The hint protocol: Using a broadcast method to enable ID-free data transmission for dense IoT devices

Ren, Yi ORCID: https://orcid.org/0000-0001-7423-6719, Wu, Ren-Jie and Tseng, Yu-Chee (2017) The hint protocol: Using a broadcast method to enable ID-free data transmission for dense IoT devices. In: 2017 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops). The Institute of Electrical and Electronics Engineers (IEEE), pp. 473-478. ISBN 978-1-5090-4339-2

[thumbnail of Accepted manuscript]
Preview
PDF (Accepted manuscript) - Accepted Version
Download (359kB) | Preview

Abstract

IoT (Internet of Things) has attracted a lot of attention recently. IoT devices need to report their data or status to base stations at various frequencies. The IoT communications observed by a base station normally exhibit the following characteristics: (1) massively connected, (2) lightly loaded per packet, and (3) periodical or at least mostly predictable. The current design principals of communication networks, when applied to IoT scenarios, however, do not fit well to these requirements. For example, an IPv6 address is 128 bits, which is much longer than a 16-bit temperature report. Also, contending to send a small packet is not cost-effective. In this work, we propose a novel framework, which is slot-based, schedule-oriented, and identity-free for uploading IoT devices' data. We show that it fits very well for IoT applications. We propose two schemes, from an ideal one to a more practical one. The main idea is to bundle time slots with certain hashing functions of device IDs, thus significantly reducing transmission overheads, including device IDs and contention overheads.

Item Type: Book Section
Faculty \ School: Faculty of Science > School of Computing Sciences
UEA Research Groups: Faculty of Science > Research Groups > Smart Emerging Technologies
Related URLs:
Depositing User: Pure Connector
Date Deposited: 26 Jan 2018 16:30
Last Modified: 22 Oct 2022 00:05
URI: https://ueaeprints.uea.ac.uk/id/eprint/66110
DOI: 10.1109/PERCOMW.2017.7917609

Downloads

Downloads per month over past year

Actions (login required)

View Item View Item