cloud computing: trends and challenges
TRANSCRIPT
OutlineFirst a brief introCloud Definition
Cloud Computing MarketBig Data on Cloud Computing
Cloud Computing: Trends and Challenges
Cesar Diaz. PhD
November 26, 2015
Cesar Diaz. PhD Cloud Computing: Trends and Challenges 1/23
OutlineFirst a brief introCloud Definition
Cloud Computing MarketBig Data on Cloud Computing
First a brief intro
Cloud DefinitionCloud Computing DefinitionCloud Service Model
Cloud Abstraction Layers
Cloud Deployment ModelsMajors actors in Cloud Computing
Interactions between the Actors in Cloud Computing
Cloud Computing Market
Big Data on Cloud ComputingData management and supporting architecturesModel development and scoringChallenges in Big DataChallenges in IoT
Cesar Diaz. PhD Cloud Computing: Trends and Challenges 2/23
OutlineFirst a brief introCloud Definition
Cloud Computing MarketBig Data on Cloud Computing
Want milk with your breakfast?1
I Buy a Cow.I Big upfront cost.
I Produces more (or less)milk than you need.
I Uses up resources.I Time spent
“maintaining it”I Unpleasant waste
product.
I Buy bottled milk.
I Continued cost.I Buy what you need.I Less resource intensive.I no maintenance.I Waste somebody else’s
problems.
1taken from Prof. Daniel Abadi presentation, Yale University.Cesar Diaz. PhD Cloud Computing: Trends and Challenges 3/23
OutlineFirst a brief introCloud Definition
Cloud Computing MarketBig Data on Cloud Computing
Want milk with your breakfast?1
I Buy a Cow.I Big upfront cost.I Produces more (or less)
milk than you need.
I Uses up resources.I Time spent
“maintaining it”I Unpleasant waste
product.
I Buy bottled milk.
I Continued cost.I Buy what you need.I Less resource intensive.I no maintenance.I Waste somebody else’s
problems.
1taken from Prof. Daniel Abadi presentation, Yale University.Cesar Diaz. PhD Cloud Computing: Trends and Challenges 3/23
OutlineFirst a brief introCloud Definition
Cloud Computing MarketBig Data on Cloud Computing
Want milk with your breakfast?1
I Buy a Cow.I Big upfront cost.I Produces more (or less)
milk than you need.I Uses up resources.
I Time spent“maintaining it”
I Unpleasant wasteproduct.
I Buy bottled milk.
I Continued cost.I Buy what you need.I Less resource intensive.I no maintenance.I Waste somebody else’s
problems.
1taken from Prof. Daniel Abadi presentation, Yale University.Cesar Diaz. PhD Cloud Computing: Trends and Challenges 3/23
OutlineFirst a brief introCloud Definition
Cloud Computing MarketBig Data on Cloud Computing
Want milk with your breakfast?1
I Buy a Cow.I Big upfront cost.I Produces more (or less)
milk than you need.I Uses up resources.I Time spent
“maintaining it”
I Unpleasant wasteproduct.
I Buy bottled milk.
I Continued cost.I Buy what you need.I Less resource intensive.I no maintenance.I Waste somebody else’s
problems.
1taken from Prof. Daniel Abadi presentation, Yale University.Cesar Diaz. PhD Cloud Computing: Trends and Challenges 3/23
OutlineFirst a brief introCloud Definition
Cloud Computing MarketBig Data on Cloud Computing
Want milk with your breakfast?1
I Buy a Cow.I Big upfront cost.I Produces more (or less)
milk than you need.I Uses up resources.I Time spent
“maintaining it”I Unpleasant waste
product.
I Buy bottled milk.
I Continued cost.I Buy what you need.I Less resource intensive.I no maintenance.I Waste somebody else’s
problems.
1taken from Prof. Daniel Abadi presentation, Yale University.Cesar Diaz. PhD Cloud Computing: Trends and Challenges 3/23
OutlineFirst a brief introCloud Definition
Cloud Computing MarketBig Data on Cloud Computing
Want milk with your breakfast?1
I Buy a Cow.I Big upfront cost.I Produces more (or less)
milk than you need.I Uses up resources.I Time spent
“maintaining it”I Unpleasant waste
product.
