CS计算机代考程序代写 SQL x86 data structure dns database deep learning file system flex android capacity planning AWS AI algorithm CRICOS code 00025BCRICOS code 00025B

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1. Course Orientation
2. History and Definition of Cloud Computing
3. Business Drivers for creation of Cloud Computing

– Capacity Planning, Cost Reduction, Organisational Agility
4. Technologies that impact Cloud Computing

– Clustering, Grid Computing, Virtualisation
5. Cloud Characteristics

– On-demand usage, Ubiquitous access, Multitenancy, Elastic, Measurable,
Resilient.

Re-cap

Cloud Computing
INFS3208

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• Cloud Delivery Models
• Cloud Deploy Models
• Cloud-Enabling Technologies

– Broadband Networks and Internet Architecture
– Virtualisation Technology (VT)
– Data Centre Technology
– Web Technology
– Multitenant Technology

• Goals and Benefits
• Risks and Challenges
• Cloud-based Applications in the World
• Summary

Outline

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A cloud delivery model represents a specific, pre-packaged combination of IT
resources offered by a cloud provider.

Three common cloud delivery models:
• Infrastructure-as-a-Service (IaaS)
• Platform-as-a-Service (PaaS)
• Software-as-a-Service (SaaS)

Cloud Delivery Models

SaaS
PaaS
IaaS

co
nt

ro
l

Less

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IaaS

Cloud Delivery Models — IaaS
Infrastructure-as-a-Service (IaaS):
• a self-contained virtual environment consists of infrastructure-centric IT

resources
• IT resources can be accessed and managed via cloud service-based

interfaces and tools
• can include hardware, network, connectivity, operating systems, and

other “raw” IT resources
• provides a high level of control and responsibility over its configuration

and utilization
• needs cloud consumers’ administrative responsibility
• can be different by different cloud providers (different specs: CPU cores,

RAM, storage, etc)
• is generally offered as freshly initialized virtual machines
• users: system admins
• examples: Amazon EC2, Google Compute Engine (GCE), Microsoft

Azure
5

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Platform-as-a-Service (PaaS):
• a pre-defined “ready-to-use” environment typically consists of already

deployed and configured IT resources
• can include a programming language execution environment, an operating

system, a web server, and a database.
• encapsulates an environment where users can build, compile, and run

program without worrying about the infrastructure.
• no need to take administrative and maintaining responsibility
• needs users to manage their own data (e.g. with SQL databases)
• Lower level of control over the underlying IT resources
• users: developers
• examples:

• AWS Elastic Beanstalk
• Google app engine (GAE)

Cloud Delivery Models — PaaS

PaaS

https://cloud.google.com/appengine

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Software-as-a-Service (SaaS):
• a shared cloud service and made available as a “product”
• provides on-demand services
• no installation of the software on users’ PCs
• assessible via a web browser or lightweight client apps.
• run a single instance of the software
• can be available for multiple users
• has very limited administrative control over a SaaS implementation.
• users: end-users
• examples:

• Google ecosystem docs/sheets/mails/calendar/etc
• Microsoft Office 365

Cloud Delivery Models — SaaS
SaaS

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Model Comparisons
Delivery Model Control Level Functionality Consumer Activities Provider Activities

SaaS Usage and
usage-related
configuration

Access to front-end
user-interface

Uses and configures
cloud services

Implements, manages, and
maintains cloud service
Monitors usage by cloud
consumers

PaaS Limited
administrative

Moderate level of
administrative control

over IT resources
relevant to cloud

consumer’s usage of
platform

Develops, tests,
deploys, and manages

cloud services and
cloud-based solutions

Pre-configures platform
and provisions underlying
infrastructure, middleware,
and other needed IT
resources, as necessary
Monitors usage by cloud
consumers

IaaS Full
administrative

Full access to
virtualized

infrastructure-related IT
resources and possibly
to underlying physical

IT resources

Sets up and configures
bare infrastructure,

and installs, manages,
and monitors any
needed software

Provisions and manages
the physical processing,
storage, networking, and
hosting required
Monitors usage by cloud
consumers

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Model Comparisons
On

Premises
Infrastructure Platform Software

(as a Service) (as a Service) (as a Service)
Application Application Application Application

Data Data Data Data
Runtime Runtime Runtime Runtime

Middleware Middleware Middleware Middleware
O/S O/S O/S O/S

Virtualizatio
n

Virtualization Virtualization Virtualization

Servers Servers Servers Servers

Storage Storage Storage Storage

Networking Networking Networking Networking

M
anaged by U

sers

M
anaged by U

sers

M
anaged by U

sers

M
anaged by
P

roviders

M
anaged by
P

roviders

M
anaged by
P

roviders
Network Architects

System Admins
Application
Developers

End Users
9

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New Adventures in the Cloud

https://www.cnbc.com/2020/08/04/microsoft-reveals-more-details-about-its-xcloud-game-streaming-service.html
https://www.xbox.com/en-US/xbox-game-pass/cloud-gaming
https://stadia.google.com/ 10

https://www.cnbc.com/2020/08/04/microsoft-reveals-more-details-about-its-xcloud-game-streaming-service.html
https://www.xbox.com/en-US/xbox-game-pass/cloud-gaming
https://stadia.google.com/

