CS432 Subjective

Q: Object Inspection and its types

A: An object inspector is a GUI window associated with a simulation object

• Displays contents and properties

Three types

• Network Display
• Log Viewer
• Object Inspector

Q: Computer Models A: The model definition could be

Descriptive Analytical Mathematical Algorithmic

The computer models can be described into various types

Stochastic vs Deterministic Continuous vs discrete Steady state vs Dynamic Local or Distributed Linear or nonlinear Open or closed

Q: Difference between Stochastic vs Deterministic?

A: A deterministic model always gives the same output for the same input, with no randomness—it's used in systems where behavior is predictable, like physics or engineering. A stochastic model includes randomness, so results can vary; it's used when uncertainty is important, like in weather forecasting, stock market analysis, or population studies. Deterministic models are simpler and faster, while stochastic models are better for simulating real-world variability.

Q: Components of a simulator and types of simulations.

A: Components of a simulator

A self-contained program Event queue Simulation clock State variables Event routines Input routine Report generation routine Initialization routine Main program

Types of simulations

Monte Carlo simulation Trace driven Discrete events Continuous events

Q: Continuous event and Discrete event?

A: In network modeling, discrete events happen at specific times (like packet arrivals), and they usually involve a finite number of events and outputs, making them easier to simulate and analyze. In contrast, continuous events change smoothly over time (like signal strength), and can involve infinite possible states or outputs since values change constantly. Discrete models are event-driven, while continuous models are time-driven.

Q: What is OMNET++?

A:

Objective Modular Network Testbed in C++ Simulation kernel Component-based simulation library A framework, not a simulator Designed to create & simulate any network

OMNeT++ stands for Objective Modular Network Testbed in C++. It is a framework, not just a simulator, used to create and simulate all types of networks. It has a simulation kernel and a component-based simulation library, which means you can build networks using reusable modules. OMNeT++ is mainly used for simulating communication networks like the internet or wireless systems. It uses C++ for coding behavior and NED (Network Description) language for designing network structures. It helps test how data moves, how protocols work, and how networks perform over time.

Q: Write down supported DNS operations. A:

DNS Support in OMNET++

Extensions provide classes and functions to simulate DNS and MDNS traffic Implement RFC 1035

Supported DNS Operations

Name servers with recursive resolving capabilities Authoritative servers with DNS zone configuration using master files Caching servers without zones Only recursively resolving DNS Cache base that can be extended Caches based on different policies possible DNS client that can query a DNS server

Q: Random Request Mode and Scripted Mode. A: Random request mode is when the browser generates requests to random web servers using statistical distributions. This means the requests happen in a random pattern based on probabilities.

Scripted mode is when the browsing follows a fixed list of predefined websites to visit at specific times. The behavior is planned and repeats exactly as scripted.

Q: Health Metrics

A:

Health Metrics in Network Monitoring

Incoming Traffic Variation (ITV) ITV measures how the incoming bandwidth consumption changes across different sessions. It is calculated as the difference between the current session's bandwidth (IBC₁) and the previous session's bandwidth, divided by the session length. The function q(x) evaluates the variation, where higher values of x reduce the score exponentially. If the variation is negative or zero, the score remains 1, indicating stable traffic.

Traffic Tolerance (TT) Traffic Tolerance (TT) evaluates the Round Trip Time (RTT) between the end-user and the ISP’s recursive resolver. The function q(x) decreases linearly when RTT is within acceptable limits (up to twice the average RTT), and drops to 0 if RTT exceeds that threshold. This metric helps assess how well the network handles delay-sensitive applications.

DNS Requests per Second (DNSR) DNSR indicates how many DNS queries are made per second in a session. The function q(x) decreases linearly as the number of queries increases, up to twice the average DNSR. If the queries exceed that range, the score becomes 0. This metric helps detect excessive DNS traffic, which could suggest misbehavior or attacks.