Big data caching for networking
•
0 likes•197 views
This document discusses moving big data caching from the cloud to the edge using machine learning. It proposes (1) harnessing big data and machine learning to estimate content popularity for proactive caching, (2) implementing a cache-enabled architecture at the edge where devices provide cloud-like computing instead of the cloud, and (3) using a case study analyzing real data traces to show potential backhaul offloading gains.
Report
Share
Report
Share
Download to read offline
Recommended
PhD Projects in Green Cloud Computing Research Guidance
Pertinent Concepts in Green Cloud Computing
Typical Topics in Green Cloud Computing
Foremost Subjects in Green Cloud Computing
Intellegent use of Virtual and Cloud services
Compute power is doubling every 12 to 18 months while dedicated servers are only 10% efficient. Software and storage/network systems are advancing to keep up with more powerful and cheaper computers by becoming more intelligent, quicker, and stable across platforms. Users now expect the same high availability and accessibility at work as with personal services due to expanding demands matching resource supplies.
Grid computing
Grid computing is a distributed computing approach that allows users to access networked computer systems and resources located across different areas. It provides computing resources like processors, storage, and applications to users regardless of where those resources are located, similar to how the electrical power grid provides electricity to users without knowledge of its source. Key benefits of grid computing include solving large-scale problems through parallel processing and optimally utilizing idle computing resources. Security, licensing, and performance monitoring present challenges to grid computing's adoption.
Introduction to Big Data by Manouj Bongirr
Big Logic is a US-based technology consulting and training firm focused on big data analytics using Apache Hadoop. They help enterprises successfully implement big data projects by sharing experiences and empowering clients to decide whether to build or buy solutions. Big data refers to extremely large data sets that are difficult to process using traditional software tools.
A database for the planet - Scot Chain Edinburgh - Nov 11, 2016
Bruce Pon, CEO of BigchainDB talks about a database for the planet and mass adoption. But to reach everyone, it will need scale and the possibility for interoperability with legacy systems.
ieee cloud 2015 keynote talk
this is the deck from my keynote talk at the IEEE Cloud Conference in New York 2015. Survey of cloud architecture, cloud programming and more
Accelerating your research with Microsoft Azure
How cloud computing can accelerate your research. Presentation given at Moscow State University on 19th May 2015.
Apply for Azure for Research Awards at http://research.microsoft.com/en-US/projects/azure/awards.aspx
Big data high performance computing commenting
This document discusses the rise of high performance computing and big data, and how they are transforming science, engineering, and business. It outlines how computational power is enabling new insights from massive data sets across many industries in just seconds rather than days. This requires infrastructure like Intel Xeon Phi coprocessors for parallel processing big data, solid state storage to efficiently capture and store large data volumes, and high speed 10 Gigabit Ethernet networks to rapidly import and share big data across multiple locations for processing.
Recommended
PhD Projects in Green Cloud Computing Research Guidance
Pertinent Concepts in Green Cloud Computing
Typical Topics in Green Cloud Computing
Foremost Subjects in Green Cloud Computing
Intellegent use of Virtual and Cloud services
Compute power is doubling every 12 to 18 months while dedicated servers are only 10% efficient. Software and storage/network systems are advancing to keep up with more powerful and cheaper computers by becoming more intelligent, quicker, and stable across platforms. Users now expect the same high availability and accessibility at work as with personal services due to expanding demands matching resource supplies.
Grid computing
Grid computing is a distributed computing approach that allows users to access networked computer systems and resources located across different areas. It provides computing resources like processors, storage, and applications to users regardless of where those resources are located, similar to how the electrical power grid provides electricity to users without knowledge of its source. Key benefits of grid computing include solving large-scale problems through parallel processing and optimally utilizing idle computing resources. Security, licensing, and performance monitoring present challenges to grid computing's adoption.
Introduction to Big Data by Manouj Bongirr
Big Logic is a US-based technology consulting and training firm focused on big data analytics using Apache Hadoop. They help enterprises successfully implement big data projects by sharing experiences and empowering clients to decide whether to build or buy solutions. Big data refers to extremely large data sets that are difficult to process using traditional software tools.
A database for the planet - Scot Chain Edinburgh - Nov 11, 2016
Bruce Pon, CEO of BigchainDB talks about a database for the planet and mass adoption. But to reach everyone, it will need scale and the possibility for interoperability with legacy systems.
ieee cloud 2015 keynote talk
this is the deck from my keynote talk at the IEEE Cloud Conference in New York 2015. Survey of cloud architecture, cloud programming and more
Accelerating your research with Microsoft Azure
How cloud computing can accelerate your research. Presentation given at Moscow State University on 19th May 2015.
Apply for Azure for Research Awards at http://research.microsoft.com/en-US/projects/azure/awards.aspx
Big data high performance computing commenting
This document discusses the rise of high performance computing and big data, and how they are transforming science, engineering, and business. It outlines how computational power is enabling new insights from massive data sets across many industries in just seconds rather than days. This requires infrastructure like Intel Xeon Phi coprocessors for parallel processing big data, solid state storage to efficiently capture and store large data volumes, and high speed 10 Gigabit Ethernet networks to rapidly import and share big data across multiple locations for processing.
Introducing Generalized Deduplication for Energy-efficient IoT Networks with ...
Abstract: The growing number of Internet of Things (IoT) devices is increasing the network traffic load globally. As a solution to this problem we propose Hermes, a network protocol that leverages the concept of generalized deduplication (GD) to reduce not only the network traffic, but also the energy consumption of devices. GD is a novel technique that maps identical and similar data chunks to a so called basis while applying an error correcting code onto them. The difference between the original data chunk and the basis is encoded in a deviation.
With this poster we motivate the use and purpose of the Hermes protocol. Then we outline the concept of GD and describe the architecture of a Hermes network including the message exchange. Finally, we highlight our micro- and macro-benchmark results on a synthetic data set.
Poster presented by Christian Göttel at the LEGaTO Final Event: 'Low-Energy Heterogeneous Computing Workshop'
Big data
Nandan Shah's presentation covered key topics related to big data including definitions, important technologies like Hadoop and MapReduce, benefits such as enabling real-time analysis and faster decision making, risks around data security and privacy, and applications across various domains such as banking, retail, and healthcare. The presentation also provided interesting facts about the size of data holdings and growth of the big data industry.
Big Data on Public Cloud
Presentation by Dr.Thanachart Numnonda, IMC Institute @Thailand Big Data User Group #2, 13 March 2015
Webinar: Multi-Cloud Monitoring
In this webinar, Phil Dougherty and Gunnar Aasen will show you that it actually can be simple to deploy, manage and scale containerized applications on a mix of any public or private cloud with Containership. And with this varied environment, you gather metrics and events from your apps and microservices and centrally view and manage all components with InfluxData.
BigchainDB: Blockchains for Artificial Intelligence by Trent McConaghy
How can blockchains help AI?
-Decentralized model exchange
-Model audit trail
-AI DAOs
-more
A blockchain caveat or two
Completely new code bases
Reinventing consensus
No sharding = no scaling
No querying // single-node querying
Let’s fix this...
Grid Computing
Grid computing involves linking together distributed computer resources from multiple administrative domains to achieve a common goal. Resources in a grid are heterogeneous and geographically dispersed. A grid differs from a cluster in that it provides a consistent, dependable, and transparent collection of computing resources across wide distances. Grid infrastructure must respect local autonomy, handle heterogeneous hardware, and be resilient and dynamic.
containers2016
This document discusses the growing amount of data from "long tail" science, which is estimated to generate over 1 petabyte of data per year. It also lists various tools for radio astronomy, chemical informatics, galaxies, genomes, machine learning algorithms, and data storage containers. Finally, it shows a graph of the events per second for a distributed computing system using Marathon, Mesos and Zookeeper.
HNSciCloud update @ the World LHC Computing Grid deployment board
Bob Jones, CERN & HNSciCloud Coordinator gives an update on the HNSciCloud Pre-Commercial Procurement which is now in its Solution Prototyping phase. The presentation includes also an overview of the prototypes under development.