I Buy bottled milk.I Continued cost.
I Buy what you need.I Less resource intensive.I no maintenance.I Waste somebody else’s
problems.
1taken from Prof. Daniel Abadi presentation, Yale University.Cesar Diaz. PhD Cloud Computing: Trends and Challenges 3/23
OutlineFirst a brief introCloud Definition
Cloud Computing MarketBig Data on Cloud Computing
Want milk with your breakfast?1
I Buy a Cow.I Big upfront cost.I Produces more (or less)
milk than you need.I Uses up resources.I Time spent
“maintaining it”I Unpleasant waste
product.
I Buy bottled milk.I Continued cost.I Buy what you need.
I Less resource intensive.I no maintenance.I Waste somebody else’s
problems.
1taken from Prof. Daniel Abadi presentation, Yale University.Cesar Diaz. PhD Cloud Computing: Trends and Challenges 3/23
OutlineFirst a brief introCloud Definition
Cloud Computing MarketBig Data on Cloud Computing
Want milk with your breakfast?1
I Buy a Cow.I Big upfront cost.I Produces more (or less)
milk than you need.I Uses up resources.I Time spent
“maintaining it”I Unpleasant waste
product.
I Buy bottled milk.I Continued cost.I Buy what you need.I Less resource intensive.
I no maintenance.I Waste somebody else’s
problems.
1taken from Prof. Daniel Abadi presentation, Yale University.Cesar Diaz. PhD Cloud Computing: Trends and Challenges 3/23
OutlineFirst a brief introCloud Definition
Cloud Computing MarketBig Data on Cloud Computing
Want milk with your breakfast?1
I Buy a Cow.I Big upfront cost.I Produces more (or less)
milk than you need.I Uses up resources.I Time spent
“maintaining it”I Unpleasant waste
product.
I Buy bottled milk.I Continued cost.I Buy what you need.I Less resource intensive.I no maintenance.
I Waste somebody else’sproblems.
1taken from Prof. Daniel Abadi presentation, Yale University.Cesar Diaz. PhD Cloud Computing: Trends and Challenges 3/23
OutlineFirst a brief introCloud Definition
Cloud Computing MarketBig Data on Cloud Computing
Want milk with your breakfast?1
I Buy a Cow.I Big upfront cost.I Produces more (or less)
milk than you need.I Uses up resources.I Time spent
“maintaining it”I Unpleasant waste
product.
I Buy bottled milk.I Continued cost.I Buy what you need.I Less resource intensive.I no maintenance.I Waste somebody else’s
problems.
1taken from Prof. Daniel Abadi presentation, Yale University.Cesar Diaz. PhD Cloud Computing: Trends and Challenges 3/23
OutlineFirst a brief introCloud Definition
Cloud Computing MarketBig Data on Cloud Computing
Your computer is a cow
I Your computerI Big upfront cost.I Produces more (or less) “milk”
than you need.I Uses up resources (electricity).I Time spent maintaining it.I Produces unpleasant
waste (heat, noise)
I What if you could get computingpower even more convenientlythan bottled milk?
Cesar Diaz. PhD Cloud Computing: Trends and Challenges 4/23
OutlineFirst a brief introCloud Definition
Cloud Computing MarketBig Data on Cloud Computing
Cloud computing is Bottled Milk
I Companies willing to rentcomputing resources from theirdata centers.
I Resources include storage,processing cycles, software stacks.
I Google, Microsoft, Amazon, Sun,Hewlett-Packard, Yahoo, EMC,and AT&T all taking part.
I e.g., for $0.10/hour Amazon willgive you:
I 1.7 GB memoryI Equivalent of 1.2 GHz processorI 350GB storage
Cesar Diaz. PhD Cloud Computing: Trends and Challenges 5/23
OutlineFirst a brief introCloud Definition
Cloud Computing MarketBig Data on Cloud Computing
Cloud computing concerns
I What if my data or service provider becomes unavailable?
I What if my supplier suddenly increases, how much theycharge me?
I What about security?
I What about lock in?
