Cristian's Algorithm is a clock synchronization algorithm is used to synchronize time with a time server by client processes. This algorithm works well with low-latency networks where Round Trip Time is short as compared to accuracy while redundancy-prone distributed systems/applications do not go hand in hand with this algorithm. Here Round Trip Time refers to the time duration between the start of a Request and the end of the corresponding Response.
Below is an illustration imitating the working of Cristian's algorithm:

Algorithm:
1) The process on the client machine sends the request for fetching clock time(time at the server) to the Clock Server at time T_0 .
2) The Clock Server listens to the request made by the client process and returns the response in form of clock server time.
3) The client process fetches the response from the Clock Server at time T_1 and calculates the synchronized client clock time using the formula given below.
\[ T_{CLIENT} = T_{SERVER} + (T_1 - T_0)/2 \]
where T_{CLIENT} refers to the synchronized clock time,
T_{SERVER} refers to the clock time returned by the server,
T_0 refers to the time at which request was sent by the client process,
T_1 refers to the time at which response was received by the client process
Working/Reliability of the above formula:
T_1 - T_0 refers to the combined time taken by the network and the server to transfer the request to the server, process the request, and return the response back to the client process, assuming that the network latency T_0 and T_1 are approximately equal.
The time at the client-side differs from actual time by at most (T_1 - T_0)/2 seconds. Using the above statement we can draw a conclusion that the error in synchronization can be at most (T_1 - T_0)/2 seconds.
Hence,
\[ error\, \epsilon\, [-(T_1 - T_0)/2, \, (T_1 - T_0)/2] \]
Python Codes below illustrate the working of Cristian's algorithm:
Code below is used to initiate a prototype of a clock server on local machine:
C++
// C++ equivalent
#include <iostream>
#include <string>
#include <chrono>
#include <ctime>
#include <sys/socket.h>
// Function used to initiate the Clock Server
void initiateClockServer() {
// Create socket
int socketfd = socket(AF_INET, SOCK_STREAM, 0);
std::cout << "Socket successfully created" << std::endl;
// Set port
int port = 8000;
// Bind socket to port
struct sockaddr_in server_addr;
server_addr.sin_family = AF_INET;
server_addr.sin_addr.s_addr = INADDR_ANY;
server_addr.sin_port = htons(port);
bind(socketfd, (struct sockaddr*)&server_addr, sizeof(server_addr));
std::cout << "Socket is listening..." << std::endl;
// Start listening to requests
listen(socketfd, 5);
// Clock Server Running forever
while (true) {
// Establish connection with client
struct sockaddr_in client_addr;
int client_len = sizeof(client_addr);
int connfd = accept(socketfd, (struct sockaddr*) &client_addr, (socklen_t*)&client_len);
std::cout << "Server connected to " << client_addr.sin_addr.s_addr << std::endl;
// Respond the client with server clock time
std::chrono::time_point<std::chrono::system_clock> now = std::chrono::system_clock::now();
std::time_t time = std::chrono::system_clock::to_time_t(now);
std::string time_str = std::ctime(&time);
send(connfd, time_str.c_str(), time_str.size(), 0);
// Close the connection with the client process
close(connfd);
}
}
// Driver function
int main() {
// Trigger the Clock Server
initiateClockServer();
return 0;
}
Java
import java.net.*;
import java.io.*;
import java.util.Date;
public class ClockServer {
// Function used to initiate the Clock Server
public static void initiateClockServer() throws IOException
{
// Create socket
ServerSocket serverSocket = new ServerSocket(8000);
System.out.println("Socket successfully created");
// Clock Server Running forever
while (true)
{
// Start listening to requests
System.out.println("Socket is listening...");
Socket clientSocket = serverSocket.accept();
System.out.println("Server connected to " + clientSocket.getInetAddress());
// Respond the client with server clock time
Date now = new Date();
String timeStr = now.toString();
OutputStream os = clientSocket.getOutputStream();
OutputStreamWriter osw = new OutputStreamWriter(os);
BufferedWriter bw = new BufferedWriter(osw);
bw.write(timeStr + "\n");
bw.flush();
// Close the connection with the client process
clientSocket.close();
}
}
// Driver function
public static void main(String[] args) throws IOException
{
// Trigger the Clock Server
initiateClockServer();
}
}
Python3
# Python3 program imitating a clock server
import socket
import datetime
# function used to initiate the Clock Server
def initiateClockServer():
s = socket.socket()
print("Socket successfully created")
# Server port
port = 8000
s.bind(('', port))
# Start listening to requests
s.listen(5)
print("Socket is listening...")
