Geodesic
Multi-constrained Network Occupancy Optimization
Computer Science and Information Systems, Tome 20 (2023) no. 1.

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The greater the number of devices on a network, the higher load in the network, the more chance of a collision occurring, and the longer it takes to transmit a message. The size of load can be identified by measuring the network occupancy, hence it is desirable to minimize the latter. In this paper, we present an approach for network occupancy minimization by optimizing the packing process while satisfying multiple constraints. We formulate the minimization problem as a bin packing problem and we implement a modification of the Best-Fit Decreasing algorithm to find the optimal solution. The approach considers grouping signals that are sent to different destinations in the same package. The analysis is done on a medium-sized plant model, and different topologies are tested. The results show that the proposed solution lowers the network occupancy compared to a reference case.
Keywords: industrial control networking, packing algorithms, network performance 
@article{CSIS_2023_20_1_a16,
     author = {Amar Halilovic and Nedim Zaimovic and Tiberiu Seceleanu and Hamid Feyzmahdavian},
     title = {Multi-constrained {Network} {Occupancy} {Optimization}},
     journal = {Computer Science and Information Systems},
     publisher = {mathdoc},
     volume = {20},
     number = {1},
     year = {2023},
     url = {http://geodesic.mathdoc.fr/item/CSIS_2023_20_1_a16/}
}
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Amar Halilovic; Nedim Zaimovic; Tiberiu Seceleanu; Hamid Feyzmahdavian. Multi-constrained Network Occupancy Optimization. Computer Science and Information Systems, Tome 20 (2023) no. 1. http://geodesic.mathdoc.fr/item/CSIS_2023_20_1_a16/