This document provides an overview of distributed computing. It discusses the history and introduction of distributed computing. It describes the working of distributed systems and common types like grid computing, cluster computing and cloud computing. It covers the motivations, goals, characteristics, architectures, security challenges and examples of distributed computing. Advantages include improved performance and fault tolerance, while disadvantages are security issues and lost messages.
A Distributed computing architeture consists of very lightweight software agents installed on a number of client systems , and one or more dedicated distributed computing managment servers.
Middleware and Middleware in distributed applicationRishikese MR
The seminar discuss about the common middleware concept and middleware in distributed applications .Also we discuss about 4 different types of middleware. MOM( Message oriented Middleware), ORB (object request broker), TP Monitors, Request procedure calls RPC.
The slide also gives the advantages and disadvantages of each.
A Distributed computing architeture consists of very lightweight software agents installed on a number of client systems , and one or more dedicated distributed computing managment servers.
Middleware and Middleware in distributed applicationRishikese MR
The seminar discuss about the common middleware concept and middleware in distributed applications .Also we discuss about 4 different types of middleware. MOM( Message oriented Middleware), ORB (object request broker), TP Monitors, Request procedure calls RPC.
The slide also gives the advantages and disadvantages of each.
Overview of Network Programming, Remote Procedure Calls, Remote Method Invocation, Message Oriented Communication, and web services in distributed systems
Cloud computing is used to define a new class of computing that is based on the network technology. Cloud computing takes place over the internet. It comprises of a collection of integrated and networked hardware, software and internet infrastructures. These infrastructures are used to provide various services to the users. Distributed computing comprises of multiple software components that belong to multiple computers. The system works or runs as a single system. Cloud computing can be referred to as a form that originated from distributed computing and virtualization.
Evolution of Distributed computing: Scalable computing over the Internet – Technologies for network based systems – clusters of cooperative computers - Grid computing Infrastructures – cloud computing - service oriented architecture – Introduction to Grid Architecture and standards – Elements of Grid – Overview of Grid Architecture.
Replication in computing involves sharing information so as to ensure consistency between redundant resources, such as software or hardware components, to improve reliability, fault-tolerance, or accessibility.
Overview of Network Programming, Remote Procedure Calls, Remote Method Invocation, Message Oriented Communication, and web services in distributed systems
Cloud computing is used to define a new class of computing that is based on the network technology. Cloud computing takes place over the internet. It comprises of a collection of integrated and networked hardware, software and internet infrastructures. These infrastructures are used to provide various services to the users. Distributed computing comprises of multiple software components that belong to multiple computers. The system works or runs as a single system. Cloud computing can be referred to as a form that originated from distributed computing and virtualization.
Evolution of Distributed computing: Scalable computing over the Internet – Technologies for network based systems – clusters of cooperative computers - Grid computing Infrastructures – cloud computing - service oriented architecture – Introduction to Grid Architecture and standards – Elements of Grid – Overview of Grid Architecture.
Replication in computing involves sharing information so as to ensure consistency between redundant resources, such as software or hardware components, to improve reliability, fault-tolerance, or accessibility.
Introduction to Cloud Computing
Cloud computing is a transformative technology that allows businesses and individuals to access computing resources over the internet. Instead of owning and maintaining physical hardware and software, users can leverage cloud services provided by companies like Amazon Web Services (AWS), Microsoft Azure, Google Cloud Platform (GCP), and others. This shift has revolutionized how we think about IT infrastructure, software development, data storage, and more.
Key Concepts of Cloud Computing
On-Demand Self-Service:
Users can provision computing resources as needed without human intervention from the service provider. This includes servers, storage, and applications.
Broad Network Access:
Cloud services are available over the network and accessed through standard mechanisms, enabling use from a variety of devices like laptops, smartphones, and tablets.
Resource Pooling:
Providers use a multi-tenant model to serve multiple customers with dynamically assigned resources. This model allows for economies of scale and efficient resource utilization.
Rapid Elasticity:
Resources can be elastically provisioned and released, sometimes automatically, to scale rapidly outward and inward commensurate with demand.