# Clock Server Running forever
while True:
# Establish connection with client
connection, address = s.accept()
print('Server connected to', address)
# Respond the client with server clock time
connection.send(str(
datetime.datetime.now()).encode())
# Close the connection with the client process
connection.close()
# Driver function
if __name__ == '__main__':
# Trigger the Clock Server
initiateClockServer()
C#
using System;
using System.Net;
using System.Net.Sockets;
using System.Text;
using System.Threading;
class Program
{
static void Main(string[] args)
{
// Trigger the Clock Server
initiateClockServer();
}
static void initiateClockServer()
{
// Create socket
Socket socketfd = new Socket(AddressFamily.InterNetwork, SocketType.Stream, ProtocolType.Tcp);
Console.WriteLine("Socket successfully created");
// Set port
int port = 8000;
// Bind socket to port
IPEndPoint serverAddr = new IPEndPoint(IPAddress.Any, port);
socketfd.Bind(serverAddr);
Console.WriteLine("Socket is listening...");
// Start listening to requests
socketfd.Listen(5);
// Clock Server Running forever
while (true)
{
// Establish connection with client
Socket clientSock = socketfd.Accept();
Console.WriteLine("Server connected to " + clientSock.RemoteEndPoint.ToString());
// Respond the client with server clock time
DateTime now = DateTime.Now;
string time_str = now.ToString();
byte[] time_bytes = Encoding.ASCII.GetBytes(time_str);
clientSock.Send(time_bytes);
// Close the connection with the client process
clientSock.Shutdown(SocketShutdown.Both);
clientSock.Close();
}
}
}
JavaScript
const net = require('net');
const port = 8000;
// function used to initiate the Clock Server
function initiateClockServer() {
const server = net.createServer(function(connection) {
console.log('Server connected to', connection.remoteAddress);
// Respond the client with server clock time
connection.write(new Date().toString());
// Close the connection with the client process
connection.end();
});
server.listen(port, function() {
console.log("Socket is listening...");
});
}
// Driver function
if (require.main === module) {
// Trigger the Clock Server
initiateClockServer();
}
// This code is contributed by rishab
Output:
Socket successfully created
Socket is listening...
Code below is used to initiate a prototype of a client process on the local machine:
Python3
# Python3 program imitating a client process
import socket
import datetime
from dateutil import parser
from timeit import default_timer as timer
# function used to Synchronize client process time
def synchronizeTime():
s = socket.socket()
# Server port
port = 8000
# connect to the clock server on local computer
s.connect(('127.0.0.1', port))
request_time = timer()
# receive data from the server
server_time = parser.parse(s.recv(1024).decode())
response_time = timer()
actual_time = datetime.datetime.now()
print("Time returned by server: " + str(server_time))
process_delay_latency = response_time - request_time
print("Process Delay latency: " \
+ str(process_delay_latency) \
+ " seconds")
print("Actual clock time at client side: " \
+ str(actual_time))
# synchronize process client clock time
client_time = server_time \
+ datetime.timedelta(seconds = \
(process_delay_latency) / 2)
print("Synchronized process client time: " \
+ str(client_time))
# calculate synchronization error
error = actual_time - client_time
print("Synchronization error : "
+ str(error.total_seconds()) + " seconds")
s.close()
# Driver function
if __name__ == '__main__':
# synchronize time using clock server
synchronizeTime()
Output:
Time returned by server: 2018-11-07 17:56:43.302379
Process Delay latency: 0.0005150819997652434 seconds
Actual clock time at client side: 2018-11-07 17:56:43.302756
Synchronized process client time: 2018-11-07 17:56:43.302637
Synchronization error : 0.000119 seconds
Improvision in Clock Synchronization:
Using iterative testing over the network, we can define a minimum transfer time using which we can formulate an improved synchronization clock time(less synchronization error).
