Green Software Services From requirements to Business Models

Schahram Dustdar

TU Wien

Austria

Distributed Systems Group

dsg.tuwien.ac.at

eHealth &

Smart Health

networks Game Machine

Telephone

PC

DVD

Audio

TV

STB DVC

Smart

Homes

Smart eGovernments &

eAdministrations Smart Buildings

and Energy

Networks

Smart Evolution – People, Services,Things

Elastic Systems

Smart Transport

Networks

Computing Models

Machine-based Computing

Human-based Computing Things-based computing

Grid

Pro

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U

nit

A

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C

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SMP

S. Dustdar, H. Truong, “Virtualizing Software and Humans

for Elastic Processes in Multiple Clouds – a Service

Management Perspective”, in International Journal of Next

Generation Computing, 2012

Ad hoc networks Web of things

Autonomic Nervous System

Organic System – Everything connected

More than 7 billion devices and sensors exist for M2M application

IoT and Cloud Computing enable smart services ecosystem and collaboration opportunities

Managed services

• Portfolio management • Event management • Analytics

Provisioning • Services • SIM profile

configuration • Network configuration

Controls • Activation • Deactivation • Privacy • Security

Transaction Mgmt. • Visibility • Billing • Reporting

Integration framework

Algorithm engine Chart

builder

Predictive modeling

Incidents manager

Expert rule engine

FDD Service Mgmt

Storage policies

Database manger

Operations manager

Portfolio Mgmt Analyics

engine

Blackbox module

Location awareness

GUI builder

Event mgmt

Data mining

Resource mgmt.

Regression engine

Open integration

platform

Resource manager

Point metering

framework Numerous Forms Of Smart Services..

Access control Environment Compliance

Street Light Management

Food Transfer Process

Public Safety Industrial process

parameters

Parking Control

Waste Management

Facilities Control

HealthCare

Power

Quality Control Lighting Control

KIOSK Monitoring

CCTV

Monitoring

Hospitality Sector Healthcare Sector

Education Sector Transport Sector

Datacenters

Government Sector

Industrial Sector Finance Sector

Utilities and Smart Grid

Airports, ports and

Critical Infrastructure

Ubiquitous Managed Services Solution Across Business Verticals

ICT for energy

savings in buildings

Command Control Center

ICT enabled Security Services

Saudi Command Control Center

Command Control Center

Shopping malls

Airports

Schools

Factories

Hospitals

ICT enabled Telematics Command Control Center

Vehicle tracking

system

Logistics

Management

ICT enabled services for food storage and delivery Command Control Center

Freezer rooms

Cold storage system

Food display cabinets

ICT enabled services for health care

Command Control Center

Hospital operations

management

Hospital security systems

Hospital equipments

monitoring

ICT enabled smart education systems

Command Control Center

Campus infrastructure

management

Smart classrooms

Smart Universities

Monitoring

Chiller Plant Analysis Tool

Measurement &

Verification

Continuous

Commissioning

Carbon Footprint Analysis

& GHG Accounting

Fault Detection

& Diagnostics

Asset Performance

Management

Energy Analysis

Maintenance

Management

Alarm Management

Dashboards &

Reports

Boilers

UPS Pumps Generators

HVTS

Signage

ATMs

Chillers

Database Enterprise Application

Smoke

Detector

Occupancy

Sensor

Humidity

Sensor

Pressure

Sensor

Power

Meter

KW

Meter

Temperature

Sensor

Cameras

Vehicle

Tracking

Device

Presentation Integration

End Users

Facilities

Management

Vehicle Tracking

System

Fire Alarms

ICT Network

OEM

Third Party Application

Developers

Service

Providers

SIM

FAHU

AHU

KW

Meter

Flow

Meter

Security System

Command Control Center for Managed

Services

Smart City Stakeholders

Core Stakeholders

• Business Service Providers

– Operate business utilizing GSS

– Common objectives e.g., maximizing sustainability of their business -> impacting their business financials

• OEMs

– Produce equipment (source of energy consumption)

– Their efforts have significant impact on savings (e.g., via energy saving capabilities)

Core Stakeholders /2

• GSS providers

– Provide services to Business service providers

– GSS retain service interfaces

– Establish direct business relationsships with customers who need GSS

• GSS developers

– Implement business logic and optimization methods -> significant impact

– Domain knowledge required

Supporting Stakeholders

• Governments

– Are responsible for large scale sustainability activities and information providers

– Policy making and enforcement, legislation, standards

• Auditors

– Systematically assess GSS

– Provide baseline for comparing (future) GSS

– Standardized evaluation methods

• Service Consumers

– Currently “passive“, however, behavior patterns help to get data and improve GSS

Service delivery platform for Smart Cities

Service delivery workflows

Some GSS Requirements /1

1. Identifying Core Services – Collecting/Preparing data from target systems (access & acquire raw+higher

level data)

– Customizing for different target systems

– Accomodating various scales -> Elasticity

Elasticity ≠ Scaleability

Resource elasticity Software / human-based computing elements, multiple clouds

Quality elasticity Non-functional parameters e.g., performance, quality of data, service availability, human trust

Costs & Benefit elasticity rewards, incentives

Elasticity

Some GSS Requirements /2

2. Supporting Process optimization & analytics

– Data modeling & simulation, Context-aware controls, agent based systems

3. Supporting of sustainability policies

– Modeling & understanding policies of target systems

– Finding efficient ways for meeting goals

4. Ensuring Privacy & Security

– Securing controls for privacy & security

5. Supporting stakeholder collaborations

– Building interfaces and marketplaces for collaborations

Business Models

Infrastructure Services

Platform Services

Virtual Vertical

Data Services

3rd party applications

Analytics as a Service

First Conclusions

• GSS require tight integration from Requirements, Design & Implementation, to the Business Models

• Understanding & Support for Stakeholders needed (Data, Elasticity, collaboration models)

• Cloud service models and GSS collaboration models needed

Some Research Challenges /1

• Virtual Verticals

– Dynamic number of devices

– Various (amounts of) real-time data

– Ad hoc application usage on Clouds

• Cross-layer planning methodologies needed

– Providing an isolated environment per tenant

– Dynamic resources (Elasticity)

• Coherent model for scheduling/predicting resource usage

– Impact on Elasticity

Some Research Challenges /2

• Programing Model – Inherent in PaaS

– Decoupling applications from device specifics

– Control logic often executed in Gateways -> standardization issues

• Quality-aware real-time data – Data quality is highly volatile

– Data quality assurance is needed -> methods e.g. statistical, selective data sources, etc.

• Metering, Billing, and SLA – Needs support for all resources and various contexts

– Metering & Billing for all stakeholders -> Configurability

Thanks for your attention

Schahram Dustdar

Distributed Systems Group

TU Vienna - Austria - Europe

dsg.tuwien.ac.at

Forthcoming paper: IEEE Internet Computing 2013