Planet lab : cloud vs grid computing
PlanetLab is a global research network supporting network services development since 2003. It has over 1000 researchers using its 530 nodes across 717 sites to develop technologies like distributed storage, networking mapping, peer-to-peer systems, and distributed query processing. Cloud computing provides resources through services rather than direct access, while grid computing involves aggregating distributed resources for tasks like number crunching. The objective is to understand how PlanetLab can maintain benefits while preparing for the future, and to compare grid and cloud computing models in terms of assembly, offered services, and differences in scale. The conclusion is that cloud computing will become the main information technology as it realizes the vision of grid computing through standardization and dynamic pricing models.
The Science Cloud Users: Challenges and Needs
This presentation, given by Bob Jones, CERN & HNSciCloud Coordinator, at the ESA-ESPI Workshop on “Space Data & Cloud Computing Infrastructures: Policies and Regulations”, describes what are the challenges and needs of the cloud users and explains how an hybrid cloud model can support them.
No sql understanding
This document provides an introduction and overview of NoSQL databases. It discusses topics including what NoSQL is, how it differs from SQL databases, the CAP theorem, examples of the NoSQL ecosystem, use cases for NoSQL, and approaches to hybrid database designs. The document aims to explain key concepts about NoSQL beyond it just being a buzzword and demonstrates how big data is now common across many domains, from social media to healthcare.
Sharing Big Data - Bob Jones
Bob Jones' presentation at the World Summit on the Information Society (WSIS) Forum 2017, 15 June, Geneva, Switzerland.
Globus toolkit in grid
For more information visit http://www.presentationat.blogspot.in/
Paper Presentation on:Globus toolkit in grid
Grid computing
Grid computing connects computer resources from multiple locations to achieve common goals. It allows users, grid servers, and grid clients to share computing power, databases, and other applications across organizational boundaries and geographic locations. Key components of grid computing include security, user interfaces, workload management, scheduling, data management, and resource management. Common applications of grid computing are in financial services, government agencies, and life sciences companies seeking to solve large-scale computing problems.
Results from Retrofit for the Future.
The document summarizes the results of a two-year Internet of Things project funded by TSB to monitor energy savings in 26 highly instrumented homes across the UK. Data was collected from the homes every minute via Wattbox devices and totaled over 800 million records over two years. A cloud-based solution was developed to compress, encrypt, transmit, process, and format the data for delivery to two separate databases. The solution successfully delivered over 70% of the data to the central database, and all 26 Wattbox properties were included upon completion of the monitoring period. Initial analysis of the data is now available online.
Fog computing may help to save energy in cloud computing
Fog computing may help to save energy in cloud computing
+91-9994232214,7806844441, ieeeprojectchennai@gmail.com,
www.projectsieee.com, www.ieee-projects-chennai.com
IEEE PROJECTS 2016-2017
-----------------------------------
Contact:+91-9994232214,+91-7806844441
Email: ieeeprojectchennai@gmail.com
Xanadu for Big Data + Deep Learning + Cloud + IoT Integration Strategy
This event summary describes a presentation by Alex G. Lee from Xanadu Big Data about their technology platform. The event is by invitation only on June 29th, 2017 from 11:30am to 3pm at the DLA Piper office in Palo Alto, California. The agenda includes check-in, lunch, an introduction by DLA Piper, a presentation by Alex G. Lee on Xanadu and how it can support big data, deep learning, cloud, and IoT applications, and a networking session.
grid computing
The document discusses grid computing and the development of computational grids. Key points:
- Grids allow for sharing of computing power and resources across geographic locations through networked supercomputers, databases, and instruments.
- Major organizations like NASA, DOE, and NSF are working to build computational grids for applications like scientific simulations and instrument control.
- Indiana University is involved in grid research through various departments and projects focused on resource sharing, portals, middleware, and more.
HNSciCloud Introduction - Bob Jones - Prototype Phase kickoff meeting
The Helix Nebula Science Cloud (HNSciCloud) project is a pre-commercial procurement action funded by the EU Horizon 2020 programme to develop an innovative hybrid cloud platform for the European research community. A group of procuring organizations, including CERN, have committed procurement funds, resources for testing, use cases, and in-house IT infrastructure. The multi-phase tender process will result in the development of integrated cloud services accessible to end-users. Challenges include providing compute, storage, networking, and payment models to support scientific workloads using datasets in the petabyte range across the procurers' resources and public e-infrastructure.
Roberto minerva 20181130
The document discusses challenges and perspectives for developing the next generation internet by integrating networking, data management, and computing. It notes that data traffic is growing exponentially and will be dominated by video. Edge computing and its relationship to cloud computing are discussed as potential new choke points. The "data flood" from IoT devices and how to handle raw versus processed data is also examined. Finally, it explores how user, environmental, and content data flows are aggregated and used for profiling identities and behaviors.
Xanadu for Big Data + IoT + Deep Learning + Cloud Integration Strategy
Big Data in IoT & Deep Learning
Challenges of IoT Big Data Analytics Applications
Challenges of Cloud-based IoT Platform
Cloud-based IoT Platform Use Case: GE Predix for Smart Building Energy Management
Fog/Edge Computing & Micro Data Centers
Deep Learning for IoT Big Data Analytics Introduction
Deep Learning for IoT Big Data Analytics Use Case
Distributed Deep Learning
Big Data + IoT + Cloud + Deep Learning Insights from Patents
Big Data + IoT + Cloud + Deep Learning Strategy Development
Designing Data-Intensive Applications
Xanadu Functionality
Xanadu Use Case
Xanadu + Deep Learning + Hadoop Integration
BIG DATA
Concepts of Big data and some of the tools used for solving Big Data is Explained in this Presentation
More Related Content
What's hot
Introducing Generalized Deduplication for Energy-efficient IoT Networks with ...
Abstract: The growing number of Internet of Things (IoT) devices is increasing the network traffic load globally. As a solution to this problem we propose Hermes, a network protocol that leverages the concept of generalized deduplication (GD) to reduce not only the network traffic, but also the energy consumption of devices. GD is a novel technique that maps identical and similar data chunks to a so called basis while applying an error correcting code onto them. The difference between the original data chunk and the basis is encoded in a deviation.
With this poster we motivate the use and purpose of the Hermes protocol. Then we outline the concept of GD and describe the architecture of a Hermes network including the message exchange. Finally, we highlight our micro- and macro-benchmark results on a synthetic data set.
Poster presented by Christian Göttel at the LEGaTO Final Event: 'Low-Energy Heterogeneous Computing Workshop'
Big data
Nandan Shah's presentation covered key topics related to big data including definitions, important technologies like Hadoop and MapReduce, benefits such as enabling real-time analysis and faster decision making, risks around data security and privacy, and applications across various domains such as banking, retail, and healthcare. The presentation also provided interesting facts about the size of data holdings and growth of the big data industry.
Big Data on Public Cloud
Presentation by Dr.Thanachart Numnonda, IMC Institute @Thailand Big Data User Group #2, 13 March 2015
Webinar: Multi-Cloud Monitoring
In this webinar, Phil Dougherty and Gunnar Aasen will show you that it actually can be simple to deploy, manage and scale containerized applications on a mix of any public or private cloud with Containership. And with this varied environment, you gather metrics and events from your apps and microservices and centrally view and manage all components with InfluxData.
BigchainDB: Blockchains for Artificial Intelligence by Trent McConaghy
How can blockchains help AI?
-Decentralized model exchange
-Model audit trail
-AI DAOs
-more
A blockchain caveat or two
Completely new code bases
Reinventing consensus
No sharding = no scaling
No querying // single-node querying
Let’s fix this...
Grid Computing
Grid computing involves linking together distributed computer resources from multiple administrative domains to achieve a common goal. Resources in a grid are heterogeneous and geographically dispersed. A grid differs from a cluster in that it provides a consistent, dependable, and transparent collection of computing resources across wide distances. Grid infrastructure must respect local autonomy, handle heterogeneous hardware, and be resilient and dynamic.
containers2016
This document discusses the growing amount of data from "long tail" science, which is estimated to generate over 1 petabyte of data per year. It also lists various tools for radio astronomy, chemical informatics, galaxies, genomes, machine learning algorithms, and data storage containers. Finally, it shows a graph of the events per second for a distributed computing system using Marathon, Mesos and Zookeeper.
