@inproceedings{77f56bdb3ac74d31804ee5b38c8ab6fe,
title = "Energy Cost and Performance-Sensitive Bi-objective Scheduling of Tasks in Clouds",
abstract = "Cloud computing attracts a growing number of organizations to deploy their applications in distributed data centers for low latency and cost-effectiveness. The growth of arriving instructions makes it challenging to minimize their energy cost and improve Quality of Service (QoS) of applications by optimizing resource provisioning and instruction scheduling. This work formulates a bi-objective constrained optimization problem, and solves it with a Simulated-annealing-based Adaptive Differential Evolution (SADE) algorithm to jointly minimize both energy cost and instruction response time. The minimal Manhattan distance method is adopted to obtain a knee for good tradeoff between energy cost minimization and QoS maximization. Real-life data-based experiments demonstrate SADE achieves lower instruction response time, and smaller energy cost than several state-of-the-art peers.",
keywords = "Data centers, cloud computing, multi-objective optimization, performance modeling, task scheduling",
author = "Haitao Yuan and Jing Bi and Zhou, {Meng Chu}",
note = "Funding Information: This work was supported in part by the National Natural Science Foundation of China (NSFC) under Grants 61802015 and 61703011, in part by the Major Science and Technology Program for Water Pollution Control and Treatment of China under Grant 2018ZX07111005, and in part by the National Defense Pre-Research Foundation of China under Grants 41401020401 and 41401050102. Publisher Copyright: {\textcopyright} 2020 IEEE.; 2020 IEEE International Conference on Networking, Sensing and Control, ICNSC 2020 ; Conference date: 30-10-2020 Through 02-11-2020",
year = "2020",
month = oct,
day = "30",
doi = "10.1109/ICNSC48988.2020.9238080",
language = "English (US)",
series = "2020 IEEE International Conference on Networking, Sensing and Control, ICNSC 2020",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2020 IEEE International Conference on Networking, Sensing and Control, ICNSC 2020",
address = "United States",
}