Data replication and synchronization tool

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Pradeeban Kathiravelu, Ph.D.

Draft Presentation on Data Replication and Synchronization Tool.. Introduction and Motivation Slides are yet to be included.. ;)

Ingénierie Technologie Business

Powerpoint Templates 1Powerpoint Templates
Data Replication and
Synchronization Tool
Ashish Sharma
Pradeeban Kathiravelu

Powerpoint Templates 2
Introduction

Powerpoint Templates 3
Motivation

Powerpoint Templates 4
Solution Architecture
• Users create, share, and update
replica sets from a data source.
• Infinispan In-Memory Data Grid
(version 6.0.2) to store the replica
sets.
Fig 1. Deployment Architecture

Powerpoint Templates 5
Execution Flow
• Publisher-Consumer API to consume
the replica sets and Data Provider API
to communicate with the data
source.
Fig 2. Execution Flow

Powerpoint Templates 6
Design
• DataProSpecs API
– createReplicaSet
– updateReplicaSet
– duplicateReplicaSet
– deleteReplicaSet
Fig 3. Back-end Class Hierarchy

Powerpoint Templates 7
Extensibility
• Not tightly coupled to the technology.
– Other data-grids
• Hazelcast, Terracotta Big
Memory, Oracle Coherence
– Persistence
• Integration to SQL or NoSQL
solutions such as Mongo DB.
– Data sources other than TCIA.

Powerpoint Templates 8
What Infinispan offers?
• High Performance and Scalability.
• Fault-tolerance
– Multiple nodes with TCP-IP or
Multicast based JGroups clustering
configurations.
• Distributed Execution.
– Optimized for single node as a local
cache as well as a multiple-node
execution.
• MapReduce Framework.

Powerpoint Templates 9
What Infinispan offers?
• High Performance and Scalable.
• Fault-tolerant
– Multiple nodes with TCP-IP or
Multicast based JGroups clustering
configurations.
• Distributed Execution.
– Optimized for single node as a local
cache as well as a multiple-node
execution.
• MapReduce Framework.
Thank you!

Powerpoint Templates 10
What Infinispan offers?
• High Performance and Scalable.
• Fault-tolerant
– Multiple nodes with TCP-IP or
Multicast based JGroups clustering
configurations.
• Distributed Execution.
– Optimized for single node as a local
cache as well as a multiple-node
execution.
• MapReduce Framework.
Thank you!

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Pradeeban Kathiravelu, Ph.D.

Services that access or process a large volume of data are known as data services. Big data frameworks consist of diverse storage media and heterogeneous data formats. Through their service-based approach, data services offer a standardized execution model to big data frameworks. Software-Defined Networking (SDN) increases the programmability of the network, by unifying the control plane centrally, away from the distributed data plane devices. In this paper, we present Software-Defined Data Services (SDDS), extending the data services with the SDN paradigm. SDDS consists of two aspects. First, it models the big data executions as data services or big services composed of several data services. Then, it orchestrates the services centrally in an interoperable manner, by logically separating the executions from the storage. We present the design of an SDDS orchestration framework for network-aware big data executions in data centers. We then evaluate the performance of SDDS through microbenchmarks on a prototype implementation. By extending SDN beyond data centers, we can deploy SDDS in broader execution environments. https://kkpradeeban.blogspot.com/2018/04/software-defined-data-services.html

Software-Defined Data Services: Interoperable and Network-Aware Big Data Exec...

Software-Defined Data Services: Interoperable and Network-Aware Big Data Exec...

Software-Defined Data Services: Interoperable and Network-Aware Big Data Exec...

Pradeeban Kathiravelu, Ph.D.

On-Demand Service-Based Big Data Integration: Optimized for Research Collabor...

On-Demand Service-Based Big Data Integration: Optimized for Research Collabor...

On-Demand Service-Based Big Data Integration: Optimized for Research Collabor...

Pradeeban Kathiravelu, Ph.D.

Scalability and Resilience of Multi-Tenant Distributed Clouds in the Big Serv...

Scalability and Resilience of Multi-Tenant Distributed Clouds in the Big Serv...

Scalability and Resilience of Multi-Tenant Distributed Clouds in the Big Serv...

Pradeeban Kathiravelu, Ph.D.

Software-Defined Inter-Cloud Composition of Big Services

Software-Defined Inter-Cloud Composition of Big Services

Software-Defined Inter-Cloud Composition of Big Services

Pradeeban Kathiravelu, Ph.D.

Scalability and Resilience of Multi-Tenant Distributed Clouds in the Big Serv...