HNSciCloud update @ the World LHC Computing Grid deployment board
Bob Jones, CERN & HNSciCloud Coordinator gives an update on the HNSciCloud Pre-Commercial Procurement which is now in its Solution Prototyping phase. The presentation includes also an overview of the prototypes under development.
Planet lab : cloud vs grid computing
PlanetLab is a global research network supporting network services development since 2003. It has over 1000 researchers using its 530 nodes across 717 sites to develop technologies like distributed storage, networking mapping, peer-to-peer systems, and distributed query processing. Cloud computing provides resources through services rather than direct access, while grid computing involves aggregating distributed resources for tasks like number crunching. The objective is to understand how PlanetLab can maintain benefits while preparing for the future, and to compare grid and cloud computing models in terms of assembly, offered services, and differences in scale. The conclusion is that cloud computing will become the main information technology as it realizes the vision of grid computing through standardization and dynamic pricing models.
The Science Cloud Users: Challenges and Needs
This presentation, given by Bob Jones, CERN & HNSciCloud Coordinator, at the ESA-ESPI Workshop on “Space Data & Cloud Computing Infrastructures: Policies and Regulations”, describes what are the challenges and needs of the cloud users and explains how an hybrid cloud model can support them.
No sql understanding
This document provides an introduction and overview of NoSQL databases. It discusses topics including what NoSQL is, how it differs from SQL databases, the CAP theorem, examples of the NoSQL ecosystem, use cases for NoSQL, and approaches to hybrid database designs. The document aims to explain key concepts about NoSQL beyond it just being a buzzword and demonstrates how big data is now common across many domains, from social media to healthcare.
Sharing Big Data - Bob Jones
Bob Jones' presentation at the World Summit on the Information Society (WSIS) Forum 2017, 15 June, Geneva, Switzerland.
Globus toolkit in grid
For more information visit http://www.presentationat.blogspot.in/
Paper Presentation on:Globus toolkit in grid
Grid computing
Grid computing connects computer resources from multiple locations to achieve common goals. It allows users, grid servers, and grid clients to share computing power, databases, and other applications across organizational boundaries and geographic locations. Key components of grid computing include security, user interfaces, workload management, scheduling, data management, and resource management. Common applications of grid computing are in financial services, government agencies, and life sciences companies seeking to solve large-scale computing problems.
Results from Retrofit for the Future.
The document summarizes the results of a two-year Internet of Things project funded by TSB to monitor energy savings in 26 highly instrumented homes across the UK. Data was collected from the homes every minute via Wattbox devices and totaled over 800 million records over two years. A cloud-based solution was developed to compress, encrypt, transmit, process, and format the data for delivery to two separate databases. The solution successfully delivered over 70% of the data to the central database, and all 26 Wattbox properties were included upon completion of the monitoring period. Initial analysis of the data is now available online.
Fog computing may help to save energy in cloud computing
Fog computing may help to save energy in cloud computing
+91-9994232214,7806844441, ieeeprojectchennai@gmail.com,
www.projectsieee.com, www.ieee-projects-chennai.com
IEEE PROJECTS 2016-2017
-----------------------------------
Contact:+91-9994232214,+91-7806844441
Email: ieeeprojectchennai@gmail.com
Xanadu for Big Data + Deep Learning + Cloud + IoT Integration Strategy
This event summary describes a presentation by Alex G. Lee from Xanadu Big Data about their technology platform. The event is by invitation only on June 29th, 2017 from 11:30am to 3pm at the DLA Piper office in Palo Alto, California. The agenda includes check-in, lunch, an introduction by DLA Piper, a presentation by Alex G. Lee on Xanadu and how it can support big data, deep learning, cloud, and IoT applications, and a networking session.
grid computing
The document discusses grid computing and the development of computational grids. Key points:
- Grids allow for sharing of computing power and resources across geographic locations through networked supercomputers, databases, and instruments.
- Major organizations like NASA, DOE, and NSF are working to build computational grids for applications like scientific simulations and instrument control.
- Indiana University is involved in grid research through various departments and projects focused on resource sharing, portals, middleware, and more.
HNSciCloud Introduction - Bob Jones - Prototype Phase kickoff meeting
The Helix Nebula Science Cloud (HNSciCloud) project is a pre-commercial procurement action funded by the EU Horizon 2020 programme to develop an innovative hybrid cloud platform for the European research community. A group of procuring organizations, including CERN, have committed procurement funds, resources for testing, use cases, and in-house IT infrastructure. The multi-phase tender process will result in the development of integrated cloud services accessible to end-users. Challenges include providing compute, storage, networking, and payment models to support scientific workloads using datasets in the petabyte range across the procurers' resources and public e-infrastructure.
What's hot (19)
Introducing Generalized Deduplication for Energy-efficient IoT Networks with ...
Introducing Generalized Deduplication for Energy-efficient IoT Networks with ...
BigchainDB: Blockchains for Artificial Intelligence by Trent McConaghy
BigchainDB: Blockchains for Artificial Intelligence by Trent McConaghy
HNSciCloud update @ the World LHC Computing Grid deployment board
HNSciCloud update @ the World LHC Computing Grid deployment board
Fog computing may help to save energy in cloud computing
Fog computing may help to save energy in cloud computing
Xanadu for Big Data + Deep Learning + Cloud + IoT Integration Strategy
Xanadu for Big Data + Deep Learning + Cloud + IoT Integration Strategy
HNSciCloud Introduction - Bob Jones - Prototype Phase kickoff meeting
HNSciCloud Introduction - Bob Jones - Prototype Phase kickoff meeting
Similar to Big data caching for networking
Roberto minerva 20181130
The document discusses challenges and perspectives for developing the next generation internet by integrating networking, data management, and computing. It notes that data traffic is growing exponentially and will be dominated by video. Edge computing and its relationship to cloud computing are discussed as potential new choke points. The "data flood" from IoT devices and how to handle raw versus processed data is also examined. Finally, it explores how user, environmental, and content data flows are aggregated and used for profiling identities and behaviors.
Xanadu for Big Data + IoT + Deep Learning + Cloud Integration Strategy
Big Data in IoT & Deep Learning
Challenges of IoT Big Data Analytics Applications
Challenges of Cloud-based IoT Platform
Cloud-based IoT Platform Use Case: GE Predix for Smart Building Energy Management
Fog/Edge Computing & Micro Data Centers
Deep Learning for IoT Big Data Analytics Introduction
Deep Learning for IoT Big Data Analytics Use Case
Distributed Deep Learning
Big Data + IoT + Cloud + Deep Learning Insights from Patents
Big Data + IoT + Cloud + Deep Learning Strategy Development
Designing Data-Intensive Applications
Xanadu Functionality
Xanadu Use Case
Xanadu + Deep Learning + Hadoop Integration
BIG DATA
Concepts of Big data and some of the tools used for solving Big Data is Explained in this Presentation
The Data Platform Administration Handling the 100 PB.pdf
Rakuten Developer Meetup vol.02: How to Manage Large-scale Infrastructure
https://rakuten.connpass.com/event/243219/
Bigdata-Intro.pptx
The document provides an overview of big data analytics. It defines big data as high-volume, high-velocity, and high-variety information assets that require cost-effective and innovative forms of processing for insights and decision making. Big data is characterized by the 3Vs - volume, velocity, and variety. The emergence of big data is driven by the massive amount of data now being generated and stored, availability of open source tools, and commodity hardware. The course will cover Apache Hadoop, Apache Spark, streaming analytics, visualization, linked data analysis, and big data systems and AI solutions.
MapR Edge : Act Locally Learn Globally
Industrial IoT is currently transforming how businesses capitalize their big data. Changes in how business is done, combined with multiple technology drivers make geo-distributed data increasingly important for enterprises. These changes are causing serious disruption across a wide range of industries.
