Joint Optimization of Energy Efficiency and Data Compression in TDMA-Based Medium Access Control for the IoT - Extended Version

TL;DR

This paper presents a joint optimization framework for energy-efficient data compression and transmission in IoT networks using TDMA, aiming to extend network lifetime while maintaining low data distortion.

Contribution

It introduces a scalable offline optimal policy for joint source coding and transmission parameter allocation in TDMA-based IoT networks.

Findings

Optimized energy and transmission parameters extend network lifetime.

Achieved low distortion levels with joint design approach.

Applicable to dynamic channel and source conditions.

Abstract

Energy efficiency is a key requirement for the Internet of Things, as many sensors are expected to be completely stand-alone and able to run for years without battery replacement. Data compression aims at saving some energy by reducing the volume of data sent over the network, but also affects the quality of the received information. In this work, we formulate an optimization problem to jointly design the source coding and transmission strategies for time-varying channels and sources, with the twofold goal of extending the network lifetime and granting low distortion levels. We propose a scalable offline optimal policy that allocates both energy and transmission parameters (i.e., times and powers) in a network with a dynamic Time Division Multiple Access (TDMA)-based access scheme.