Reducing the power consumption and operational cost of IT servers is
of great concern today. With the growth of the Internet and online
services, the number of data centers is increasing day by day. Servers
for many cloud applica- tions and other large providers are spread
globally. Energy costs across the globe vary dynamically. Servers
operate at varied energy costs based on their location and time of
use. The load of a server varies based on its geographical location
and the time of operation. This paper focuses on exploiting the
dynamic nature of electrical power pricing, so that a cost saving is
obtained by geo-location of requests to servers operating at lower
costs at particular times. There exist patterns of load that are
similar for different types of servers. Scheduling decisions are made
considering both loads and operating costs of the servers into
account, i.e., requests are scheduled to run on servers operating at
low cost that also have low expected load. In order to meet the
business requirements of an application, scheduling decisions for
requests that have stringent SLA considerations or high server
affinity, are made by assigning high priority for these
requests. Geo-location of requests is done for low priority requests.