Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
}
TY - JOUR
T1 - Cross-Network Fusion and Scheduling for Heterogeneous Networks in Smart Factory
AU - Wan, J.
AU - Yang, J.
AU - Wang, S.
AU - Li, D.
AU - Li, P.
AU - Xia, M.
PY - 2020/9/1
Y1 - 2020/9/1
N2 - In the context of Industry 4.0, extensive deployment and application of advanced manufacturing equipment and various sensors is leading to a growing demand for data exchange between different devices. In smart factories, network transmission has multiprotocol features of wired/wireless communication, and different data flows have different real-time requirements. In this article, a heterogeneous network architecture based on software-defined network is proposed for realizing cross-network flexible forwarding of multisource manufacturing data and optimized utilization of network resources. Subsequently, the mechanism of cross-network fusion and scheduling (CNFS) is analyzed from the perspective of high dynamic characteristics and different delay requirements of data flows. Based on this analysis, a route-aware data flow dynamic reconstruction algorithm is proposed. The proposed algorithm improves the efficiency of manufacturing data cross-network fusion, especially for multivariety and small-batch intelligent manufacturing systems. Furthermore, for meeting the bandwidth requirements of different delay flows, a delay-sensitive network bandwidth scheduling algorithm is proposed. Finally, the effectiveness of the proposed CNFS mechanism is verified using a candy packaging intelligent production line prototype platform. © 2005-2012 IEEE.
AB - In the context of Industry 4.0, extensive deployment and application of advanced manufacturing equipment and various sensors is leading to a growing demand for data exchange between different devices. In smart factories, network transmission has multiprotocol features of wired/wireless communication, and different data flows have different real-time requirements. In this article, a heterogeneous network architecture based on software-defined network is proposed for realizing cross-network flexible forwarding of multisource manufacturing data and optimized utilization of network resources. Subsequently, the mechanism of cross-network fusion and scheduling (CNFS) is analyzed from the perspective of high dynamic characteristics and different delay requirements of data flows. Based on this analysis, a route-aware data flow dynamic reconstruction algorithm is proposed. The proposed algorithm improves the efficiency of manufacturing data cross-network fusion, especially for multivariety and small-batch intelligent manufacturing systems. Furthermore, for meeting the bandwidth requirements of different delay flows, a delay-sensitive network bandwidth scheduling algorithm is proposed. Finally, the effectiveness of the proposed CNFS mechanism is verified using a candy packaging intelligent production line prototype platform. © 2005-2012 IEEE.
KW - Cross-network fusion
KW - heterogeneous networks
KW - network resource scheduling
KW - smart factory
KW - software-defined network (SDN)
KW - Bandwidth
KW - Data flow analysis
KW - Data transfer
KW - Dynamics
KW - Electronic data interchange
KW - Heterogeneous networks
KW - Manufacture
KW - Network architecture
KW - Scheduling
KW - Advanced manufacturing
KW - Bandwidth requirement
KW - Delay sensitive
KW - Intelligent manufacturing system
KW - Network bandwidth
KW - Network resource
KW - Network transmission
KW - Real time requirement
KW - Scheduling algorithms
U2 - 10.1109/TII.2019.2952669
DO - 10.1109/TII.2019.2952669
M3 - Journal article
VL - 16
SP - 6059
EP - 6068
JO - IEEE Transactions on Industrial Informatics
JF - IEEE Transactions on Industrial Informatics
SN - 1551-3203
IS - 9
ER -