data structure presentation

8/8/2019 Data Structure Presentation

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Introduction to Simulation:

OVERVIEW:

This implies that:

1. All data must be stored symbolically. All operations such as

bitwise operations, arithmetic operations, comparisons and

assignments must also be performed symbolically.2. For all statements, which split the control-flow, e.g., if-then-

else statements or loops, all possible execution paths must be

simulated.

DEFINITION:

Simulation is a formal verification technique, which combines

the flexibility of conventional simulation with powerful

symbolic methods.


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The Simulation Algorithm:


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Simulation Techniques :

1. Algorithm Visualization

2. Algorithm Animation

3. Algorithm Simulation


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Visualization of a sorting algorithm


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Bubble sort Animation


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The challenge is to construct a simulation toolbased on this theoretical framework.

A user could then use this simulation tool for examine of states of behavior of

algorithms and data structures.

The goal ofAlgorithm Simulation is to further the understanding of algorithms and data

structures.

Another possible views of Simulation:1. In the context of a vehicle:

2. The researcher's point of view:

3. An experimental technique: comprising such aspects as model calibration and data

collection as well as experimental design and output analysis.

4. Representation : Representation will always be needed for simulation, since it is by

definition an experimental technique where data generatedby each experiment must

be collected, summarizedandreportedin a meaningful way.


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1. Deterministic Algorithms

Deterministic algorithms deal with the aggregated quantity of

concentration and rate of change of concentration.The methods are:

Euler Forward method Euler Backward method Trapezoidal method Explicit 4th order Runge-Kutta method Rosenbrock method (Generalized fourth order Runge-Kutta method) Advanced ODE Solver (Adams-Bashforth)


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The Trapezoidal method:-

The trapezoidal method is a used to approximate the area

under a curve. This is done by inscribing or

circumscribing n number of trapezoids under a curve. The

areas of the trapezoids are then summed.


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First start with the area of one trapezoid:

The trapezoids are circumscribed under the curve,

lengths a and bbecome dependant on:


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Animation Algorithms for Trapezoidal Method


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2. Stochastic Algorithms

Stochastic algorithms can be used for modeling such stochastic or

random events.The methods are:

3. Hybrid Algorithms

StochODE method

Gillespie's Direct method

Gibson Next Reaction methodExplicit Tau-Leap method


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Monte Carlo method:

INTRODUCTION :

Monte Carlo methods are a class of computational algorithms that rely

on repeated random sampling to compute their results. Monte Carlo

methods are often used when simulating physical and mathematicalsystems.

The term Monte Carlo Method was coined by S. Ulam and Nicholas Metropolis

in reference to games of chance, a popular attraction in Monte Carlo.

DEFINITION:

A Monte Carlo method is a technique that involves using random

numbers and probability to solve problems.


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Monte Carlo simulation methods are used in studying systemswith a large number of coupled degrees of tools like :

1. Fluids,

2. Disordered materials,

3. Strongly coupled solids, and

4. Cellular structures


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The steps in Monte Carlo simulation corresponding to theuncertainty propagation shown in Previous figure.

For that we need to do is follow the five simple steps listed below:

Step 1: Create a parametric model, y = f(x1, x2, ..., xq).Step 2: Generate a set of random inputs, xi1, xi2, ..., xiq.

Step 3: Evaluate the model and store the results as yi.Step 4: Repeat steps 2 and 3 for i = 1 to n.Step 5: Analyze the results using histograms, summary statistics,confidence intervals, etc.


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Scheduling algorithms are used in:

Computer networks

Operating systems

Real time applications

Real life Applications :


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Network simulator

A network simulator is a software program that imitates the working of a

computer network. In simulators, the computer network is typically modelled

with devices, traffic etc and the performance is analysed. Typically, users can

then customize the simulator to fulfil their specific analysis needs. Simulators

typically come with support for the most popular protocols in use today, such

as IPv4, IPv6, UDP, and TCP.


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Scheduling in RTOS

More information about the tasks are known

1. No of tasks

2. Resource Requirements

3. Release Time

4. Execution time

5. Deadlines

Being a more deterministic system better scheduling

algorithms can be devised.


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Real-Time Operating Systems

Real-time operating systems are an integral part of real-time

systems. Not surprisingly,four main functional areas that they support are process

management and synchroniza-

tion, memory management, interprocess communication, and

I/O.


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Definition : Simulation is a formal verification technique, which combines theflexibility of conventional simulation with powerful symbolic methods.

Summary

Use of simulation tool for user is Examine of states ofbehavior of


The goal of Algorithm Simulation is to further the understanding of


Types of Simulation Algorithms :

1. Deterministic Algorithms2. Stochastic Algorithms3. Hybrid Algorithms

Real life Applications :

Simulation Techniques :



3. Algorithm Simulation


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Thank You

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