An Environmental Chargeback for Data Center and Cloud Computing Consumers

Copyright 2011 Digital Enterprise Research Institute. All rights reserved.

Digital Enterprise Research Institute www.deri.ie

Enabling Networked Knowledge

An Environmental Chargeback for Data Center & Cloud Computing

ConsumersEdward Curry, Souleiman Hasan, Mark White, Hugh Melvin

[email protected] - www.edwardcurry.org

1st International Workshop on Energy-Efficient Data Centres, Madrid, 2012

Digital Enterprise Research InstituteNational University of Ireland, Galway



Motivation for Environmental Chargeback

Environmental Chargeback Model Requirements Definition Methodology Allocating Impacts

Proof of Concept at DERI

Related Work

Conclusions & Future Work

Overview



The Impact of Search?

Figures and Image from www.google.com/green



Cost of Other Services?




Google’s Carbon Footprint


Is Google solely responsible for these emissions?

What about the 1 billion users that use Google’s services everyday?

Do the users bear some responsibility?



Google’s Carbon Footprint




DC Service Supply Chain

IaaS

Home User

Data Center

Corporate User

CSR

Renewable Energy

Coal Power Plant

Power Generation (Utility or On-site)

High CO2 Intensity

ZeroCO2 Intensity

PaaS

SaaS

End Consumers

BPaaS

XaaS

Server 1

Service …

Service …

Service N

ProvideServicesSupply Power

Cause of Environmental

Impacts

Cause of Environmental

Impacts



Principle of ‘The Polluter Pays’ Acceptance by governments, businesses, and public

End-users IT needs are reason for existence of DC Little information flows to consumers on the

environmental impacts of their service usage Little opportunity to change behavior to be more

ecologically sound

The Challenge: Tie emissions back to point of usage, so consumer are better informed

Solution: An Environmental Chargeback Model

The Polluter Pays



Raising Consumer Awareness of Envir. Impacts Understand the relationships between actions and

impacts Induce Efficient Usage of Data Center Resources

Improving access to resource consumption information– Can reduce usage (i.e. paper, energy)

Empower end-users to make sustainable choices:– Could the service be scheduled (invoked) when renewable

power sources are available? – Could it be invoked less often?

Embed Service Usage within Sustainable IT Practices Include environmental impacts in business and decision-

making processes

Empowering the Consumer






Related Work


Overview



Equitable Consumer only charged for the impacts they cause. One consumer should

not subsidize the impacts of another consumer Accuracy & Auditability

Charge for actual impacts, and maintain records to handle inquiries Understandable

Consumer must understand the charging process & methodology Controllable & Predictable

Ability to control or predict the cost of performing activity Flexible & Adaptable

Support multiple service types (i.e. PaaS, IaaS, SaaS) and dynamic cost models (i.e. include capital impacts, operational impacts

Scalable Capacity to handle small- and large-scale services

Economical Inexpensive to design, implement, deploy, and run, including data

collection, processing and reporting to consumers

Model Requirements



Step 1. Identify service and define environmental system boundary: Identify the target service Define the system boundary of the model Define functional units (CO2, kWh, cost per use, etc)

Step 2. Identify billable Items and, for each one, identify the smallest unit that will be available as a service to consumers Find a reasonable easily understood unit of measurement: Billable Service Items: resources which consumers will be

charged – Consumers will be able to purchase these items– Servers, virtual machines, storage, email, search, etc.

Atomic Service Units: smallest unit of measurement– Consumer bill will detail how many units of a resource were used– Examples Server/VM uptime, transactions, MB/GB, etc…

Definition Methodology



Step 3. Identify, analyze and document relevant environmental impacts: Determine service resource use and associated environmental

impacts within the model boundaries Step 4. Define an environmental cost allocation

strategy for each billable item: Associating impacts to billable items Can be fixed, variable, or mixed charging Should reflect actual usage instead of allocation/reservation

Step 5. Identify, integrate, and deploy tools necessary to collect data and to calculate environmental chargeback: Environmental data collection DC resource utilization, service

workload, chargeback, and customer billing & reporting Tools will vary based on the service and the data center.