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Amazon’s AWS:
• leading company in Cloud Computing
• provides IaaS and PaaS
• famous for EC2
Google Cloud:
• offers IaaS, PaaS (GAE), and SaaS (Google

docs/sheets/calendar/gmail)
Microsoft Azure:
• provides IaaS, PaaS, and SaaS (Office 365)
iCloud:
• majorly for Apple products (Macbook, iPad, iPhone, etc)
• store and backup users’ documents online.
• Storage-as-a-service (aka STaaS)

Examples of Cloud Computing Usage

Netflix

Google App
Engine

Google Doc

AWS Elastic
Beanstalk

VM on GCE

Dropbox

SaaS

PaaS

IaaS

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• Cloud Delivery Models
• Cloud Deploy Models
• Cloud-Enabling Technologies

– Broadband Networks and Internet Architecture
– Virtualisation Technology (VT)
– Data Centre Technology
– Web Technology
– Multitenant Technology

• Goals and Benefits
• Risks and Challenges
• Cloud-based Applications in the World

Outline

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A cloud deployment model represents a specific type of cloud environment
In terms of ownership, size, and access, models can be divided into four common groups:

• Public cloud
– a publicly accessible cloud environment owned by a third-party cloud provider
– usually supplied via the delivery models and offered to consumers at a cost
– is created and on-going maintained by the cloud provider.
– typical examples: GCP, AWS, AZURE, etc.

• Community cloud
– is similar to a public cloud except that its access is limited to a community of cloud consumers.
– may be jointly owned by the community members or by a third-party cloud provider
– cloud consumers of the community typically share the responsibility for defining and evolving the

community cloud
– Typical examples: Cloud for multiple governmental departments.

Cloud Deployment Models

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• Private cloud
– is owned by a single organization and enables an organization to use CC technology to

access to IT resources by different parts, locations, or departments.
– actual administration may be carried out by internal or outsourced staff.
– within a private cloud, the same organization is technically both the cloud consumer and

provider
– Typical examples: UQCloud (VMs) and UQRDM cloud (STaaS)

• Hybrid cloud
– is a cloud environment comprised of two or more different cloud deployment models.
– Example: private cloud (sensitive data) + public cloud (less sensitive cloud services)
– can be complex and challenging to create and maintain due to the potential disparity in

cloud environments

Cloud Deployment Models

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• Cloud Delivery Models
• Cloud Deploy Models
• Cloud-Enabling Technologies

– Broadband Networks and Internet Architecture
– Virtualisation Technology (VT)
– Data Centre Technology
– Web Technology
– Multitenant Technology

• Goals and Benefits
• Risks and Challenges
• Cloud-based Applications in the World
• Summary

Outline

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Modern-day clouds are underpinned by a set of primary technology components
that collectively enable key features and characteristics associated with
contemporary cloud computing:
• Broadband Networks and Internet Architecture
• Virtualisation Technology
• Data Centre Technology
• Web Technology
• Multitenant Technology

Cloud-Enabling Technology (CET)

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• All clouds must be connected to a network (an
inherent dependency on WWW, most clouds are
Internet-enabled).

• Worldwide connectivity is enabled through a
hierarchical topology composed of Tiers 1, 2, and 3.

• Cloud consumers and cloud providers typically use
the Internet to communicate.

• Easily configuration of IT resources (external and
internal users via WWW) and superior connectivity

• The potential of cloud platforms therefore generally
grows in parallel with advancements in Internet
connectivity and service quality (bandwidth, latency,
protocols, etc.)

CET I – Broadband Networks and Internet Architecture

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• VT is the process of converting a physical IT resource into a virtual IT
resource.

• Most types of IT resources can be virtualised, including:
– Servers – A physical server can be abstracted into a virtual server.
– Storage – A physical storage device can be abstracted into a virtual

storage device or a virtual disk.
– Network – Physical routers and switches can be abstracted into logical

network fabrics, such as VLANs.
– Power – A physical UPS and power distribution units can be abstracted

into what are commonly referred to as virtual UPSs.
• A physical server is called a host or physical host.
• A software that manages VMs and hardware is called as Virtual Machine

Monitor (VMM), also known as hypervisor in cloud computing context.
• An operating system in a virtual machine is called as guest OS.

CET II: Virtualisation Technology (VT)

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• Steps of creating a new virtual server through virtualisation software:
I. the allocation of physical IT resources (e.g. specify #CPU, Mem, Storage in VirtualBox by

Oracle);
II. followed by the installation of an operating system (e.g. Install Ubuntu or Windows

systems in VirtualBox).
• Virtual servers use their own guest operating systems, which are independent of the

operating system in which they were created.
• Guest OS and the application software on the virtual server are unaware of the virtualisation

process.

