most efficient physical node (physician). AGOGT optimizes using objective functions such as the CPU, memory, and available bandwidth of the nodes. newline newline