Cesar Diaz. PhD Cloud Computing: Trends and Challenges 6/23
OutlineFirst a brief introCloud Definition
Cloud Computing MarketBig Data on Cloud Computing
Cloud Computing DefinitionCloud Service ModelCloud Deployment ModelsMajors actors in Cloud Computing
Preliminaries
User%
User%
User%
User%
User%
User%
PC%
PC%
PC%
PC%
PC%
PC%
Terminal%Mainframe%
Server%
Server%
Internet%Server%
Server%
Server%Server%
Cloud%Compu8ng%
Laptop%
1. Mainframe%Compu8ng%
2. PC%Compu8ng%
3. Network%Compu8ng%
4. Internet%Compu8ng%
5. Grid%Compu8ng%
6. Cloud%Compu8ng%
Adapted from Voas and Zhang2, shows six phases of computing
paradigms, from dummy terminals/mainframes, to PCs, networking
computing, to grid and cloud computing.2
Jeffrey Voas and Jia Zhang. Cloud computing: New wine or just a new bottle?, 11(2):1517, March 2009.
Cesar Diaz. PhD Cloud Computing: Trends and Challenges 7/23
OutlineFirst a brief introCloud Definition
Cloud Computing MarketBig Data on Cloud Computing
Cloud Computing DefinitionCloud Service ModelCloud Deployment ModelsMajors actors in Cloud Computing
Cloud Computing Definition
NIST - Visual Model of Cloud Computing Definition3
http://clean-clouds.com/2012/12/07/nist-visual-model-of-cloud-computing-definition/
3“Cloud computing is a model for enabling ubiquitous, convenient, on-demand network access to a shared pool
of configurable computing resources (e.g., networks, servers, storage, applications, and services) that can be rapidlyprovisioned and released with minimal management effort or service provider interaction”
Cesar Diaz. PhD Cloud Computing: Trends and Challenges 8/23
OutlineFirst a brief introCloud Definition
Cloud Computing MarketBig Data on Cloud Computing
Cloud Computing DefinitionCloud Service ModelCloud Deployment ModelsMajors actors in Cloud Computing
Software Stack Model
Packaged(So+ware(
Applica2ons(
Data(
Middleware(
O/S(
Virtualiza2on(
Hardware(
Infrastructure((as(a(service)(
Applica2ons(
Data(
Middleware(
O/S(
Virtualiza2on(
Hardware(
PlaCorm((as(a(service)(
Applica2ons(
Data(
Middleware(
O/S(
Virtualiza2on(
Hardware(
So+ware((as(a(service)(
Applica2ons(
Data(
Middleware(
O/S(
Virtualiza2on(
Hardware(
You(manage(
You(manage(
You(manage(
Managed((
by(vendor(
Managed(by(vendor(
Managed(by(vendor(
Cesar Diaz. PhD Cloud Computing: Trends and Challenges 9/23
OutlineFirst a brief introCloud Definition
Cloud Computing MarketBig Data on Cloud Computing
Cloud Computing DefinitionCloud Service ModelCloud Deployment ModelsMajors actors in Cloud Computing
Cloud Abstraction Layers
Business'process'
• Business'orchestra0on'
So2ware'SaaS'
• Gmail'• Office365'
Pla=orm'PaaS'
• Google'cloud'• Container'based'approach'
Infrastructure'IaaS'
• Amazon'web'services'• Virtual'machines'
Hardware'HaaS'
• Real'hardware'• Hos0ng'
Cloud'abstrac0on'layers'
Cesar Diaz. PhD Cloud Computing: Trends and Challenges 10/23
OutlineFirst a brief introCloud Definition
Cloud Computing MarketBig Data on Cloud Computing
Cloud Computing DefinitionCloud Service ModelCloud Deployment ModelsMajors actors in Cloud Computing
Cloud Deployment Models
Cesar Diaz. PhD Cloud Computing: Trends and Challenges 11/23
OutlineFirst a brief introCloud Definition
Cloud Computing MarketBig Data on Cloud Computing
Cloud Computing DefinitionCloud Service ModelCloud Deployment ModelsMajors actors in Cloud Computing
Actors in Cloud Computing
Table: Actors in Cloud Computing
Actor DefinitionCloud consumer A person or organization that maintains a business relationship with, and uses service
from, Cloud ProvidersCloud Provider A person, organization or entity responsible for making a service available to interested
parties.Cloud Auditor A party that can conduct independent assessment of cloud services, information system
operations, performance and security of the cloud implementation.Cloud Broker An entity that manages the use, performance and delivery of cloud services, and ne-
gotiates relationship between Cloud providers and Cloud Consumers.Cloud Carrier An intermediary that provides connectivity and transport of cloud from Cloud Providers
to Cloud Consumers.
