Paper Info
Title
Toward Optimal Resource Scheduling for Internet of Things Under Imperfect CSI
Abstract
The Internet of Things (IoT) increases the number of connected devices and supports the ever-growing complexity of applications. Owing to the constrained physical size, the IoT devices can significantly enhance the computational capacity by offloading computation-intensive tasks to the resource-rich edge servers deployed at the base station (BS) via wireless networks. However, how to achieve optimal resource scheduling remains a challenge due to stochastic task arrivals, time-varying wireless channels, and imperfect estimation of channel state information (CSI). In this article, by virtue of the Lyapunov optimization technique, we propose the toward optimal resource scheduling algorithm under imperfect CSI (TORS) to optimize resource scheduling in an IoT environment. A convex transmit power and subchannel allocation problem in TORS is formulated. This problem is then solved via the Lagrangian dual decomposition method. We derive analytical bounds for the time-averaged system throughput and queue backlog. We show that TORS can arbitrarily approach the optimal system throughput by simply tuning an introduced control parameter <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\beta $ </tex-math></inline-formula> without prior knowledge of stochastic task arrivals and the CSI of wireless channels. Extensive simulation results confirm the theoretical analysis on the performance of TORS.
Year
DOI
Venue
2020
10.1109/JIOT.2019.2952721
IEEE Internet of Things Journal
Keywords
DocType
Volume
Channel estimation,imperfect channel state information (CSI),Lyapunov optimization,resource scheduling
Journal
7
Issue
ISSN
Citations 
3
2327-4662
1
PageRank 
References 
Authors
0.35
0
4
Name
Order
Citations
PageRank
Libo Jiao110.35
Yulei Wu248051.95
Jiaqing Dong321.03
Zexun Jiang4233.25