Found 10 Articles for Distributed Systems

Introduction In context of distributed systems, exception handling refers to process of detecting, diagnosing, and recovering from errors that occur in a distributed system. In such systems, errors can occur at any point in communication and coordination process, including network failures, hardware malfunctions, and software bugs. Thus, effective exception handling is crucial to ensure reliability and availability of a distributed system. In this article, we will explore various techniques and best practices for exception handling in distributed systems. Importance of Exception Handling in Distributed Systems In a distributed system, multiple processes run on different machines and communicate with each other ... Read More

Introduction Distributed computing systems refer to a network of interconnected devices that share resources and work together to achieve a common goal. evolution of distributed computing systems has been rapid, and it has transformed way we use technology in our daily lives. From simple file sharing systems to advanced cloud computing, distributed computing systems have come a long way. In this article, we will discuss evolution of distributed computing systems and explore some of examples. Early Days of Distributed Computing The early days of distributed computing can be traced back to 1960s, where researchers began experimenting with idea of sharing ... Read More

Introduction Distributed systems have become an integral part of our modern-day technological infrastructure. They have made it possible to deliver services at scale, provide better resilience, and enable better fault tolerance. However, designing distributed systems is a challenging task, and one of most significant challenges is maintaining ordering of events in system. This article will discuss event ordering in distributed systems and provide examples of different techniques used to achieve it. Event Ordering Event ordering is essential in distributed systems because it determines order in which events occur. In a distributed system, events can happen concurrently on different nodes, and ... Read More

Raymond’s tree-based algorithm is used to protect the distributed systems from the occurrence of sections by the lock method. Distributed systems are networks with numerous numbers of nodes that involves the message flow from one node to another. When the process is locked or in the critical section, then only one thread or process can be allowed inside and other threads will be in the waiting state. As there are many nodes involved in the distributed systems, it can be reduced by spanning trees.Raymond’s Tree Based Algorithm Definition The Algorithm follows the method that only the threads with tokens are ... Read More

Deadlock in an operating system happens when a process gets into a waiting state as other processes hold the resources which need to be used. This problem generally happens during multi-processing environments, distributes systems, and parallel computation systems. In distributed systems, deadlocks are considered the major problem, where the resources requested by the process are not available due to other processes holding onto it. A distributed system contains a set of processes p1, p2, p3…pn that do not share a common memory, and communication is made only by passing messages through the network. This does not have a global clock ... Read More

Distributed Consensus Distributed consensus plays a vital role in decentralized systems, ensuring reliability, fault tolerance, and agreement among multiple parties. Distributed consensus occurs when multiple parties try to accept some values, which is difficult as agreeing is not easy. The complexity to achieve consensus increases as an increase in the number of parties agree on an agreement. Various sites are working together to do a common task by communicating with each other via a network and agreeing to some values which come under distributed consensus. Importance of Distributed Consensus in Distributed Systems In a distributed or decentralized multi−agent platform, ... Read More

Distributed systems are computing systems composed of multiple interconnected nodes that work together to perform a unified task. In such systems, algorithms play a crucial role in coordinating and managing the distributed resources efficiently. One fundamental aspect of these algorithms is the method they employ to control access to shared resources, known as synchronization. Two commonly used approaches for synchronization in distributed systems are token-based and non-token-based algorithms. In this discussion, we will explore the key differences between these two types of algorithms and their implications in distributed systems. What are Token-based Algorithms? Token-based algorithms use a token as a ... Read More

In this article, we will discuss the different methodologies like waterfall, agile and DevOps methodologies. We will also compare them in tabular format. Large Scale Distributed Systems Large-scale distributed systems have large amounts of data, many concurrent users, scalability requirements, and throughput requirements such as latency, etc. So, We need methods that can help developers and engineers efficiently. This can build and manage these Large-scale distributed systems. In large scale distributed systems, there are various challenges and the major challenge is that the platform has become huge. So it is not able to meet all these needs present in the ... Read More

In this article, we will study the Transparency of RPC in distributed Networks. Communication between different nodes is essential in a distributed network to achieve the desired functionality. RPC also called a Remote Procedure Call allows communication between different nodes or systems. RPC can be termed as a protocol that one program uses to execute the programs on remote servers as if that program was located locally. But RPC transparency is sometimes critical to the success of distributed networks. RPC can also be defined as a function call used by one program to request a service from another program. These ... Read More

The PACELC theorem is a fundamental concept in distributed systems that deals with the trade-offs between consistency, availability, latency, partition tolerance, durability, and efficiency. This theorem was introduced in the early 2000s and has since become a cornerstone of modern distributed system design. In this article, we will discuss the PACELC theorem in depth, exploring each of its components and how they are related to one another. We will also talk about how the theorem affects the design and implementation of distributed systems. Consistency A distributed system's consistency guarantees that all nodes in the system have the same view of ... Read More