Cesar Diaz. PhD Cloud Computing: Trends and Challenges 12/23
OutlineFirst a brief introCloud Definition
Cloud Computing MarketBig Data on Cloud Computing
Cloud Computing DefinitionCloud Service ModelCloud Deployment ModelsMajors actors in Cloud Computing
Interactions between the Actors in Cloud Computing
Cloud&Consumer&
Cloud&Broker& Cloud&Provider&
Cloud&Auditor&
The&communica7on&path&between&a&cloud&provider&and&a&cloud&consumer&&The&communica7on&paths&for&a&cloud&auditor&to&collect&audi7ng&informa7on&&The&communica7on&paths&for&a&cloud&broker&to&provide&service&to&a&cloud&consumer&
Cloud&carrier&
Cesar Diaz. PhD Cloud Computing: Trends and Challenges 13/23
OutlineFirst a brief introCloud Definition
Cloud Computing MarketBig Data on Cloud Computing
Cloud Computing Market
Cloud Computing Market: $241 billion in 2020http://www.zdnet.com/blog/btl/cloud-computing-market-241-billion-in-2020/47702
Cesar Diaz. PhD Cloud Computing: Trends and Challenges 14/23
OutlineFirst a brief introCloud Definition
Cloud Computing MarketBig Data on Cloud Computing
Data management and supporting architecturesModel development and scoringChallenges in Big DataChallenges in IoT
Big Data on Cloud Computing
I Previous work has focused on issues such as data formats,data representation, storage, access, privacy, and data quality.
I Now focus on Cloud Analytics, that concern datamanagement, integration and processing. Analytics as aService.
I Environments for carrying out analytics on Clouds for BigData applications.
I Data management andsupporting architectures.
I Model development andscoring.
I Visualization and userinteraction.
I Business models.
I Based on the traditional analytics workflow.
Cesar Diaz. PhD Cloud Computing: Trends and Challenges 15/23
OutlineFirst a brief introCloud Definition
Cloud Computing MarketBig Data on Cloud Computing
Data management and supporting architecturesModel development and scoringChallenges in Big DataChallenges in IoT
Big Data on Cloud Computing
I Previous work has focused on issues such as data formats,data representation, storage, access, privacy, and data quality.
I Now focus on Cloud Analytics, that concern datamanagement, integration and processing. Analytics as aService.
I Environments for carrying out analytics on Clouds for BigData applications.
I Data management andsupporting architectures.
I Model development andscoring.
I Visualization and userinteraction.
I Business models.
I Based on the traditional analytics workflow.
Cesar Diaz. PhD Cloud Computing: Trends and Challenges 15/23
OutlineFirst a brief introCloud Definition
Cloud Computing MarketBig Data on Cloud Computing
Data management and supporting architecturesModel development and scoringChallenges in Big DataChallenges in IoT
Big Data on Cloud Computing
I Previous work has focused on issues such as data formats,data representation, storage, access, privacy, and data quality.
I Now focus on Cloud Analytics, that concern datamanagement, integration and processing. Analytics as aService.
I Environments for carrying out analytics on Clouds for BigData applications.
I Data management andsupporting architectures.
I Model development andscoring.
I Visualization and userinteraction.
I Business models.
I Based on the traditional analytics workflow.
Cesar Diaz. PhD Cloud Computing: Trends and Challenges 15/23
OutlineFirst a brief introCloud Definition
Cloud Computing MarketBig Data on Cloud Computing
Data management and supporting architecturesModel development and scoringChallenges in Big DataChallenges in IoT
Big Data on Cloud Computing
I Previous work has focused on issues such as data formats,data representation, storage, access, privacy, and data quality.
I Now focus on Cloud Analytics, that concern datamanagement, integration and processing. Analytics as aService.
