Dynamic adjustment for proactive flow installation mechanism in SDN-based IoT

Abstract

To satisfy various network requirements in the Internet of Things (IoT), software-defined networking (SDN) is viewed as an indispensable technology. Given the flow table resources in switches are limited, we proposed the periodic subflow-based proactive flow installation mechanism (PSPFIM) in our previous work. By separating subflows, PSPFIM can accurately detect the transmission periods and preinstall flow entry into switches before the transmissions arrive to reduce flow table occupancy. PSPFIM, however, is dysfunctional if transmission periods are at the millisecond level or subflows cannot be separated. In this paper, we propose the dynamic adjustment for PFIM (DAPFIM). DAPFIM is more widely applicable because the enhanced detection algorithm is less affected by noises and can detect transmission periods at the millisecond level. Besides, the adjustment algorithm can correct the error between an expected transmission period and a real transmission period. Through simulations, DAPFIM can detect transmission periods that cannot be detected by PSPFIM and other related work. Besides, DAPFIM averagely reduces up to 78% flow entry duration compared to other related work by changing the unit of the idle timeout from seconds to milliseconds, which saves much more flow table resources in switches.