CET II: Virtualisation Technology (VT)

VM1 VM2 VM3 VM4

MySQL

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Hardware Independence
• VT can convert and translate IT hardware into emulated and standardised software-based copies.
• Due to HI, virtual servers can easily be moved to another virtualisation host
• Thus, cloning and manipulating virtual IT resources is much easier than duplicating physical hardware.

Server Consolidation
• VT enables different virtual servers to share one physical server, which is called server consolidation
• SC is commonly used to increase hardware utilisation, load balancing, and optimisation of available IT

resources.
• The resulting flexibility: different virtual servers can run different guest operating systems on the same

host.
• supports common cloud features, e.g. on-demand usage, resource pooling, elasticity, scalability, and

resiliency.

CET II: Virtualisation Technology (VT)

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Resource Replication
• Virtual servers are created as virtual disk images that contain binary file copies of hard disk

content.
• Host’s OS can access these disk images e.g. copy, move, and paste (replicate, migrate, and

back up the virtual server).
• In this way, it enables:

– Standard virtual machine creations with common configurations
– Increased agility in the migration and deployment of a virtual machine’s new instances
– Backup & Roll back abilities

CET II: Virtualisation Technology (VT)

copy

One
Host

copy

Host
A

Host
B 21

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Operating System-Based Virtualisation
• virtualisation is the installation of virtualisation software in a pre-

existing operating system (called the host operating system)
• example: Install ubuntu on Windows with VMware/VirtualBox
• processing overhead: virtualisation software and host OS.

Hardware-Based Virtualisation
• the installation of virtualisation software directly on the physical host

hardware bypassing the host OS
• example: Oracle VM Server for x86 (up to 384 CPUs and 6TB RAM)
• VMM is also named as Hypervisor
• more efficient (no hosting OS), but compatible issues.

CET II: Virtualisation Technology (VT)
operating system-based virtualisation

Hardware-based virtualisation

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A data centre is a specialised IT infrastructure that houses
centralised IT resources

• Servers (rack in cabinet);
• Databases and software systems;
• Networking and telecommunication devices.

Typical technologies and components
• Virtualisation:

– Data centres consist of both physical and virtualised IT
resources.

– The physical IT resource layer refers to the facility
infrastructure that houses:

� computing/networking systems and equipment,
� hardware systems and their operating systems.

CET III – Data Centre Technology

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Typical technologies and components of Data Centre:
• Standardisation and Modularity:

– DCs are built upon standardised commodity hardware and designed with modular
architectures.

– reduce investment and operational costs.
• Automation:

– DCs have specialised platforms that automate general management tasks such as
provisioning, configuration, patching, and monitoring without supervision.

• Remote Operation and Management:
– Remotely access via consoles and management systems: most of the tasks in DCs (e.g.

operational and administrative tasks).
– On-site jobs: highly specific tasks – equipment handling and cabling or hardware-level

installation and maintenance.

CET III – Data Centre Technology

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Typical technologies and components of Data Centre:
• High Availability:

– Aiming to high-level availability, DCs usually have redundant, uninterruptable power supplies,
cabling, and environmental control subsystems in anticipation of system failure, along with
communication links and clustered hardware for load balancing.

• Security-Aware Design, Operation and Management:
– Security requirements (e.g. physical and logical access controls and data recovery strategies)

need to be comprehensive for DCs.
• Facilities:

– Site: custom-designed locations that are outfitted with specialised computing, storage, and
network equipment.

– Layout: multiple functional areas
– various power supplies, cabling, and environmental control stations that regulate heating,

ventilation, air conditioning, fire protection, and other related subsystems.

CET III – Data Centre Technology

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Hardware of Data Centres:
• Computing Hardware:

– rackmount form factor server (multiple racks in a cabinet);
– a power-efficient multi-core CPU architecture (many cores but

low frequency, e.g. Xeon/EPYC CPUs);
– redundant and hot-swappable components, such as hard disks,

power supplies, network interfaces, and storage controller cards.
• Storage Hardware:

– specialised storage systems that maintain enormous amounts of
digital information in order to fulfill considerable storage capacity
needs by using arrays of disks;

– frequently used storage technologies: RAID, Hot-Swappable,
Virtualisation, and Fast Data Replication Mechanisms.

• Network Hardware:
– LAN fabric, high-performance switches & adaptors (up to 10 G/s),

etc.

CET III – Data Centre Technology

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5 Largest Data Centres in the world 1 (as of date 22 May 2018)
1. Digital Reality Main Data Centre (San Francisco, US)
2. Global Switch (Singapore)
3. DuPont Fabros Technology data center in Virginia (Virginia, US)
4. CyrusOne’s Chandler I Data Center (Arizona, US)
5. China Telecom’s Inner Mongolia data center (China) (No 1 in 2020)

Largest Data Centre in Australia:
EQUINIX SY3 Data Centre (Sydney) 2

CET III – World-class Data Centres

1. https://www.avalon.host/blog/5-largest-data-centers-in-the-world/
2. https://cloudscene.com/market/data-centers-in-australia/all 27

https://www.avalon.host/blog/5-largest-data-centers-in-the-world/

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CET III – Data Centre in Brisbane

NEXTDC Brisbane Data Centre https://www.nextdc.com/

We’re
here!

https://www.nextdc.com/

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CET IV – Web Technology
• Web technology is very commonly used for cloud service implementations and for front-ends used to remotely

manage cloud-based IT resources.

