  The Internet-of-things (IoT) is the paradigm where anything will be
connected. There are two main approaches to handle the surge in the uplink (UL)
traffic the IoT is expected to generate, namely, Scheduled UL (SC-UL) and
random access uplink (RA-UL) transmissions. SC-UL is perceived as a viable tool
to control Quality-of-Service (QoS) levels while entailing some overhead in the
scheduling request prior to any UL transmission. On the other hand, RA-UL is a
simple single-phase transmission strategy. While this obviously eliminates
scheduling overheads, very little is known about how scalable RA-UL is. At this
critical junction, there is a dire need to analyze the scalability of these two
paradigms. To that end, this paper develops a spatiotemporal mathematical
framework to analyze and assess the performance of SC-UL and RA-UL. The
developed paradigm jointly utilizes stochastic geometry and queueing theory.
Based on such a framework, we show that the answer to the "scheduling vs.
random access paradox" actually depends on the operational scenario.
Particularly, RA-UL scheme offers low access delays but suffers from limited
scalability, i.e., cannot support a large number of IoT devices. On the other
hand, SC-UL transmission is better suited for higher device intensities and
traffic rates.