I Environments for carrying out analytics on Clouds for BigData applications.
I Data management andsupporting architectures.
I Model development andscoring.
I Visualization and userinteraction.
I Business models.
I Based on the traditional analytics workflow.
Cesar Diaz. PhD Cloud Computing: Trends and Challenges 15/23
OutlineFirst a brief introCloud Definition
Cloud Computing MarketBig Data on Cloud Computing
Data management and supporting architecturesModel development and scoringChallenges in Big DataChallenges in IoT
Big Data on Cloud Computing
I Previous work has focused on issues such as data formats,data representation, storage, access, privacy, and data quality.
I Now focus on Cloud Analytics, that concern datamanagement, integration and processing. Analytics as aService.
I Environments for carrying out analytics on Clouds for BigData applications.
I Data management andsupporting architectures.
I Model development andscoring.
I Visualization and userinteraction.
I Business models.
I Based on the traditional analytics workflow.
Cesar Diaz. PhD Cloud Computing: Trends and Challenges 15/23
OutlineFirst a brief introCloud Definition
Cloud Computing MarketBig Data on Cloud Computing
Data management and supporting architecturesModel development and scoringChallenges in Big DataChallenges in IoT
Big Data on Cloud Computing
I Previous work has focused on issues such as data formats,data representation, storage, access, privacy, and data quality.
I Now focus on Cloud Analytics, that concern datamanagement, integration and processing. Analytics as aService.
I Environments for carrying out analytics on Clouds for BigData applications.
I Data management andsupporting architectures.
I Model development andscoring.
I Visualization and userinteraction.
I Business models.
I Based on the traditional analytics workflow.
Cesar Diaz. PhD Cloud Computing: Trends and Challenges 15/23
OutlineFirst a brief introCloud Definition
Cloud Computing MarketBig Data on Cloud Computing
Data management and supporting architecturesModel development and scoringChallenges in Big DataChallenges in IoT
Big Data on Cloud Computing
I Previous work has focused on issues such as data formats,data representation, storage, access, privacy, and data quality.
I Now focus on Cloud Analytics, that concern datamanagement, integration and processing. Analytics as aService.
I Environments for carrying out analytics on Clouds for BigData applications.
I Data management andsupporting architectures.
I Model development andscoring.
I Visualization and userinteraction.
I Business models.
I Based on the traditional analytics workflow.
Cesar Diaz. PhD Cloud Computing: Trends and Challenges 15/23
OutlineFirst a brief introCloud Definition
Cloud Computing MarketBig Data on Cloud Computing
Data management and supporting architecturesModel development and scoringChallenges in Big DataChallenges in IoT
Big Data on Cloud Computing
I Previous work has focused on issues such as data formats,data representation, storage, access, privacy, and data quality.
I Now focus on Cloud Analytics, that concern datamanagement, integration and processing. Analytics as aService.
I Environments for carrying out analytics on Clouds for BigData applications.
I Data management andsupporting architectures.
I Model development andscoring.
I Visualization and userinteraction.
I Business models.
I Based on the traditional analytics workflow.
Cesar Diaz. PhD Cloud Computing: Trends and Challenges 15/23
OutlineFirst a brief introCloud Definition
Cloud Computing MarketBig Data on Cloud Computing
Data management and supporting architecturesModel development and scoringChallenges in Big DataChallenges in IoT
Overview of the analytics workflow for Big Data 4
4taken from MD Assuncao, et al., Big Data computing and clouds: Trendsand future directions, J. Parallel Distrib. Comput. (2014)
Cesar Diaz. PhD Cloud Computing: Trends and Challenges 16/23
OutlineFirst a brief introCloud Definition
Cloud Computing MarketBig Data on Cloud Computing
Data management and supporting architecturesModel development and scoringChallenges in Big DataChallenges in IoT
Data management and supporting architectures
Preparation of data for analysis.Some ‘Vs’ of Big Data
I Variety: Data TypesI Structured: Formal
scheme and datamodels.
I Unstructured: Nopredefined data model.
I Semi-structured:Lacks strict data modelstructure.
I Mixed: Various typetogether
I Velocity: Data productionand processing speed.Speed of arrival andprocessing.
I Batch: at timeintervals.
