# Intelligent Network Service Optimization in the Context of 5G/NFV
## 2 Related Work  
Over the past half century, the deployment of network management systems (NMSs) was the established practice for applying monitoring and management operations to computer networks [21], and exemplary attempts have been made to modernize their functionality. The authors of [22] conceptualized a novel architecture for network management where applications are treated as software-oriented equipment, and therefore all resources, either physical or intangible, can be managed under the same model. By incorporating a mechanism known as active network technology [23], they theorized the dynamic construction of the governing functions and the active distribution of the related code across the network system. Although the idea may be conceptually relevant to adaptive network administration, its core architecture is based on obsolete technologies. Thus, the aforementioned model may not be applicable in modern, cloud-based applications where self-adaptation and optimal placement of resources with near-real-time responsiveness may be considered as prerequisites. Another approach to network services optimization uses virtual network embedding (VNE) strategies [24]. The solution proposed in [25] seeks to address the problem of mapping virtual networks (VNs) of incoming virtual network requests (VNRs) onto a substrate underlay in an optimal way by maximizing the metric of revenue. The authors decompose the VNE problem into the two distinct subproblems of virtual node mapping (VNM) and virtual link mapping (VLM) and then deal with them separately. A greedy algorithm is used to solve VNM by choosing a set of eligible substrate nodes for each virtual node and then assigning the computational demands to the prominent one in every case, based on its available resources. However, the absence of coordination between the VNM and VLM results in disproportionally distancing the neighboring virtual nodes on the substrate topology, thus increasing the overall cost of the embedded paths and consequently resulting in low acceptance ratios, high network latencies, and low long-term revenue. The adoption of cloud computing technology introduces new challenges regarding virtual resources management and network services performance. In this context, the authors in [26] propose an evolution-oriented, cloud-specific solution that focuses on security properties. The developed framework provides support for the evolution of applications by means of monitoring mechanisms that enable the analysis of experiences gathered during the deployment phase. To mitigate future security risks and vulnerabilities that cannot be predicted, the proposed solution integrates an evolution process oriented around real-time analysis and control operations, which includes the distributed and heterogeneous functionalities of cloud applications in the process loop. Consideration of novel security mechanisms and comparisons between the respective implementations are beyond the scope of this study. In [27], the authors introduce techniques that are oriented around policy management, in order to securely orchestrate cloud infrastructure. Intuitively, the proposed framework provides the capability of expressing these policies in multiple programming languages, supporting also various levels of abstraction. However, the challenges that remain represent a significant obstacle. The development of a formal policy language designed to express the desired policies that would cover key areas ranging from resource management and security to monitoring and access control is yet to be substantiated and materialized. Nevertheless, the modernization process of integrating applications and services into IoT-oriented CNAs dictates compliance with the same set of principles, in order to overcome the challenges of self-adaptation, allowing these managed systems to auto-adjust with minimal or no human intervention.