Renewable-aware geographical load balancing of web applications for sustainable data centers

Adel Nadjaran Toosi, Chenhao Qu, Marcos Dias de Assunção, Rajkumar Buyya

Research output: Contribution to journalArticleResearchpeer-review

Abstract

The ever-increasing demand for web applications deployed across multiple data centers results in large electricity costs for service providers and significant impact on the environment. This has motivated service providers to move towards more sustainable data centers powered by renewable or green sources of energy, such as solar or wind. However, efficient utilization of green energy to service web applications is a challenging problem due to intermittency and unpredictability of both application workload and renewable energy availability. One possible solution to reduce cost and increase renewable energy utilization is to exploit the spatio-temporal variations in on-site power and grid power prices by balancing the load among multiple data centers geographically distributed. In this paper, we propose a framework for reactive load balancing of web application requests among Geo-distributed sustainable data centers based on the availability of renewable energy sources on each site. A system prototype is developed, its underlying design and algorithms are described, and experiments are conducted with it using real infrastructure (Grid'5000 in France) and workload traces (real traffic to English Wikipedia). The experimental results demonstrate that our approach can reduce cost and brown energy usage with efficient utilization of green energy and without a priori knowledge of future workload, availability of renewable energy, and grid electricity prices.

Original languageEnglish
Pages (from-to)155-168
Number of pages14
JournalJournal of Network and Computer Applications
Volume83
DOIs
Publication statusPublished - 1 Apr 2017
Externally publishedYes

Keywords

  • Auto-scaling
  • Brown energy
  • Cost saving
  • Geographical load balancing
  • Green computing
  • Green Energy
  • Renewable energy
  • System prototype
  • Web applications
  • Wikipedia

Cite this

@article{25d082697bea4c45ab5f2a422e3ed09c,
title = "Renewable-aware geographical load balancing of web applications for sustainable data centers",
abstract = "The ever-increasing demand for web applications deployed across multiple data centers results in large electricity costs for service providers and significant impact on the environment. This has motivated service providers to move towards more sustainable data centers powered by renewable or green sources of energy, such as solar or wind. However, efficient utilization of green energy to service web applications is a challenging problem due to intermittency and unpredictability of both application workload and renewable energy availability. One possible solution to reduce cost and increase renewable energy utilization is to exploit the spatio-temporal variations in on-site power and grid power prices by balancing the load among multiple data centers geographically distributed. In this paper, we propose a framework for reactive load balancing of web application requests among Geo-distributed sustainable data centers based on the availability of renewable energy sources on each site. A system prototype is developed, its underlying design and algorithms are described, and experiments are conducted with it using real infrastructure (Grid'5000 in France) and workload traces (real traffic to English Wikipedia). The experimental results demonstrate that our approach can reduce cost and brown energy usage with efficient utilization of green energy and without a priori knowledge of future workload, availability of renewable energy, and grid electricity prices.",
keywords = "Auto-scaling, Brown energy, Cost saving, Geographical load balancing, Green computing, Green Energy, Renewable energy, System prototype, Web applications, Wikipedia",
author = "{Nadjaran Toosi}, Adel and Chenhao Qu and {de Assun{\cc}{\~a}o}, {Marcos Dias} and Rajkumar Buyya",
year = "2017",
month = "4",
day = "1",
doi = "10.1016/j.jnca.2017.01.036",
language = "English",
volume = "83",
pages = "155--168",
journal = "Journal of Network and Computer Applications",
issn = "1084-8045",
publisher = "Elsevier",

}

Renewable-aware geographical load balancing of web applications for sustainable data centers. / Nadjaran Toosi, Adel; Qu, Chenhao; de Assunção, Marcos Dias; Buyya, Rajkumar.

In: Journal of Network and Computer Applications, Vol. 83, 01.04.2017, p. 155-168.

Research output: Contribution to journalArticleResearchpeer-review

TY - JOUR

T1 - Renewable-aware geographical load balancing of web applications for sustainable data centers

AU - Nadjaran Toosi, Adel

AU - Qu, Chenhao

AU - de Assunção, Marcos Dias

AU - Buyya, Rajkumar

PY - 2017/4/1

Y1 - 2017/4/1

N2 - The ever-increasing demand for web applications deployed across multiple data centers results in large electricity costs for service providers and significant impact on the environment. This has motivated service providers to move towards more sustainable data centers powered by renewable or green sources of energy, such as solar or wind. However, efficient utilization of green energy to service web applications is a challenging problem due to intermittency and unpredictability of both application workload and renewable energy availability. One possible solution to reduce cost and increase renewable energy utilization is to exploit the spatio-temporal variations in on-site power and grid power prices by balancing the load among multiple data centers geographically distributed. In this paper, we propose a framework for reactive load balancing of web application requests among Geo-distributed sustainable data centers based on the availability of renewable energy sources on each site. A system prototype is developed, its underlying design and algorithms are described, and experiments are conducted with it using real infrastructure (Grid'5000 in France) and workload traces (real traffic to English Wikipedia). The experimental results demonstrate that our approach can reduce cost and brown energy usage with efficient utilization of green energy and without a priori knowledge of future workload, availability of renewable energy, and grid electricity prices.

AB - The ever-increasing demand for web applications deployed across multiple data centers results in large electricity costs for service providers and significant impact on the environment. This has motivated service providers to move towards more sustainable data centers powered by renewable or green sources of energy, such as solar or wind. However, efficient utilization of green energy to service web applications is a challenging problem due to intermittency and unpredictability of both application workload and renewable energy availability. One possible solution to reduce cost and increase renewable energy utilization is to exploit the spatio-temporal variations in on-site power and grid power prices by balancing the load among multiple data centers geographically distributed. In this paper, we propose a framework for reactive load balancing of web application requests among Geo-distributed sustainable data centers based on the availability of renewable energy sources on each site. A system prototype is developed, its underlying design and algorithms are described, and experiments are conducted with it using real infrastructure (Grid'5000 in France) and workload traces (real traffic to English Wikipedia). The experimental results demonstrate that our approach can reduce cost and brown energy usage with efficient utilization of green energy and without a priori knowledge of future workload, availability of renewable energy, and grid electricity prices.

KW - Auto-scaling

KW - Brown energy

KW - Cost saving

KW - Geographical load balancing

KW - Green computing

KW - Green Energy

KW - Renewable energy

KW - System prototype

KW - Web applications

KW - Wikipedia

UR - http://www.scopus.com/inward/record.url?scp=85013218316&partnerID=8YFLogxK

U2 - 10.1016/j.jnca.2017.01.036

DO - 10.1016/j.jnca.2017.01.036

M3 - Article

VL - 83

SP - 155

EP - 168

JO - Journal of Network and Computer Applications

JF - Journal of Network and Computer Applications

SN - 1084-8045

ER -