# A Decentralized Optimization Framework for Energy Harvesting Devices

**Authors:** Alessandro Biason, Subhrakanti Dey, Michele Zorzi

arXiv: 1701.02081 · 2017-01-10

## TL;DR

This paper introduces a decentralized optimization framework using Dec-MDPs for energy harvesting wireless sensor networks, enabling nodes to independently optimize their channel access policies based on periodic synchronization, improving energy and collision management.

## Contribution

It develops a novel multi-layer Dec-MDP framework for decentralized policy optimization in energy harvesting networks with periodic synchronization.

## Key findings

- Orthogonal schemes are suboptimal in energy harvesting scenarios.
- Optimal policies balance orthogonal and random access strategies.
- Decentralized policies outperform fixed schemes in simulations.

## Abstract

Designing decentralized policies for wireless communication networks is a crucial problem, which has only been partially solved in the literature so far. In this paper, we propose the Decentralized Markov Decision Process (Dec-MDP) framework to analyze a wireless sensor network with multiple users which access a common wireless channel. We consider devices with energy harvesting capabilities, so that they aim at balancing the energy arrivals with the data departures and with the probability of colliding with other nodes. Randomly over time, an access point triggers a SYNC slot, wherein it recomputes the optimal transmission parameters of the whole network, and distributes this information. Every node receives its own policy, which specifies how it should access the channel in the future, and, thereafter, proceeds in a fully decentralized fashion, without interacting with other entities in the network. We propose a multi-layer Markov model, where an external MDP manages the jumps between SYNC slots, and an internal Dec-MDP computes the optimal policy in the near future. We numerically show that, because of the harvesting, a fully orthogonal scheme (e.g., TDMA-like) is suboptimal in energy harvesting scenarios, and the optimal trade-off lies between an orthogonal and a random access system.

## Full text

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## Figures

19 figures with captions in the complete paper: https://tomesphere.com/paper/1701.02081/full.md

## References

38 references — full list in the complete paper: https://tomesphere.com/paper/1701.02081/full.md

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Source: https://tomesphere.com/paper/1701.02081