Remote procedure contains the Server different semantics this presentation contains the complete idea of the server Creation and call semantics with its working
This ppt covers different aspects about timing issues and various algorithms involved in having better sync between different systems in a distributed environment
Synchronization Pradeep K Sinha
Introduction
Issues in Synchronization
Clock synchronization
Event Ordering
Mutual Exclusion
Deadlock
Election algorithms
Clock Synchronization
How Computer Clocks are Implemented
Drifting of Clocks
Types of Clock Synchronization and issues in them
Clock Synchronization Algorithms
Distributed and Centralized Algorithms
Case Study
Event Ordering
Happened Before Relation
Logical Clocks Concept and Implementation
Mutual Exclusion
Centralized Approach, Distributed Approach, Token Passing Approach
Deadlocks
Election algorithms
This ppt covers different aspects about timing issues and various algorithms involved in having better sync between different systems in a distributed environment
Synchronization Pradeep K Sinha
Introduction
Issues in Synchronization
Clock synchronization
Event Ordering
Mutual Exclusion
Deadlock
Election algorithms
Clock Synchronization
How Computer Clocks are Implemented
Drifting of Clocks
Types of Clock Synchronization and issues in them
Clock Synchronization Algorithms
Distributed and Centralized Algorithms
Case Study
Event Ordering
Happened Before Relation
Logical Clocks Concept and Implementation
Mutual Exclusion
Centralized Approach, Distributed Approach, Token Passing Approach
Deadlocks
Election algorithms
File Replication : High availability is a desirable feature of a good distributed file system and file replication is the primary mechanism for improving file availability. Replication is a key strategy for improving reliability, fault tolerance and availability. Therefore duplicating files on multiple machines improves availability and performance.
Replicated file : A replicated file is a file that has multiple copies, with each copy located on a separate file server. Each copy of the set of copies that comprises a replicated file is referred to as replica of the replicated file.
Replication is often confused with caching, probably because they both deal with multiple copies of data. The two concepts has the following basic differences:
A replica is associated with server, whereas a cached copy is associated with a client.
The existence of cached copy is primarily dependent on the locality in file access patterns, whereas the existence of a replica normally depends on availability and performance requirements.
Satynarayanana [1992] distinguishes a replicated copy from a cached copy by calling the first-class replicas and second-class replicas respectively
In this we discuss about DATA RATE LIMITS
Two theoretical formulas were developed to calculate the data rate:
Nyquist bit rate for a noiseless channel
BitRate = 2 * bandwidth * log 2 L
2: Shannon Capacity for a noisy channel
Capacity = bandwidth * log 2 (1 + SNR)
...............
PERFORMANCE (Network PERFORMANCE) :
Bandwidth: ( Bandwidth in Hertz and Bandwidth in Bits per Seconds) :
Throughput:
These above topics covered in this slide
Thanks You!
Distributed Mutual Exclusion and Distributed Deadlock DetectionSHIKHA GAUTAM
Distributed Mutual Exclusion: Classification of distributed mutual exclusion, requirement of mutual exclusion theorem, Token based and non token based algorithms. Distributed Deadlock Detection: system model, resource Vs communication deadlocks, deadlock prevention, avoidance, detection & resolution, centralized dead lock detection
Agreement Protocols, Distributed Resource Management: Issues in distributed File Systems, Mechanism for building distributed file systems, Design issues in Distributed Shared Memory, Algorithm for Implementation of Distributed Shared Memory.
File Replication : High availability is a desirable feature of a good distributed file system and file replication is the primary mechanism for improving file availability. Replication is a key strategy for improving reliability, fault tolerance and availability. Therefore duplicating files on multiple machines improves availability and performance.
Replicated file : A replicated file is a file that has multiple copies, with each copy located on a separate file server. Each copy of the set of copies that comprises a replicated file is referred to as replica of the replicated file.
Replication is often confused with caching, probably because they both deal with multiple copies of data. The two concepts has the following basic differences:
A replica is associated with server, whereas a cached copy is associated with a client.
The existence of cached copy is primarily dependent on the locality in file access patterns, whereas the existence of a replica normally depends on availability and performance requirements.
