LAUSR

Virtualization and softwarization have driven the widespread adoption of the cloud computing paradigm, with savings in CAPEX, OPEX, and environmental footprint, by transferring to and sharing computational resources in datacenters. Represented by some leading technologies - as Software Defined Networks, Network Function Virtualization, and Service Function Chaining - they bring new network and service management challenges. The autonomous resource elasticity that demands new techniques to detect overloaded functions, also known as bottlenecks, is a challenge. Most research efforts in this area have focused on traditional hardware metrics like CPU, memory, throughput, and tailored application metrics. These approaches may be imprecise and hard to transfer between different scenarios. This paper presents the Network Queue Assessment (NQA) technique for detecting bottlenecks in Service Function Chaining based on network queue occupation, which requires no end-user feedback or knowledge about its internal architecture, and no definition of thresholds. Our results confirm the accuracy of NQA for bottleneck detection in a testbed evaluation with virtualized versions of five network functions: Intrusion Detection System (IDS), Network Address Translation (NAT), Virtual Private Network (VPN), Proxy-cache, and Firewall. Also, we combine the previously evaluated functions in four more complex scenarios to confirm our conclusions.