To simulate Vehicular Named Data Networking (NDN) projects in MATLAB has includes to designing the communication in a vehicular environment in which the content is requested and transmitted according to content names instead of long-established IP addresses. In a vehicular NDN (VNDN) network, vehicles interchange Interest and Data packets to request and recover content, creating it an interesting and dynamic environment for research.
Here is a step-by-step guide to simulate Vehicular NDN (VNDN) projects using MATLAB:
Steps to Simulate Vehicular NDN Projects in MATLAB
Step 1: Understand the VNDN Architecture
In Vehicular NDN, interaction happens among vehicles (nodes) according to the following conditon:
- Interest Packets: Vehicles transmit interest packets to request the certain content by name.
- Data Packets: Once the content is situated, data packets are transmit back to the requester beside the reverse path.
- Content Store (CS): Vehicles cache received content for upcoming requests to minimize redundancy and enhance performance.
- Pending Interest Table (PIT): Equip the names of requested content that hasn’t yet been satisfied.
- Forwarding Information Base (FIB): Utilized to forward interest packets in the direction of possible data sources.
Step 2: Set Up the Environment
We will utilize MATLAB to design the network, the mobility of vehicles, and the interchange of Interest/Data packets. MATLAB’s Communications Toolbox can be utilized for wireless communication modelling, since simple vehicle mobility design can be executed using 2D or 3D positions.
Step 3: Define Vehicular Network Topology
Describe a set of vehicles transferring on a road network. Each vehicle signifies a node in the NDN-based vehicular network.
% Define the number of vehicles
num_vehicles = 10;
% Define initial positions of vehicles (random positions along a straight road)
vehicle_positions = [linspace(0, 100, num_vehicles)’, rand(num_vehicles, 1) * 5]; % [X, Y] positions
% Define vehicle speed (random speeds)
vehicle_speeds = rand(num_vehicles, 1) * 20 + 10; % Speeds between 10 and 30 m/s
Step 4: Implement Vehicle Mobility
To replicate the movement, update vehicle positions over time according to their speed and direction.
% Time step for the simulation
dt = 0.1; % Time step in seconds
% Update positions of vehicles over time
for t = 1:1000 % Simulate for 1000 time steps
vehicle_positions(:, 1) = vehicle_positions(:, 1) + vehicle_speeds * dt; % Update X position
end
Step 5: Implement NDN Packet Exchange
We required replicating the interchange of Interest and Data packets among vehicles according to proximity and content names.
- Interest Packet Generation: Vehicles create Interest packets to request content.
- Interest Packet Forwarding: Interest packets are sends to neighboring vehicles using a Forwarding Information Base (FIB).
- Data Packet Transmission: Once content is established, Data packets are transmit back along the opposite path.
% Example: Interest Packet Structure
interest_packet = struct(‘content_name’, ‘Video1’, ‘source_vehicle’, 1);
% Example: Data Packet Structure
data_packet = struct(‘content_name’, ‘Video1’, ‘data’, ‘Content Data’, ‘source_vehicle’, 1);
% Example: Forward Interest Packet
function forward_interest(interest_packet, vehicle_id, vehicles, comm_range)
% Find neighboring vehicles within communication range
for i = 1:length(vehicles)
if i ~= vehicle_id && pdist2(vehicles(vehicle_id, :), vehicles(i, :)) < comm_range
% Forward the interest packet to the neighboring vehicle
receive_interest(i, interest_packet);
end
end
end
% Example: Receive Interest Packet
function receive_interest(vehicle_id, interest_packet)
% Check if the content is in the Content Store (CS)
if is_in_content_store(vehicle_id, interest_packet.content_name)
send_data_packet(vehicle_id, interest_packet.source_vehicle, interest_packet.content_name);
else
% Forward the interest packet if the content is not found
forward_interest(interest_packet, vehicle_id, vehicle_positions, 50); % Communication range of 50 meters
end
end
Step 6: Implement the Content Store (CS)
Each vehicle stores beforehand the requested data to assist advanced upcoming requests. Usage a cache to mimic the content store.
