Adaptive timeout & eviction orchestrator for software-defined networking

Flow table management plays a vital role in enhancing the scalability, efficiency, and overall performance of Software-Defined Networking (SDN). In this thesis, an innovative mechanism called Adaptive Timeout Assignment and Eviction Orchestrator (ATEO) is presented. Multi-layered timeout assignment module enhanced with Z-score-based flow classification, a reactive heuristic-driven eviction mechanism, and a dynamic threshold adjuster module to adapt to various network conditions are introduced as a comprehensive flow management strategy with ATEO. The timeout assignment module of ATEO intelligently modifies timeout values by analyzing the statistical characteristics of flows. The Z-score-based flow classification module differentiates between short-lived "mice" flows and long-lived "elephant" flows. This classification helps ATEO to dynamically allocate more persistent timeouts to frequently accessed or critical flows. On the other hand, the heuristic-based eviction module identifies and removes flow rules that are expected to have a lower impact in the future. This allows ATEO to create space for the newcomer flows that are potentially more important. In addition, it ensures that the flow table is populated with high-priority flows which minimizes the unnecessary packet-in messages and the controller overhead. Additionally, ATEO's proposed dynamic threshold adjuster monitors the occupancy of the flow table and the changes in the number of rejected flows. It uses these data to generate a near real-time response. Thresholds that are used in timeout and eviction processes are updated to keep the number of rejected flows lower while having high Quality of Service (QoS). It significantly reduces the rejected flows while keeping the packet-in count competitive with other algorithms. The results show that ATEO achieved an efficient flow table management which is essential for modern network infrastructures.