Satynarayanana [1992] distinguishes a replicated copy from a cached copy by calling the first-class replicas and second-class replicas respectively
In this we discuss about DATA RATE LIMITS
Two theoretical formulas were developed to calculate the data rate:
Nyquist bit rate for a noiseless channel
BitRate = 2 * bandwidth * log 2 L
2: Shannon Capacity for a noisy channel
Capacity = bandwidth * log 2 (1 + SNR)
...............
PERFORMANCE (Network PERFORMANCE) :
Bandwidth: ( Bandwidth in Hertz and Bandwidth in Bits per Seconds) :
Throughput:
These above topics covered in this slide
Thanks You!
Distributed Mutual Exclusion and Distributed Deadlock DetectionSHIKHA GAUTAM
Distributed Mutual Exclusion: Classification of distributed mutual exclusion, requirement of mutual exclusion theorem, Token based and non token based algorithms. Distributed Deadlock Detection: system model, resource Vs communication deadlocks, deadlock prevention, avoidance, detection & resolution, centralized dead lock detection
Agreement Protocols, Distributed Resource Management: Issues in distributed File Systems, Mechanism for building distributed file systems, Design issues in Distributed Shared Memory, Algorithm for Implementation of Distributed Shared Memory.
IBM MQ: Managing Workloads, Scaling and Availability with MQ ClustersDavid Ware
MQ Clustering can be used to solve many problems, from simplified administration and workload management in an MQ network, to horizontal scalability and continuous availability of messaging applications. This session will show the full range of uses of MQ Clusters to solve real problems, highlighting the underlying technology being used. A basic understanding of IBM MQ clustering would be beneficial.
What we've learned from running thousands of production RabbitMQ clusters - L...RabbitMQ Summit
Watch the full lecture on YouTube: https://www.youtube.com/watch?v=ez9kQEhHsnc&list=PLDUzG2yLXrU4Lz33ZzSdHyfqdHJ8Zum5A
Since 2012 CloudAMQP has been running dedicated and shared RabbitMQ clusters for customers around the world, in seven different clouds. In this talk Lovisa will address the most common misconception, misconfigurations and anti-patterns in RabbitMQ usage, and how they can be avoided. Lovisa will talk about how you can increase RabbitMQ reliability and performance and she will also mention common RabbitMQ use cases among CloudAMQP’s customers.
--
The first RabbitMQ Summit connected RabbitMQ users and developers from around the world in London on November 12, 2018. Learn what's happening in and around RabbitMQ, and how top companies utilize RabbitMQ to power their services.
https://www.rabbitmqsummit.com
RabbitMQ Summit was organized by:
- Erlang Solutions, offering world-leading RabbitMQ Consultancy, Support, Health Checks & Tuning solutions https://www.erlang-solutions.com/
- CloudAMQP, offering fully managed RabbitMQ clusters https://www.cloudamqp.com
RabbitMQ Summit 2018 was sponsored by the following companies.
Platinum sponsors:
Pivotal
LShift
Gold sponors:
Trifork
AWS
Silver sponsor:
Cogin Queue Explorer
Optimizing for performance and reducing latency is a hard problem. Examples could be: choosing a different algorithm and data structures, improving SQL queries, adding a cache, serving requests asynchronously, or some low-level optimization that requires a deep understanding of the OS, kernel, compiler, or the network stack. The engineering effort is usually nontrivial, and only if you're lucky, you'll see some tangible results.
That being said, there are some performance optimization techniques, with a few lines of code — even exist in the built-in library — it can lead to noticeable surprising results. One of these techniques is to "fail fast, retry soon". These techniques are often neglected or taken for granted.
In distributed systems, a service or a database consists of a fleet of nodes that functions as one unit. It is not uncommon for some nodes to go down, usually, for a short time. When this occurs, failures can happen on the client-side and can lead to an outage. To build resilient systems, and reduce the probability of failure, we're going to explore these topics: timeouts, backoff, and jitter. We'll talk about timeouts, what timeout to set, pitfalls of retries, how backoff improves resource utilization, and jitters reduce congestion. Furthermore, we're going to see an adaptive mechanism to dynamically adjust these configurations.
