Joint Optimization of Sensing and Computation for Status Update in Mobile Edge Computing Systems

TL;DR

This paper proposes a joint optimization framework for sensing and computation in mobile edge computing systems to improve status update freshness and reduce energy consumption, addressing the challenges of limited resources and data validity.

Contribution

It introduces a novel joint optimization model for sensing and offloading in MEC systems, with an iterative algorithm to minimize system costs under freshness and energy constraints.

Findings

The proposed method effectively reduces system cost in simulations.

Joint optimization improves status update freshness and energy efficiency.

The algorithm outperforms baseline approaches in various scenarios.

Abstract

IoT devices recently are utilized to detect the state transition in the surrounding environment and then transmit the status updates to the base station for future system operations. To satisfy the stringent timeliness requirement of the status updates for the accurate system control, age of information (AoI) is introduced to quantify the freshness of the sensory data. Due to the limited computing resources, the status update can be offloaded to the mobile edge computing (MEC) server for execution to ensure the information freshness. Since the status updates generated by insufficient sensing operations may be invalid and cause additional processing time, the data sensing and processing operations need to be considered simultaneously. In this work, we formulate the joint data sensing and processing optimization problem to ensure the freshness of the status updates and reduce the energy consumption of IoT devices. Then, the formulated NP-hard problem is decomposed into the sampling, sensing and computation offloading optimization problems. Afterwards, we propose a multi-variable iterative system cost minimization algorithm to optimize the system overhead. Simulation results show the efficiency of our method in decreasing the system cost and dominance of sensing and processing under different scenarios.