Abstract
Within the ongoing activities devoted to the defi-
nition of 5G networks, massive Internet of Things (mIoT) is
regarded as a compelling use case, both for its relevance from
business perspective, and for the technical challenges it poses
to network design. With their envisaged massive deployment of
devices requiring sporadic connectivity and small data transmission,
yet QoS constrained, mIoT services will require adhoc
end-to-end (E2E) solutions, i.e., featuring access and core
network enhanced Control and User planes (CP/UP) mechanisms.
This paper presents and evaluates a novel connectivity solution
to manage massive number of devices. The paper presents an
analytical model developed to evaluate the performance of the
proposed solution. Quantitative results derived from the model
demonstrate the effectiveness of the solution proposed in this
paper, compared to 4G systems, and its ability to reduce CP
signaling and optimize UP resource utilization for massive device
deployment.
nition of 5G networks, massive Internet of Things (mIoT) is
regarded as a compelling use case, both for its relevance from
business perspective, and for the technical challenges it poses
to network design. With their envisaged massive deployment of
devices requiring sporadic connectivity and small data transmission,
yet QoS constrained, mIoT services will require adhoc
end-to-end (E2E) solutions, i.e., featuring access and core
network enhanced Control and User planes (CP/UP) mechanisms.
This paper presents and evaluates a novel connectivity solution
to manage massive number of devices. The paper presents an
analytical model developed to evaluate the performance of the
proposed solution. Quantitative results derived from the model
demonstrate the effectiveness of the solution proposed in this
paper, compared to 4G systems, and its ability to reduce CP
signaling and optimize UP resource utilization for massive device
deployment.
Original language | English |
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Title of host publication | IEEE ICC |
Publication status | Published - May 2018 |