% Example: Content Store Implementation
content_store = containers.Map(); % Each vehicle has a content store (cache)
% Function to check if the content is in the content store
function in_cs = is_in_content_store(vehicle_id, content_name)
global content_store;
if isKey(content_store, content_name)
in_cs = true;
else
in_cs = false;
end
end
% Function to cache content
function cache_content(vehicle_id, content_name, data)
global content_store;
content_store(content_name) = data;
end
Step 7: Implement Forwarding Information Base (FIB)
The FIB has includes to forwarding rules to forward Interest packets to neighbours who are possible to have the requested data.
% Example: Forwarding Information Base (FIB)
FIB = containers.Map();
% Function to forward Interest based on FIB
function next_hop = get_fib_entry(vehicle_id, content_name)
global FIB;
if isKey(FIB, content_name)
next_hop = FIB(content_name); % Forward to the next hop
else
next_hop = [];
end
end
Step 8: Implement Routing and Data Packet Transmission
Once the data is placed, Data packets are transmit back to the requester. Routing can be as basic as transmitting the data back beside the reverse path kept in the Pending Interest Table (PIT).
% Example: Send Data Packet
function send_data_packet(vehicle_id, destination_id, content_name)
global content_store;
data_packet = struct(‘content_name’, content_name, ‘data’, content_store(content_name), ‘source_vehicle’, vehicle_id);
% Forward the data packet back to the requester
forward_data(destination_id, data_packet);
end
% Example: Forward Data Packet
function forward_data(vehicle_id, data_packet)
% Check if the vehicle is the destination
if vehicle_id == data_packet.source_vehicle
disp(‘Data received at destination’);
else
% Forward the data packet to the next hop
next_hop = get_fib_entry(vehicle_id, data_packet.content_name);
forward_data(next_hop, data_packet);
end
end
Step 9: Simulate Traffic and Requests
Create random content requests from vehicles and replicate the interchange of Interest/Data packets.
% Simulate content requests
for t = 1:1000
% Each vehicle randomly generates an Interest packet
for i = 1:num_vehicles
content_name = [‘Video’, num2str(randi([1 10]))]; % Randomly request Video1 to Video10
interest_packet = struct(‘content_name’, content_name, ‘source_vehicle’, i);
forward_interest(interest_packet, i, vehicle_positions, 50);
end
end
Step 10: Visualize Vehicle Movements and Communication
We can utilize MATLAB’s plotting functions to envision the vehicle movements and the interaction among vehicles.
% Visualize vehicle movements and communication links
figure;
hold on;
for t = 1:1000
clf;
plot(vehicle_positions(:, 1), vehicle_positions(:, 2), ‘bo’); % Plot vehicle positions
for i = 1:num_vehicles
for j = i+1:num_vehicles
if pdist2(vehicle_positions(i, :), vehicle_positions(j, :)) < 50
plot([vehicle_positions(i, 1), vehicle_positions(j, 1)], …
[vehicle_positions(i, 2), vehicle_positions(j, 2)], ‘r-‘); % Communication link
end
end
end
pause(0.1); % Pause for visualization
end
Step 11: Evaluate Performance
Measure the parameters like:
- Content Retrieval Time: Time taken to recover content for an Interest.
- Cache Hit Ratio: Percentage of content requests functioned from the cache.
- Packet Delivery Ratio (PDR): Ratio of successfully delivered data packets to the total amount of requested packets.
% Example: Calculate Cache Hit Ratio
function hit_ratio = calculate_cache_hit_ratio(total_requests, cache_hits)
hit_ratio = cache_hits / total_requests;
end
Step 12: Run the Simulation
After configuring all the components, we can execute the simulation and learn on how the vehicular NDN network act as in different conditions, like changing vehicle densities, mobility patterns, or communication ranges.
Overall the simulation will be successfully demonstrated and illustrated for Vehicular Named Data Networking with the help of MATLAB tool that has contain brief procedures along with code snippets. If you did like to know more information we will offered it.
If you are looking for best simulation and novel topics for your Vehicular NDN Projects Using MATLAB for your research, then we will provide you with customized support. Stay in touch with us we are glad to give you best research assistance.