Measured Service:
Cloud systems automatically control and optimize resource use by leveraging a metering capability, allowing for pay-as-you-go pricing models.
Types of Cloud Computing Services
Infrastructure as a Service (IaaS):
Provides virtualized computing resources over the internet. Examples include AWS EC2, Google Compute Engine, and Azure Virtual Machines.
Platform as a Service (PaaS):
Offers hardware and software tools over the internet, typically used for application development. Examples include Google App Engine, AWS Elastic Beanstalk, and Azure App Services.
Software as a Service (SaaS):
Delivers software applications over the internet, on a subscription basis. Examples include Google Workspace, Microsoft Office 365, and Salesforce.
Deployment Models
Public Cloud:
Services are delivered over the public internet and shared across multiple organizations. It offers cost savings but might pose concerns regarding data security and privacy.
Private Cloud:
Dedicated to a single organization, offering enhanced security and control over data and infrastructure. It's more expensive than public cloud but can be tailored to specific business needs.
Hybrid Cloud:
Combines public and private clouds, allowing data and applications to be shared between them. This model offers greater flexibility and optimization of existing infrastructure, security, and compliance.
Community Cloud:
Shared between organizations with common concerns (e.g., security, compliance, jurisdiction). It can be managed internally or by a third-party.
Advantages of Cloud Computing
Cost Efficiency: Reduces the need for significant capital expenditure on hardware and software.
Scalability and Flexibility: Easily scales up or down based on
Global warming, also referred to as climate change, is the observed century-scale rise in the average temperature of the Earth's climate system and its related effects
Immunizing Image Classifiers Against Localized Adversary Attacksgerogepatton
This paper addresses the vulnerability of deep learning models, particularly convolutional neural networks
(CNN)s, to adversarial attacks and presents a proactive training technique designed to counter them. We
introduce a novel volumization algorithm, which transforms 2D images into 3D volumetric representations.
When combined with 3D convolution and deep curriculum learning optimization (CLO), itsignificantly improves
the immunity of models against localized universal attacks by up to 40%. We evaluate our proposed approach
using contemporary CNN architectures and the modified Canadian Institute for Advanced Research (CIFAR-10
and CIFAR-100) and ImageNet Large Scale Visual Recognition Challenge (ILSVRC12) datasets, showcasing
accuracy improvements over previous techniques. The results indicate that the combination of the volumetric
input and curriculum learning holds significant promise for mitigating adversarial attacks without necessitating
adversary training.
Student information management system project report ii.pdfKamal Acharya
Our project explains about the student management. This project mainly explains the various actions related to student details. This project shows some ease in adding, editing and deleting the student details. It also provides a less time consuming process for viewing, adding, editing and deleting the marks of the students.
Quality defects in TMT Bars, Possible causes and Potential Solutions.PrashantGoswami42
Maintaining high-quality standards in the production of TMT bars is crucial for ensuring structural integrity in construction. Addressing common defects through careful monitoring, standardized processes, and advanced technology can significantly improve the quality of TMT bars. Continuous training and adherence to quality control measures will also play a pivotal role in minimizing these defects.
CFD Simulation of By-pass Flow in a HRSG module by R&R Consult.pptxR&R Consult
CFD analysis is incredibly effective at solving mysteries and improving the performance of complex systems!
Here's a great example: At a large natural gas-fired power plant, where they use waste heat to generate steam and energy, they were puzzled that their boiler wasn't producing as much steam as expected.
R&R and Tetra Engineering Group Inc. were asked to solve the issue with reduced steam production.
An inspection had shown that a significant amount of hot flue gas was bypassing the boiler tubes, where the heat was supposed to be transferred.
R&R Consult conducted a CFD analysis, which revealed that 6.3% of the flue gas was bypassing the boiler tubes without transferring heat. The analysis also showed that the flue gas was instead being directed along the sides of the boiler and between the modules that were supposed to capture the heat. This was the cause of the reduced performance.