Here, by defining a minimum transfer time, with a high confidence, we can say that the server time will
always be generated after T_0 + T_{min} and the T_{SERVER} will always be generated before T_1 - T_{min} , where T_{min} is the minimum transfer time which is the minimum value of T_{REQUEST} and T_{RESPONSE} during several iterative tests. Here synchronization error can be formulated as follows:
\[ error\, \epsilon\, [-((T_1 - T_0)/2 - T_{min}), \, ((T_1 - T_0)/2 - T_{min})] \]
Similarly, if T_{REQUEST} and T_{RESPONSE} differ by a considerable amount of time, we may substitute T_{min} by T_{min1} and T_{min2} , where T_{min1} is the minimum observed request time and T_{min2} refers to the minimum observed response time over the network.
The synchronized clock time in this case can be calculated as:
\[ T_{CLIENT} = T_{SERVER} + (T_1 - T_0)/2 + (T_{min2} - T_{min1})/2 \]
So, by just introducing response and request time as separate time latencies, we can improve the synchronization of clock time and hence decrease the overall synchronization error. A number of iterative tests to be run depends on the overall clock drift observed.
Advantages:
Simple and easy to implement: Cristian's Algorithm is a relatively simple algorithm and can be implemented easily on most computer systems.
Fast synchronization: The algorithm can synchronize the system clock with the time server quickly and efficiently.
Low network traffic: The algorithm requires only one round trip between the client and the server, which reduces network traffic and improves performance.
Works well for small networks: Cristian's Algorithm works well for small networks where the network latency is relatively low.
Disadvantages:
Requires a trusted time server: Cristian's Algorithm requires a trusted time server that provides accurate time information. If the time server is compromised or provides incorrect time information, it can lead to incorrect time synchronization.
Limited scalability: The algorithm is not suitable for large networks where the network latency can be high, as it may not be able to provide accurate time synchronization.
Not resilient to network failures: The algorithm does not handle network failures well, which can result in inaccurate time synchronization.
Vulnerable to malicious attacks: The algorithm is vulnerable to malicious attacks, such as man-in-the-middle attacks, which can lead to incorrect time synchronization.
References:
1) https://en.wikipedia.org/wiki/Cristian%27s_algorithm
2) https://en.wikipedia.org/wiki/Round-trip_delay_time
3) https://www.geeksforgeeks.org/socket-programming-python
4) https://en.wikipedia.org/wiki/Clock_drift
Similar Reads
Distributed Systems Tutorial A distributed system is a system of multiple nodes that are physically separated but linked together using the network. Each of these nodes includes a small amount of the distributed operating system software. Every node in this system communicates and shares resources with each other and handles pr
8 min read
Introduction to Distributed System
What is a Distributed System?A distributed system is a collection of independent computers that appear to the users of the system as a single coherent system. These computers or nodes work together, communicate over a network, and coordinate their activities to achieve a common goal by sharing resources, data, and tasks.Table o
7 min read
Features of Distributed Operating SystemA Distributed Operating System manages a network of independent computers as a unified system, providing transparency, fault tolerance, and efficient resource management. It integrates multiple machines to appear as a single coherent entity, handling complex communication, coordination, and scalabil
9 min read
Evolution of Distributed Computing SystemsIn this article, we will see the history of distributed computing systems from the mainframe era to the current day to the best of my knowledge. It is important to understand the history of anything in order to track how far we progressed. The distributed computing system is all about evolution from
8 min read
Types of Transparency in Distributed SystemIn distributed systems, transparency plays a pivotal role in abstracting complexities and enhancing user experience by hiding system intricacies. This article explores various types of transparencyâranging from location and access to failure and securityâessential for seamless operation and efficien
6 min read
What is Scalable System in Distributed System?In distributed systems, a scalable system refers to the ability of a networked architecture to handle increasing amounts of work or expand to accommodate growth without compromising performance or reliability. Scalability ensures that as demand growsâwhether in terms of user load, data volume, or tr
10 min read
