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.

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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