Machine-Type Communication is essential to make the Internet of Things real. This new kind of communication, however, entails a lot of challenges that need to be addressed, especially for what concerns the integration between the human-triggered traffic, i.e., the traffic generated by the people through smartphones and tablets, and machine-triggered traffic, i.e., the data that are autonomously generated by Machine-Type Devices, in the next generation cellular networks, i.e., the 5G. These two types of traffic are completely different, but while the former has been widely studied and appropriately modeled, the latter is still lacking a generally accepted model. In this paper, after a brief survey on traffic models that have been proposed by the academic and the standardization community, we propose and test a general framework to evaluate the performance of a generic cellular network architecture in the context of joint human-triggered and machine-triggered traffic.

A study on M2M traffic and its impact on cellular networks

M. Centenaro;
2015-01-01

Abstract

Machine-Type Communication is essential to make the Internet of Things real. This new kind of communication, however, entails a lot of challenges that need to be addressed, especially for what concerns the integration between the human-triggered traffic, i.e., the traffic generated by the people through smartphones and tablets, and machine-triggered traffic, i.e., the data that are autonomously generated by Machine-Type Devices, in the next generation cellular networks, i.e., the 5G. These two types of traffic are completely different, but while the former has been widely studied and appropriately modeled, the latter is still lacking a generally accepted model. In this paper, after a brief survey on traffic models that have been proposed by the academic and the standardization community, we propose and test a general framework to evaluate the performance of a generic cellular network architecture in the context of joint human-triggered and machine-triggered traffic.
2015
978-1-5090-0366-2
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11582/318658
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