This is inspired by a real-production use case where DynamoDB latency p99 & max went down from > 10s to ~500ms after employing these three techniques: timeouts, backoff, and jitter.
This is inspired by a real-production use case where DynamoDB latency p99 & max went down from > 10s to ~500ms. AWS articles, specifically M. Brooker’s writings, and SDKs code have been great resources to dive into these techniques:
- Timeouts, retries and backoff with jitter in the AWS Builder's Library, 2019 (https://aws.amazon.com/builders-library/timeouts-retries-and-backoff-with-jitter/)
- Exponential Backoff and Jitter on the AWS Architecture Blog, 2016 (https://aws.amazon.com/blogs/architecture/exponential-backoff-and-jitter/)
- Fixing retries with token buckets and circuit breakers, Marc's Blog, 2022 (https://brooker.co.za/blog/2022/02/28/retries.html)
Resilience4j is a lightweight fault tolerance library that provides a variety of fault tolerance and stability patterns to a web application. In this knolx session, we'll learn how to use this library with a simple Spring Boot application.
Basically everything you need to get started on your Zookeeper training, and setup apache Hadoop high availability with QJM setup with automatic failover.
The session will be about Twitter's RPC Library, Finagle. We well see why Finagle is a powerful library for asynchronous programming and will have a working implementation of simple use case.
This session is all about Reactive Messaging Patterns. Such messaging patterns are used to build message-driven systems. These systems are those that communicate primarily through asynchronous and non-blocking messages. Messages enable us to build systems that are both resilient, and elastic, and therefore responsive under a variety of situations.
This presentation contains the total understanging of Digital Certificate ,What is the need and what are the main types of Digital certificates available.
This presentation contains the information about the OpenVAS understanding installation procedure in Linux and also contains the Working and it's screen shots
Welcome to WIPAC Monthly the magazine brought to you by the LinkedIn Group Water Industry Process Automation & Control.
In this month's edition, along with this month's industry news to celebrate the 13 years since the group was created we have articles including
A case study of the used of Advanced Process Control at the Wastewater Treatment works at Lleida in Spain
A look back on an article on smart wastewater networks in order to see how the industry has measured up in the interim around the adoption of Digital Transformation in the Water Industry.
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.
Saudi Arabia stands as a titan in the global energy landscape, renowned for its abundant oil and gas resources. It's the largest exporter of petroleum and holds some of the world's most significant reserves. Let's delve into the top 10 oil and gas projects shaping Saudi Arabia's energy future in 2024.
Courier management system project report.pdfKamal Acharya
It is now-a-days very important for the people to send or receive articles like imported furniture, electronic items, gifts, business goods and the like. People depend vastly on different transport systems which mostly use the manual way of receiving and delivering the articles. There is no way to track the articles till they are received and there is no way to let the customer know what happened in transit, once he booked some articles. In such a situation, we need a system which completely computerizes the cargo activities including time to time tracking of the articles sent. This need is fulfilled by Courier Management System software which is online software for the cargo management people that enables them to receive the goods from a source and send them to a required destination and track their status from time to time.
Forklift Classes Overview by Intella PartsIntella Parts
Discover the different forklift classes and their specific applications. Learn how to choose the right forklift for your needs to ensure safety, efficiency, and compliance in your operations.
For more technical information, visit our website https://intellaparts.com
Automobile Management System Project Report.pdfKamal Acharya
The proposed project is developed to manage the automobile in the automobile dealer company. The main module in this project is login, automobile management, customer management, sales, complaints and reports. The first module is the login. The automobile showroom owner should login to the project for usage. The username and password are verified and if it is correct, next form opens. If the username and password are not correct, it shows the error message.
When a customer search for a automobile, if the automobile is available, they will be taken to a page that shows the details of the automobile including automobile name, automobile ID, quantity, price etc. “Automobile Management System” is useful for maintaining automobiles, customers effectively and hence helps for establishing good relation between customer and automobile organization. It contains various customized modules for effectively maintaining automobiles and stock information accurately and safely.
When the automobile is sold to the customer, stock will be reduced automatically. When a new purchase is made, stock will be increased automatically. While selecting automobiles for sale, the proposed software will automatically check for total number of available stock of that particular item, if the total stock of that particular item is less than 5, software will notify the user to purchase the particular item.