I Near-time: at smalltimes intervals.
I Real-time: Continuosinput, process, output.
I Streams: Data flows
Cesar Diaz. PhD Cloud Computing: Trends and Challenges 17/23
OutlineFirst a brief introCloud Definition
Cloud Computing MarketBig Data on Cloud Computing
Data management and supporting architecturesModel development and scoringChallenges in Big DataChallenges in IoT
Data management and supporting architectures
Preparation of data for analysis.Some ‘Vs’ of Big Data
I Variety: Data TypesI Structured: Formal
scheme and datamodels.
I Unstructured: Nopredefined data model.
I Semi-structured:Lacks strict data modelstructure.
I Mixed: Various typetogether
I Velocity: Data productionand processing speed.Speed of arrival andprocessing.
I Batch: at timeintervals.
I Near-time: at smalltimes intervals.
I Real-time: Continuosinput, process, output.
I Streams: Data flows
Cesar Diaz. PhD Cloud Computing: Trends and Challenges 17/23
OutlineFirst a brief introCloud Definition
Cloud Computing MarketBig Data on Cloud Computing
Data management and supporting architecturesModel development and scoringChallenges in Big DataChallenges in IoT
Data management and supporting architectures
Some ‘Vs’ of Big Data
I Volume: Data size.I Google File System
(GFS).I Amazon Simple Storage
Service (S3).I Nirvanix Cloud Storage.I OpenStack Swift.I Windows Azure Binary
Large Object (Blob)storage.
I Veracity: Data reliabilityand trust.Data integrations solutions
I Value: Worth derivedfrom exploiting Big Data.
Cesar Diaz. PhD Cloud Computing: Trends and Challenges 18/23
OutlineFirst a brief introCloud Definition
Cloud Computing MarketBig Data on Cloud Computing
Data management and supporting architecturesModel development and scoringChallenges in Big DataChallenges in IoT
Model development and scoring
Use the data to build models that can be utilized for forecasts andprescriptions. Existing work has discussed means to offload suchactivities termed here as model building and scoring to Cloudproviders and ways to parallelize certain machine learningalgorithms.
Work Goal Service model Deployment modelGuazelli et al. Predictive analytics (socring) IaaS Public
Zementis Data analysis and model building SaaS Public or privateGoogle Prediction API Model building SaaS Public
Apache Mahout Data analysis and model building IaaS AnyHazy Model building IaaS Any
Cesar Diaz. PhD Cloud Computing: Trends and Challenges 19/23
OutlineFirst a brief introCloud Definition
Cloud Computing MarketBig Data on Cloud Computing
Data management and supporting architecturesModel development and scoringChallenges in Big DataChallenges in IoT
Model development and scoring
I Google prediction API allows users to create ML models topredict numeric values for a new item based on values ofpreviously submitted training data.
I The Apache Mahout project aims to provide tools to buildscalable machine learning libraries on top of Hadoop using theMapReduce paradigm.
I The Hazy project focuses on identifying and validating twocategories of abstractions in building trained systems, namelyprogramming abstractions and infrastructure abstractions.
Cesar Diaz. PhD Cloud Computing: Trends and Challenges 20/23
OutlineFirst a brief introCloud Definition
Cloud Computing MarketBig Data on Cloud Computing
Data management and supporting architecturesModel development and scoringChallenges in Big DataChallenges in IoT
Model development and scoring
I Google prediction API allows users to create ML models topredict numeric values for a new item based on values ofpreviously submitted training data.
I The Apache Mahout project aims to provide tools to buildscalable machine learning libraries on top of Hadoop using theMapReduce paradigm.
I The Hazy project focuses on identifying and validating twocategories of abstractions in building trained systems, namelyprogramming abstractions and infrastructure abstractions.
Cesar Diaz. PhD Cloud Computing: Trends and Challenges 20/23
OutlineFirst a brief introCloud Definition
Cloud Computing MarketBig Data on Cloud Computing
Data management and supporting architecturesModel development and scoringChallenges in Big DataChallenges in IoT
Model development and scoring
I Google prediction API allows users to create ML models topredict numeric values for a new item based on values ofpreviously submitted training data.
