The major IT companies, such as Microsoft, Google, Amazon, and IBM, pioneered the field of cloud computing and keep increasing their offerings in data distribution and computational hosting.

Gartner group estimates energy consumptions to account for up to 10% of the current data center operational expenses (OPEX), and this estimate may rise to 50% in the next few years.

Along with the computing-based energy high power consumption generates heat and requires an accompanying cooling system that costs in a range of $2 to $5 million per year. There are a growing number of cases when a data center facility cannot be further extended due to the limited available power capacity offered to the facility.

GREENCLOUD: A PACKET-LEVEL SIMULATOR OF ENERGY-AWARE CLOUD COMPUTING DATA

CENTERSDzmitry Kliazovich, Pascal Bouvry, Yury Audzevich, and Samee Ullah Khan

2 GREENCLOUD SIMULATOR

GreenCloud is a simulation environment for advanced energy-aware studies of cloud computing data centers, developed as an extension of a packet-level network simulator Ns2. It offers a detailed fine-grained modeling of the energy consumed by the elements of the data center, such as servers, switches, and links.

3 SIMULATOR COMPONENTS1 INTRODUCTION

Distribution of Data Center Energy Consumption

Simulator Architecture

From the energy efficiency perspective, a cloud computing data center can be defined as a pool of computing and communication resources organized in the way to transform the received power into computing or data transfer work to satisfy user demands.

CoreNetwork

AggregationNetwork

AccessNetwork

Computing Server

1 RU Rack Switch

L3 Switch

TaskSchedulerTask

Scheduler

Links

10 GE 1 GE

WorkloadGenerator

CloudUserCloud

User

Data Center

Data CenterCharacteristics

TaskScheduler

TaskComAgent

L3 Energymodel

L2 Energymodel

ServerCharacteristics

TaskComSink

Connect ()

SchedulerServerEnergy model

S S S S S S S S S

WorkloadTrace File

Servers

Interconnection fabric that delivers workload to any of the computing servers for execution in as timely manner is performed using switches and links.

Switches’ energy model:

The execution of each workload object requires a successful completion of its two main components computational and communicational, and can be computationally Intensive, data-Intensive, or of the balanced nature.

Chassis~ 36%

Linecards~ 53%

Port transceivers~ 11%

CloudUserCloud

User Workloads

Fmax

Fmin

0

0.2

0.4

0.6

Pfixed

Ppeak

CPU FrequencyServer load

Pow

er c

onsu

mpt

ion

Switches and Links

GREENCLOUD: A PACKET-LEVEL SIMULATOR OF ENERGY-AWARE CLOUD COMPUTING DATA CENTERS

5 SIMULATION SETUP

The data center composed of 1536 computing nodes employed energy-aware “green” scheduling policy for the incoming workloads arrived in exponentially distributed time intervals. The “green” policy aims at grouping the workloads on a minimum possible set of computing servers allowing idle servers to be put into sleep.

7 ACKNOWLEDGEMENTS

4 DATA CENTER ARCHITECTURES

Two-tier architecture

Workload distribution

The dynamic shutdown shows itself equally effective for both servers and switches, while DVFS scheme addresses only 43% of the servers’ and 3% of switches’ consumptions.

Characteristics:•Up to 5500 nodes•Access & core layers•1/10 Gb/s links•Full mesh•ICMP load balancing

The computing servers are physically arranged into racks interconnected by layer-3 switches providing full mesh connectivity.

Three-tier architecture

Being the most common nowadays, three-tier architecture interconnects computing servers with access, aggregation, and core layers increasing the number of supported nodes while keeping inexpensive layer-2 switches in the access.

Characteristics:•Over 10,000 servers•ECMP routing•1/10 Gb/s links

Three-tier high-speed architecture

With the availability of 100 GE links (IEEE 802.3ba) reduces the number of the core switches, reduces cablings, and considerably increases the maximum size of the data center due to physical limitations.

ParameterData center architectures

Two-tier Three-TierThree-tier high-speed

TopologiesCore nodes (C1)Aggregation nodes (C2)Access switches (C3)Servers (S)Link (C1-C2)Link (C2-C3)Link (C3-S)

16-

5121536

10 GE1 GE1 GE

816512

153610 GE1 GE1 GE

24

5121536

100 GE10 GE1 GE

Link propagation delay 10 nsData center

Data center average loadTask generation timeTask sizeAverage task sizeSimulation time

30%Exponentially distributedExponentially distributed

4500 bytes (3 Ethernet packets)60.minutes

Setup parameters

Parameter Power consumption (kW·h)  No energy-

savingDVFS DNS DVFS+DNS

Data centerServersSwitches

503.4351152.4

486.1 (96%)340.5 (97%)145.6 (95%)

186.7 (37%)138.4 (39%)48.3 (32%)

179.4 (35%)132.4 (37%)47 (31%)

Energy cost/year $441k $435k $163.5k $157k

6 SIMULATION RESULTS

The authors would like to acknowledge the funding from Luxembourg FNR in the framework of GreenIT project (C09/IS/05) and a research fellowship provided by the European Research Consortium for Informatics and Mathematics (ERCIM).

Energy consumption in data center

0 200 400 600 800 1000 1200 1400 1600

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Server #

Ser

ver

load

Servers at the peak load Under-loaded servers,

DVFS can be applied

Idle servers,DNS can be applied

Characteristics:•Over 100,000 hosts•1/10/100 Gb/s links

S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S

CoreNetwork

AggregationNetwork

AccessNetwork

S

Links

10 GE 1 GE

Nodes

L3 Switch L2/L3 Rack Switch Computing Server

S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S S

CoreNetwork

AggregationNetwork

AccessNetwork

S

Links

10 GE 1 GE

Nodes

L3 Switch L2/L3 Rack Switch Computing Server100 GE