Middleware in Distributed SystemIn distributed systems, middleware is a software component that provides services between two or more applications and can be used by them. Middleware can be thought of as an application that sits between two separate applications and provides service to both. In this article, we will see a role of
7 min read
Difference between Hardware and MiddlewareHardware and Middleware are both parts of a Computer. Hardware is the combination of physical components in a computer system that perform various tasks such as input, output, processing, and many more. Middleware is the part of software that is the communication medium between application and opera
4 min read
What is Groupware in Distributed System?Groupware in distributed systems refers to software designed to support collaborative activities among geographically dispersed users, enhancing communication, coordination, and productivity across diverse and distributed environments.Groupware in Distributed SystemImportant Topics for Groupware in
6 min read
Difference between Parallel Computing and Distributed ComputingIntroductionParallel Computing and Distributed Computing are two important models of computing that have important roles in todayâs high-performance computing. Both are designed to perform a large number of calculations breaking down the processes into several parallel tasks; however, they differ in
5 min read
Difference between Loosely Coupled and Tightly Coupled Multiprocessor SystemWhen it comes to multiprocessor system architecture, there is a very fine line between loosely coupled and tightly coupled systems, and this is why that difference is very important when choosing an architecture for a specific system. A multiprocessor system is a system in which there are two or mor
5 min read
Design Issues of Distributed SystemDistributed systems are used in many real-world applications today, ranging from social media platforms to cloud storage services. They provide the ability to scale up resources as needed, ensure data is available even when a computer fails, and allow users to access services from anywhere. However,
8 min read
Introduction to Distributed Computing Environment (DCE)The Benefits of Distributed Systems have been widely recognized. They are due to their ability to Scale, Reliability, Performance, Flexibility, Transparency, Resource-sharing, Geo-distribution, etc. In order to use the advantages of Distributed Systems, appropriate support and environment are needed
3 min read
Limitations of Distributed SystemsDistributed systems are essential for modern computing, providing scalability and resource sharing. However, they face limitations such as complexity in management, performance bottlenecks, consistency issues, and security vulnerabilities. Understanding these challenges is crucial for designing robu
8 min read
Various Failures in Distributed SystemDSM implements distributed systems shared memory model in an exceedingly distributed system, that hasnât any physically shared memory. The shared model provides a virtual address space shared between any numbers of nodes. The DSM system hides the remote communication mechanism from the appliance aut
3 min read
Types of Operating SystemsOperating Systems can be categorized according to different criteria like whether an operating system is for mobile devices (examples Android and iOS) or desktop (examples Windows and Linux). Here, we are going to classify based on functionalities an operating system provides.8 Main Operating System
11 min read
Types of Distributed SystemPre-requisites: Distributed System A Distributed System is a Network of Machines that can exchange information with each other through Message-passing. It can be very useful as it helps in resource sharing. It enables computers to coordinate their activities and to share the resources of the system
8 min read
Centralized vs. Decentralized vs. Distributed SystemsUnderstanding the architecture of systems is crucial for designing efficient and effective solutions. Centralized, decentralized, and distributed systems each offer unique advantages and challenges. Centralized systems rely on a single point of control, providing simplicity but risking a single poin
8 min read
Three-Tier Client Server Architecture in Distributed SystemThe Three-Tier Client-Server Architecture divides systems into presentation, application, and data layers, increasing scalability, maintainability, and efficiency. By separating the concerns, this model optimizes resource management and allows for independent scaling and updates, making it a popular
7 min read
Communication in Distributed Systems
Remote Procedure Calls in Distributed System
What is Remote Procedural Call (RPC) Mechanism in Distributed System?A remote Procedure Call (RPC) is a protocol in distributed systems that allows a client to execute functions on a remote server as if they were local. RPC simplifies network communication by abstracting the complexities, making it easier to develop and integrate distributed applications efficiently.
