Evolutionary Large-scale Sparse Multi-objective Optimization for Collaborative Edge-cloud Computation Offloading

Guang Peng, Huaming Wu, Han Wu, Katinka Wolter

2020

Abstract

This paper proposes evolutionary large-scale sparse multi-objective optimization (ELSMO) algorithms for collaboratively solving edge-cloud computation offloading problems. To begin with, a collaborative edge-cloud computation offloading multi-objective optimization model is established in a mobile environment, where the offloading decision is represented as a binary encoding. Considering the large-scale and sparsity property of the computation offloading model, the restricted Boltzmann machine (RBM) is applied to reduce the dimensionality and learn the Pareto-optimal subspace. In addition, the contribution score of each decision variable is assumed to generate new offsprings. Combining the RBM and the contribution score, two evolutionary algorithms using non-dominated sorting and crowding distance methods are designed, respectively. The proposed algorithms are compared with other state-of-the-art algorithms and offloading strategies on a number of test problems with different scales. The experiment results demonstrate the superiority of the proposed algorithms.

Paper Citation

in Harvard Style

Peng G., Wu H., Wu H. and Wolter K. (2020). Evolutionary Large-scale Sparse Multi-objective Optimization for Collaborative Edge-cloud Computation Offloading. In Proceedings of the 12th International Joint Conference on Computational Intelligence (IJCCI 2020) - Volume 1: ECTA; ISBN 978-989-758-475-6, SciTePress, pages 100-111. DOI: 10.5220/0010145501000111

in Bibtex Style

@conference{ecta20,
author={Guang Peng and Huaming Wu and Han Wu and Katinka Wolter},
title={Evolutionary Large-scale Sparse Multi-objective Optimization for Collaborative Edge-cloud Computation Offloading},
booktitle={Proceedings of the 12th International Joint Conference on Computational Intelligence (IJCCI 2020) - Volume 1: ECTA},
year={2020},
pages={100-111},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010145501000111},
isbn={978-989-758-475-6},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 12th International Joint Conference on Computational Intelligence (IJCCI 2020) - Volume 1: ECTA
TI - Evolutionary Large-scale Sparse Multi-objective Optimization for Collaborative Edge-cloud Computation Offloading
SN - 978-989-758-475-6
AU - Peng G.
AU - Wu H.
AU - Wu H.
AU - Wolter K.
PY - 2020
SP - 100
EP - 111
DO - 10.5220/0010145501000111
PB - SciTePress