CaltechAUTHORS
  A Caltech Library Service

Online Algorithms for Geographical Load Balancing

Lin, Minghong and Liu, Zhenhua and Wierman, Adam and Andrew, Lachlan L. H. (2012) Online Algorithms for Geographical Load Balancing. In: Third International Green Computing Conference (IGCC'12) , 5-8 June 2012, San Jose, CA. (Unpublished) http://resolver.caltech.edu/CaltechAUTHORS:20120612-143750915

[img]
Preview
PDF - Accepted Version
See Usage Policy.

177Kb

Use this Persistent URL to link to this item: http://resolver.caltech.edu/CaltechAUTHORS:20120612-143750915

Abstract

It has recently been proposed that Internet energy costs, both monetary and environmental, can be reduced by exploiting temporal variations and shifting processing to data centers located in regions where energy currently has low cost. Lightly loaded data centers can then turn off surplus servers. This paper studies online algorithms for determining the number of servers to leave on in each data center, and then uses these algorithms to study the environmental potential of geographical load balancing (GLB). A commonly suggested algorithm for this setting is “receding horizon control” (RHC), which computes the provisioning for the current time by optimizing over a window of predicted future loads. We show that RHC performs well in a homogeneous setting, in which all servers can serve all jobs equally well; however, we also prove that differences in propagation delays, servers, and electricity prices can cause RHC perform badly, So, we introduce variants of RHC that are guaranteed to perform as well in the face of such heterogeneity. These algorithms are then used to study the feasibility of powering a continent-wide set of data centers mostly by renewable sources, and to understand what portfolio of renewable energy is most effective.


Item Type:Conference or Workshop Item (Paper)
Additional Information:This work was supported by NSF grants CCF 0830511, CNS 0911041, and CNS 0846025 MURI grant W911NF-08-1-0233, Microsoft Research, the Lee Center for Advanced Networking, and ARC grant FT0991594.
Funders:
Funding AgencyGrant Number
NSF CCF 0830511
NSFCNS 0911041
NSFCNS 0846025
Army Research Office (ARO) Multidisciplinary University Research Initiative (MURI)W911NF-08-1-0233
Microsoft ResearchUNSPECIFIED
Lee Center for Advanced Networking, CaltechUNSPECIFIED
ARCFT0991594
Record Number:CaltechAUTHORS:20120612-143750915
Persistent URL:http://resolver.caltech.edu/CaltechAUTHORS:20120612-143750915
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:31886
Collection:CaltechAUTHORS
Deposited By: George Porter
Deposited On:12 Jun 2012 21:52
Last Modified:26 Dec 2012 15:19

Repository Staff Only: item control page