How to Start Distributed Computing Projects Using NS2

To start a Distributed Computing project in NS2 (Network Simulator 2), we will want to design the interaction in a distributed system among nodes to deliberate the network infrastructure and protocols, which permit the distributed computing. NS2 is robust network simulator and it does not have high-level and advanced distributed computing models but we can model the simulation for denoting distributed computing environment.

Below is a structured method to starting a Distributed Computing project using NS2:

Steps to Start Distributed Computing Project in NS2

  1. Install NS2

We make sure that NS2 installed on the system. We should download it through official NS2 website or utilities its repositories. Adhere to the provided installation instruction based on OS.

  • Download NS2 from: NS2 Website
  • We follow the installation steps depends on Ubuntu, MacOS, Windows, and so on.

Make sure we install Tcl (Tool Command Language) and OTcl, since they are crucial to inscribe and run the NS2 scripts.

  1. Understand the Key Concepts of Distributed Computing

Distributed Computing includes several computing nodes (computers) for resolving a problem or executing a task. The main concepts can replicate within NS2 project:

  • Nodes: In the distributed system, denote the computing machines or processes.
  • Communication Links: Signify the network connections among the nodes.
  • Task Distribution: To replicate the division of work (tasks) among diverse nodes.
  • Fault Tolerance and Synchronization: To manage failures and coordinate state through the nodes.
  • Distributed Algorithms: Replicating MapReduce, consensus protocols, or distributed databases mechanisms.
  1. Create a Network Topology in NS2

We create network topology using Tcl scripts in NS2. The topology signifies how the distributed nodes interact with each other. For instance, we will need to make a basic topology in which several nodes are associated through the switches or routers.

Example: Basic Distributed Network Topology

# Define the simulator

set ns [new Simulator]

# Create nodes representing distributed computing nodes

set node1 [$ns node]

set node2 [$ns node]

set node3 [$ns node]

set node4 [$ns node]

# Create links between the nodes with specified bandwidth and delay

$ns duplex-link $node1 $node2 10Mb 10ms DropTail

$ns duplex-link $node2 $node3 10Mb 10ms DropTail

$ns duplex-link $node3 $node4 10Mb 10ms DropTail

# Attach a TCP agent to each node to simulate task communication

set agent1 [new Agent/TCP]

$ns attach-agent $node1 $agent1

set agent2 [new Agent/TCP]

$ns attach-agent $node2 $agent2

set agent3 [new Agent/TCP]

$ns attach-agent $node3 $agent3

set agent4 [new Agent/TCP]

$ns attach-agent $node4 $agent4

# Start communication (simulating task transfer between nodes)

$ns connect $agent1 $agent2

$ns connect $agent2 $agent3

$ns connect $agent3 $agent4

# Set up routing and other configurations

$ns run

This example configures a simple distributed computing network including 4 nodes that are linked through TCP agents. We also want to alter this topology for exposing the certain use case like inserting additional nodes, routers, or different link bandwidths.

  1. Simulate Task Distribution (Job/Task Scheduling)

Distributed computing frequently splits a larger problem to smaller tasks and sharing those tasks for parallel execution to various nodes. In NS2, we will need to replicate this method by means of making custom agents or components, which denote the task distribution algorithm.

Example: Simulating Task Distribution

We can make a custom module to utilise OTcl for replicating the task distribution. Below is an instance of a simple task distribution agent:

# Define a custom task distribution agent

namespace eval TaskDistributor {

variable task_counter 0

# Function to distribute tasks to nodes

proc distributeTask {src dst task_data} {

set task_id [incr task_counter]

set task [new Packet]

$task set task_id $task_id

$task set data $task_data

$task set timestamp [timestamp]

# Send task to the destination node

$src send $task $dst

}

}

  • This TaskDistributor agent want to deliver tasks to various nodes. Every single task contains an ID, data, and timestamp.
  • The distributeTask function replicates transmit a task to another node like a packet.

Also, we should add it to the distributed computing network by means of transmitting tasks among the nodes with the support of distributeTask function.