Scalability and Resilience of Multi-Tenant Distributed Clouds in the Big Serv...

Scalability and Resilience of Multi-Tenant Distributed Clouds in the Big Serv...

Pradeeban Kathiravelu, Ph.D.

Plus de Pradeeban Kathiravelu, Ph.D. (20)

Google Summer of Code_2023.pdf

Google Summer of Code_2023.pdf

Google Summer of Code_2023.pdf

Google Summer of Code (GSoC) 2022

Google Summer of Code (GSoC) 2022

Google Summer of Code (GSoC) 2022

Google Summer of Code (GSoC) 2022

Google Summer of Code (GSoC) 2022

Google Summer of Code (GSoC) 2022

Niffler: A DICOM Framework for Machine Learning and Processing Pipelines.

Niffler: A DICOM Framework for Machine Learning and Processing Pipelines.

Niffler: A DICOM Framework for Machine Learning and Processing Pipelines.

Google summer of code (GSoC) 2021

Google summer of code (GSoC) 2021

Google summer of code (GSoC) 2021

A DICOM Framework for Machine Learning Pipelines against Real-Time Radiology ...

A DICOM Framework for Machine Learning Pipelines against Real-Time Radiology ...

A DICOM Framework for Machine Learning Pipelines against Real-Time Radiology ...

Google Summer of Code (GSoC) 2020 for mentors

Google Summer of Code (GSoC) 2020 for mentors

Google Summer of Code (GSoC) 2020 for mentors

Google Summer of Code (GSoC) 2020

Google Summer of Code (GSoC) 2020

Google Summer of Code (GSoC) 2020

Data Services with Bindaas: RESTful Interfaces for Diverse Data Sources

Data Services with Bindaas: RESTful Interfaces for Diverse Data Sources

Data Services with Bindaas: RESTful Interfaces for Diverse Data Sources

The UCLouvain Public Defense of my EMJD-DC Double Doctorate Ph.D. degree

The UCLouvain Public Defense of my EMJD-DC Double Doctorate Ph.D. degree

The UCLouvain Public Defense of my EMJD-DC Double Doctorate Ph.D. degree

My Ph.D. Defense - Software-Defined Systems for Network-Aware Service Compos...

My Ph.D. Defense - Software-Defined Systems for Network-Aware Service Compos...

My Ph.D. Defense - Software-Defined Systems for Network-Aware Service Compos...

My Ph.D. Defense - Software-Defined Systems for Network-Aware Service Composi...

My Ph.D. Defense - Software-Defined Systems for Network-Aware Service Composi...

My Ph.D. Defense - Software-Defined Systems for Network-Aware Service Composi...

UCL Ph.D. Confirmation 2018

UCL Ph.D. Confirmation 2018

UCL Ph.D. Confirmation 2018

Software-Defined Systems for Network-Aware Service Composition and Workflow P...

Software-Defined Systems for Network-Aware Service Composition and Workflow P...

Software-Defined Systems for Network-Aware Service Composition and Workflow P...

Moving bits with a fleet of shared virtual routers

Moving bits with a fleet of shared virtual routers

Moving bits with a fleet of shared virtual routers

Software-Defined Data Services: Interoperable and Network-Aware Big Data Exec...

Software-Defined Data Services: Interoperable and Network-Aware Big Data Exec...

Software-Defined Data Services: Interoperable and Network-Aware Big Data Exec...

On-Demand Service-Based Big Data Integration: Optimized for Research Collabor...

On-Demand Service-Based Big Data Integration: Optimized for Research Collabor...

On-Demand Service-Based Big Data Integration: Optimized for Research Collabor...

Scalability and Resilience of Multi-Tenant Distributed Clouds in the Big Serv...

Scalability and Resilience of Multi-Tenant Distributed Clouds in the Big Serv...

Scalability and Resilience of Multi-Tenant Distributed Clouds in the Big Serv...

Software-Defined Inter-Cloud Composition of Big Services

Software-Defined Inter-Cloud Composition of Big Services

Software-Defined Inter-Cloud Composition of Big Services

Scalability and Resilience of Multi-Tenant Distributed Clouds in the Big Serv...

Scalability and Resilience of Multi-Tenant Distributed Clouds in the Big Serv...

Scalability and Resilience of Multi-Tenant Distributed Clouds in the Big Serv...