• Fundamental technologies of Web architecture:
– Uniform Resource Locator (URL) – A standard syntax used for creating identifiers that point to Web-

based resources, the URL is often structured using a logical network location.
– Hypertext Transfer Protocol (HTTP) – This is the primary communications protocol used to exchange

content and data throughout the World Wide Web. URLs are typically transmitted via HTTP.
– Markup Languages (HTML, XML) – Markup languages provide a lightweight means of expressing Web-

centric data and metadata: HTML (webpages) and XML (data).
• Example: a web browser can request to execute an action like read, write, update, or delete on a web

resource on the Internet, and proceed to identify and locate the Web resource through its URL. The request is
sent using HTTP to the resource host, which is also identified by a URL. The Web server locates the Web
resource and performs the requested operation, which is followed by a response being sent back to the client.
The response may be comprised of content that includes HTML and XML statements.

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CET V – Multitenant Technology
• Multitenant application enables multiple users (tenants) to access the same application logic

simultaneously.
• Each tenant has its own view of the application that it uses, administers, and customises as a dedicated

instance of the software while remaining unaware of other tenants that are using the same application.
• Multitenant applications ensure that tenants do not have access to data and configuration information

that is not their own.
• Tenants can individually customise features of the application:

– User Interface – Tenants can define a specialised “look and feel” for their application interface.
– Business Process – Tenants can customise the rules, logic, and workflows of the business

processes that are implemented in the application.
– Data Model – Tenants can extend the data schema of the application to include, exclude, or rename

fields in the application data structures.
– Access Control – Tenants can independently control the access rights for users and groups.

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CET V – Multitenant Technology
• Multitenant application architecture is significantly more complex than that of single-tenant

applications.
• Common characteristics of multitenant applications include:

– Usage Isolation – individual behaviour does NOT affect the other tenants’ behaviours.
– Data Security – Tenants cannot access data that belongs to other tenants.
– Recovery – Backup and restore procedures are separately executed for the data of each tenant.
– Application Upgrades – Tenants are not negatively affected by the synchronous upgrading of

shared software artifacts.
– Scalability – The application can scale to accommodate increases in usage by existing tenants

and/or increases in the number of tenants.
– Metered Usage – Tenants are charged only for the application processing and features that are

actually consumed.
– Data Tier Isolation – Tenants can have individual databases, tables, and/or schemas isolated from

other tenants. Alternatively, databases, tables, and/or schemas can be designed to be intentionally
shared by tenants.

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CET V – Multitenant Technology
Multitenancy vs. Virtualisation
Multitenancy is sometimes mistaken for virtualisation because the concept of
multiple tenants is similar to the concept of virtualised instances.
The differences lie in what is multiplied within a physical server acting as a host:
• With virtualisation:

– Multiple virtual copies of the server environment can be hosted by a single
physical server.

– Each copy can be provided to different users, can be configured
independently, and can contain its own operating systems and applications.

• With multitenancy:
– A physical or virtual server hosting an application is designed to allow

usage by multiple different users.
– Each user feels as though they have exclusive usage of the application.

Hardware

VMM

VM1 VM2 VM3

Hardware

Multitenant
application

U1 U2 U3

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• Cloud Delivery Models
• Cloud Deploy Models
• Cloud-Enabling Technologies

– Broadband Networks and Internet Architecture
– Virtualisation Technology (VT)
– Data Centre Technology
– Web Technology
– Multitenant Technology

• Goals and Benefits
• Risks and Challenges
• Cloud-based Applications in the World
• Summary

Outline

CRICOS code 00025BCRICOS code 00025B

changing demand
for an IT resource
over a day

Reduced Investments and Proportional
Costs
• Capital reduced by cloud provider (mass-inquisition,

hardware/software sharing, and data centre deployments)
• Elimination or minimization of IT investments (focus on core

business)
• Common measurable benefits, e.g. on-demand access to pay-as-

you-go computing resources (CPU by hr)

Increased Scalability
• can instantly and dynamically allocate IT resources
• always meet and fulfil unpredictable demands avoids potential loss

Increased Availability and Reliability
• resilient IT resources
• failover support (recovery)

Goals and Benefits

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Who should adopt cloud computing
• Users/Business who need Collaboration work
• Users/Business want reduce operation cost
• Users/Business with increasing and changing needs

Who shouldn’t consider cloud computing
• Offline users/business
• The security-conscious
• Anyone tied to existing applications and without alternative

Cloud Computing is for whom?

