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 ever-growing complexity of applications. Owing to the constrained physical size, the IoT devices can significantly enhance computation 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 paper, 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 β 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.

Source‐sum‐power minimization in multiple‐sensor single‐AF relay‐based IoT networks with outage constraints and under hardware impairments and imperfect CSI

“…Besides transceiver hardware impairments, channel estimation errors do exist in the system while estimating the channel state information (CSI) with the help of pilot symbols prior to the data symbols transmission. The impact of imperfect CSI is widely investigated in the IoT networks (see other works [36][37][38][39] and the references therein). Specifically, Jiao et al 36 have proposed an optimal resource scheduling algorithm under imperfect CSI in an IoT environment.…”

“…The impact of imperfect CSI is widely investigated in the IoT networks (see other works [36][37][38][39] and the references therein). Specifically, Jiao et al 36 have proposed an optimal resource scheduling algorithm under imperfect CSI in an IoT environment. Ansere et al 37 have investigated joint optimization of user selection, power allocation, and the number of activated base station antennas of multiple IoT devices under imperfect CSI in order to maximize energy-efficiency.…”

“…However, the works [30][31][32][33][34][35][36][37][38][39][40][41] were mainly focused on the performance evaluation of IoT networks in terms of outage probability, ergodic sum rate, energy-efficiency, etc., and did not consider the source-sum-power consumption minimization problem into account which is important to investigate. Recently, the authors in Kharwar et al 42 have put an effort to present the exact solution of optimal power allocation scheme that minimizes the source-sum-power consumption under transceiver hardware impairments for IoT networks.…”

Dimensions of Internet of Things: Technological Taxonomy Architecture Applications and Open Challenges—A Systematic Review

“…Alli and Alam [33] surveyed the fog-edge computing for solutions proposed in studies involving IoT-fog-cloud ecosystems and predicted future growth patterns and raised open issues of the fog cloud of things and concluded that fogging offers a forum for providing services between resource-constrained and latency-sensitive connected devices. Jiao et al [34] analyzed the resource scheduling to optimize the time-averaged network performance for uplink IoT systems based on OFDMA. An optimization problem has been solved by using the Lyapunov optimization theory and the Lagrangian technique of dual decomposition.…”

Predictive model for battery life in IoT networks

“…[6]. Other applications include smart doorbells, smart transportation, smart restaurants, smart health devices, smart farms in agriculture, smart learning tools, pills enabled digestive sensors, smart medical bottles and smart clothes [7][8][9][10][11][12][13][14][15][16][17][18]. US National Intelligence Council has recommended IoT as one of the six 'disruptive civil technologies'.…”