Mixed integer formulations for the probabilistic minimum energy broadcast problem in wireless networks

2008 ◽  
Vol 190 (2) ◽  
pp. 578-585 ◽  
Author(s):  
Roberto Montemanni ◽  
Valeria Leggieri ◽  
Chefi Triki
Keyword(s):  
Wireless Networks ◽  
Minimum Energy ◽  
Mixed Integer ◽  
Integer Formulations

scholarly journals Mixed integer formulations for a routing problem with information collection in wireless networks

2020 ◽  
Vol 280 (2) ◽  
pp. 621-638 ◽  
Author(s):  
Luis Flores-Luyo ◽  
Agostinho Agra ◽  
Rosa Figueiredo ◽  
Eladio Ocaña
Keyword(s):  
Wireless Networks ◽  
Mixed Integer ◽  
Information Collection ◽  
Routing Problem ◽  
Integer Formulations

Minimum Energy Cost Broadcasting in Wireless Networks

2016 ◽  
pp. 1308-1312
Author(s):  
Peng-Jun Wan ◽  
Xiang-Yang Li ◽  
Ophir Frieder
Keyword(s):  
Wireless Networks ◽  
Energy Cost ◽  
Minimum Energy ◽  
Minimum Energy Cost

scholarly journals Energy Versus Throughput Optimisation for Machine-to-Machine Communication

Sensors ◽  
2020 ◽  
Vol 20 (15) ◽  
pp. 4122
Author(s):  
Emma Fitzgerald ◽  
Michał Pióro ◽  
Artur Tomaszewski
Keyword(s):  
Mesh Networks ◽  
Numerical Study ◽  
Minimum Energy ◽  
Mixed Integer ◽  
Energy Usage ◽  
Maximum Throughput ◽  
Machine To Machine ◽  
Machine To Machine Communication ◽  
Optimisation Model ◽  
Machine Communication

We investigate the trade-off between energy usage and (packet) throughput in wireless mesh networks performing machine-to-machine communication. For this we provide a novel mixed-integer programming formulation to maximise the throughput while maintaining minimal energy usage, together with an effective price-and-branch solution algorithm based on column generation. The resulting optimisation model is the main original contribution of the presented paper. We conducted a numerical study using network examples from 10 to 40 nodes, in which periodic sensor measurements are aggregated and disseminated to actuators. In almost all cases, we were able to achieve maximum throughput and minimum energy usage simultaneously, and in those cases where this was not possible, the costs incurred in one objective in order to achieve the other were typically low. The solution times for all network sizes were of the order of seconds, showing that our optimisation model is feasible to use in practice.

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