## 2 Motivation and Related Work  
In both the academic and industrial communities, it is clear that to support the variety of emerging concepts such as Machine-to-Machine (M2M) communications, Internet of Vehicles (IoV), remote healthcare, and emergency communications, NG systems are mandatedto achieve serious performance goals such as greater system capacity, higher data rates, lower latency, stronger security, and improved Quality of Service (QoS) [19, 31]. When evaluating resources for E2E or Cloud-to-End (C2E) NS for critical applications, compromises in performance are unacceptable. However, a considerable number of well-received publications rest their performance-driven resource allocations on weak foundations. Specifically, either the technique of the shortest path (SP) algorithm or one-dimensional QoS metrics like delay is exploited for path evaluation. Nonetheless, the diverse and heterogeneous user-centric applications of NGNs demand a more sophisticated multidimensional perspective. The main motivation of this research is to develop an architecture-independent tool so that VNOs are able to efficiently deal with the resource allocation of modern VNRs, in terms of high performance. AI/ML orchestration models are outside the scope of this study. Intelligent frameworks work effectively in pattern recognition but are still not reliable in solving deterministic problems. Especially in low-interoperable mixed architecture domains, they produce invalid results compared to traditional heuristics or exact models [32, 33]. The authors of [34] introduce a distributed VNE approach, focusing on minimizing the Round-Trip Time (RTT) in the dynamic conditions of Internet of Things (IoT) and Edge Computing (EC). By focusing on limiting the EC infrastructure's resource utilization, they develop a heuristic that concentrates on the optimal initial mapping of a VNR's VNFs within that EC space. Although their algorithm achieves near-optimal results regarding the minimization of delay in favorable execution times, the monothematic use of an SP variant for performance-oriented path embeddings is distinctively deficient for serving modern user-centric applications. The study illustrated in [35] ventures to address the delay challenge for different application scenarios in 5G environments by proposing a delay-sensitive cross-domain VNE algorithm. Their simulations demonstrate that the fragmentation of the SN resources is reduced and the acceptance ratio of VNRs is inversely increased. To this end, the utilization of a novel three-step mapping mechanism contributes greatly, shifting the focus to the link embedding phase, which is more delay-prone. Nonetheless, the intricate user-centric specifications would be impossible to meet using the proposed solution. Not only the SP method is utilized for path evaluation prior to the embedding process, but also the delay metric is incorporated as the single optimization objective, rendering their algorithm unidimensional. In [36], the authors contemplate a resource reservation method for low latency in Satellite Terrestrial Integrated Networks (STINs). Since STINs are expected to provide diverse services with seamless coverage for communication systems like 5G, 6G, and beyond, STIN-based NS requires delay-avoiding end-to-end connectivity. The proposed VNE algorithm reserves resources by invoking low-latency slicing techniques. While the authors' data reveal that satellite Network Slicing is susceptible to irregular delay values due to the mobility of satellites, they do not integrate jitter into their resource classification mechanism. Thus, end-to-end NS remains vulnerable to considerable delay variance, despite the deployment of delay-sensitive VNE administration. A service orchestration framework is presented in [37] for placing virtual resources over NFV-enabled SDNs. The researchers exploit the customization capabilities of NFV and SDN and present a dynamic VNF placement mechanism of fog or edge resources, for the support of NG edge and IoT-oriented applications.