The rise of “Big Data” on cloud computing
The rise of “Big Data” on cloud computing: Review and open research issues
Paper Link: https://www.researchgate.net/publication/264624667_The_rise_of_Big_Data_on_cloud_computing_Review_and_open_research_issues
Its detroit2018 ndot
"Building an ITS Network for the Future" as presented by Seth Daniels, Chief Traffic Operations Engineer at NDOT at ITS Americas 2018 in Detroit.
Sdn in big data
The document discusses using SDN (software-defined networking) to improve big data applications. SDN can optimize data flows within and between data centers to improve the efficiency of big data tasks like transferring large files. By controlling data flows, an SDN controller can prioritize large transfers and handle varying traffic patterns to help big data applications run smoothly. Open issues that remain include scalable controller management and intelligent flow table and rule management.
Big Data and OSS at IBM
Presentation by Ivan Portilla and Ryan Dejana at Boulder Java User's Group, June 11, 2013. See http://boulderjug.org for more details.
Storage, Cloud, Web 2.0, Big Data Driving Growth
Storage, cloud computing, web 2.0 technologies, and big data are driving significant growth opportunities for Mellanox. Mellanox's InfiniBand and Ethernet interconnect solutions provide significantly higher performance compared to alternatives across HPC, database, cloud, and web 2.0 workloads. Mellanox is uniquely positioned to capitalize on the shift to more efficient cloud infrastructures and the convergence of storage, compute, and networking fabrics in the data center. Rapid changes in the market are creating opportunities for Mellanox to deliver faster, more scalable, and virtualized interconnect solutions to support continued exponential data growth.
Dell_whitepaper[1]
1) The document discusses how oil and gas companies are increasingly relying on big data and advanced analytics to make strategic decisions, but face challenges in capturing, analyzing, and utilizing large volumes of complex data.
2) It provides examples of how oil and gas companies can use big data for intelligent modeling of underground structures, precise computation to accelerate decisions, and faster exploration and discovery.
3) The document also describes how high performance computing architectures and technologies like GPUs and co-processors can help oil and gas companies more effectively process and gain insights from big data.
Long Live Posix - HPC Storage and the HPC Datacenter
In this deck from the Swiss HPC Conference, Robert Triendly from DDN presents: Long Live Posix - HPC Storage and the HPC Datacenter.
"The Portable Operating System Interface (POSIX) is a family of standards specified by the IEEE Computer Society for maintaining compatibility between operating systems. Since it was developed over 30 years ago, storage has changed dramatically. To improve the IO performance of applications, many users have called for the relaxation in POSIX IO that could lead to the development of new storage mechanisms to improve not only application performance but management, reliability, portability, and scalability."
Watch the video: https://wp.me/p3RLHQ-kaR
Learn more: http://ddn.com
and
http://hpcadvisorycouncil.com/events/2019/swiss-workshop/agenda.php
Sign up for our insideHPC Newsletter: http://insidehpc.com/newsletter
Big data analytics
This document summarizes a seminar presentation on big data analytics. It reviews 25 research papers published between 2011-2014 on issues related to big data analysis, real-time big data analysis using Hadoop in cloud computing, and classification of big data using tools and frameworks. The review process involved a 5-stage analysis of the papers. Key issues identified include big data analysis, real-time analysis using Hadoop in clouds, and classification using tools like Hadoop, MapReduce, HDFS. Promising solutions discussed are MapReduce Agent Mobility framework, PuntStore with pLSM index, IOT-StatisticDB statistical database mechanism, and visual clustering analysis.
HPC DAY 2017 | The network part in accelerating Machine-Learning and Big-Data
HPC DAY 2017 - http://www.hpcday.eu/
The network part in accelerating Machine-Learning and Big-Data
Boris Neiman | Sr. System Engineer at Mellanox
EnBIS 2016 opening
Opening presentation of the EnBIS workshop on energy-awareness and big data management in information systems.
Guest Lecture: Introduction to Big Data at Indian Institute of Technology
This document provides an introduction to big data, including definitions of big data and why it is important. It discusses characteristics of big data like volume, velocity, variety and veracity. It provides examples of big data applications in various industries like GE, Boeing, social media, finance, CERN, journalism, politics and more. It also introduces NoSQL and the CAP theorem, and concludes that big data is changing business and technology by enabling new insights from data to reduce costs and optimize operations.
Data Virtualization: An Introduction
Watch full webinar here: https://bit.ly/3puUCIc
What is Data Virtualization and why do I care? In this webinar we intend to help you understand not only what Data Virtualization is but why it's a critical component of any organization's data fabric and how it fits. How data virtualization liberates and empowers your business users via data discovery, data wrangling to generation of reusable reporting objects and data services. Digital transformation demands that we empower all consumers of data within the organization, it also demands agility too. Data Virtualization gives you meaningful access to information that can be shared by a myriad of consumers.
Watch on-demand this session to learn:
- What is Data Virtualization?
- Why do I need Data Virtualization in my organization?
- How do I implement Data Virtualization in my enterprise? Where does it fit?
Emulex Presents Why I/O is Strategic Global Survey Results
This webcast is the first in a monthly series on why I/O is strategic for the data center. Emulex will present findings from a global survey of more than 1,500 IT professionals that demonstrate the strategic importance of I/O in the data center across four key technology trends: virtualization, cloud, big data and convergence.
MapR and Cisco Make IT Better
You’re not the only one still loading your data into data warehouses and building marts or cubes out of it. But today’s data requires a much more accessible environment that delivers real-time results. Prepare for this transformation because your data platform and storage choices are about to undergo a re-platforming that happens once in 30 years.
With the MapR Converged Data Platform (CDP) and Cisco Unified Compute System (UCS), you can optimize today’s infrastructure and grow to take advantage of what’s next. Uncover the range of possibilities from re-platforming by intimately understanding your options for density, performance, functionality and more.
Similar to Big data caching for networking (20)
Xanadu for Big Data + IoT + Deep Learning + Cloud Integration Strategy
Xanadu for Big Data + IoT + Deep Learning + Cloud Integration Strategy
The Data Platform Administration Handling the 100 PB.pdf
The Data Platform Administration Handling the 100 PB.pdf
Long Live Posix - HPC Storage and the HPC Datacenter
Long Live Posix - HPC Storage and the HPC Datacenter
HPC DAY 2017 | The network part in accelerating Machine-Learning and Big-Data
HPC DAY 2017 | The network part in accelerating Machine-Learning and Big-Data
Guest Lecture: Introduction to Big Data at Indian Institute of Technology
Guest Lecture: Introduction to Big Data at Indian Institute of Technology
Emulex Presents Why I/O is Strategic Global Survey Results
Emulex Presents Why I/O is Strategic Global Survey Results
Recently uploaded
Experts live - Improving user adoption with AI
Bekijk de slides van onze sessie Enhancing Modern Workplace Efficiency op Experts Live 2024.
