Cloud computing final

Cloud
ComputingGets its name as a metaphor for the internet
Omer K. Jasim
Ph.D. qualifier exam
FCIS-ASU’2013

Agenda
FCSI, ASU, Egypt. Omer K. Jasim
1. Cloud Computing Definitions
2. Cloud Computing Layers
2.1 Cloud Architecture
2.2 Cloud Data Center
3. Main Cloud Process
3.1 Cloud Migration
3.2 Virtualization
4. Integration of Cloud Application
5. SLA’s in Cloud Computing
6. Workflow Management System
7. Cloud Computing Parallelism
7.1 Map-Reduce Model
7.2 Cloud Federation
8. Dissertation with this topics
9. References

Definitions
• A large pool of easily usable and accessible virtualized resources (such
as hardware, development platforms and/or services).
“ Stallman 2011”.
• A parallel and distributed computing system consisting of a collection
of inter-connected and virtualized computers that are dynamically
provisioned and presented as one or more unified computing
resources based on service-level agreements (SLA) established through
negotiation between the service provider and
consumers. “Nicolas 2013

Cloud computing:- is the provision of dynamically scalable and often virtualized
resources as a service over the internet (public cloud) or intranet (private cloud).
The “Cloud” is the default
symbol of the internet in
diagrams.
Cloud Computing
The broader term of
“Computing” encompasses:
- no. of Computations
- Coordination logic
- Storage
Cloud Computing is about moving computing from the single desktop
pc/data centers to the internet.
Definition (cont.)
set up an account with the
provider, start and configure a
virtual cluster with one or more
nodes for computation, and
return the results to your local
machine

Cloud Computing Layers
Computer, phones, Brow
ser.
Cloud
Services
Networks, Virtualization
Client
Applications
Platform
Infrastructure
Server

1- Clients
 Hardware and/or software
 Essentially useless without the cloud
Ex: Laptop & phones, Thin and Thick computer.

Cloud layers (cont.)
Application
Platform
Infrastructure
Cloud
Services

2- Cloud Service
Data Centers
Clusters
Storage
Other Grids/Clouds
Virtualization
VM Management & Deployment
Amazon S3, EC2
OpenNebula, Eucalyptus
Mosso
Web 2.0 Interface
Programming API
Scripting & Programming
Languages
Google AppEngine
Microsoft Azure
Manjrasoft Aneka
Google Apps (Gmail, Docs,…)
Salesforce.com
Infrastructure as a Service(IaaS)
Platform as a Service(PaaS)
Software as a Service(SaaS)
QoSMetering
SLA
NegotiationAdmissionControl
PricingandBilling
Accounting
SPI

2.1.Software as a Services (SaaS)
- SaaS is a model of software deployment where an application
is hosted as a service provided to customers cross the Internet.
-Features:
• Multi-tenancy, Multi -instance
– One application instance may be serving hundreds of companies
– Opposite of multi-instance where each customer is provisioned their own
server running one instance
• Metadata driven configurability
– Instead of customizing the application for a customer (requiring code
changes), one allows the user to configure the application through metadata

SaaS Maturity Levels
• Level 1: Ad-Hoc/Custom
• Level 2: Configurable
• Level 3: Configurable, Multi-
Tenant-Efficient
• Level 4:
Scalable, Configurable, Multi
-Tenant-Efficient
Source: Microsoft MSDN Architecture Center
• Level 1: Ad-Hoc/Custom
• Level 2: Configurable
• Level 3: Configurable, Multi-
Tenant-Efficient
• Level 4:
Scalable, Configurable, Multi
-Tenant-Efficient

2.2. Platform as a Services (PaaS)
– Providing all the facilities necessary to support the complete
process of building and delivering web applications and
services, all available over the Internet.
– Entirely virtualized platform that includes one or more servers,
operating systems and specific applications.
Examples:- Middleware, VM, etc..

2.3.Infrastrcture as a Services (IaaS)
– Provision model in which an organization outsources
the equipment used to support operations, including
storage, hardware, servers and networking
components.
– Also known as Hardware as a Service (HaaS).
– Service provider owns the equipment; responsible for
housing, running and maintaining it.
– Client typically pays on a per-use basis.
Examples:- IBM Blue house, VMWare, Amazon EC2, Microsoft Azure Platform, Sun
Parascale and more

(Customer vs. Provider) view XaaS

3- Server
 Hardware/Software
 Specialized for cloud
 OS, multi core processors
 Network of virtualized computers
FCSI, ASU, Egypt. Omer K.
Jasim

Cloud Architecture
The Cloud Computing Architecture of a cloud solution is the structure of the system,
which comprise enterprise arch. and cloud resources, services, middleware, and software
components, SOA, the externally visible properties of those, and the relationships between
them
Collection of services
, communicate with
each other or two or
more services
coordinate to preform
some activities
Any program supported
“glue together”, allow
programs written for
access to a particular
DB.
Structure and operation
of an organization
Set of structures
needed to reason about
the system software

Deployment Models
• Public cloud (off-site and remote) : resources dynamically
provisions on the internet
• A private cloud : consolidating shared services on
virtualized hardware deployed from a primary datacenter
to serve local and remote users (intranet).
• A hybrid cloud environment consists of some portion of
computing resources on-site (on premise) and off-site
(public cloud).
• A community cloud is formed when several organizations
with similar requirements share common infrastructure.

