Visible to the public Adaptive Flow-Level Scheduling for the IoT MAC

TitleAdaptive Flow-Level Scheduling for the IoT MAC
Publication TypeConference Paper
Year of Publication2020
AuthorsSharma, P., Nair, J., Singh, R.
Conference Name2020 International Conference on COMmunication Systems NETworkS (COMSNETS)
Date PublishedJan. 2020
PublisherIEEE
ISBN Number978-1-7281-3187-0
Keywordsaccess protocols, adaptive flow-level scheduling, Admission control, best-effort scheduling, carrier sense multiple access, clean slate, Collaboration, distributed CSMA, distributed MAC protocols, high-density networks, high-speed mobile Internet access, Human Behavior, Internet of Things, IoT communications, IoT MAC, IoT-M2M applications, machine-to-machine communication, Metrics, mobile computing, policy-based approach, Protocols, pubcrawl, QoS requirements, quality of service, resilience, Resiliency, Schedules, telecommunication scheduling, WiFi networks, Wireless communication, Wireless fidelity, wireless LAN, wireless MAC, wireless networks
Abstract

Over the past decade, distributed CSMA, which forms the basis for WiFi, has been deployed ubiquitously to provide seamless and high-speed mobile internet access. However, distributed CSMA might not be ideal for future IoT/M2M applications, where the density of connected devices/sensors/controllers is expected to be orders of magnitude higher than that in present wireless networks. In such high-density networks, the overhead associated with completely distributed MAC protocols will become a bottleneck. Moreover, IoT communications are likely to have strict QoS requirements, for which the `best-effort' scheduling by present WiFi networks may be unsuitable. This calls for a clean-slate redesign of the wireless MAC taking into account the requirements for future IoT/M2M networks. In this paper, we propose a reservation-based (for minimal overhead) wireless MAC designed specifically with IoT/M2M applications in mind.

URLhttps://ieeexplore.ieee.org/document/9027315
DOI10.1109/COMSNETS48256.2020.9027315
Citation Keysharma_adaptive_2020