一比一原版美国帕森斯设计学院毕业证（parsons毕业证书）如何办理
原版一模一样【微信：741003700 】【美国帕森斯设计学院毕业证（parsons毕业证书）成绩单】【微信：741003700 】学位证，留信认证（真实可查，永久存档）原件一模一样纸张工艺/offer、雅思、外壳等材料/诚信可靠,可直接看成品样本，帮您解决无法毕业带来的各种难题！外壳，原版制作，诚信可靠，可直接看成品样本。行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备。十五年致力于帮助留学生解决难题，包您满意。
本公司拥有海外各大学样板无数，能完美还原。
1:1完美还原海外各大学毕业材料上的工艺：水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠。文字图案浮雕、激光镭射、紫外荧光、温感、复印防伪等防伪工艺。材料咨询办理、认证咨询办理请加学历顾问Q/微741003700
【主营项目】
一.毕业证【q微741003700】成绩单、使馆认证、教育部认证、雅思托福成绩单、学生卡等！
二.真实使馆公证(即留学回国人员证明,不成功不收费)
三.真实教育部学历学位认证（教育部存档！教育部留服网站永久可查）
四.办理各国各大学文凭(一对一专业服务,可全程监控跟踪进度)
如果您处于以下几种情况：
◇在校期间，因各种原因未能顺利毕业……拿不到官方毕业证【q/微741003700】
◇面对父母的压力，希望尽快拿到；
◇不清楚认证流程以及材料该如何准备；
◇回国时间很长，忘记办理；
◇回国马上就要找工作，办给用人单位看；
◇企事业单位必须要求办理的
◇需要报考公务员、购买免税车、落转户口
◇申请留学生创业基金
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
办理美国帕森斯设计学院毕业证（parsons毕业证书）【微信：741003700 】外观非常简单，由纸质材料制成，上面印有校徽、校名、毕业生姓名、专业等信息。
办理美国帕森斯设计学院毕业证（parsons毕业证书）【微信：741003700 】格式相对统一，各专业都有相应的模板。通常包括以下部分：
校徽：象征着学校的荣誉和传承。
校名:学校英文全称
授予学位：本部分将注明获得的具体学位名称。
毕业生姓名：这是最重要的信息之一，标志着该证书是由特定人员获得的。
颁发日期：这是毕业正式生效的时间，也代表着毕业生学业的结束。
其他信息：根据不同的专业和学位，可能会有一些特定的信息或章节。
办理美国帕森斯设计学院毕业证（parsons毕业证书）【微信：741003700 】价值很高，需要妥善保管。一般来说，应放置在安全、干燥、防潮的地方，避免长时间暴露在阳光下。如需使用，最好使用复印件而不是原件，以免丢失。
综上所述，办理美国帕森斯设计学院毕业证（parsons毕业证书）【微信：741003700 】是证明身份和学历的高价值文件。外观简单庄重，格式统一，包括重要的个人信息和发布日期。对持有人来说，妥善保管是非常重要的。
Beyond the Basics of A/B Tests: Highly Innovative Experimentation Tactics You...
This webinar will explore cutting-edge, less familiar but powerful experimentation methodologies which address well-known limitations of standard A/B Testing. Designed for data and product leaders, this session aims to inspire the embrace of innovative approaches and provide insights into the frontiers of experimentation!
一比一原版南十字星大学毕业证(SCU毕业证书)学历如何办理
原版办理【微信号:BYZS866】【南十字星大学毕业证(SCU毕业证书)】【微信号:BYZS866】《成绩单、外壳、雅思、offer、真实留信官方学历认证（永久存档/真实可查）》采用学校原版纸张、特殊工艺完全按照原版一比一制作（包括：隐形水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠，文字图案浮雕，激光镭射，紫外荧光，温感，复印防伪）行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备，十五年致力于帮助留学生解决难题，业务范围有加拿大、英国、澳洲、韩国、美国、新加坡，新西兰等学历材料，包您满意。
【我们承诺采用的是学校原版纸张（纸质、底色、纹路）我们拥有全套进口原装设备，特殊工艺都是采用不同机器制作，仿真度基本可以达到100%，所有工艺效果都可提前给客户展示，不满意可以根据客户要求进行调整，直到满意为止！】
【业务选择办理准则】
一、工作未确定，回国需先给父母、亲戚朋友看下文凭的情况，办理一份就读学校的毕业证【微信号BYZS866】文凭即可
二、回国进私企、外企、自己做生意的情况，这些单位是不查询毕业证真伪的，而且国内没有渠道去查询国外文凭的真假，也不需要提供真实教育部认证。鉴于此，办理一份毕业证【微信号BYZS866】即可
三、进国企，银行，事业单位，考公务员等等，这些单位是必需要提供真实教育部认证的，办理教育部认证所需资料众多且烦琐，所有材料您都必须提供原件，我们凭借丰富的经验，快捷的绿色通道帮您快速整合材料，让您少走弯路。
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
留信网服务项目：
1、留学生专业人才库服务（留信分析）
2、国（境）学习人员提供就业推荐信服务
3、留学人员区块链存储服务
【关于价格问题（保证一手价格）】
我们所定的价格是非常合理的，而且我们现在做得单子大多数都是代理和回头客户介绍的所以一般现在有新的单子 我给客户的都是第一手的代理价格，因为我想坦诚对待大家 不想跟大家在价格方面浪费时间
对于老客户或者被老客户介绍过来的朋友，我们都会适当给一些优惠。
选择实体注册公司办理，更放心，更安全！我们的承诺：客户在留信官方认证查询网站查询到认证通过结果后付款，不成功不收费！
社内勉強会資料_Hallucination of LLMs .
社内エンジニア・リサーチャー勉強会の発表資料「Hallucination of LLMs」を公開しました！
大規模言語モデル(LLM)に起こるハルシネーションのメカニズムと、それらを軽減する方法について紹介しています。
Cell The Unit of Life for NEET Multiple Choice Questions.docx
celltheunitoflife
ribosomes
thegolgi
nuclearmembrane
cilia
phragmoplast
End-to-end pipeline agility - Berlin Buzzwords 2024
We describe how we achieve high change agility in data engineering by eliminating the fear of breaking downstream data pipelines through end-to-end pipeline testing, and by using schema metaprogramming to safely eliminate boilerplate involved in changes that affect whole pipelines.
A quick poll on agility in changing pipelines from end to end indicated a huge span in capabilities. For the question "How long time does it take for all downstream pipelines to be adapted to an upstream change," the median response was 6 months, but some respondents could do it in less than a day. When quantitative data engineering differences between the best and worst are measured, the span is often 100x-1000x, sometimes even more.
A long time ago, we suffered at Spotify from fear of changing pipelines due to not knowing what the impact might be downstream. We made plans for a technical solution to test pipelines end-to-end to mitigate that fear, but the effort failed for cultural reasons. We eventually solved this challenge, but in a different context. In this presentation we will describe how we test full pipelines effectively by manipulating workflow orchestration, which enables us to make changes in pipelines without fear of breaking downstream.
Making schema changes that affect many jobs also involves a lot of toil and boilerplate. Using schema-on-read mitigates some of it, but has drawbacks since it makes it more difficult to detect errors early. We will describe how we have rejected this tradeoff by applying schema metaprogramming, eliminating boilerplate but keeping the protection of static typing, thereby further improving agility to quickly modify data pipelines without fear.
UofT毕业证如何办理
原件一模一样【微信：95270640】【多伦多大学毕业证UofT学位证成绩单】【微信：95270640】（留信学历认证永久存档查询）采用学校原版纸张、特殊工艺完全按照原版一比一制作（包括：隐形水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠，文字图案浮雕，激光镭射，紫外荧光，温感，复印防伪）行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备，十五年致力于帮助留学生解决难题，业务范围有加拿大、英国、澳洲、韩国、美国、新加坡，新西兰等学历材料，包您满意。
【业务选择办理准则】
一、工作未确定，回国需先给父母、亲戚朋友看下文凭的情况，办理一份就读学校的毕业证【微信：95270640】文凭即可
二、回国进私企、外企、自己做生意的情况，这些单位是不查询毕业证真伪的，而且国内没有渠道去查询国外文凭的真假，也不需要提供真实教育部认证。鉴于此，办理一份毕业证【微信：95270640】即可
三、进国企，银行，事业单位，考公务员等等，这些单位是必需要提供真实教育部认证的，办理教育部认证所需资料众多且烦琐，所有材料您都必须提供原件，我们凭借丰富的经验，快捷的绿色通道帮您快速整合材料，让您少走弯路。
留信网认证的作用:
1:该专业认证可证明留学生真实身份【微信：95270640】
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
→ 【关于价格问题（保证一手价格）
我们所定的价格是非常合理的，而且我们现在做得单子大多数都是代理和回头客户介绍的所以一般现在有新的单子 我给客户的都是第一手的代理价格，因为我想坦诚对待大家 不想跟大家在价格方面浪费时间
对于老客户或者被老客户介绍过来的朋友，我们都会适当给一些优惠。
选择实体注册公司办理，更放心，更安全！我们的承诺：可来公司面谈，可签订合同，会陪同客户一起到教育部认证窗口递交认证材料，客户在教育部官方认证查询网站查询到认证通过结果后付款，不成功不收费！
办理多伦多大学毕业证硕士毕业证成绩单UofT学位证【微信：95270640 】外观非常精致，由特殊纸质材料制成，上面印有校徽、校名、毕业生姓名、专业等信息。
办理多伦多大学毕业证UofT学位证硕士毕业证成绩单【微信：95270640 】格式相对统一，各专业都有相应的模板。通常包括以下部分：
校徽：象征着学校的荣誉和传承。
校名:学校英文全称
授予学位：本部分将注明获得的具体学位名称。
毕业生姓名：这是最重要的信息之一，标志着该证书是由特定人员获得的。
颁发日期：这是毕业正式生效的时间，也代表着毕业生学业的结束。
其他信息：根据不同的专业和学位，可能会有一些特定的信息或章节。
办理多伦多大学毕业证硕士毕业证成绩单UofT学位证【微信：95270640 】价值很高，需要妥善保管。一般来说，应放置在安全、干燥、防潮的地方，避免长时间暴露在阳光下。如需使用，最好使用复印件而不是原件，以免丢失。
综上所述，办理多伦多大学毕业证硕士毕业证成绩单UofT学位证【微信：95270640 】是证明身份和学历的高价值文件。外观简单庄重，格式统一，包括重要的个人信息和发布日期。对持有人来说，妥善保管是非常重要的。
4th Modern Marketing Reckoner by MMA Global India & Group M: 60+ experts on W...