Cloud Data Center
• Data center: large server farms + data warehouses.
- managed infrastructure
- Supported transmission from web hosting to cloud
computing
- individual web/content providers: must provision for peak
load.
• web hosting: third party provides and owns the (server farm)
infrastructure, hosting web services for content providers
• “server consolidation” via virtualization and “ Collaboration
mechanism “

WAN Network
Functional Servers
WAN Edge
Data Center Core/
Gateway
Customer Edge
L2 Aggregator
Server Rack
Virtual Server
Application
VM/Server Control
Server
Hypervisor
Virtual Subnet/VLAN
1
Virtual
Subnet/VLAN 2
Application
Virtual Machine
(VM)
Application
Virtual Machine
(VM)
Application
Virtual Machine
(VM)
Application
Virtual Machine
(VM)
Application
Virtual Machine
(VM)
Application
Virtual Machine
(VM)
Application
Virtual Machine
(VM)
Application
Virtual Machine
(VM)
Provisioning, Billing, Security, Load Balancing, Monitoring,
Auditing, Logging, and ETC.
Functional Servers
Collaboration level
Basic
components

Agenda
3.1 Cloud Migration
3.2 Virtualization
6. Workflow Management System
8. Dissertation with this topics.
9. References

Main Process
- Migration Process
- Transmitted the enterprise application from
the desktop to open cloud environment.
- Virtualization
- Abstraction of computer resources.
- Hides the physical characteristics of
computing resources from their users, be they
applications, or end users.

Migration to the Cloud
- Move the enterprise application to the open
cloud environment, captive cloud data center
- Implemented in one of the several ways:
(code, architecture, and usage )
- The migration of an enterprise application is
based capture by the following:
P P’C+P’l P’OFC+P’l

Optimiz
e
Assess
Test
Augment
Re-
architect
Map
Isolate
Start
End
Migration Life Cycle

Virtualization
• Virtualization:- the abstraction of computer resources.
• Virtualization hides the physical characteristics of
computing resources from their users, be they
applications, or end users.
• This includes making a single physical resource (such as a
server, an operating system, an application, or storage
device) appear to function as multiple virtual resources; it
can also include making multiple physical resources (such
as storage devices or servers) appear as a single virtual
resource.

VM-Architecture
Hardware
Virtual Machine Monitor (VMM) / Hypervisor
Guest OS
(Linux)
Guest OS
(NetBSD)
Guest OS
(Windows)
VM VM VM
AppApp AppAppApp
Xen
VM-Ware
UML
Denali
etc.
Hypervisor is a software program that manages multiple operating systems (or multiple instances of the same operating
system) on a single computer system. The hypervisor manages the system's processor, memory, and other resources to
allocate what each operating system requires.
Hypervisors are designed for a particular processor architecture and may also be called virtualization managers.

Full Virtualization
• Provides a complete simulation of the underlying hardware.
• The result is a system in which all software (including all
OS’s) capable of execution on the raw hardware can be run
in the virtual machine.
• Comprehensively simulate all computing elements as
instruction set, main memory, interrupts, exceptions, and
device access.
• Full virtualization is only possible given the right
combination of hardware and software elements.

Para virtualization
Do not try to emulate everything ,
• Work as a guard
• Pass safe instructions directly to CPU and device
• Guests have some exposure to the hardware
• Better performance
• Need to slightly modify guest OS, but no need to modify
applications
• Xen, Sun Logical Domains

Cloud based virtualization
• PROVIDER
- Support cloud to improve IT efficiency, agility and
reliability.
- Delivers everything IT needs to
build, operate, rent, and manage their cloud.
. CUSTOMER
- Helps customers evolve technical
foundations, organizational models, operational
processes and financial measures to establish both a
cloud infrastructure and cloud operations model.

Integration of Cloud Computing
• Important factor in the cloud.
• Data enterprise and applications must be linked up
via one or more standard integration platform .
• Integration middle (I-MW or C-MW) ware simplify
the mapping between Application to Application
(A2A), Application to Cloud (A2C), Cloud to
Cloud(C2C).