9 min read
Distributed System - Transparency of RPCRPC is an effective mechanism for building client-server systems that are distributed. RPC enhances the power and ease of programming of the client/server computing concept. A transparent RPC is one in which programmers can not tell the difference between local and remote procedure calls. The most d
3 min read
Stub Generation in Distributed SystemA stub is a piece of code that translates parameters sent between the client and server during a remote procedure call in distributed computing. An RPC's main purpose is to allow a local computer (client) to call procedures on another computer remotely (server) because the client and server utilize
3 min read
Marshalling in Distributed SystemA Distributed system consists of numerous components located on different machines that communicate and coordinate operations to seem like a single system to the end-user.External Data Representation:Data structures are used to represent the information held in running applications. The information
9 min read
Server Management in Distributed SystemEffective server management in distributed systems is crucial for ensuring performance, reliability, and scalability. This article explores strategies and best practices for managing servers across diverse environments, focusing on configuration, monitoring, and maintenance to optimize the operation
12 min read
Distributed System - Parameter Passing Semantics in RPCA Distributed System is a Network of Machines that can exchange information with each other through Message-passing. It can be very useful as it helps in resource sharing. In this article, we will go through the various Parameter Passing Semantics in RPC in distributed Systems in detail. Parameter P
4 min read
Distributed System - Call Semantics in RPCThis article will go through the Call Semantics, its types, and the issues in RPC in distributed systems in detail. RPC has the same semantics as a local procedure call, the calling process calls the procedure, gives inputs to it, and then waits while it executes. When the procedure is finished, it
3 min read
Communication Protocols For RPCsThis article will go through the concept of Communication protocols for Remote Procedure Calls (RPCs) in Distributed Systems in detail. Communication Protocols for Remote Procedure Calls:The following are the communication protocols that are used: Request ProtocolRequest/Reply ProtocolThe Request/Re
5 min read
Client-Server ModelThe Client-Server Model is a distributed application architecture that divides tasks or workloads between servers (providers of resources or services) and clients (requesters of those services). In this model, a client sends a request to a server for data, which is typically processed on the server
6 min read
Lightweight Remote Procedure Call in Distributed SystemLightweight Remote Procedure Call is a communication facility designed and optimized for cross-domain communications in microkernel operating systems. For achieving better performance than conventional RPC systems, LRPC uses the following four techniques: simple control transfer, simple data transfe
5 min read
Difference Between RMI and DCOMIn this article, we will see differences between Remote Method Invocation(RMI) and Distributed Component Object Model(DCOM). Before getting into the differences, let us first understand what each of them actually means. RMI applications offer two separate programs, a server, and a client. There are
2 min read
Difference between RPC and RMIRPC stands for Remote Procedure Call which supports procedural programming. It's almost like an IPC mechanism wherever the software permits the processes to manage shared information Associated with an environment wherever completely different processes area unit death penalty on separate systems an
2 min read
Synchronization in Distributed System
Synchronization in Distributed SystemsSynchronization in distributed systems is crucial for ensuring consistency, coordination, and cooperation among distributed components. It addresses the challenges of maintaining data consistency, managing concurrent processes, and achieving coherent system behavior across different nodes in a netwo
11 min read
Logical Clock in Distributed SystemIn distributed systems, ensuring synchronized events across multiple nodes is crucial for consistency and reliability. Enter logical clocks, a fundamental concept that orchestrates event ordering without relying on physical time. By assigning logical timestamps to events, these clocks enable systems
10 min read
Lamport's Algorithm for Mutual Exclusion in Distributed SystemPrerequisite: Mutual exclusion in distributed systems Lamport's Distributed Mutual Exclusion Algorithm is a permission based algorithm proposed by Lamport as an illustration of his synchronization scheme for distributed systems. In permission based timestamp is used to order critical section request
5 min read
