Energy-Efficient Client Relay Scheme for Machine-to-Machine Communication

Author(s):  
S. Andreev ◽  
O. Galinina ◽  
Y. Koucheryavy
Author(s):  
O. S. Galinina ◽  
S. D. Andreev ◽  
A. M. Tyurlikov

Introduction: Machine-to-machine communication assumes data transmission from various wireless devices and attracts attention of cellular operators. In this regard, it is crucial to recognize and control overload situations when a large number of such devices access the network over a short time interval.Purpose:Analysis of the radio network overload at the initial network entry stage in a machine-to-machine communication system.Results: A system is considered that features multiple smart meters, which may report alarms and autonomously collect energy consumption information. An analytical approach is proposed to study the operation of a large number of devices in such a system as well as model the settings of the random-access protocol in a cellular network and overload control mechanisms with respect to the access success probability, network access latency, and device power consumption. A comparison between the obtained analytical results and simulation data is also offered. 


Sensors ◽  
2020 ◽  
Vol 20 (15) ◽  
pp. 4122
Author(s):  
Emma Fitzgerald ◽  
Michał Pióro ◽  
Artur Tomaszewski

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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