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• Cloud Delivery Models
• Cloud Deploy Models
• Cloud-Enabling Technologies

– Broadband Networks and Internet Architecture
– Virtualisation Technology (VT)
– Data Centre Technology
– Web Technology
– Multitenant Technology

• Goals and Benefits
• Risks and Challenges
• Cloud-based Applications in the World
• Summary

Outline

CRICOS code 00025BCRICOS code 00025B

• Increased Security Vulnerabilities

• Reduced Operational Governance Control

• Limited Portability Between Cloud Providers

• Multi-regional Compliance and Legal Issues

Risks and Challenges

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• Cloud Delivery Models
• Cloud Deploy Models
• Cloud-Enabling Technologies

– Broadband Networks and Internet Architecture
– Virtualisation Technology (VT)
– Data Centre Technology
– Web Technology
– Multitenant Technology

• Goals and Benefits
• Risks and Challenges
• Cloud-based Applications in the World
• Summary

Outline

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• It is projected that there will be 24 billion devices on the Internet by 2020.
• The cloud will become more important as a controller of and resource provider for the Internet of
Things (IoT).

• Gartner predicts that the cloud services marketplace will be worth $206.2 billion in 2019, and will grow to
$278.3 billion in 2021.

• IDC predicts a similar market size of $210 billion in 2019, rising to $370 billion in 2022.
• Ten years ago, many people claimed that cloud computing was a fad that would never catch on. But today

there can be no doubt that cloud computing is a very significant and growing computing trend.
• In the future, “ubiquitous cities” and “smart homes” can be built on cloud computing (cloud

supported/controlled robotics).
– Cloud robotics is an emerging field of robotics ingrained in cloud computing.
– Cloud robotics provides a shared knowledge database.
– Cloud robotics has the abilities about powerful computational, storage, and communications

resources with cloud.
– Cloud robotics offloads heavy computing tasks to the cloud.

Revisit: Importance of Cloud Computing

https://www.gartner.com/en/newsroom/press-releases/2018-09-12-gartner-forecasts-worldwide-public-
cloud-revenue-to-grow-17-percent-in-2019
https://www.idc.com/getdoc.jsp?containerId=prUS44891519

https://www.explainingcomputers.com/cloud.html

https://www.gartner.com/en/newsroom/press-releases/2018-09-12-gartner-forecasts-worldwide-public-cloud-revenue-to-grow-17-percent-in-2019
https://www.idc.com/getdoc.jsp?containerId=prUS44891519
https://www.explainingcomputers.com/cloud.html

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Who are using Google Cloud Platform (GCP)?

https://cloud.google.com/customers/#/
40

https://cloud.google.com/customers/

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E-Health: Analysing breast cancer images faster and better with machine learning by ACS
Background:
• Cancer is the second most common cause of death in the United States (nearly ¼ deaths).
• breast cancer is the most commonly diagnosed type of cancer and the second leading cause of cancer death in the

United States.
• If detected early, breast cancer is one of the most survivable cancers: the five- and ten-year relative survival rates for

women with invasive breast cancer are 90 percent and 83 percent, respectively.
• However, some molecular subtypes of breast cancer have a poor prognosis and there is limited understanding of these

subtypes.
• Since 1992, the American Cancer Society has conducted the Cancer Prevention Study-II (CPS-II) Nutrition cohort, a

prospective study of more than 188,000 American men and women.
– CPS-II provides valuable factors: height, weight, demographic characteristics, family history, use of medicines, etc.
– CPS-II provides medical records and surgical tissue samples for approximately 1,700 CPS-II participants diagnosed with

breast cancer
Aim to answer:
• What lifestyle, medical, and genetic factors are related to molecular subtypes of breast cancer?
• Do different features in the breast cancer tissue translate to a better survival rate?

Examples of Cloud-based Applications – I

https://cloud.google.com/customers/american-cancer-society/
https://www.cancer.org/content/dam/cancer-org/research/cancer-facts-and-statistics/annual-cancer-facts-and-
figures/2018/cancer-facts-and-figures-2018.pdf

https://www.cancer.org/content/dam/cancer-org/research/cancer-facts-and-statistics/annual-cancer-facts-and-figures/2018/cancer-facts-and-figures-2018.pdf
https://www.cancer.org/
https://www.cancer.org/research/we-conduct-cancer-research/epidemiology/cancer-prevention-study-2.html
https://cloud.google.com/customers/american-cancer-society/

CRICOS code 00025BCRICOS code 00025B

Challenges:
• The computing power to analyse the high-resolution tissue;
• Effective and efficient detection by human experts;
• Labour costs of novel pattern detection in the image data.
Solutions:
• Convert the tissue images into TIF format and store on Cloud

Storage (scalable and data security)
• Pre-process Data (colour normalisation, etc)
• Run ML models on Cloud ML Engine (ease of use and latest):

unsupervised deep learning models – allow algorithms to determine
the accuracy of their predictions and make adjustments without an
engineer stepping in.

Results:
• 12x faster image analysis with ML for improved patient outcomes
• Understandable outcomes guide clinicians for more effective

treatments.