Cloud -MW
• Cloud middleware will be made available as a
service.
• Due to varying integration requirements and
scenarios, there are a number of middleware
technologies and products.
• For performance sake, clusters, fabrics, grids, and
federations of hubs, brokers, and buses are being
leveraged.

Cloud-MW
App1
App2
ISB
Pub.
CloudISB
Cloud CloudISB
Application
App2App
App2C
C2C

Understandi
ng
Testing
Design
Definition
Integration life cycle
Understanding the
source system or the
application on this
system, target system
Acquire information from previous
phase to define the
metadata, physical
attribute, relation ship between
objects
Determined the data
extract from the one or
more system to target
system
Assuring the
integration is done

Service Level Agreement in Cloud
• Framework for provider, costumer .
• Negotiation between service consumer and service provider,
records common understanding about services.
• Guarantee multiple QoS parameters across layers, highly
dynamic environments, resources heterogeneity, Xaas
service definition.
• Capacity Planning:
- dynamic workload amount, customer satisfaction level,
• Maximize the profit:
by reducing the resource cost (the number and type of
initiated virtual machines and penalties cost).

SLA-life Cycle

• Infrastructure SLA. The infrastructure provider
manages and offers guarantees on availability of
the infrastructure, namely, server
machine, power, network connectivity, and so
on.
• Application SLA. In the application co-location
hosting model, the server capacity is available to
the applications based solely on their resource
demands.
SLA-Type

SLA Hierarchy
SLA at an upper layer depends on SLAs at lower layers.

Cloud Workflow (CW)
• A process consist of a series of steps that simplifies the
complexity of execution and management of application.
• Data Management
• Data replication
• Data Placement
• Intermediate data storage

CW: Data Management
• New features in cloud computing
– Independent of users and provider
– Cost driven
• computation cost, storage cost, data transfer cost
– Data dependency
• Task – data, data – data.
• Some research issues
– Data partition, placement, replication, synchronisation.
Example : Aneka, open Nebula .

CW: Data Placement
• Data Placement: to decide where to store the application data in the
distributed data centres
• Aims:
– Reduce data movement
– Reduce task waiting time
• Strategy:
– Data dependency: dataset – dataset

CW: Data Replication
• Data replication: for one dataset, store several copies in different
places (data centres)
• Aims:
– Increase data security
– Fast data access
– Reduce data movement
• Strategy:
– Dynamic replication.

CW: Intermediate Data Storage
• Intermediate data storage is especially importance in scientific
workflows
• Aim:
– Reduce system cost
• Strategy:
– Intermediate data can be regenerated with data
provenance information
– Selectively store some key intermediate datasets

Agenda
3.1 Cloud Migration
3.2 Virtualization
6. Cloud Workflow system
8. Dissertation with this topics
9.References

Cloud Computing Parallelism
• “Cloud” refers to large Internet services like
Google, Yahoo, etc. that run on 10,000’s of
machines
• - Want to parallelize across hundreds/thousands of CPUs
– How to parallelize
– How to distribute
-Map-Reduce model based to answer the above
questions.

Map –Reduce
• Map-Reduce is a data processing approach(data
parallel programming model) that presents a
simple programming model for processing
highly parallelizable data sets. It is implemented
as a cluster, with many nodes working in parallel
on different parts of the data.
• Pioneered by Google
– Processes 20 petabytes of data per day
• Popularized by open-source Hadoop project
– Used at Yahoo!, Facebook, Amazon, …

Data Distribution
• Input files are split into M pieces on distributed
file system
– Typically ~ 64 MB blocks
• Intermediate files created from map tasks are
written to local disk
• Output files are written to distributed file
system

Assigning Tasks
• Many copies of user program are started
• Tries to utilize data localization by running map
tasks on machines with data
• One instance becomes the Master
• Master finds idle machines and assigns them
tasks

Master
worker1 Worker nworker3worker2
Data
tasks
Task1
Task2
.
.
.
Task n
Data distributed
Assigning to the tasks

Example for MapReduce
• Page 1: computer study is good
• Page 2: cloud computing is good
• Page 3: my study in cloud computing
• …….
• …..
• Page n.: ….. Any data ?

Map output
• Worker 1:
– (computer 1), (study 1), (is 1), (good 1).
• Worker 2:
– (cloud 1), (computing 1), (is 1), (good 1).
• Worker 3:
– (My 1), (study 1), (in 1), (cloud 1), (computing 1).