Vector Clocks in Distributed SystemsVector clocks are a basic idea in distributed systems to track the partial ordering of events and preserve causality across various nodes. Vector clocks, in contrast to conventional timestamps, offer a means of establishing the sequence of events even when there is no world clock, which makes them e
10 min read
Event Ordering in Distributed SystemIn this article, we will look at how we can analyze the ordering of events in a distributed system. As we know a distributed system is a collection of processes that are separated in space and which can communicate with each other only by exchanging messages this could be processed on separate compu
4 min read
Mutual exclusion in distributed systemMutual exclusion is a concurrency control property which is introduced to prevent race conditions. It is the requirement that a process can not enter its critical section while another concurrent process is currently present or executing in its critical section i.e only one process is allowed to exe
5 min read
Performance Metrics For Mutual Exclusion AlgorithmMutual exclusion is a program object that refers to the requirement of satisfying that no two concurrent processes are in a critical section at the same time. It is presented to intercept the race condition. If a current process is accessing the critical section then it prevents entering another con
4 min read
Cristian's AlgorithmCristian's Algorithm is a clock synchronization algorithm is used to synchronize time with a time server by client processes. This algorithm works well with low-latency networks where Round Trip Time is short as compared to accuracy while redundancy-prone distributed systems/applications do not go h
8 min read
Berkeley's AlgorithmBerkeley's Algorithm is a clock synchronization technique used in distributed systems. The algorithm assumes that each machine node in the network either doesn't have an accurate time source or doesn't possess a UTC server.Algorithm 1) An individual node is chosen as the master node from a pool node
6 min read
Difference between Token based and Non-Token based Algorithms in Distributed SystemA distributed system is a system in which components are situated in distinct places, these distinct places refer to networked computers which can easily communicate and coordinate their tasks by just exchanging asynchronous messages with each other. These components can communicate with each other
3 min read
RicartâAgrawala Algorithm in Mutual Exclusion in Distributed SystemPrerequisite: Mutual exclusion in distributed systems RicartâAgrawala algorithm is an algorithm for mutual exclusion in a distributed system proposed by Glenn Ricart and Ashok Agrawala. This algorithm is an extension and optimization of Lamport's Distributed Mutual Exclusion Algorithm. Like Lamport'
3 min read
SuzukiâKasami Algorithm for Mutual Exclusion in Distributed SystemPrerequisite: Mutual exclusion in distributed systems SuzukiâKasami algorithm is a token-based algorithm for achieving mutual exclusion in distributed systems.This is modification of RicartâAgrawala algorithm, a permission based (Non-token based) algorithm which uses REQUEST and REPLY messages to en
3 min read
Source Management and Process Management
Distributed File System and Distributed shared memory
What is DFS (Distributed File System)? A Distributed File System (DFS) is a file system that is distributed on multiple file servers or multiple locations. It allows programs to access or store isolated files as they do with the local ones, allowing programmers to access files from any network or computer. In this article, we will discus
8 min read
Andrew File SystemThe Andrew File System (AFS) is a distributed file system that allows multiple computers to share files and data seamlessly. It was developed by Morris ET AL. in 1986 at Carnegie Mellon University in collaboration with IBM. AFS was designed to make it easier for people working on different computers
5 min read
File Service Architecture in Distributed SystemFile service architecture in distributed systems manages and provides access to files across multiple servers or locations. It ensures efficient storage, retrieval, and sharing of files while maintaining consistency, availability, and reliability. By using techniques like replication, caching, and l
12 min read
File Models in Distributed SystemFile Models in Distributed Systems" explores how data organization and access methods impact efficiency across networked nodes. This article examines structured and unstructured models, their performance implications, and the importance of scalability and security in modern distributed architectures
6 min read
File Accessing Models in Distributed SystemIn Distributed File Systems (DFS), multiple machines are used to provide the file systemâs facility. Different file system utilize different conceptual models of a file. The two most usually involved standards for file modeling are structure and modifiability. File models in view of these standards
4 min read
