MANET NS3 PROJECTS

MANET NS3 PROJECTS is an important network simulator used to evaluate various network applications based scenario in wired and wireless network. We offer M.Tech network simulation 3 projects are develop also for M.Tech students with ECE and also CSE domain. We also develop Manet based various application for M.Tech students. Also, We implement various network application based on Elsevier paper with NS3 simulation. We also develop fuzzy logic based application with MANET network structure and NS3 simulation model. So We apply fuzzy logic method also in wireless sensor network and mesh network.

MANET NS3 PROJECTS:

We also implement various nodes for academic projects are

Cluster head:

It also defined as local coordinator for cluster. It also keeps regular contact with member nodes & gateway nodes of neighboring cluster. We also perform inter cluster routing, data forwarding also for mobile node communication.

Gateway node:

It is also a node acts as a communication medium among various clusters. It also provides access to neighboring cluster & permit packet transmission hardware clusters.

Cluster member:

It used to communicate with cluster head also by cluster. By creating communication cluster members are update also by routing tale information also based on cluster head.

Fuzzy logic in network:

We also use fuzzy system to get approximate functions it is used to model any continuous function. Results always based on some unknown non linear function which also create changes with respect to time. To ensure proper decision also in any network model we also use fuzzy logic approach.

The basic units of fuzzy functions are:

Fuzzy inputs.
Fuzzifier.
Fuzzy inference system.
De Fuzzifier.
Rule base.

Fuzzy input:

In this process, we also obtain input for particular application & determine degree also to each appropriate fuzzy set via membership functions.

Fuzzy operator:

We use this process to identify degrees to which part of antecedent which satisfy each rule in fuzzy system. Fuzzy operator is used to get one number which represents result for corresponding rule. To ensure output in fuzzy logic system, we use either AND or OR operations.

Implication method:

Before applying implication method proper weights are assigned for each rule and implication process takes input as single number and output is fuzzy set.

Defuzzifier:

We apply fuzzy set is apply into input for defuzzification process. The output of defuzzification process is single number. We also evolve aggregation process give range of output values to resolve function and produce single output value from set defuzzification.

We also develop more than 80+ projects in NS3 simulation with various network communications by our team.

Current Work progress