Cloud Computing

Introduction
Lecture Contents
 What is Cloud Computing?
 Early models of Cloud Computing.
 Delivery models and services.
 Ethical issues in Cloud Computing.
 Cloud vulnerabilities.
 Parallel Computing.
 Distributed Systems.

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What is Cloud Computing?
▪ What do you think?

▪ “Cloud computing is an information technology (IT) paradigm that enables us

to access a shared pools of configurable system resources and higher-level
services over the Internet.
▪ Cloud computing relies on sharing of resources to achieve coherence and
economies of scale, similar to a public utility.”
https://en.wikipedia.org/wiki/Cloud_computing
▪ The delivery of computing services – servers, storage, databases, networking,
software, analytics and more – over the Internet is called the cloud. Companies
offering these computing services are called cloud providers and typically
charge for cloud computing services based on usage, similar to how you’re
billed for gas or electricity at home.

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Cloud Computing Models, Resources, Attributes
Delivery models
Software as a Service (SaaS) Deployment models
Platform as a Service (PaaS) Public cloud

Infrastructure as a Service (IaaS) Private cloud

Community cloud
Hybrid cloud

Cloud computing
Infrastructure
Distributed infrastructure
Defining attributes
Resource virtualization
Massive infrastructure
Autonomous systems
Utility computing. Pay-per-usage
Resources
Accessible via the Internet
Compute & storage servers
Networks Services Elasticity

Applications

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Early Models of Cloud Computing
 Basic reasoning: information and data processing can be done more
efficiently on large farms of computing and storage systems accessible
via the Internet.
 Two early models:
1.Grid computing – initiated by the National Labs in the early 1990s;
targeted primarily at scientific computing.
 “Grid computing is the collection of computer resources from multiple locations to
reach a common goal. The grid can be thought of as a distributed system with
non-interactive workloads that involve a large number of files.” from Wikipedia
2.Utility computing – initiated in 2005-2006 by IT companies and
targeted at enterprise computing.
 “Utility computing is a service provisioning model in which a service provider
makes computing resources and infrastructure management available to the
customer as needed, and charges them for specific usage rather than a flat rate.”
from Wikipedia

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Cloud computing - Characteristics
“Cloud Computing offers on-demand, scalable and elastic computing
(and storage services). The resources used for these services can be
metered and users are charged only for the resources used. “

Shared Resources and Resource Management:

1.Cloud uses a shared pool of resources
2.Uses Internet techn. to offer scalable and elastic services.
3.The term “elastic computing” refers to the ability of dynamically
and on-demand acquiring computing resources and supporting a
variable workload.
4.Resources are metered and users are charged accordingly.
5.It is more cost-effective due to resource-multiplexing. Lower costs
for the cloud service provider are passed to the cloud users.
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Cloud computing (cont’d)
Data Storage:
6.Data is stored:
 in the “cloud”, in certain cases closer to the site where it is used.
 appears to the users as if stored in a location-independent manner.
7.The data storage strategy can increase reliability, as well as
security, and can lower communication costs.

Management:
8.The maintenance and security are operated by service
providers.
9.The service providers can operate more efficiently due to
specialisation and centralisation.

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Cloud Computing Advantages
1. Resources, such as CPU cycles, storage, network bandwidth, are
shared.

2. When multiple applications share a system, their peak demands

for resources are not synchronised thus, multiplexing leads to a
higher resource utilization.

3. Resources can be aggregated to support data-intensive

applications.

4. Data sharing facilitates collaborative activities. Many applications

require multiple types of analysis of shared data sets and multiple
decisions carried out by groups scattered around the globe.
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Cloud Computing Advantages
5. Eliminates the initial investment costs for a private
computing infrastructure and the maintenance and operation
costs.

6. Cost reduction: concentration of resources creates the

opportunity to pay as you go for computing.

7. Elasticity: the ability to accommodate workloads with very

large peak-to-average ratios.