Examples of Cloud-based Applications – I

high-resolution tissue images – uncompressed, proprietary
format

Conversion
Pre-

processing Clustering

Compute Engine
Cloud Storage

Cloud ML Engine

https://cloud.google.com/customers/american-cancer-society/

CRICOS code 00025BCRICOS code 00025B

Social Media Analysis: Queensland University of Technology (QUT)
Background:
• Social media has significantly change our daily life and style
• 500 mil tweets per day (5,787 tw/sec)
• Public opinions and sentiments about events are becoming more available and useful
• A group of world-leading researcher and academics in QUT Digital Media Research Centre are

collecting, analysing, and visualising Aussie tweets in the QUT Digital Observatory project.

Aims:
• analyses of the response to and interaction with particular events on digital platforms – short term
• tracking of public communication and consumption of content – long term
• support to research projects that explore social media activities

Examples of Cloud-based Applications – II

https://cloud.google.com/customers/qut/
https://www.qut.edu.au/institute-for-future-environments/facilities/digital-observatory

https://www.qut.edu.au/institute-for-future-environments/facilities/digital-observatory
https://www.qut.edu.au/institute-for-future-environments/facilities/digital-observatory

CRICOS code 00025BCRICOS code 00025B

Challenges:
• Storage infrastructure to support such a huge and live dataset:

– A collection of tweets from all identified Australian accounts, collected since 2006.
– A live data storage: 2.4 billion tweets — growing at about 1.3 mil tw/day.
– User information: 3.7 mil Australian Twitter accounts & 140k daily active users.

• Processing capacity:
– Online queries, analysis and visualisation

Solutions:
• Google BigQuery: an analytics data warehouse to capture fast-growing datasets
• Google Reporting and Visualisation Tools
Results:
• Support projects with industry partners, such as analyses of social media activity around natural crises.
• Help deliver insights about the sharing and consumption of news sources on Twitter

Examples of Cloud-based Applications – II

CRICOS code 00025BCRICOS code 00025B

QSearch: Creating marketing opportunities with social media analytics

Background:
• Opinions, thoughts, reviews, comments are usually posted and shared on

social media
• Behaviours and demographics can be discovered by pattern recognition
• Social networks are a rich repository of user experiences and information for

agencies, businesses, and government organisations.

Aims:
Analysing social networks for product, brand, or topic trends to
• identify opportunities,
• spend campaign dollars wisely,
• manage crises effectively.

Examples of Cloud-based Applications – III

https://cloud.google.com/customers/qsearch/
45

https://cloud.google.com/customers/qsearch/

CRICOS code 00025BCRICOS code 00025B

Challenges:
• Big data storage and analytic power
• Data visualisation kits
• Infrastructure expense control for a start-up company with 10 employees
Solutions:
• BigQuery analytics data warehouse
• App Engine application development
• visualisation tools
Results:
• Records only one error per one million requests for short-URL customer tracking

service
• Enables the business to connect to and integrate social media search and

measurement tools
• Measures employee productivity and controls access to customer projects
• Analyses 43.2 billion records in 8 hours, not days

Examples of Cloud-based Applications – III

https://cloud.google.com/customers/qsearch/
46

https://cloud.google.com/customers/qsearch/

CRICOS code 00025BCRICOS code 00025B

E-Government: Improving the customer experience and worker
productivity by Service NSW
Background:
• Service NSW is a whole of New South Wales Government Service

access point that provides online, and in-person offices that handle
more than 800 types of transactions including:
– Drivers licences, photo cards and vehicle and boat registration

services
– Functions of NSW Registry of Births Deaths & Marriages
– Obtaining Opal cards for public transport, Seniors Card
– Etc.

• In 130 offices across the entire state, there are many customer-
service kiosks serving 7.89 million people (as of 2018).

Examples of Cloud-based Applications – IV

https://cloud.google.com/customers/service-nsw/
https://www.service.nsw.gov.au/service-centre

http://www.population.net.au/population-of-new-south-wales/ 47

https://cloud.google.com/customers/service-nsw/
https://www.service.nsw.gov.au/service-centre

Population of New South Wales 2022

CRICOS code 00025BCRICOS code 00025B

Challenges:
• Old kiosks’ operating system lacked remote service features and required time-consuming hard drive repairs
• Maintaining all the kiosks across the entire state is expensive

Solutions:
• Chrome devices for kiosks
• G Suite: Gmail, Hangouts, Calendar, and Google+ for communication; Drive for

storage; Docs, Sheets, Slides, Forms, and Sites for collaboration.

