Spatiotemporal Model for Uplink IoT Traffic: Scheduling & Random Access Paradox
Type
ArticleKAUST Department
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) DivisionElectrical Engineering Program
Date
2018-10-24Online Publication Date
2018-10-24Print Publication Date
2018-12Permanent link to this record
http://hdl.handle.net/10754/629948
Metadata
Show full item recordAbstract
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.Citation
Gharbieh M, El Sawy H, Yang H-C, Bader A, Alouini M-S (2018) Spatiotemporal Model for Uplink IoT Traffic: Scheduling & Random Access Paradox. IEEE Transactions on Wireless Communications: 1–1. Available: http://dx.doi.org/10.1109/TWC.2018.2876522.arXiv
arXiv:1810.05309Additional Links
https://ieeexplore.ieee.org/document/8506623ae974a485f413a2113503eed53cd6c53
10.1109/TWC.2018.2876522