Clouds as Enablers for M2M Service Provisioning Roch Glitho, PhD Roch Glitho, PhD Associate Professor and Canada Research Chair Concordia University, Montreal, Canada and Monique Morrow Distinguished Consulting Engineer, Cisco
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Clouds as Enablers for M2M Service Provisioning
Roch Glitho, PhDRoch Glitho, PhD
Associate Professor and Canada Research Chair
Concordia University, Montreal, Canada
and
Monique Morrow
Distinguished Consulting Engineer, Cisco
Agenda 1. Framing the Problem: The Big Picture
1. M2M service provisioning problem and why cloud computing
a powerful enabler for solving it
2. Early research on cloud based – approaches for M2M 2. Early research on cloud based – approaches for M2M
service provisioning and limitations
3. Proposed cloud based architecture for M2M service
provisioning
Vision of IoT and M2M: Trillion of End Points
Converging Evolution of IP and Mobile Networks
Million
PC /
Billion
IP Device
Office & Home
Million
Voice
Trillion
End Points
From RFID to
Smart Sensors to
Machines to More
Complex Objects
(e.g., a car)
Billion
Mobile Voice,
Internet,
SMS
The Evolution of IP Networks The Evolution of Mobile Networks
PC /
Laptop
The Evolution of
IP Networks
Voice
Source: Cisco ([email protected])
One Common IT Infrastructure: The Ultimate Convergence
of
Enterprise, Service Provider, and Data Center
Technologies
Complex Applications
IoT Evolution Beyond Connectivity
Simple Applications Compound Applications
Complex Applications
Source: Harbor Research, 2012
M2M Service provisioning problem and why cloud
computing is a powerful enabler
� On M2M Service Provisioning
� Current approaches to M2M � Current approaches to M2M service provisioning
� Advantages expected from cloud based approaches
On M2M Service Provisioning:Basics
M2M
� Interactions between devices (e.g. wireless sensors, robots)
with little or no human intervention
M2M Service provisioning
� Process that brings to life the numerous applications � Process that brings to life the numerous applications
expected from the interactions between M2M devices (e.g.
demand/response in smart grids, health monitoring,
surveillance)
� M2M service provisioning: M2M applications development,
deployment and management
On M2M Service Provisioning:The Problem
Current Approaches to M2M Service Provisioning
1. Proprietary “silo” solutions
• No interoperability
• No re-use
2. A few early standards (e.g. OGC, IETF CoAP) that do not yet 2. A few early standards (e.g. OGC, IETF CoAP) that do not yet
allow plug-and-play at all stages of the provisioning process
Cloud Computing as Enabler
-
Cloud Computing could help move from the current proprietary
“silo” approach to an horizontal plug and play approach building on
the early standards (e.g. CoAP) and developing new standards !!!
Expected benefits: efficient use of M2M resources, easy M2M
applications development, management and access.
