five LAYERS:
client (computers, phones, GPS...)
Cloud SaaS D
Cloud PaaS a
Cloud IaaS a
servers S
The term software as a service (SaaS) is considered to be part of the nomenclature of cloud computing, along with infrastructure as a service (IaaS) and platform as a service (PaaS).
Data (MetaData, Web History, Ip server/client...) as a Service (DaaS) is implicit or explicit (in all the layers). Data = water (and metadata about plumbing) and SaaS-PaaS-IaaS-servers = plumbing.
Client and servers: actual life lived by real people and real computers/phones/GPS...
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software (application) as a service (SaaS)
"on-demand software" is a software delivery model
- in which software (and its associated data) are hosted in the Internet cloud
- software and data are accessed by users using a thin client using a web browser.
Gartner: SaaS sales will grow 16.2% to $10.7bn in 2011
Gartner estimates that 75% of the current SaaS delivery revenue could be considered as a cloud service, and that could extend to 90% by 2014.
platform as a service (PaaS)
The consumer does not manage or control the underlying cloud infrastructure including network, servers, operating systems, or storage, but has control over the deployed applications and possibly application hosting environment configurations.
PaaS offerings facilitate deployment of applications without the cost and complexity of buying and managing the underlying hardware and software and provisioning hosting capabilities, providing all of the facilities required to support the complete life cycle of building and delivering web applications and services.
infrastructure as a service (IaaS)
The National Institute of Standards and Technology (NIST) provides a concise and specific definition:
Cloud computing (IaaS) is a model for enabling on-demand network access to a shared pool of configurable computing resources (e.g., networks, servers, storage, and services) that can be rapidly provisioned and released with minimal management effort or service provider interaction.
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The main problem is data migration and interoperability. Another issue is related with the data migration or porting when a user wants to change his cloud provider. There is no defined standard between the operators and such a change is extremely complex. The case of bankruptcy of the company of the cloud provider could be extremely dangerous for the users.
In the NIST document : 6.4.1 Lack of Portability between PaaS Clouds
Portability is a concern for new application development, particularly when platforms require
proprietary languages and run-time environments. Even when standard languages are used,
implementations of platform services may vary widely between providers – for example, one platform’s
file, queue, or hash-table interface may not be compatible with another’s. Subscribers creating new
applications may mitigate portability risks by creating generalized interfaces to platform services instead
of creating specialized implementations for specific platform providers. Such a strategy, however, incurs
costs and also does not entirely mitigate the risks since a general interface that hides provider-specific
variations will likely limit the use of provider-specific value added features, thus resulting in a “lowest
common denominator” for application features.
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Data as a Service (DaaS):
1)the data are stored in three different types :
- BLObs (binary large object), is a collection of binary data stored as a single entity. Blobs are typically images, audio and multimedia objects, though sometimes binary executable code is stored as a blob. BLObs are used for moving large amounts of data from one database to another (the new host for the data) without filters or error correction. It is not the same of binary blob which is a pejorative term for an object file loaded into the kernel without publicly available source code.
- queues, it's a First-In-First-Out (FIFO) data structure (the first element added to the queue will be the first one to be removed). A queue is an example of a linear data structure.
- tables, it's a set of data elements (values) that is organized using a model of vertical columns (which are identified by their name) and horizontal rows (2D table). A table has a specified number of columns, but can have any number of rows. Tables are also a matrice, and could be 3D, 4D...nD.
2)The problem of Data communication.
Seminar on Emerging Trends in Data Communication and Dissemination.
Statistical Data as a Service and Internet Mashups
(data@feb 2010)
by Zoltan Nagy:
What is a Mashup?
A web application that combines data from more than one source into a single integrated tool
An example is the use of data from Google Maps to add location information to statistical data, thereby creating a new and distinct service that was not originally provided by either source.
UNDATA API project (http://www.undata-api.org/): an API version of the great data made available by the United Nations on the UNDATA site. The aim is to make this data accessible and reusable in a variety or ways so it can be easily mashed up and recombined into new applications or analysis.
The service uses a straightforward REST API hosted on Google’s Java AppEngine and makes UNDATA sets easily queryable from any application. Currently we have 62 datasets from the World Health organization on line and we’ll add more over time.
Visualization/mashup:
Thematic Mapping API (http://thematicmapping.org/api/) is a new JavaScript library which allows you to create thematic maps from your own data source. It's OK with google earth not with google maps!
Conclusion:
We need "Interoperability as a service" (In-aaS) in all layers.
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