Also when the user tries to sale items which are not in stock, the system will prompt the user that the stock is not enough. Customers of this system can search for a automobile; can purchase a automobile easily by selecting fast. On the other hand the stock of automobiles can be maintained perfectly by the automobile shop manager overcoming the drawbacks of existing system.
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Water scarcity is the lack of fresh water resources to meet the standard water demand. There are two type of water scarcity. One is physical. The other is economic water scarcity.
2. Server Creation Semantics
● In RPC (Remote Procedure Call) a client process lies in a server process that
is totally independent of the client process. Independence here means that
the client and server processes have separate lifetimes, they normally run on
separate machines, and they have their own address spaces,Since a server
process is independent of a client process that makes a remote procedure
call to it.
● Server processes may either be created and installed before their client
processes or be created on a demand basis. Based on the time duration for
which RPC servers survive, they may be classified in 3 Types:
1. Instance-per-Call Servers
2. Instance-per-Session Servers
3. Persistent Servers
3. 1.Instance-per-Call Servers
● This Category of Servers exists only for the duration of single Call.
● A server of this type is created by RPC Runtime on the server machine only
when a call message arrives and deleted after the call has been executed.
4. Issues in Instance per Call Servers
This approach for server creation is not commonly used because of the following
problems associated with it:
1. Servers are Stateless
2. More expensive
5. 2.Instance-per-Sessions Servers
● This category of server exist for the entire session for which a client and a
server interact. Since a server of this type exists for the entire session.
● It can maintain intercall state information
7. Persistent Server
● A persistent server generally remains in existence indefinitely.
● Servers of this type are usually created and installed before the clients that
use them.
● Each server independently exports its service by registering itself with the
binding agent.
8. Working of Persistence Server
Server Manager
Service-1 Service-2 Service-3
Binding Agent
Client 1
Client 2
9. Advantages of Persistence Server
➢ Load balancing
➢ Shared by Many users
➢ High performance and reliability
10. Call Semantics
There are mainly 5 types of Call Semantics
1.Possibly or May-Be Call Semantics
2.Last-Once Call Semantics
3.Last-of-Many Call Semantics
4.At-Least-Once Call Semantics
5.Exactly-Once Call Semantics
11. 1.Possibly or May-Be Call Semantics
● This is the weakest semantics in which a timeout mechanism is used that
prevents the caller from waiting indefinitely for a response from the callee.
● This means that the caller waits until a predetermined timeout period and
then continues to execute.
● Hence this semantics does not guarantee the receipt of call message nor the
execution. This semantics is applicable where the response message is less
important and applications that operate within a local network with
successful transmission of messages.
12. 2.Last-One Call Semantics
● This call semantics uses the idea of retransmitting the call message based on
timeouts until the caller receives a response.
● The call execution and result of will keep repeating until the result of
procedure execution is received by the caller.
● The results of the last executed call are used by the caller, hence it known as
last-one semantics.
● Last one semantics can be easily achieved only when two nodes are involved
in the RPC, but it is tricky to implement it for nested RPCs and cases by
orphan calls.
13. 3.Last-Of-Many call semantics
● This semantics neglects orphan calls unlike last-once call semantics.
● Orphan call is one whose caller has expired due to node crash.
● To identify each call, unique call identifiers are used which to neglect orphan
calls.
● When a call is repeated, it is assigned to a new call identifier and each
response message has a corresponding call identifier.
● A response is accepted only if the call identifier associated with it matches
the identifier of the most recent call else it is ignored.
14. 4.At-Least-Once call Semantics
● This semantics guarantees that the call is executed one or more times but
does not specify which results are returned to the caller.
● It can be implemented using timeout based retransmission without
considering the orphan calls.
15. 5.Exactly-Once Call Semantics
● This is the strongest and the most desirable call semantics. It eliminates the
possibility of a procedure being executed more than once irrespective of the
number of retransmitted call.
● The implementation of exactly-once call semantics is based on the use of
timeouts, retransmission, call identifiers with the same identifier for repeated
calls and a reply cache associated with the callee.
