Online Cognitive Data Sensing and Processing Optimization in Energy-harvesting Edge Computing Systems

06/27/2021
by   Xian Li, et al.
0

Mobile edge computing (MEC) has recently become a prevailing technique to alleviate the intensive computation burden in Internet of Things (IoT) networks. However, the limited device battery capacity and stringent spectrum resource significantly restrict the data processing performance of MEC-enabled IoT networks. To address the two performance limitations, we consider in this paper an MEC-enabled IoT system with an energy harvesting (EH) wireless device (WD) which opportunistically accesses the licensed spectrum of an overlaid primary communication link for task offloading. We aim to maximize the long-term average sensing rate of the WD subject to quality of service (QoS) requirement of primary link, average power constraint of MEC server (MS) and data queue stability of both MS and WD. We formulate the problem as a multi-stage stochastic optimization and propose an online algorithm named PLySE that applies the perturbed Lyapunov optimization technique to decompose the original problem into per-slot deterministic optimization problems. For each per-slot problem, we derive the closed-form optimal solution of data sensing and processing control to facilitate low-complexity real-time implementation. Interestingly, our analysis finds that the optimal solution exhibits an threshold-based structure. Simulation results collaborate with our analysis and demonstrate more than 46.7% data sensing rate improvement of the proposed PLySE over representative benchmark methods.

READ FULL TEXT

page 7

page 9

page 14

page 15

page 17

page 18

page 19

page 30

research
11/04/2021

Energy-Efficient Online Data Sensing and Processing in Wireless Powered Edge Computing Systems

This paper focuses on developing energy-efficient online data processing...
research
10/03/2020

Lyapunov-guided Deep Reinforcement Learning for Stable Online Computation Offloading in Mobile-Edge Computing Networks

Opportunistic computation offloading is an effective method to improve t...
research
06/08/2018

Computation Rate Maximization in UAV-Enabled Wireless Powered Mobile-Edge Computing Systems

Mobile edge computing (MEC) and wireless power transfer (WPT) are two pr...
research
02/05/2021

Stable Online Computation Offloading via Lyapunov-guided Deep Reinforcement Learning

In this paper, we consider a multi-user mobile-edge computing (MEC) netw...
research
07/11/2021

Sharing is Caring: A Mobile Edge Computing Perspective

In this paper, we consider a system model in conjunction with two major ...
research
03/16/2021

Queuing Analysis of Opportunistic Cognitive Radio IoT Network with Imperfect Sensing

In this paper, we analyze a Cognitive Radio-based Internet-of-Things (CR...
research
01/29/2022

Joint Sensing and Communication Rates Control for Energy Efficient Mobile Crowd Sensing

Driven by the fast development of Internet of Things (IoT) applications,...

Please sign up or login with your details

Forgot password? Click here to reset