File Caching in Distributed File SystemsFile caching enhances I/O performance because previously read files are kept in the main memory. Because the files are available locally, the network transfer is zeroed when requests for these files are repeated. Performance improvement of the file system is based on the locality of the file access
12 min read
What is Replication in Distributed System?Replication in distributed systems involves creating duplicate copies of data or services across multiple nodes. This redundancy enhances system reliability, availability, and performance by ensuring continuous access to resources despite failures or increased demand.Replication in Distributed Syste
9 min read
Atomic Commit Protocol in Distributed SystemIn distributed systems, transactional consistency is guaranteed by the Atomic Commit Protocol. It coordinates two phasesâvoting and decisionâto ensure that a transaction is either fully committed or completely canceled on several nodes. Distributed TransactionsDistributed transaction refers to a tra
4 min read
Design Principles of Distributed File SystemA distributed file system is a computer system that allows users to store and access data from multiple computers in a network. It is a way to share information between different computers and is used in data centers, corporate networks, and cloud computing. Despite their importance, the design of d
6 min read
What is Distributed Shared Memory and its Advantages?Distributed shared memory can be achieved via both software and hardware. Hardware examples include cache coherence circuits and network interface controllers. In contrast, software DSM systems implemented at the library or language level are not transparent and developers usually have to program th
4 min read
Architecture of Distributed Shared Memory(DSM)Distributed Shared Memory (DSM) implements the distributed systems shared memory model in a distributed system, that hasnât any physically shared memory. Shared model provides a virtual address area shared between any or all nodes. To beat the high forged of communication in distributed system. DSM
3 min read
Difference between Uniform Memory Access (UMA) and Non-uniform Memory Access (NUMA)In computer architecture, and especially in Multiprocessors systems, memory access models play a critical role that determines performance, scalability, and generally, efficiency of the system. The two shared-memory models most frequently used are UMA and NUMA. This paper deals with these shared-mem
5 min read
Algorithm for implementing Distributed Shared MemoryDistributed shared memory(DSM) system is a resource management component of distributed operating system that implements shared memory model in distributed system which have no physically shared memory. The shared memory model provides a virtual address space which is shared by all nodes in a distri
3 min read
Consistency Model in Distributed SystemIt might be difficult to guarantee that all data copies in a distributed system stay consistent over several nodes. The guidelines for when and how data updates are displayed throughout the system are established by consistency models. Various approaches, including strict consistency or eventual con
6 min read
Distributed System - Thrashing in Distributed Shared MemoryIn this article, we are going to understand Thrashing in a distributed system. But before that let us understand what a distributed system is and why thrashing occurs. In naive terms, a distributed system is a network of computers or devices which are at different places and linked together. Each on
4 min read
Distributed Scheduling and Deadlock
Scheduling and Load Balancing in Distributed SystemIn this article, we will go through the concept of scheduling and load balancing in distributed systems in detail. Scheduling in Distributed Systems:The techniques that are used for scheduling the processes in distributed systems are as follows: Task Assignment Approach: In the Task Assignment Appro
7 min read
Issues Related to Load Balancing in Distributed SystemThis article explores critical challenges and considerations in load balancing within distributed systems. Addressing factors like workload variability, network constraints, scalability needs, and algorithmic complexities are essential for optimizing performance and resource utilization across distr
6 min read
Components of Load Distributing Algorithm - Distributed SystemsIn distributed systems, efficient load distribution is crucial for maintaining performance, reliability, and scalability. Load-distributing algorithms play a vital role in ensuring that workloads are evenly spread across available resources, preventing bottlenecks, and optimizing resource utilizatio
6 min read
Distributed System - Types of Distributed DeadlockA Deadlock is a situation where a set of processes are blocked because each process is holding a resource and waiting for another resource occupied by some other process. When this situation arises, it is known as Deadlock. DeadlockA Distributed System is a Network of Machines that can exchange info
