Abstract
In this paper, we introduce a framework for designing energy efficient cloud computing
services over non-bypass IP/WDM core networks. We investigate network related factors including
the centralization versus distribution of clouds and the impact of demand, content popularity and
access frequency on the clouds placement, and cloud capability factors including the number of
servers, switches and routers and amount of storage required in each cloud. We study the
optimization of three cloud services: cloud content delivery, storage as a service (StaaS), and
virtual machines (VMS) placement for processing applications. First, we develop a mixed integer
linear programming (MILP) model to optimize cloud content delivery services. Our results indicate
that replicating content into multiple clouds based on content popularity yields 43% total saving
in power consumption compared to power un-aware centralized content delivery. Based on the model
insights, we develop an energy efficient cloud content delivery heuristic, DEER-CD, with
comparable power efficiency to the MILP results. Second, we extend the content delivery model to
optimize StaaS applications. The results show that migrating content according to its access
frequency yields up to 48% network power savings compared to serving content from a single central
location. Third, we optimize the placement of VMs to minimize the total power consumption. Our
results show that slicing the VMs into smaller VMs and placing them in proximity to their users
saves 25% of the total power compared to a single virtualized cloud scenario. We also develop a
heuristic for real time VM placement (DEER-VM) that achieves comparable power savings.
© 2014 OAPA
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