This document provides an overview of Aneka, an open-source platform for building and managing distributed applications in multi-cloud environments. It describes Aneka's architecture, application development process using its SDK, and supported programming models including task, thread, MapReduce, and parameter sweeping. Features of Aneka allow users to build, accelerate, and manage applications across different runtime environments like PC grids, clusters, multicore processors, and public/private clouds. Current and example applications using Aneka include scientific, commercial, educational projects. Ongoing research with Aneka focuses on areas like cooperative scheduling, virtual execution environments, and quality of service.

1. CASE STUDY OF
ANEKA
Prepared By
Ronak Ahir Enrolment No : 140870702501
Lekha Chauhan Enrolment No : 140870702502
Ankit Mulani Enrolment No : 140870702504

2. OUTLINES
 Introduction
 Aneka Architecture
 Application Development
 Application Programming Models
 Features of Aneka
 Applications
 Projects

3. INTRODUCTION
ANEKA is one type of SOA that is used to build, accelerate
and manage distributed applications with the help of .NET
framework
It is a software that works on RAD (Rapid Application
Development) environment
Languages :
 C#, C++, VB, Delphi, Java…
 … and 20 more languages
Platforms :
 Windows XP/2000/2003
 Linux & Mac OS X

4. CONT.
WHY ANEKA IS AVAILABLE ONLY IN PaaS LAYER?
ANEKA is available at PaaS in cloud environment It means that
it provides programming application programming interfaces
(API’s) for developing distributed applications and virtual
execution environment in which the applications developed as
per API can be made to run

5. ARCHITECTURE OF ANEKA

6. APPLICATION DEVELOPMENT
Aneka Provides Software Development Kit (SDK) for
Developer
A Collection of tutorials explain how to develop Applications in Aneka
A Collection of class libraries constituting the Aneka Application Model

7. APPLICATION PROGRAMMING
MODELS
Task Programming Model
Thread Programming Model
MapReduce Programming Model
Parameter Sweeping Model

8. TASK PROGRAMMING
MODEL
It works on independent tasks only. The model is collection of
execution unit that is independent of others
Operations : Submit and Forget
Compatibility : User API includes Interface and Grid Task.
Interface executes only one operation. Grid Task is used for
remote hosts. Middleware deals with task scheduling services
and execution services
Application Manager : Build Task Based Apps

9. THREAD PROGRAMMING
MODEL
A Thread is Basic Execution Unit of System
Operations : Start, Stop, State Query and Join
Features : Provides Resources Easily in Distributed Networks and Multi-
Threaded Applications
Compatibility : User API includes Grid Thread class for execution of remote
hosts. Middleware deals with thread scheduling services and maintains
schedule of objects created of Grid Thread class
Application Manager : Build Thread Based Apps

10. MAPREDUCE
PROGRAMMING MODEL
The concept is defined as transforming initial values into list with its
final values. It is called Mapping
Reduction means using final value of list along with its source and
reduces it to shorter term with new value of list
Operations : Map (map ::( key1, value1)= list (key2, value 2) Reduce
(reduce: (key2, list value 2) = list (value 3)
Compatibility : Distributed applications User API include Mapper
and Reducer
Application Manager : Build Map Reduce Based Apps

11. PARAMETER SWEEPING
MODEL
Uses concept of task programming model. It is different from
task model in such a way that all tasks are homogenous as they
are subjected to different parameters and all combinations of
values are checked out to generate task instance
Operations : Parallelism
Compatibility : Legacy applications User API deals with micro
tasks like copy, delete and execute to compose interface.
Application Manager : Build Task Based Apps

12. COMPARISON
 Task and Thread Models are Task-Based
 The user Defines the Tasks that will be Executed
 The user Submits the Task to the Middleware
 MapReduce Model is Function-Based
 The user Defines the Functions Operating on the Data
 The user Configures the Middleware with Functions
 The user Provides the Data

13. FEATURES OF ANEKA

14. BUILD
 Build Different types of Run-time Environments
PC Grids (Enterprise Grids)
Clusters (Data Centers)
Multicore Processors (A Multi-core Processor is a Single Computing
Component with Two or more Independent actual Processing Units)
Public and/or Private Networks
Virtual Machines

15. ACCELERATE
 Aneka Accelerate Development and Deployment
 Aneka uses physical machines as much as possible to
achieve maximum utilization in local environment
 As Demand Increases, Aneka Provides VMs via Private
Clouds (VMWare) or Public Clouds
 Aneka Scheduler allows you to run multiple applications
on same Run-time environment either Concurrently or in a
Queue Arrangement

16. MANAGE
 Aneka Management Includes Following to Set-
up, Monitor, Manage and Maintain Remote and
Global Aneka Compute Clouds
 Graphical User Interface (GUI)
 Application Program Interface (API)
 Aneka Manages Priorities and Scalability Based
on SLA (Service Level Agreement) / QoS
(Quality of Service)

17. APPLICATIONS
 Current Applications
 Scientific
 Distributed Evolutionary Computation
 Proteine Structure Prediction
 Commercial
 Engineering : Go Front (China): Train Models Rendering
 Media and games : Platform for On-line Gaming
 Financial : Risk Analysis
 Office Automation: Excel Integration
 Educational
 Image Filtering
 Image Rendering
 Distributed Systems Teaching

18. PROJECTS
 Research
 Cooperative Scheduling
 Virtual Execution Environment
 Advanced Quality of Service
 Resource Pricing
 Cloud shift (happens)
 Development
 Programming and Deployment Models
 Dataflow
 MPI
 Workflow implementation
 Platform Porting

19. THANK YOU

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