TY - JOUR
T1 - Dynamic adjustment for proactive flow installation mechanism in SDN-based IoT
AU - Cai, Yun Zhan
AU - Wang, Yu Ting
AU - Tsai, Meng Hsun
N1 - Funding Information:
The work of Y.-Z. Cai and M.-H. Tsai was supported by the Center for Open Intelligent Connectivity through the Featured Areas Research Center Program within the Framework of the Higher Education Sprout Project by the Ministry of Education in Taiwan . The work of M.-H. Tsai was also supported in part by the MOST, Taiwan under Grant 108-2221-E-006-112- and 109-2221-E-006-160- , and in part by the Industrial Technology Research Institute, Taiwan .
Funding Information:
This work is sponsored by the R&D enhancement project “ R&D of Network Behavior Security Analyzes for IoT Devices on Advanced Edge Switch in an AIOT plus SDN Integrated Platform, Taiwan ”, which is executed by EstiNet Technologies Inc. and partially sponsored by Hsinchu Science Park Bureau, Ministry of Science and Technology , Taiwan, R.O.C.
Publisher Copyright:
© 2021
PY - 2021/7/20
Y1 - 2021/7/20
N2 - 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.
AB - 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.
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U2 - 10.1016/j.comnet.2021.108167
DO - 10.1016/j.comnet.2021.108167
M3 - Article
AN - SCOPUS:85105556406
VL - 194
JO - Computer Networks
JF - Computer Networks
SN - 1389-1286
M1 - 108167
ER -