Based on our results, Tetra Engineering installed covering plates to reduce the bypass flow. This improved the boiler's performance and increased electricity production.
It is always satisfying when we can help solve complex challenges like this. Do your systems also need a check-up or optimization? Give us a call!
Work done in cooperation with James Malloy and David Moelling from Tetra Engineering.
More examples of our work https://www.r-r-consult.dk/en/cases-en/
Explore the innovative world of trenchless pipe repair with our comprehensive guide, "The Benefits and Techniques of Trenchless Pipe Repair." This document delves into the modern methods of repairing underground pipes without the need for extensive excavation, highlighting the numerous advantages and the latest techniques used in the industry.
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Democratizing Fuzzing at Scale by Abhishek Aryaabh.arya
Presented at NUS: Fuzzing and Software Security Summer School 2024
This keynote talks about the democratization of fuzzing at scale, highlighting the collaboration between open source communities, academia, and industry to advance the field of fuzzing. It delves into the history of fuzzing, the development of scalable fuzzing platforms, and the empowerment of community-driven research. The talk will further discuss recent advancements leveraging AI/ML and offer insights into the future evolution of the fuzzing landscape.
2. Contents
Overview
History
Introduction
Working of Distributed System
Type
Motivation
Goals
Characteristics
Architecture
Security and Standards Challenges
Example
Advantages
Disadvantages
Conclusion
Reference
3. Overview of Distributed Computing
• Distributed Computing is a field of computer science that
studies distributed systems.
• A Distributed System is One in Which H/W & S/W
Components Located at Networked Computers Communicate
their Actions Only By Message Passing
• In The Term Distributed Computing The Word Distributed
Means Spread out across space. Thus, Distributed Computing
is an activity performed on a distributed system.
• These Networked Computers may be in the same city, same
country i.e. in same world.
4. History
• The use of concurrent processes that communicate by
message-passing has its roots in operating system
architectures studied in the 1960s
• The study of distributed computing became its own
branch of computer science in the late 1970s and
early 1980s.
• The first conference in the field, Symposium on
Principles of Distributed Computing (PODC), dates
back to 1982, and its European
counterpart International Symposium on Distributed
Computing (DISC) was first held in 1985.
6. Introduction
• The word distributed in terms such as “ distributed
system", "distributed programming", and " distributed
algorithm " originally referred to computer networks
where individual computers were physically
distributed within some geographical area.
• The terms are nowadays used in a much wider sense,
even referring to autonomous processes that run on
the same physical computer and interact with each
other by message passing.
7. Working of Distributed System
• A distributed computing architecture consists of very
lightweight software agents installed on a number of
client systems, and one or more dedicated distributed
computing management servers.
• There may also be requesting clients with software
that allows them to submit jobs along with lists of
their required resources.
10. Types of Distributed System
Distributed Computing System
• Grid Computing
• Cluster Computing
• Cloud Computing
Distributed Information System
Distributed Pervasive System
11. Distributed Computing System
Grid Computing :-
Grid computing is the collection of computer resources
from multiple locations to reach a common goal. Grid
computing is a processor architecture that combines
computer resources from various domains to reach a
main objective. In grid computing, the computers on the
network can work on a task together, thus functioning as
a supercomputer.
12.
13. • Cluster Computing :-
A computer cluster is a single logical unit consisting of
multiple computers that are linked through a LAN. The
networked computers essentially act as a single, much
more powerful machine. A computer cluster provides
much faster processing speed, larger storage capacity,
better data integrity, superior reliability and wider
availability of resources.
Computer clusters are, however, much more costly to
implement and maintain. This results in much higher
running overhead compared to a single computer.
14.
15. • Cloud Computing :-
Cloud computing is a type of computing that relies
on sharing computing resources rather than having local
servers or personal devices to handle applications.
In cloud computing, the word cloud (also phrased as "the
cloud") is used as a metaphor for "the Internet," so the
phrase cloud computing means "a type of Internet-based
computing," where different services — such as servers,
storage and applications — are delivered to an
organization's computers and devices through the Internet.
16.
