Service Profile-Aware Control Plane: Multi-Instance Fixed Point Approximation within Multi-Granularity VPN Loss Networks Perspective Project Concept Project Impact/Significance Goals and Objectives All traffic management (TM) schemes of Service-Oriented model provides a reduction in blocking probability compared to the IETF-SR and ITU-SR control plane models. The reduction in blocking probability is 40-80% and 19-78% respectively  Depending on net. topology, Service-Oriented TM scheme Highest reduction in blocking probability in “w/(NE,IM)” TM scheme Reduction of 58-80% of blocking probability depending on the network topology Lowest reduction in blocking probability in “w/o(NE,IM)” Service-Oriented TM scheme Reduction of 19-40% of blocking probability depending on network topology This work introduces a novel concept of service profile-aware control plane model Differs from existing Internet Engineering Task Force (IETF) and International Telecommunications Union (ITU) control plane models in multiple aspects:  Full realization of the multi-granularity network resources  Complete consideration for services’ architectures and their associated service profile feature set Including: service flow connectivity, load partitioning flexibility, and service demand granularity Detailed comparison between the three control plane models were considered from multiple dimensions: Traffic management scheme of each control plane model Component-level interaction between service profile layer, control plane layer and network infrastructure layer Infrastructure realization from both horizontal “network domains” and vertical “resource granularity and network partitions” perspective Multiple service architectures and their related mathematical models were analyzed Based on their service profile parameters Detailed mathematical analysis of the three control plane models demonstrated superiority of the Service Profile-Aware control plane model over IETF and ITU models Define detailed architectures for the service configuration models from the following three perspectives: Service flow connectivity, load partitioning, and service demand granularity Define detailed architectures for the three control plane models from the following three perspectives: Transport network granularity realization, component-level, and operational-level Develop detailed mathematical models for the service configuration models to compute the following performance metrics: Input load on each of the topology links based on the service flow connectivity Link blocking probability based on link’s capacity and applied input load Using Fixed Point Approximation (FPA), define detailed mathematical models for the three control plane models to compute the following parameters: Routing probability for each possible route for a source-destination pair Occupancy probability “Utilization” for each of the transport network granularity levels Network-Wide permissible “non-blocked” load Network-Wide service blocking probability The need to establish network connections in a service profile-aware fashion Variety of candidate wired and wireless client networks Current network infrastructure operation via the control plane is independent of the service profile layer Without considering service profile parameters as input to the control plane layer while establishing network connections The optimization of network connections routed paths will have to take into account a number of service profile parameters and network constraints Electrical Engineering & Computer Science