8. User convenience: virtualization allows users to operate in

familiar environments rather than in different ones.
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Types of clouds
1. Public Cloud - the infrastructure is made available to the general
public or a large industry group and is owned by the organization
selling cloud services.

2. Private Cloud – the infrastructure is operated solely for an

organization.

3. Hybrid Cloud - composition of two or more Clouds (public, private,

or community) as unique entities but bound by a standardised
technology that enables data and application portability.

4. Other types: e.g., Community/Federated Cloud - the

infrastructure is shared by several organizations and supports a
community that has shared concerns.
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Why cloud computing is (could be) successful when
other paradigms have failed?
 It is in a better position to exploit recent advances in
software, networking, storage, and processor technologies
promoted by the same companies who provide Cloud
services.
 Economical reasons: It is used for enterprise computing; its
adoption by industrial organizations, financial institutions,
government, and so on has a huge impact on the economy.
 Infrastructures Management reasons:
 A single Cloud consists of a mostly homogeneous (now more
heterogeneous) set of hardware and software resources.
 The resources are in a single administrative domain (AD). Security,
resource management, fault-tolerance, and quality of service are less
challenging than in a heterogeneous environment with resources in
multiple ADs.

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Challenges for cloud computing
1. Availability of service: what happens when the service provider
cannot deliver?

2. Data confidentiality and auditability, a serious problem.

3. Diversity of services, data organization, user interfaces

available at different service providers limit user mobility; once
a customer is hooked to one provider it is hard to move to
another.

4. Data transfer bottleneck; many applications are data-intensive.

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More challenges
5. Performance unpredictability, one of the consequences of
resource sharing.
 How to use resource virtualization and performance isolation for QoS
guarantees?
 How to support elasticity, the ability to scale up and down quickly?

6. Resource management: It is a big challenge to manage

different workloads running on large data centers. Are self-
organization and self-management the solution?

7. Security and confidentiality: major concern for sensitive

applications, e.g., healthcare applications.

Addressing these challenges is on-going work!

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Cloud Delivery Models
1. Software as a Service (SaaS) (high level)
2. Platform as a Service (PaaS)
3. Infrastructure as a Service (IaaS) (low level)

source Wikipedia 15
Infrastructure-as-a-Service (IaaS)
 Infrastructure is compute resources, CPU, VMs, storage, etc
 The user is able to deploy and run arbitrary software, which can
include operating systems and applications.
 The user does not manage or control the underlying Cloud
infrastructure but has control over operating systems, storage,
deployed applications, and possibly limited control of some
networking components, e.g., host firewalls.

 Services offered by this delivery model include:

server hosting,
storage, computing hardware, operating systems, virtual instances,
load balancing, Internet access, and bandwidth provisioning.

 Example: Amazon EC2 16

Platform-as-a-Service (PaaS)
 Allows a cloud user to deploy consumer-created or acquired
applications using programming languages and tools supported
by the service provider.
 The user:
 Has control over the deployed applications and, possibly, application
hosting environment configurations.
 Does not manage or control the underlying Cloud infrastructure including
network, servers, operating systems, or storage.
 Not particularly useful when:
 The application must be portable.
 Proprietary programming languages are used.
 The hardware and software must be customised to improve the
performance of the application.
 Examples: Google App Engine, Windows Azure
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Software-as-a-Service (SaaS)
 Applications are supplied by the service provider.
 The user does not manage or control the underlying Cloud
infrastructure or individual application capabilities.
 Services offered include:
 Enterprise services such as: workflow management, communications,
digital signature, customer relationship management (CRM), desktop
software, financial management, geo-spatial, and search.
 Not suitable for real-time applications or for those where data is
not allowed to be hosted externally.

 Examples: Gmail, Salesforce

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The Three delivery models of Cloud Computing

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Cloud activities
 Service management and provisioning including:
 Virtualization.
 Service provisioning.
 Call center.
 Operations management.
 Systems management.
 QoS management.
 Billing and accounting, asset management.
 SLA management.
 Technical support and backups.