I The Apache Mahout project aims to provide tools to buildscalable machine learning libraries on top of Hadoop using theMapReduce paradigm.
I The Hazy project focuses on identifying and validating twocategories of abstractions in building trained systems, namelyprogramming abstractions and infrastructure abstractions.
Cesar Diaz. PhD Cloud Computing: Trends and Challenges 20/23
OutlineFirst a brief introCloud Definition
Cloud Computing MarketBig Data on Cloud Computing
Data management and supporting architecturesModel development and scoringChallenges in Big DataChallenges in IoT
Sumarize
I Data Management: Performing analytics on large volumes ofdata requires efficient methods to store, filter, transform, andretrieve the data.
I Model Development and Scoring: build models that can beutilized for forecasts and prescriptions.
I Visualization and user interaction: The type of visualizationmay need to be selected according to the amount of data tobe displayed, to improve both displaying and performance.
I Business Models: providing tools that customers can use tobuild their Big Data analytics solutions on the Cloud, modelsfor delivering analytics capabilities as services on a Cloud.
Cesar Diaz. PhD Cloud Computing: Trends and Challenges 21/23
OutlineFirst a brief introCloud Definition
Cloud Computing MarketBig Data on Cloud Computing
Data management and supporting architecturesModel development and scoringChallenges in Big DataChallenges in IoT
Sumarize
I Data Management: Performing analytics on large volumes ofdata requires efficient methods to store, filter, transform, andretrieve the data.
I Model Development and Scoring: build models that can beutilized for forecasts and prescriptions.
I Visualization and user interaction: The type of visualizationmay need to be selected according to the amount of data tobe displayed, to improve both displaying and performance.
I Business Models: providing tools that customers can use tobuild their Big Data analytics solutions on the Cloud, modelsfor delivering analytics capabilities as services on a Cloud.
Cesar Diaz. PhD Cloud Computing: Trends and Challenges 21/23
OutlineFirst a brief introCloud Definition
Cloud Computing MarketBig Data on Cloud Computing
Data management and supporting architecturesModel development and scoringChallenges in Big DataChallenges in IoT
Sumarize
I Data Management: Performing analytics on large volumes ofdata requires efficient methods to store, filter, transform, andretrieve the data.
I Model Development and Scoring: build models that can beutilized for forecasts and prescriptions.
I Visualization and user interaction: The type of visualizationmay need to be selected according to the amount of data tobe displayed, to improve both displaying and performance.
I Business Models: providing tools that customers can use tobuild their Big Data analytics solutions on the Cloud, modelsfor delivering analytics capabilities as services on a Cloud.
Cesar Diaz. PhD Cloud Computing: Trends and Challenges 21/23
OutlineFirst a brief introCloud Definition
Cloud Computing MarketBig Data on Cloud Computing
Data management and supporting architecturesModel development and scoringChallenges in Big DataChallenges in IoT
Sumarize
I Data Management: Performing analytics on large volumes ofdata requires efficient methods to store, filter, transform, andretrieve the data.
I Model Development and Scoring: build models that can beutilized for forecasts and prescriptions.
I Visualization and user interaction: The type of visualizationmay need to be selected according to the amount of data tobe displayed, to improve both displaying and performance.
I Business Models: providing tools that customers can use tobuild their Big Data analytics solutions on the Cloud, modelsfor delivering analytics capabilities as services on a Cloud.
Cesar Diaz. PhD Cloud Computing: Trends and Challenges 21/23
OutlineFirst a brief introCloud Definition
Cloud Computing MarketBig Data on Cloud Computing
Data management and supporting architecturesModel development and scoringChallenges in Big DataChallenges in IoT
Challenges in IoT
I Transport.
I Smart Home.
I Smart City.
I Smart Factory.
I Emergency.
I Health Care.
I Lifestyle.
I Agriculture.
I Culture and Tourism.
I User Interaction.
I Environment.
I Energy.
Cesar Diaz. PhD Cloud Computing: Trends and Challenges 22/23
OutlineFirst a brief introCloud Definition
Cloud Computing MarketBig Data on Cloud Computing
Data management and supporting architecturesModel development and scoringChallenges in Big DataChallenges in IoT
Cesar Diaz. PhD Cloud Computing: Trends and Challenges 23/23