Results:
• Chromebases require only 5 percent of support hours needed by Microsoft devices
• Cloud tools eliminate the need for costly private WAN networks
• Reduced annual IT operational costs by 46 percent
• Helps Service NSW meet goal to perform 70 percent of government transactions digitally by 2019
• Improves employee productivity, collaboration and data security

Examples of Cloud-based Applications – IV

https://cloud.google.com/customers/service-nsw/
48

https://cloud.google.com/customers/service-nsw/

CRICOS code 00025BCRICOS code 00025B

HKTaxi: Using Google to deliver an intelligent, reliable taxi booking service

Background:
• Hongkong is one of most crowded cities in the world – 7.492 million (2019)

and density is 7,134 p/km2 (3 for Australia)
• Hailing taxis in Hongkong can be a frustrating experience — particularly

during demand peaks.
• Mobile phones and apps are making the experience easier and more

transparent.

Aims:
• Highly efficient booking service: enable drivers and users locate each other
• Effective routes to destinations during peaking hours
• Less administration, more app development

Examples of Cloud-based Applications – V

https://cloud.google.com/customers/hktaxi/
https://hktaxiapp.com/ 49

https://cloud.google.com/customers/hktaxi/
https://hktaxiapp.com/

CRICOS code 00025BCRICOS code 00025B

Challenges:
• Support electronic payment services
• Service rating: enable users to rate drivers (better service)
• 24*7 connections of drivers and users
• Support staff to resolve any issues.
Solutions:
• Google Maps SDK for iOS/Android
• Cloud Machine Learning Engine: to predict the attractiveness of orders to

drivers
Results:
• Stable service for both drivers and users
• More focus on app development, less administration cost

Examples of Cloud-based Applications – V

https://cloud.google.com/customers/hktaxi/
https://hktaxiapp.com/ 50

https://cloud.google.com/customers/hktaxi/
https://hktaxiapp.com/

CRICOS code 00025BCRICOS code 00025B

GO-JEK: Using Machine Learning for forecasting and dynamic pricing
Background:
• Traffic congestion is a fact of life for most Indonesian residents.
• The nation’s roads and associated infrastructure strains to support the country’s 260 million people,

about 10 million of whom reside in the capital, Jakarta.
• To minimise delays, Indonesians rely heavily on motorcycles, including motorcycle taxis, to travel to and

from work or personal engagements.
Aims:
• Spatial and temporal data collection
• Customer behaviour analysis
• Routes optimisation for food delivery, taxi, etc.
• Estimations of arrivals and pricing

Examples of Cloud-based Applications – VI

https://cloud.google.com/customers/go-jek/
51

https://cloud.google.com/customers/go-jek/

CRICOS code 00025BCRICOS code 00025B

Challenges:
• Manage over 1 mil drivers, or hundreds of thousands of active drivers concurrently online
• Manage over 300,000 merchants (restaurants, private sellers) for food deliver
• Ping each driver and customer every 10 seconds across the whole country – 6 million pings per minute and 8

billion pings per day
• Deal with customer interaction – generate about 4TB to 5TB of data every day
• Dynamically match the right driver with the right request (deliver person or food from A to B)
Solutions:
• Google Maps Platform: core components in the framework to find out optimised routes and estimated times of

arrival
• Big Data Package: Cloud Dataflow, Cloud Bigtable, and BigQuery form the basis of the company’s platform.
Results:
• Supports 1 million motorcycle drivers with rapid access to riders and optimised routes
• Enables demand forecasting and pricing adjustments
• Positions business for international expansion

Examples of Cloud-based Applications – VI

CRICOS code 00025BCRICOS code 00025B

There are over 90 products in nine categories:

Products and Services under Google Cloud

https://cloud.google.com/products/

Compute
Storage &
Databases Networking Big Data Cloud AI

Manageme
nt Tools

Identity &
Security

API
Platform

App Engine
Cloud
Storage

VPC – Virtual
Private Cloud BigQuery

Cloud
AutoML Stackdriver

Cloud
Identity

Maps
Platform

Compute
Engine Cloud SQL

Cloud Load
Balancing

Cloud
Dataflow Cloud TPU

Cloud
Deployment
Manager Cloud IAM

Apigee
API
Platform

Kubernetes
Engine
(GKE)

Cloud
BigTable Cloud Armor

Cloud
Dataproc

Cloud
Machine
Learning
Engine

Cloud
Console

Cloud
Identity-
Aware
Proxy

API
Monetizati
on

https://cloud.google.com/products/

CRICOS code 00025BCRICOS code 00025B

Amazon Web Service v.s. Google Cloud Platform
Category Service AWS GCP

Compute IaaS Amazon Elastic Compute Cloud Compute Engine
PaaS AWS Elastic Beanstalk App Engine

Containers
Amazon Elastic Container
Service

Google Kubernetes
Engine

Serverless Functions AWS Lambda Cloud Functions
Managed Batch Computing AWS Batch N/A

Network Virtual Networks Amazon Virtual Private Cloud Virtual Private Cloud
Load Balancer Elastic Load Balancer Cloud Load Balancing
Dedicated Interconnect Direct Connect Cloud Interconnect

Domains and DNS Amazon Route 53
Google Domains,
Cloud DNS

CDN Amazon CloudFront Cloud CDN
54

CRICOS code 00025BCRICOS code 00025B

Amazon Web Service v.s. Google Cloud Platform
Category Service AWS GCP

Storage Object Storage Amazon Simple Storage Service Cloud Storage
Block Storage Amazon Elastic Block Store Persistent Disk

