@inproceedings{8493043283884055bad4ac2360a6f7db,
title = "Multi-user Multi-provider Resource Allocation in Cloud Computing",
abstract = "In a cloud computing environment, cloud service providers offer cloud services to users. How to achieve reasonable and efficient service resource allocation to meet a user's demands is an important problem. Considering a multi-user and multi-provider environment, we propose a service resource allocation framework to optimize an objective function of load and completion time. We design an improved differential evolution algorithm for optimal resource allocation given a batch of multiple tasks. Experimental results show that proposed method can better balance loads among computing resources while achieving better optimized results for the entire system than some existing methods.",
keywords = "Cloud computing, optimization, resource allocation",
author = "Peiyun Zhang and Xuelei Wang and Mengchu Zhou",
note = "Funding Information: *This work is in part supported by the National Natural Science Foundation of China under Grants 61472005 and 61201252 and CERNET Innovation Project under Grant NGII20160207. Publisher Copyright: {\textcopyright} 2018 IEEE.; 14th IEEE International Conference on Automation Science and Engineering, CASE 2018 ; Conference date: 20-08-2018 Through 24-08-2018",
year = "2018",
month = dec,
day = "4",
doi = "10.1109/COASE.2018.8560365",
language = "English (US)",
series = "IEEE International Conference on Automation Science and Engineering",
publisher = "IEEE Computer Society",
pages = "1428--1433",
booktitle = "2018 IEEE 14th International Conference on Automation Science and Engineering, CASE 2018",
address = "United States",
}