End-to-End Delay Minimization-Based Joint Rule Caching and Flow Forwarding Algorithm for SDN

• Main Authors: Lei Luo, Rong Chai, Qiongfang Yuan, Jinyan Li, Chengli Mei
• Format: Article
• Language: English
• Published: IEEE 2020-01-01
• Series: IEEE Access
• Subjects: Software-defined networking; end-to-end delay; rule caching; flow forwarding; resource sharing
• Online Access: https://ieeexplore.ieee.org/document/9166472/

Software-defined networking (SDN) technology is expected to offer higher flexibility and programmability and enhanced transmission performance by decoupling control plane from data plane and enabling centralized network management. In SDN, switches may cache a certain number of flow forwarding rules, so that user flows can be forwarded accordingly. In this article, stressing the limited caching space of switches and the heterogeneous transmission performance of switches and links, we jointly design rule caching and flow forwarding strategy for multiple user flows in SDN. To emphasize the importance of the end-to-end delay caused by the transmission and processing of user flows in both the data plane and control plane, we formulate the joint optimization problem as an end-to-end delay minimization problem. As the original optimization problem is a non-deterministic polynomial hard (NP-hard) problem, which cannot be solved directly, we propose a heuristic algorithm which successively solves three subproblems, i.e., flow forwarding subproblem, rule caching and candidate path selection subproblem, and resource sharing subproblem. By applying the K-shortest path algorithm, a priority-based rule caching algorithm, and Lagrangian dual method, respectively, the three subproblems are solved and the joint rule caching and flow forwarding strategy is obtained. Simulation experiments are conducted to examine the effectiveness of the proposed algorithm, and the results indicate that our proposed algorithm is capable of improving system performance by about 20% compared with the previous solutions.