Early Research on Cloud Based M2M Service Provisioning
� A Use Case
� The drawbacks� The drawbacks
A Use Case: Managing Wearable Sensor Data
through Cloud
C. Doukas and I. Maglogiannis, Managing Wearable Sensor
Data through Cloud Computing, 2011 Third International
Conference on Cloud Computing Technology and Science
Managing Wearable Data Through Cloud
Managing Wearable Data Through Cloud
Managing Wearable Data Through Cloud
The Drawbacks
Early research on cloud based – M2M service provisioning
focuses on how M2M applications could re-use resources that
reside in clouds
� Drawbacks
� Do not generally enable
� An efficient use of M2M resources through virtualization (IaaS)
� An easy development and management of M2M applications � An easy development and management of M2M applications
(PaaS)
� An access anywhere, anytime of the developed M2M
applications
Proposed cloud based – M2M service provisioning architecture
� General IoT/M2M End to End Architecture
� Envisioned Cloud Based Service Provisioning architecture
� Open research issues and issues for standardization
Business
Services
SAP/ OracleSAP/ Oracle
IoT/M2M End-to-End ArchitectureB
usin
ess
Bu
sin
ess
Ap
pli
cati
on
sA
pp
licati
on
s Applications
mHealthmHealth/ Fleet / Fleet
Management / Industrial Management / Industrial AutomationAutomation
Connectivity Connectivity ServiceService
Carr
ier
SP
C
arr
ier
SP
M2M
M2M
Clo
ud
Serv
ices
Clo
ud
Serv
ices
Syste
ms I
nte
gra
tor
Syste
ms I
nte
gra
tor
Compliance MgrCompliance Mgr
Integration Integration ServiceService
Apps Development Apps Development ServiceService
Remote Remote Monitoring Monitoring
ServiceServiceDevice MgmtDevice Mgmt
Service Delivery Service Delivery PlatformPlatform
Security ServiceSecurity Service
SDK & SDK & Open APIOpen API
Asset MgmtAsset Mgmt Billing ServiceBilling Service
Maintenance & Maintenance & Customer SupportCustomer Support Big Data MgmtBig Data Mgmt
Net
wo
rk-
Aw
are
VA
S
Personalization Personalization ManagerManager
Identity MgmtIdentity Mgmt Data AnalyticsData Analytics
Transport Transport
Asset
(Sen
so
r) &
A
sset
(Sen
so
r) &
M
2M
M2M
GW
GW
(Ed
ge
(Ed
ge
Co
mp
uti
ng
Co
mp
uti
ng
Carr
ier
SP
C
arr
ier
SP
C
lou
d S
erv
ices
Clo
ud
Serv
ices
Syste
ms I
nte
gra
tor
Syste
ms I
nte
gra
tor
Wireless/WirelineM2M GW3G/4G/WiFi/GPS
M2M GW
2G/3GModem
Sensor # 2
Sensor # nSensor # 1
Policy ManagerPolicy Manager
EPC
2G/3GModem
2G/3GModem
EPC
Netw
ork
sN
etw
ork
s
EPC / BNG
Network, subscriber and Services Abstraction and Orchestration Layer
HTTP RESTful – SOAP XML – XMPP – OneAPI
Data Analytics & Apps Orchestration Layer
RealReal--TimeTimeSubscriber MgmtSubscriber Mgmt
Network Network IntelligenceIntelligence
Transport Transport OptimizationOptimization
Inte
llig
ent
M2
MN
etw
ork
Ser
vic
es
Envisioned cloud based - architecture
Envisioned cloud based architecture
� M2M applications re-used functionality / applications offered as SaaS. However, unlike the current state of the art
� M2M applications are offered as SaaS, developed an managed using a PaaS, an furthermore their resource are used optimally thanks to virtualization.
A Use Case
� Let us consider a robotic application offered as SaaS, used by doctors, nurses and other
hospital staff for goods / materials transportation and delivery within the hospital locate
and (i.e goods / material are transported by robots)
� Orders are placed using smart phones, computers, tablets or even the keyboards that
may be on some robots - Users can submit requests using text of voice
� Some examples
� Kitchen staff load robots with meals and order the transportation of those meals to
various
patients’ rooms
� A doctor orders through a smart phones, transportation of the radiology results of
her patients from the radiology department to her office, ready for her to check the
next day.
A Use Case
� Since orders can be placed by voice, a speech recognition application can be used by
the robots and this application might reside in a separate cloud where it is offered by a
third party as SaaS
� A knowledge data base offered by a third party as a SaaS in another cloud might also be
used by the robots to learn how to load and unload
� The robotic application that enables transportation and delivery is offered as SaaS and
developed and managed using a PaaSdeveloped and managed using a PaaS
� The fleet of robots that are used are virtualized to enable efficiency
Summary:Open Research Issues and Items for Standardization
� Research issues
� M2M devices / network virtualization
� Specialized M2M apps engine
� Modelling of M2M applications as SaaS
� Inter-cloud interactions (i.e. interactions between M2M � Inter-cloud interactions (i.e. interactions between M2M
applications and resources residing in a different cloud)
� Examples of items for standardization
� M2M PaaS and M2M IaaS interactions
� Programmatic interfaces for exposing M2M applications
� Inter-cloud interfaces
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