Reservation frame slotted ALOHA for multi-class IOT networks
Author
Fiaz, Mahzeb
Advisor
Akar, Nail
Date
2019-01Publisher
Bilkent University
Language
English
Type
ThesisItem Usage Stats
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Abstract
The Internet of Things (IoT) is a promising technology capable of revolutionizing
our work and daily lives. ALOHA based medium access schemes are widely used
in IoT applications due to their low complexity despite lower throughput figures.
In this study, we aim to improve the performance of Frame Slotted Aloha (FSA)
for a single hop IoT network without increasing the overall complexity. Duty cycling
is a key concept for managing energy consumption of wireless networks with
battery powered nodes having maximum duty cycle constraints. The goal of this
study is to improve the performance of frame slotted Aloha by exploiting duty
cycle patterns in these networks and using reservations in advance. We discuss
the system model for a single class IoT network and study via simulations the
performance of Reservation Frame Slotted Aloha (RFSA) as compared to FSA,
as well as the performance implications of different system parameters related to
traffic patterns. With the insight gained from this preliminary study, we next
study a multi-class IoT network with nodes belonging to different classes with
different duty cycle constraints. Adopting RFSA for such a network requires different
schemes for allocating channel resources for each class. We propose several
static and dynamic channel allocation schemes based on our traffic model and
study their performance as compared to FSA. Static partitioning has better performance
for low traffic loads but dynamic partitioning offers better throughput
at higher traffic loads. Selection of an appropriate channel allocation scheme can
vary according to the load as well as several system parameters of the network.