Definition Methodology



Capital Impacts – Initial Setup Amortized over est. life of item as fixed charge Building the data center facilities

– Lifespan of 10 to 15 years

IT Equipment (Server, storage, cabling, etc.)– Servers have a lifespan of 3 to 5 years

Software i.e. cost of search index vs. user search– Lifespan in days, weeks, months,…

Operational Impacts – Running Straightforward allocation by usage Power generation and water for cooling

Allocating Impacts



Allocating Impacts

Environmental Data Collection

DC Resource Utilization

Chargeback Model BillingkWh

CO2 intensity

CO2/atomic unit

Service Workload atomic unit






Related Work


Overview



Developed a proof of concept Instantiation has been realized in the DERI data center

Steps 1-3 Service: Transaction-based data service System boundary: carbon dioxide from power

generation Units: CO2 (gCO2), kilowatts (kW) and kilowatt-hours

(kWh) Billable Service Items: User accounts Atomic Service Units: Single data transactions Environmental Impacts: 27 servers, power supplied is

mixture of fossil fuel & renewable sources (variable CO2)

Proof of Concept



Step 4. Define allocation strategy for each billable item: Computational workload of all transactions is similar,

– Treat transactions as equal from impact allocation perspective

Proof of Concept



Step 5. Data collection and reporting Leverages existing monitoring infrastructures

– Real-Time Web Service for Power CO2 Intensity – DC Resource Energy Monitor– Data Service Workload Monitor

Charge calculated with real-time assessment sliding window– Encoded as rules within a Complex Event Processing (CEP) engine – CEP receives events allocates impacts in real-time

Billing System Limitations

Network & data storage excluded due to insufficient metering Approach ignores transactions initiated prior to the start of

the window and those not completed prior at end of window No Capital charges included in current version

Proof of Concept



Chargeback in Action



Linked dataspace for Energy Intelligence

Ap

plic

ati

on

s

Energy Analysis Model

Complex Events

Situation Awareness Apps

Energy and Sustainability Dashboards

Decision Support Systems

Lin

ked

Data

S

up

port

S

erv

ices

Entity Management

Service

Data Catalog

Complex Event Processing

Engine

Provenance

Search & Query

Sou

rces

Faci

litie

s

Build

ing

IS

ERP

Fina

nce

Asse

ts

Sens

ors

HR

Trav

el

Com

mut

e

IT

Offi

ce D

ata

Cent

erAdapter Adapter Adapter Adapter Adapter

Uses W3C web standards for sharing and integrating energy data Linked Data Semantic Sensor

Networks



iEnergy – Personal Usage



Metering and Monitoring Piggy-backed on existing infrastructure

Service & Infrastructure Complexity Shared and federated across multiple data

centers will be more difficult to allocate impacts

Stakeholder Collaboration Require collaboration from more players, such

as service managers and developers Security and Privacy

Considered within wider area of security and privacy for data centers and cloud computing

Experience






Related Work


Overview



Model complements existing research on DC EE SLA@SOI, GAMES, FIT4Green, OPTIMIS, ALL4Green, etc, …

Green Grid Metrics Power usage effectiveness (PUE), Data Center

infrastructure Efficiency (DCiE), Water Usage Effectiveness (WUE), Carbon Usage Effectiveness (CUE), Data Center compute Efficiency (DCcE), The Data Center Productivity (DCP) framework

Focus on DC efficiency

Not Consumer-centric Do not inform consumer of cost of their service usage Do not give information necessary to change behavior to

be more sustainable

Related Work






Related Work


Overview



Environmental Chargeback Model Correlate service utilization back to service consumers Provide visibility into service & associated resource utilization Enable consumers to understand environmental footprint Bring transparency to sustainability of outsourced enterprise IT Encourage use of green power with lower footprint

Future Work User evaluation to determine if model can effectively change

user behavior and reduce the impacts of services Deployment challenges in different environments (i.e.

homogenous & heterogeneous), at large scale (i.e. warehouse) Methods for allocation of capital environmental impacts

Conclusion & Future Work



Curry, E.; Hasan, S.; White, M.; and Melvin, H. 2012. AnEnvironmental Chargeback for Data Center and Cloud Computing Consumers. In Huusko, J.; de Meer, H.; Klingert, S.; and Somov, A., eds., First International Workshop on Energy-Efficient Data Centers. Madrid, Spain: Springer Berlin / Heidelberg.

www.edwardcurry.org

Further Reading

An Environmental Chargeback for Data Center and Cloud Computing Consumers

Technology

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