The Modern Marketing Reckoner (MMR) is a comprehensive resource packed with POVs from 60+ industry leaders on how AI is transforming the 4 key pillars of marketing – product, place, price and promotions.
Build applications with generative AI on Google Cloud
We will explore Vertex AI - Model Garden powered experiences, we are going to learn more about the integration of these generative AI APIs. We are going to see in action what the Gemini family of generative models are for developers to build and deploy AI-driven applications. Vertex AI includes a suite of foundation models, these are referred to as the PaLM and Gemini family of generative ai models, and they come in different versions. We are going to cover how to use via API to: - execute prompts in text and chat - cover multimodal use cases with image prompts. - finetune and distill to improve knowledge domains - run function calls with foundation models to optimize them for specific tasks. At the end of the session, developers will understand how to innovate with generative AI and develop apps using the generative ai industry trends.
[VCOSA] Monthly Report - Cotton & Yarn Statistics March 2024
We are pleased to share with you the latest VCOSA statistical report on the cotton and yarn industry for the month of March 2024.
Starting from January 2024, the full weekly and monthly reports will only be available for free to VCOSA members. To access the complete weekly report with figures, charts, and detailed analysis of the cotton fiber market in the past week, interested parties are kindly requested to contact VCOSA to subscribe to the newsletter.
一比一原版卡尔加里大学毕业证（uc毕业证）如何办理
原版一模一样【微信：741003700 】【卡尔加里大学毕业证（uc毕业证）成绩单】【微信：741003700 】学位证，留信认证（真实可查，永久存档）原件一模一样纸张工艺/offer、雅思、外壳等材料/诚信可靠,可直接看成品样本，帮您解决无法毕业带来的各种难题！外壳，原版制作，诚信可靠，可直接看成品样本。行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备。十五年致力于帮助留学生解决难题，包您满意。
本公司拥有海外各大学样板无数，能完美还原。
1:1完美还原海外各大学毕业材料上的工艺：水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠。文字图案浮雕、激光镭射、紫外荧光、温感、复印防伪等防伪工艺。材料咨询办理、认证咨询办理请加学历顾问Q/微741003700
【主营项目】
一.毕业证【q微741003700】成绩单、使馆认证、教育部认证、雅思托福成绩单、学生卡等！
二.真实使馆公证(即留学回国人员证明,不成功不收费)
三.真实教育部学历学位认证（教育部存档！教育部留服网站永久可查）
四.办理各国各大学文凭(一对一专业服务,可全程监控跟踪进度)
如果您处于以下几种情况：
◇在校期间，因各种原因未能顺利毕业……拿不到官方毕业证【q/微741003700】
◇面对父母的压力，希望尽快拿到；
◇不清楚认证流程以及材料该如何准备；
◇回国时间很长，忘记办理；
◇回国马上就要找工作，办给用人单位看；
◇企事业单位必须要求办理的
◇需要报考公务员、购买免税车、落转户口
◇申请留学生创业基金
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
办理卡尔加里大学毕业证（uc毕业证）【微信：741003700 】外观非常简单，由纸质材料制成，上面印有校徽、校名、毕业生姓名、专业等信息。
办理卡尔加里大学毕业证（uc毕业证）【微信：741003700 】格式相对统一，各专业都有相应的模板。通常包括以下部分：
校徽：象征着学校的荣誉和传承。
校名:学校英文全称
授予学位：本部分将注明获得的具体学位名称。
毕业生姓名：这是最重要的信息之一，标志着该证书是由特定人员获得的。
颁发日期：这是毕业正式生效的时间，也代表着毕业生学业的结束。
其他信息：根据不同的专业和学位，可能会有一些特定的信息或章节。
办理卡尔加里大学毕业证（uc毕业证）【微信：741003700 】价值很高，需要妥善保管。一般来说，应放置在安全、干燥、防潮的地方，避免长时间暴露在阳光下。如需使用，最好使用复印件而不是原件，以免丢失。
综上所述，办理卡尔加里大学毕业证（uc毕业证）【微信：741003700 】是证明身份和学历的高价值文件。外观简单庄重，格式统一，包括重要的个人信息和发布日期。对持有人来说，妥善保管是非常重要的。
Jio cinema Retention & Engagement Strategy.pdf
Introduction to Jio Cinema**:
- Brief overview of Jio Cinema as a streaming platform.
- Its significance in the Indian market.
- Introduction to retention and engagement strategies in the streaming industry.
2. **Understanding Retention and Engagement**:
- Define retention and engagement in the context of streaming platforms.
- Importance of retaining users in a competitive market.
- Key metrics used to measure retention and engagement.
3. **Jio Cinema's Content Strategy**:
- Analysis of the content library offered by Jio Cinema.
- Focus on exclusive content, originals, and partnerships.
- Catering to diverse audience preferences (regional, genre-specific, etc.).
- User-generated content and interactive features.
4. **Personalization and Recommendation Algorithms**:
- How Jio Cinema leverages user data for personalized recommendations.
- Algorithmic strategies for suggesting content based on user preferences, viewing history, and behavior.
- Dynamic content curation to keep users engaged.
5. **User Experience and Interface Design**:
- Evaluation of Jio Cinema's user interface (UI) and user experience (UX).
- Accessibility features and device compatibility.
- Seamless navigation and search functionality.
- Integration with other Jio services.
6. **Community Building and Social Features**:
- Strategies for fostering a sense of community among users.
- User reviews, ratings, and comments.
- Social sharing and engagement features.
- Interactive events and campaigns.
7. **Retention through Loyalty Programs and Incentives**:
- Overview of loyalty programs and rewards offered by Jio Cinema.
- Subscription plans and benefits.
- Promotional offers, discounts, and partnerships.
- Gamification elements to encourage continued usage.
8. **Customer Support and Feedback Mechanisms**:
- Analysis of Jio Cinema's customer support infrastructure.
- Channels for user feedback and suggestions.
- Handling of user complaints and queries.
- Continuous improvement based on user feedback.
9. **Multichannel Engagement Strategies**:
- Utilization of multiple channels for user engagement (email, push notifications, SMS, etc.).
- Targeted marketing campaigns and promotions.
- Cross-promotion with other Jio services and partnerships.
- Integration with social media platforms.
10. **Data Analytics and Iterative Improvement**:
- Role of data analytics in understanding user behavior and preferences.
- A/B testing and experimentation to optimize engagement strategies.
- Iterative improvement based on data-driven insights.