17. Distributed Information System :-
Goal :- Distributed Information System across several
servers
Remote processes called Clients access the servers to
manipulate the information.
Different communication models are used.
The most usual are RPC (Remote Procedure Calls) and
the object oriented RMI (Remote Method Invocations)
often associated with Transaction systems Examples:
o Banks
o Travel Agencies
o Rent-a-Cars………Etc……
18. Distributed Pervasive System
These are the distributed system involving mobile and
embedded computer devices like small, wireless, battery-
powered devices(PDA’s, smart phone….etc.)
These system characterized by their “instability” when
compared to more “traditional” distributed systems
pervasive system are all around us, and ideally should be
able to adapt to the lack of human administrative control:
• Automatically connect to a different n/w;
• Discover services and react accordingly;
• Automatic self configuration (e.g.: UPnP-Universal
Plug and Play)…..
Examples …. Home system, electronic Health care
system, sensor networks, ……
19. Motivation
The main motivation in Distributed System are the
following ……….
o Inherently distributed application.
o Performance/Cost.
o Resource Sharing.
o Flexibility and Extensibility.
o Availability and Fault Tolerance.
o Scalability
20. Goals
• Making Resources Accessible:
The main goal od DS is to make it easy for the users and application to
access remote resources, and to share then in a controlled and efficient
way.
• Distribution Transparency:
An important goal of DS is to hide the fact that its processes and
resources are physically across multiple computers.
• Openness:
An open DS is a system that offers services according to standard
rules that describe the syntax and semantics of those services.
• Scalability
scalability of a system can be measured along at least
three different dimensions.
23. Client–server
Architectures where smart clients contact the server for data
then format and display it to the users. Input at the client is
committed back to the server when it represents a permanent
change.
Three-tier
Architectures that move the client intelligence to a middle tier
so that stateless clients can be used. This simplifies application
deployment. Most web applications are three-tier.
N-tier
Architectures that refer typically to web applications which
further forward their requests to other enterprise services. This
type of application is the one most responsible for the success
of application servers.
Peer-to-peer
Architectures where there are no special machines that provide
a service or manage the network resources. Instead all
responsibilities are uniformly divided among all machines,
known as peers. Peers can serve both as clients and as servers
24. Security and Standards Challenges
• The major challenges come with increasing scale. As
soon as you move outside of a corporate firewall,
security and standardization challenges become quite
significant.
• Most of today's vendors currently specialize in
applications that stop at the corporate firewall, though
Avail, in particular, is staking out the global grid
territory.
• Beyond spanning firewalls with a single platform, lies
the challenge of spanning multiple firewalls and
platforms, which means standards.
25. Example
Examples of distributed systems and applications of distributed
computing include the following….
Telecommunication Networks:
telephone networks and cellular networks
computer networks such as the Internet
wireless sensor networks
routing algorithms
Network Applications:
World Wide Web and peer-to-peer networks
massively multiplayer online games and virtual reality communities,
distributed databases and distributed database management systems
Network file systems
26. real-time process control:
aircraft control systems
industrial control systems
parallel computation:
scientific computing, including cluster computing and grid
computing and various volunteer computing projects (see
the list of distributed computing projects),
distributed rendering in computer graphics
27. Advantages
Give more performance than single system
If one pc in distributed system malfunction or
corrupts then other node or pc will take care of
More resources can be added easily
Resources like printers can be shared on multiple pc’s
28. Disadvantages
Security problem due to sharing
Some messages can be lost in the network system
Bandwidth is another problem if there is large data then
all network wires to be replaced which tends to become
expensive
Overloading is another problem in distributed operating
systems
If there is a database connected on local system and
many users accessing that database through remote or
distributed way then performance become slow
The databases in network operating is difficult to
administrate then single user system
29. Conclusion
• In this age of optimization everybody is trying to get
optimized output from their limited resources. The
concept of distributed computing is the most efficient
way to achieve the optimization. In case of distributed
computing the actual task is modularized and is
distributed among various computer system. It not
only increases the efficiency of the task but also
reduce the total time required to complete the task.