Map Operation
MAP: Input data  <key, value> pair
Data
Collection: split1
web 1
weed 1
green 1
sun 1
moon 1
land 1
part 1
web 1
green 1
… 1
KEY VALUE
Split the data to
Supply multiple
processors
Data
Collection: split 2
Data
Collection: split n
Map
……
Map
web 1
weed 1
green 1
sun 1
moon 1
land 1
part 1
web 1
green 1
… 1
KEY VALUE
web 1
weed 1
green 1
sun 1
moon 1
land 1
part 1
web 1
green 1
… 1
KEY VALUE
web 1
weed 1
green 1
sun 1
moon 1
land 1
part 1
web 1
green 1
… 1
KEY VALUE
web 1
weed 1
green 1
sun 1
moon 1
land 1
part 1
web 1
green 1
… 1
KEY VALUE
…

Reduce Input
• Worker 1:
– (computer 1)
• Worker 2:
– (is 1), (is 1)
• Worker 3:
– (good 1), (good 1)
• Worker 4:
– (study 1), (study1)
• Worker 5:
– (cloud 1), (cloud 1)
• Worker 6:
– (computing 1), (computing 1)
•Worker 6:
- (My 1)

Reduce Output
• Worker 1:
– (computer 1)
• Worker 2:
– (is 2)
• Worker 3:
– ( good 2)
• Worker 4:
– (study 2)
• Worker 5:
– (cloud 2)

Reduce Operation
MAP: Input data  <key, value> pair
REDUCE: <key, value> pair  <result>
Reduce
Reduce
Reduce
Data
Collection: split1 Split the data to
Supply multiple
processors
Data
Collection: split 2
Data
Collection: split n Map
Map
……
Map
…

CountCountCount
worker1
Worker n
Parse-hash
worker2
Map <key, 1> Reducers (say, Count)
P-0000
P-0001
P-0002
, count1
, count2
,count3
Work 3

Parallel Execution
No. of CPU.
Mapping

Fault Tolerance
• Network Failure:
– Detect failure via periodic heartbeats
– Re-execute completed and in-progress map tasks
– Re-execute in progress reduce tasks
– Task completion committed through master
• Master failure:
– Could handle, but don't yet (master failure unlikely)

Cloud Federation
• Cloud Federation is a collection of individual Cloud
providers, which collaborate by trading resources (e.g.
computing, storage).
• Desired feature of Cloud
– Illusion of infinite computing resources
• Resources available in a single data center are limited
– A large demand may put pressure in the data center
capacity
– One possible source for additional resources is idling
resources from other providers

- A user submit an application to the federation, the
federation select provider to run application.
Cloud federation
provider1
provider2 Provider 3 Provider n

Cloud Federation Motivations
• Obtain extra resources from other members (Outsourcing)
– Avoid losing customers
– Avoid losing reputation by violating SLAs
• Lease idle resources (Contributing to Federation
– Avoid wasting their non-storable compute resources
• Supplying resources in specific geographic locations
– Low-latency access regardless of location
– meet regulations in place for the customers
• Disaster recovery

Cloud storage
• Cloud storage enables to “throw” data into the
cloud and without worrying about how it is stored or
backing it up. When you need it again, you simply
reach into the cloud and grab it.
• User don’t know how it is stored, where it is stored,
or what has happened to all the pieces of hardware
between the time you put it in the cloud and the
time you retrieved it.

Yesterday’s storage
Local
storage
Storage
Servers

Today’s storage
e.g.
Google
Laptop Cloud Storage

Internet-service FS:
GoogleFS, HadoopFS, CloudStore, ...
Custom Storage:
Facebook Haystack Photo Store,
Microsoft StarTrack (Map Apps),
Amazon S3, EBS, ...
Key-Value Store:
Cassandra, Voldemort, ...
Structured Storage:
Yahoo! PNUTS, Google BigTable, Hbase, ...
+ Replication
+ Scale-up
+ Migration
+ ...

Agenda
3.1 Cloud Migration
3.2 Virtualization
6. Cloud Workflow system
8. Our Dissertation with this topics
9. References

Our Dissertation
- Cloud computing environment introduce more
features in on-demand
scalability/elasticity, affordability, global-scale
accessibility.
- All above features are done in open
environments, therefore it vulnerable to many
types of attacks.
- Our dissertation attempt to provide a hybrid
cryptography model based on CipherCloud and
Quantum Cryptography to present a new
concept in cloud security world.

References
1- George Reese, “Cloud Application Architectures” USA, 2009.
2- Zaigham Mahmood and Richard Hill, Cloud Computing for
Enterprise Architectures. ©Springer-Verlag London Limited
2011
3- Rajkumar Buyya and James Broberg, CLOUD COMPUTING
“Principles and Paradigms”, 2011 by John Wiley.
4- Anthony T. Velte and Robert Elsenpeter, Cloud Computing:
“A Practical Approach”© 2010 by The McGraw-Hill Companies

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