一比一原版兰加拉学院毕业证(Langara毕业证书)学历如何办理
原版办【微信号:BYZS866】【兰加拉学院毕业证(Langara毕业证书)】【微信号:BYZS866】《成绩单、外壳、雅思、offer、真实留信官方学历认证（永久存档/真实可查）》采用学校原版纸张、特殊工艺完全按照原版一比一制作（包括：隐形水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠，文字图案浮雕，激光镭射，紫外荧光，温感，复印防伪）行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备，十五年致力于帮助留学生解决难题，业务范围有加拿大、英国、澳洲、韩国、美国、新加坡，新西兰等学历材料，包您满意。
【我们承诺采用的是学校原版纸张（纸质、底色、纹路）我们拥有全套进口原装设备，特殊工艺都是采用不同机器制作，仿真度基本可以达到100%，所有工艺效果都可提前给客户展示，不满意可以根据客户要求进行调整，直到满意为止！】
【业务选择办理准则】
一、工作未确定，回国需先给父母、亲戚朋友看下文凭的情况，办理一份就读学校的毕业证【微信号BYZS866】文凭即可
二、回国进私企、外企、自己做生意的情况，这些单位是不查询毕业证真伪的，而且国内没有渠道去查询国外文凭的真假，也不需要提供真实教育部认证。鉴于此，办理一份毕业证【微信号BYZS866】即可
三、进国企，银行，事业单位，考公务员等等，这些单位是必需要提供真实教育部认证的，办理教育部认证所需资料众多且烦琐，所有材料您都必须提供原件，我们凭借丰富的经验，快捷的绿色通道帮您快速整合材料，让您少走弯路。
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
留信网服务项目：
1、留学生专业人才库服务（留信分析）
2、国（境）学习人员提供就业推荐信服务
3、留学人员区块链存储服务
【关于价格问题（保证一手价格）】
我们所定的价格是非常合理的，而且我们现在做得单子大多数都是代理和回头客户介绍的所以一般现在有新的单子 我给客户的都是第一手的代理价格，因为我想坦诚对待大家 不想跟大家在价格方面浪费时间
对于老客户或者被老客户介绍过来的朋友，我们都会适当给一些优惠。
选择实体注册公司办理，更放心，更安全！我们的承诺：客户在留信官方认证查询网站查询到认证通过结果后付款，不成功不收费！
一比一原版(UCSB文凭证书)圣芭芭拉分校毕业证如何办理
毕业原版【微信:176555708】【(UCSB毕业证书)圣芭芭拉分校毕业证】【微信:176555708】成绩单、外壳、offer、留信学历认证（永久存档真实可查）采用学校原版纸张、特殊工艺完全按照原版一比一制作（包括：隐形水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠，文字图案浮雕，激光镭射，紫外荧光，温感，复印防伪）行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备，十五年致力于帮助留学生解决难题，业务范围有加拿大、英国、澳洲、韩国、美国、新加坡，新西兰等学历材料，包您满意。
【我们承诺采用的是学校原版纸张（纸质、底色、纹路），我们拥有全套进口原装设备，特殊工艺都是采用不同机器制作，仿真度基本可以达到100%，所有工艺效果都可提前给客户展示，不满意可以根据客户要求进行调整，直到满意为止！】
【业务选择办理准则】
一、工作未确定，回国需先给父母、亲戚朋友看下文凭的情况，办理一份就读学校的毕业证【微信176555708】文凭即可
二、回国进私企、外企、自己做生意的情况，这些单位是不查询毕业证真伪的，而且国内没有渠道去查询国外文凭的真假，也不需要提供真实教育部认证。鉴于此，办理一份毕业证【微信176555708】即可
三、进国企，银行，事业单位，考公务员等等，这些单位是必需要提供真实教育部认证的，办理教育部认证所需资料众多且烦琐，所有材料您都必须提供原件，我们凭借丰富的经验，快捷的绿色通道帮您快速整合材料，让您少走弯路。
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
留信网服务项目：
1、留学生专业人才库服务（留信分析）
2、国（境）学习人员提供就业推荐信服务
3、留学人员区块链存储服务
→ 【关于价格问题（保证一手价格）】
我们所定的价格是非常合理的，而且我们现在做得单子大多数都是代理和回头客户介绍的所以一般现在有新的单子 我给客户的都是第一手的代理价格，因为我想坦诚对待大家 不想跟大家在价格方面浪费时间
对于老客户或者被老客户介绍过来的朋友，我们都会适当给一些优惠。
选择实体注册公司办理，更放心，更安全！我们的承诺：客户在留信官方认证查询网站查询到认证通过结果后付款，不成功不收费！
一比一原版(UO毕业证)渥太华大学毕业证如何办理
UO毕业证录取书【微信95270640】购买（渥太华大学毕业证成绩单硕士学历）Q微信95270640代办UO学历认证留信网伪造渥太华大学学位证书精仿渥太华大学本科/硕士文凭证书补办渥太华大学 diplomaoffer,Transcript购买渥太华大学毕业证成绩单购买UO假毕业证学位证书购买伪造渥太华大学文凭证书学位证书,专业办理雅思、托福成绩单，学生ID卡，在读证明，海外各大学offer录取通知书，毕业证书，成绩单，文凭等材料:1:1完美还原毕业证、offer录取通知书、学生卡等各种在读或毕业材料的防伪工艺（包括 烫金、烫银、钢印、底纹、凹凸版、水印、防伪光标、热敏防伪、文字图案浮雕，激光镭射，紫外荧光，温感光标）学校原版上有的工艺我们一样不会少，不论是老版本还是最新版本，都能保证最高程度还原，力争完美以求让所有同学都能享受到完美的品质服务。
文凭办理流程：
1客户提供办理信息：姓名生日专业学位毕业时间等（如信息不确定可以咨询顾问：微信95270640我们有专业老师帮你查询）；
2开始安排制作毕业证成绩单电子图；
3毕业证成绩单电子版做好以后发送给您确认；
4毕业证成绩单电子版您确认信息无误之后安排制作成品；
5成品做好拍照或者视频给您确认；
6快递给客户（国内顺丰国外DHLUPS等快读邮寄）。
7完成交易删除客户资料
高精端提供以下服务：
一：渥太华大学渥太华大学毕业证文凭证书全套材料从防伪到印刷水印底纹到钢印烫金
二：真实使馆认证（留学人员回国证明）使馆存档
三：真实教育部认证教育部存档教育部留服网站可查
四：留信认证留学生信息网站可查
五：与学校颁发的相关证件1:1纸质尺寸制定（定期向各大院校毕业生购买最新版本毕,业证成绩单保证您拿到的是鲁昂大学内部最新版本毕业证成绩单微信95270640）
A.为什么留学生需要操作留信认证?
留信认证全称全国留学生信息服务网认证,隶属于北京中科院。①留信认证门槛条件更低,费用更美丽,并且包过,完单周期短,效率高②留信认证虽然不能去国企,但是一般的公司都没有问题,因为国内很多公司连基本的留学生学历认证都不了解。这对于留学生来说,这就比自己光拿一个证书更有说服力,因为留学学历可以在留信网站上进行查询!