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Cloud activities (cont’d)
 Security management including:
 ID and authentication.
 Certification and accreditation.
 Intrusion prevention.
 Intrusion detection.
 Virus protection.
 Cryptography.
 Physical security, incident response.
 Access control, audit and trails, and firewalls.

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Cloud activities (cont’d)
 Customer services such as:
 Customer assistance and on-line help.
 Subscriptions.
 Business intelligence.
 Reporting.
 Customer preferences.
 Personalization.
 Integration services including:
 Data management.
 Development.

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Ethical issues
 Paradigm shift with implications on computing ethics:
 The control is relinquished to third party services.
 Data is stored on multiple sites administered by several
organizations.
 Multiple services interoperate across the network.
 Implications:
 Unauthorised access.
 Data corruption.
 Infrastructure failure, and service unavailability.

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De-perimeterisation
 Systems can span the boundaries of multiple organisations and
cross the security borders.

 The complex structure of Cloud services can make it difficult to

determine who is responsible in case something undesirable
happens.

 Identity fraud and theft are made possible by the unauthorised

access to personal data in circulation and by new forms of
dissemination through social networks and they could also pose
a danger to Cloud Computing.

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Privacy issues
 Cloud service providers have already collected petabytes of
sensitive personal information stored in data centers around
the world. The acceptance of Cloud Computing therefore will
be determined by privacy issues addressed by these
companies and the countries where the data centers are
located.

 Privacy is affected by cultural differences; some cultures

favour privacy, others emphasise community. This leads to an
ambivalent attitude towards privacy in the Internet which is a
global system.

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Cloud Vulnerabilities
 Clouds are affected by malicious attacks and failures of the
infrastructure, e.g., power failures.

 Such events can affect the Internet domain name servers and
prevent access to a Cloud or can directly affect the Clouds:
 in 2004 an attack at Akamai caused a domain name outage and a
major blackout that affected Google, Yahoo, and other sites.
 in 2009, Google was the target of a denial of service attack which
took down Google News and Gmail for several days;
 in 2012 lightning caused a prolonged down time at Amazon.

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Back to Basics -- Parallel Computing
 “Parallel computing is a form of computation in which many
calculations are carried out simultaneously, operating on the
principles that large problems can often be divided into smaller
ones, which are then solved concurrently (in parallel).” Wikipedia

 Hardware and software systems allow us to:

 Solve problems demanding resources not available on a
single system.
 Reduce the time required to obtain a solution.

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Parallel Computing – Amdahl’s Law
 The speedup S measures the effectiveness of parallelisation:
S(N) = T(1) / T(N)
 T(1)  the execution time of the sequential computation.
 T(N)  the execution time when N parallel computations are executed

 Amdahl's Law: if α is the fraction of running time a sequential

program spends on non-parallelisable segments of the computation
then:
S ≅ 1/ α

 This is a theoretical upper bound on the best speedup we can get

from parallelising a certain program.

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 Back to Basics -- Distributed systems
 Collection of autonomous computers, connected through a
network and distribution software (often) called middleware
which enables computers to coordinate their activities and to
share system resources for a common goal.
 Characteristics:
1. The users perceive the system as a single, integrated computing
facility.
2. The components are autonomous.
3. Scheduling and other resource management and security policies are
implemented by each system.
4. There are multiple points of control and multiple points of failure.
5. The resources may not be accessible at all times.
6. Can be scaled by adding additional resources.
7. Can be designed to maintain availability even at low levels of
hardware/software/network reliability.

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Summary
 What is Cloud Computing?
 Early models of Cloud Computing.
 Delivery models and services.
 Ethical issues in Cloud Computing.
 Cloud vulnerabilities.
 Parallel Computing and Distributed Systems (brief)

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 Course Evaluation
 Mid sem Exam : 25 marks (Average of 3 STs)
 End Sem: 50 marks (Average of two LTs)
 Continuous Assessment: 25 marks(3 surprise quizzes(10), Assignments(10),
{Attendance, Discussions, Participation}(5))