Reduced-availability
Storage

Amazon S3 Standard-Infrequent
Access, Amazon S3 One Zone-
Infrequent Access Cloud Storage Nearline

Archival Storage Amazon Glacier Cloud Storage Coldline
File Storage Amazon Elastic File System Cloud Filestore (beta)

Database RDBMS
Amazon Relational Database
Service, Amazon Aurora

Cloud SQL, Cloud
Spanner

NoSQL: Key-value Amazon DynamoDB
Cloud Firestore, Cloud
Bigtable

NoSQL: Indexed Amazon SimpleDB Cloud Firestore
Block Storage Amazon Elastic Block Store Persistent Disk

CRICOS code 00025BCRICOS code 00025B

Amazon Web Service v.s. Google Cloud Platform
Category Service AWS GCP
Big Data &
Analytics Batch Data Processing

Amazon Elastic MapReduce, AWS
Batch

Cloud Dataproc, Cloud
Dataflow

Stream Data Processing Amazon Kinesis Cloud Dataflow

Stream Data Ingest Amazon Kinesis Cloud Pub/Sub
Analytics Amazon Redshift, Amazon Athena BigQuery

Workflow Orchestration Amazon Data Pipeline, AWS Glue Cloud Composer
Application
Services Messaging

Amazon Simple Notification Service,
Amazon Simple Queueing Service Cloud Pub/Sub

Managemen
t Services Monitoring Amazon CloudWatch Stackdriver Monitoring

Logging Amazon CloudWatch Logs Stackdriver Logging

Deployment AWS CloudFormation
Cloud Deployment
Manager

CRICOS code 00025BCRICOS code 00025B

Amazon Web Service v.s. Google Cloud Platform
Category Service AWS GCP
Machine
Learning Speech Amazon Transcribe Cloud Speech-to-Text

Vision Amazon Rekognition Cloud Vision
Natural Language
Processing Amazon Comprehend Cloud Natural Language
Translation Amazon Translate Cloud Translation

Conversational Interface Amazon Lex
Dialogflow Enterprise
Edition

Video Intelligence Amazon Rekognition Video Cloud Video Intelligence
Auto-generated Models N/A Cloud AutoML (beta)

Fully Managed ML Amazon SageMaker
Cloud Machine Learning
Engine

CRICOS code 00025BCRICOS code 00025B

Reading Materials
1. “Cloud computing: concepts, technology & architecture”. Erl, Thomas, Ricardo Puttini, and Zaigham

Mahmood. Pearson Education, 2013.

2. Cynthia Harvey, 5 Things You Should Know About Hybrid Cloud, (https://www.informationweek.com/cloud/5-things-
you-should-know-about-hybrid-cloud/d/d-id/1331818?) InformationWeek, 2018-05-17.

3. Hamdaqa, Mohammad. A Reference model for developing cloud applications
(http://www.stargroup.uwaterloo.ca/~mhamdaqa/publications/A%20REFERENCEMODELFORDEVELOPINGCLOU
D%20APPLICATIONS.pdf)

4. Amazon EC2 (http://aws.amazon.com/ec2/)

https://www.informationweek.com/cloud/5-things-you-should-know-about-hybrid-cloud/d/d-id/1331818
http://www.stargroup.uwaterloo.ca/~mhamdaqa/publications/A%20REFERENCEMODELFORDEVELOPINGCLOUD%20APPLICATIONS.pdf
http://aws.amazon.com/ec2/

CRICOS code 00025BCRICOS code 00025B

Summary
• Cloud Delivery Models: SaaS, PaaS, and IaaS
• Cloud Deploy Models: Public/Private/Community/Hybrid Cloud
• Cloud-Enabling Technologies

– Broadband Networks and Internet Architecture
– Virtualisation Technology (VT)
– Data Centre Technology
– Web Technology
– Multitenant Technology

• Goals and Benefits
• Risks and Challenges
• Cloud-based Applications in the World

CRICOS code 00025BCRICOS code 00025B

Tutorial & Practical for Week 2
Tutorial 1 (Week 2)
1. What is the NIST (National Institute of Standards and Technology) definition of Cloud Computing?

2. What are the six essential characteristics of Cloud Computing? Moreover, for each characteristic, please
make a brief introduction.

3. What are the four deployment models in cloud computing? Please read these reading materials and answer
this question in detail.

4. Discuss the differences between cloud delivery models and make examples of delivery models.

5. Play with GCP Pricing Calculator (https://cloud.google.com/products/calculator) and check how much the
standard machine n1-standard-2 (no SSD, no static and no public IP address, running 24*7) costs you per
month? Discuss how you can save credit on top of that VM specs.

Practical 1 (Week 2)
1. Redeem credit on GCP and install a VM on GCP
2. Install Web server on VM.
3. Linux Prac I

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