B.为什么我们提供的毕业证成绩单具有使用价值？
查询留服认证是国内鉴别留学生海外学历的唯一途径但认证只是个体行为不是所有留学生都操作所以没有办理认证的留学生的学历在国内也是查询不到的他们也仅仅只有一张文凭。所以这时候我们提供的和学校颁发的一模一样的毕业证成绩单就有了使用价值。只硕大的蛇皮袋手里拎着长铁钩正站在门口朝黑色的屋内张望不好坏人小偷山娃一怔却也灵机一动立马仰起头双手拢在嘴边朝楼上大喊：“爸爸爸——有人找——那人一听朝山娃尴尬地笑笑悻悻地走了山娃立马“嘭的一声将铁门锁死心却咚咚地乱跳当山娃跟父亲说起这事时父亲很吃惊抚摸着山娃的头说还好醒得及时要不家早被人掏空了到时连电视也没得看啰不过父亲还是夸山娃能临危不乱随机应变有胆有谋山娃笑笑说那都是书上学的看童话和小说时多
一比一原版(lbs毕业证书)伦敦商学院毕业证如何办理
原版一模一样【微信：741003700 】【(lbs毕业证书)伦敦商学院毕业证成绩单】【微信：741003700 】学位证，留信认证（真实可查，永久存档）原件一模一样纸张工艺/offer、雅思、外壳等材料/诚信可靠,可直接看成品样本，帮您解决无法毕业带来的各种难题！外壳，原版制作，诚信可靠，可直接看成品样本。行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备。十五年致力于帮助留学生解决难题，包您满意。
本公司拥有海外各大学样板无数，能完美还原。
1:1完美还原海外各大学毕业材料上的工艺：水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠。文字图案浮雕、激光镭射、紫外荧光、温感、复印防伪等防伪工艺。材料咨询办理、认证咨询办理请加学历顾问Q/微741003700
【主营项目】
一.毕业证【q微741003700】成绩单、使馆认证、教育部认证、雅思托福成绩单、学生卡等！
二.真实使馆公证(即留学回国人员证明,不成功不收费)
三.真实教育部学历学位认证（教育部存档！教育部留服网站永久可查）
四.办理各国各大学文凭(一对一专业服务,可全程监控跟踪进度)
如果您处于以下几种情况：
◇在校期间，因各种原因未能顺利毕业……拿不到官方毕业证【q/微741003700】
◇面对父母的压力，希望尽快拿到；
◇不清楚认证流程以及材料该如何准备；
◇回国时间很长，忘记办理；
◇回国马上就要找工作，办给用人单位看；
◇企事业单位必须要求办理的
◇需要报考公务员、购买免税车、落转户口
◇申请留学生创业基金
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
办理(lbs毕业证书)伦敦商学院毕业证【微信：741003700 】外观非常简单，由纸质材料制成，上面印有校徽、校名、毕业生姓名、专业等信息。
办理(lbs毕业证书)伦敦商学院毕业证【微信：741003700 】格式相对统一，各专业都有相应的模板。通常包括以下部分：
校徽：象征着学校的荣誉和传承。
校名:学校英文全称
授予学位：本部分将注明获得的具体学位名称。
毕业生姓名：这是最重要的信息之一，标志着该证书是由特定人员获得的。
颁发日期：这是毕业正式生效的时间，也代表着毕业生学业的结束。
其他信息：根据不同的专业和学位，可能会有一些特定的信息或章节。
办理(lbs毕业证书)伦敦商学院毕业证【微信：741003700 】价值很高，需要妥善保管。一般来说，应放置在安全、干燥、防潮的地方，避免长时间暴露在阳光下。如需使用，最好使用复印件而不是原件，以免丢失。
综上所述，办理(lbs毕业证书)伦敦商学院毕业证【微信：741003700 】是证明身份和学历的高价值文件。外观简单庄重，格式统一，包括重要的个人信息和发布日期。对持有人来说，妥善保管是非常重要的。
Recently uploaded (20)
Beyond the Basics of A/B Tests: Highly Innovative Experimentation Tactics You...
Beyond the Basics of A/B Tests: Highly Innovative Experimentation Tactics You...
Cell The Unit of Life for NEET Multiple Choice Questions.docx
Cell The Unit of Life for NEET Multiple Choice Questions.docx
A presentation that explain the Power BI Licensing
A presentation that explain the Power BI Licensing
End-to-end pipeline agility - Berlin Buzzwords 2024
End-to-end pipeline agility - Berlin Buzzwords 2024
4th Modern Marketing Reckoner by MMA Global India & Group M: 60+ experts on W...
4th Modern Marketing Reckoner by MMA Global India & Group M: 60+ experts on W...
Build applications with generative AI on Google Cloud
Build applications with generative AI on Google Cloud
[VCOSA] Monthly Report - Cotton & Yarn Statistics March 2024
[VCOSA] Monthly Report - Cotton & Yarn Statistics March 2024
DATA COMMS-NETWORKS YR2 lecture 08 NAT & CLOUD.docx
DATA COMMS-NETWORKS YR2 lecture 08 NAT & CLOUD.docx
Big data caching for networking
- 1. Big Data Caching for Networking: Moving from Cloud to Edge PRESENTED BY: HICHAM HAMMOUCHI Big Data Analytics & Smart Systems Engin Zeydan, Ejder Bastug, Mehdi Bennis, Manhal Abdel Kader, Ilyas Alper Karatepe, Ahmet Salih Er, Merouane Debbah
- 2. Outline Introduction Problematic & Motivation Approach Case study Conclusion 2/2/2017 BIG DATA CACHING FOR NETWORKING : MOVING FROM CLOUD TO EDGE 2
- 3. Introduction o The era of connected people and things Anywhere-Anytime to anything connectivity o Content on demand accessible in an asynchronous fashion o Big Data Cache-Enabled Architecture to cope with the data tsunami 2/2/2017 BIG DATA CACHING FOR NETWORKING : MOVING FROM CLOUD TO EDGE 3
- 4. Problematic o Acquire new spectrum, new Base Stations Are ineffective o BackHaul Offloading problems o User terminals interact with hundreds of servers, routers and switches inside the backhaul and core network o Issue of Managing the challenge of data growth in cloud environments 2/2/2017 BIG DATA CACHING FOR NETWORKING : MOVING FROM CLOUD TO EDGE 4
- 5. Motivation The human behavior is highly predictable o Exploitation of Big Data and machine learning for content popularity prediction o Cache-Enabled architecture for higher user satisfaction and backhaul offloading gains 2/2/2017 BIG DATA CACHING FOR NETWORKING : MOVING FROM CLOUD TO EDGE 5
- 6. o Harnessing Big data and machine learning for content popularity estimation for Proactive caching and a context-aware architecture to optimize 5G wireless networks o Cache-Enabled architecture at the edge where devices provide cloud-computing-like instead of the cloud 2/2/2017 BIG DATA CACHING FOR NETWORKING : MOVING FROM CLOUD TO EDGE 6 Approach
- 7. 2/2/2017 BIG DATA CACHING FOR NETWORKING : MOVING FROM CLOUD TO EDGE 7 Cache-Enabled Architecture
- 8. o Huge data volume processing in less time o Cleansing, Parsing and Formatting Data o Data Analysis o Statistical analysis and visualizations 2/2/2017 BIG DATA CACHING FOR NETWORKING : MOVING FROM CLOUD TO EDGE 8 Big Data Platform for analysis
- 9. Big Data Platform for analysis 2/2/2017 BIG DATA CACHING FOR NETWORKING : MOVING FROM CLOUD TO EDGE 9
- 10. o Data streaming traces collected from more than 10 regional core areas in Turkey. o Hadoop cluster with 1 name Node and 3 data Nodes empowered with an Intel Xeon CPUE5-2670 @2.6 GHz (32 cores), 132 GB RAM and 20 TB HD 2/2/2017 BIG DATA CACHING FOR NETWORKING : MOVING FROM CLOUD TO EDGE 10 Case study
- 11. 2/2/2017 BIG DATA CACHING FOR NETWORKING : MOVING FROM CLOUD TO EDGE 11 Case study : Results
- 12. 2/2/2017 BIG DATA CACHING FOR NETWORKING : MOVING FROM CLOUD TO EDGE 12 Case study : Results
- 13. 2/2/2017 BIG DATA CACHING FOR NETWORKING : MOVING FROM CLOUD TO EDGE 13
- 14. 2/2/2017 BIG DATA CACHING FOR NETWORKING : MOVING FROM CLOUD TO EDGE 14
- 16. Big Data Caching for Networking: Moving from Cloud to Edge SUPERVISED BY: PRESENTED BY: ISMAIL BERRADA HICHAM HAMMOUCHI Big Data Analytics & Smart Systems Engin Zeydan, Ejder Bastug, Mehdi Bennis, Manhal Abdel Kader, Ilyas Alper Karatepe, Ahmet Salih Er, Merouane Debbah