Path Algebra Driven Classification Solution to Realize Performance Oriented VNE Embeddings

The intense diversity of the Next Generation Networking environments creates a dire need for a modular framework that can integrate with metric-based optimization constructs, to tackle on-demand service-centric and user-centric resource allocation scenarios. Our research offers a new evaluation mechanism to successfully replace traditional path ranking and path selection techniques. By applying the fundamental monotonicity and isotonicity properties of the Path Algebra framework, it can always lead to valid and optimal results. Specifically, first we introduce a new performance-oriented monotonic and isotonic synthesized metric. Afterwards, we propose a methodology that analyzes and determines the weighted influence combination depending on the characteristics of the served user-centric application. The chosen suitable weights address performance-oriented mission critical tailored objectives for adaptive optimizations. Its innovative algebraic design allows it to successfully describe and rank candidate paths multidimensionally, whether in legacy or modern architectures. The experimental data show that the proposed framework suggests more suitable paths in each studied scenarios than the compared methodologies, offering customized solutions according to the specific objective.