Dernier

A Study of Urban Area Plan for Pabna Municipality

A Study of Urban Area Plan for Pabna Municipality

A Study of Urban Area Plan for Pabna Municipality

Morshed Ahmed Rahath

Work-Permit-Receiver-in-Saudi-Aramco.pptx

Work-Permit-Receiver-in-Saudi-Aramco.pptx

Work-Permit-Receiver-in-Saudi-Aramco.pptx

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Thermal Engineering-R & A / C - unit - V

Thermal Engineering-R & A / C - unit - V

Thermal Engineering-R & A / C - unit - V

DineshKumar4165

KubeKraft presentation @CloudNativeHooghly

KubeKraft presentation @CloudNativeHooghly

KubeKraft presentation @CloudNativeHooghly

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Generative AI or GenAI technology based PPT

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UNIT - IV - Air Compressors and its Performance

UNIT - IV - Air Compressors and its Performance

UNIT - IV - Air Compressors and its Performance

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Integrated Test Rig For HTFE-25 - Neometrix

Integrated Test Rig For HTFE-25 - Neometrix

Integrated Test Rig For HTFE-25 - Neometrix

Neometrix_Engineering_Pvt_Ltd

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notes on Evolution Of Analytic Scalability.ppt

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ONLINE FOOD ORDER SYSTEM PROJECT REPORT.pdf

ONLINE FOOD ORDER SYSTEM PROJECT REPORT.pdf

ONLINE FOOD ORDER SYSTEM PROJECT REPORT.pdf

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COST-EFFETIVE and Energy Efficient BUILDINGS ptx

COST-EFFETIVE and Energy Efficient BUILDINGS ptx

COST-EFFETIVE and Energy Efficient BUILDINGS ptx

JIT KUMAR GUPTA

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Employee leave management system project.

Employee leave management system project.

Employee leave management system project.

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A Study of Urban Area Plan for Pabna Municipality

A Study of Urban Area Plan for Pabna Municipality

A Study of Urban Area Plan for Pabna Municipality

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Work-Permit-Receiver-in-Saudi-Aramco.pptx

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Thermal Engineering-R & A / C - unit - V

Thermal Engineering-R & A / C - unit - V

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KubeKraft presentation @CloudNativeHooghly

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Generative AI or GenAI technology based PPT

Generative AI or GenAI technology based PPT

UNIT - IV - Air Compressors and its Performance

UNIT - IV - Air Compressors and its Performance

UNIT - IV - Air Compressors and its Performance

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notes on Evolution Of Analytic Scalability.ppt

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ONLINE FOOD ORDER SYSTEM PROJECT REPORT.pdf

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Data replication and synchronization tool

1. Powerpoint Templates 1Powerpoint Templates Data Replication and Synchronization Tool Ashish Sharma Pradeeban Kathiravelu

2. Powerpoint Templates 2 Introduction

3. Powerpoint Templates 3 Motivation

4. Powerpoint Templates 4 Solution Architecture • Users create, share, and update replica sets from a data source. • Infinispan In-Memory Data Grid (version 6.0.2) to store the replica sets. Fig 1. Deployment Architecture

5. Powerpoint Templates 5 Execution Flow • Publisher-Consumer API to consume the replica sets and Data Provider API to communicate with the data source. Fig 2. Execution Flow

6. Powerpoint Templates 6 Design • DataProSpecs API – createReplicaSet – updateReplicaSet – duplicateReplicaSet – deleteReplicaSet Fig 3. Back-end Class Hierarchy

7. Powerpoint Templates 7 Extensibility • Not tightly coupled to the technology. – Other data-grids • Hazelcast, Terracotta Big Memory, Oracle Coherence – Persistence • Integration to SQL or NoSQL solutions such as Mongo DB. – Data sources other than TCIA.

8. Powerpoint Templates 8 What Infinispan offers? • High Performance and Scalability. • Fault-tolerance – Multiple nodes with TCP-IP or Multicast based JGroups clustering configurations. • Distributed Execution. – Optimized for single node as a local cache as well as a multiple-node execution. • MapReduce Framework.

9. Powerpoint Templates 9 What Infinispan offers? • High Performance and Scalable. • Fault-tolerant – Multiple nodes with TCP-IP or Multicast based JGroups clustering configurations. • Distributed Execution. – Optimized for single node as a local cache as well as a multiple-node execution. • MapReduce Framework. Thank you!

10. Powerpoint Templates 10 What Infinispan offers? • High Performance and Scalable. • Fault-tolerant – Multiple nodes with TCP-IP or Multicast based JGroups clustering configurations. • Distributed Execution. – Optimized for single node as a local cache as well as a multiple-node execution. • MapReduce Framework. Thank you!