4 min read
Deadlock Detection in Distributed SystemsPrerequisite - Deadlock Introduction, deadlock detection In the centralized approach of deadlock detection, two techniques are used namely: Completely centralized algorithm and Ho Ramamurthy algorithm (One phase and Two-phase). Completely Centralized Algorithm - In a network of n sites, one site is
2 min read
Conditions for Deadlock in Distributed SystemThis article will go through the concept of conditions for deadlock in distributed systems. Deadlock refers to the state when two processes compete for the same resource and end up locking the resource by one of the processes and the other one is prevented from acquiring that resource. Consider the
7 min read
Deadlock Handling Strategies in Distributed SystemDeadlocks in distributed systems can severely disrupt operations by halting processes that are waiting for resources held by each other. Effective handling strategiesâdetection, prevention, avoidance, and recoveryâare essential for maintaining system performance and reliability. This article explore
11 min read
Deadlock Prevention Policies in Distributed SystemA Deadlock is a situation where a set of processes are blocked because each process is holding a resource and waiting for a resource that is held by some other process. There are four necessary conditions for a Deadlock to happen which are: Mutual Exclusion: There is at least one resource that is no
4 min read
Chandy-Misra-Haas's Distributed Deadlock Detection AlgorithmChandy-Misra-Haas's distributed deadlock detection algorithm is an edge chasing algorithm to detect deadlock in distributed systems. In edge chasing algorithm, a special message called probe is used in deadlock detection. A probe is a triplet (i, j, k) which denotes that process Pi has initiated the
4 min read
Security in Distributed System
Security in Distributed SystemSecuring distributed systems is crucial for ensuring data integrity, confidentiality, and availability across interconnected networks. Key measures include implementing strong authentication mechanisms, like multi-factor authentication (MFA), and robust authorization controls such as role-based acce
9 min read
Types of Cyber AttacksCyber Security is a procedure and strategy associated with ensuring the safety of sensitive information, PC frameworks, systems, and programming applications from digital assaults. Cyber assaults is general phrasing that covers an enormous number of themes, however, some of the common types of assau
10 min read
Cryptography and its TypesCryptography is a technique of securing information and communications using codes to ensure confidentiality, integrity and authentication. Thus, preventing unauthorized access to information. The prefix "crypt" means "hidden" and the suffix "graphy" means "writing". In Cryptography, the techniques
8 min read
Implementation of Access Matrix in Distributed OSAs earlier discussed access matrix is likely to be very sparse and takes up a large chunk of memory. Therefore direct implementation of access matrix for access control is storage inefficient. The inefficiency can be removed by decomposing the access matrix into rows or columns.Rows can be collapsed
5 min read
Digital Signatures and CertificatesDigital signatures and certificates are two key technologies that play an important role in ensuring the security and authenticity of online activities. They are essential for activities such as online banking, secure email communication, software distribution, and electronic document signing. By pr
11 min read
Design Principles of Security in Distributed SystemDesign Principles of Security in Distributed Systems explores essential strategies to safeguard data integrity, confidentiality, and availability across interconnected nodes. This article addresses the complexities and critical considerations for implementing robust security measures in distributed
11 min read
Distributed Multimedia and Database System
Distributed Database SystemA distributed database is basically a database that is not limited to one system, it is spread over different sites, i.e, on multiple computers or over a network of computers. A distributed database system is located on various sites that don't share physical components. This may be required when a
5 min read
Functions of Distributed Database SystemDistributed database systems play an important role in modern data management by distributing data across multiple nodes. This article explores their functions, including data distribution, replication, query processing, and security, highlighting how these systems optimize performance, ensure avail
10 min read
Multimedia DatabaseA Multimedia database is a collection of interrelated multimedia data that includes text, graphics (sketches, drawings), images, animations, video, audio etc and have vast amounts of multisource multimedia data. The framework that manages different types of multimedia data which can be stored, deliv
5 min read