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Performance Analysis of Paging Strategies and Data Delivery Approaches for Supporting Group-Oriented IoT Traffic in 5G Networks
handle: 20.500.11770/327832 , 20.500.11770/327828
The future Internet of Things (IoT) landscape includes not only low-latency and low-payload machine-type communications (MTC), but it is also expected to support the growing demand of multimedia data traffic to be communicated in smart environments. Emerging IoT use cases address the delivery of the same content from the network to a large number of devices. In such scenarios, Point-to-Multipoint(PTM) technology is seen as an efficient enabler of massive IoT (mIoT) in downlink direction. In this paper, we review the capabilities of the cellular-based PTM solution and propose different paging and data delivery strategies with the aim to improve the energy and latency efficiency of group-oriented mIoT communications. The performance of the proposed solutions is evaluated through an extensive simulation campaign.
- University of Reggio Calabria Italy
- Peoples' Friendship University of Russia Russian Federation
- Peoples' Friendship University of Russia Russian Federation
- University of Calabria Italy
IoT, multimedia delivery, eMBMS, paging, 5G, energy efficiency, 004, 620
IoT, multimedia delivery, eMBMS, paging, 5G, energy efficiency, 004, 620
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).5 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Average
