Versatile Access Control for Massive IoT: Throughput, Latency, and Energy Efficiency
- Authors
- Jang, Han Seung; Jin, Hu; Jung, Bang Chul; Quek, Tony Q. S.
- Issue Date
- Aug-2020
- Publisher
- IEEE COMPUTER SOC
- Keywords
- Uplink; Resource management; Access control; Internet of Things; Collision avoidance; Performance evaluation; Machine-to-machine communications; Internet of things; low-latency; energy-efficiency; access class barring (ACB); ACB factor; backlog estimation
- Citation
- IEEE TRANSACTIONS ON MOBILE COMPUTING, v.19, no.8, pp 1984 - 1997
- Pages
- 14
- Indexed
- SCIE
SCOPUS
- Journal Title
- IEEE TRANSACTIONS ON MOBILE COMPUTING
- Volume
- 19
- Number
- 8
- Start Page
- 1984
- End Page
- 1997
- URI
- https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/956
- DOI
- 10.1109/TMC.2019.2914381
- ISSN
- 1536-1233
1558-0660
- Abstract
- In this paper, we propose a novel access control (AC) mechanism for cellular internet of things (IoT) networks with massive devices, which effectively satisfies various performance metrics such as access throughput, access delay, and energy efficiency. Basic idea of the proposed AC mechanism is to adjust access class barring (ACB) factor according to performance targets. For a given performance target, we derive the optimal ACB factors by considering not only the conventional preamble collision detection technique but also the early preamble collision detection technique, respectively. In addition, the proposed AC mechanism considers overall radio resources to optimize the ACB factor, which includes the number of preambles, random access response (RAR) messages, and physical-layer uplink shared channels (PUSCHs), while most conventional ACB schemes consider only the number of preambles. In particular, the proposed AC mechanism is illustrated with two representative performance metrics: latency and energy efficiency. Through extensive computer simulations, it is shown that the proposed versatile AC mechanism outperforms the conventional ACB schemes in terms of various performance metrics under diverse resource constraints.
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Collections - COLLEGE OF ENGINEERING SCIENCES > SCHOOL OF ELECTRICAL ENGINEERING > 1. Journal Articles
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