  1. Simulate Fault Tolerance and Synchronization

In distributed computing, we need to manage node failures and make sure that synchronization is essential through nodes. In NS2, we can replicate these concepts to utilise timeouts and message passing.

Example: Simulating Fault Tolerance

We replicate a node failure by way of inactivating a node after a particular amount of time.

# Simulate node failure after 30 seconds

$ns at 30.0 “disable-node $node3”

Example: Synchronizing Nodes

Distributed systems frequently need nodes for coordinating its states. We need to replicate synchronization including barriers or synchronization messages.

# Simulate synchronization by sending a sync message to all nodes

namespace eval Sync {

proc synchronize {nodes} {

foreach node $nodes {

# Send sync message to each node

set sync_msg [new Packet]

$sync_msg set type “sync”

$sync_msg set timestamp [timestamp]

$node send $sync_msg

}

}

}

Then we request Sync::synchronize in the distributed system to coordinate the nodes.

  1. Simulate Distributed Algorithms

We will want to execute the distributed mechanisms for advanced simulations. For instance:

  • MapReduce: We can make MapReduce jobs, which divide the tasks and then distribute the sub-tasks to various nodes. Return the outcomes that are combined after the nodes execute its sub-tasks.
  • Consensus Algorithms: We execute the consensus algorithms such as Paxos or Raft in which nodes interact deciding on a value or decision.
  • Distributed Databases: Mimic replication and synchronization of data through the distributed database nodes.

We can inscribe custom agents for specifying these algorithms behavior.

  1. Configure Simulation Parameters

Set the simulation metrics like bandwidth, delay, and various protocols behavior within Tcl configuration script as .tcl file.

For example, we need to set the metrics in terms of task distribution rate, message size, or the network’s delay and bandwidth.

# Configure task distribution rate and message size

set task_distribution_interval 1s

set message_size 512 # in bytes

# Set network parameters (delay, bandwidth, etc.)

set ns [new Simulator]

$ns duplex-link $node1 $node2 10Mb 10ms DropTail

$ns queue-limit $node1 $node2 50

These configurations support to manage how tasks are shared, how often they are transmit, and then how the network performs in bandwidth, delay, and queueing.

  1. Run the Simulation

When the simulation is configured in the network topology, task distribution, fault tolerance, and synchronization algorithms then we can execute the simulation:

ns distributed_computing.tcl

It will run in Tcl script and make output files for advanced analysis.

  1. Analyze the Results

NS2 environment offers diverse tools to examine the simulation outcomes.

  • Generate Trace Files: Monitor the progress of tasks and message passing to utilise Trace files.
  • Analyse the network performance like latency, throughput, and task completion time to utilise ns2’s built-in tools for visualization.

Also, we obtain the statistics during the simulation from the records which are generated to estimate how successfully distributed system performs in various conditions.

  1. Extend and Customize the Simulation

After execute the basic simulation then we can prolong it to:

  • Replicate various distributed algorithms such as MapReduce, Paxos, Raft.
  • Integrate more complex task scheduling mechanisms like dynamic load balancing.
  • Replicate the node failures and recovery for estimating fault tolerance.
  • Design distributed databases and its replication algorithms.
  • Execute the consensus algorithms for managing distributed decision-making.

Conclusion

To start a Distributed Computing project using NS2 includes:

  1. To configure the network topology for specifying distributed computing nodes.
  2. Designing task distribution with the support of custom agents and protocols.
  3. To replicate fault tolerance, synchronization, and distributed algorithms.
  4. Set the simulation metrics such as bandwidth, delay, and task scheduling.
  5. Utilise trace files and built-in tools for executing the simulation and examining the outcomes.

Although NS2 is robust network simulator including appropriate custom scripting and agent design, we can replicate several distributed computing systems features and then measure its performance.

In this manual, you can simulate and estimate the Distributed Computing Projects within NS2 environment through above basic approach with sample coding. Further specifics details to be included in another guide.