ABSTRACT




       Multiple-path source routing protocols allow a data source node to distribute the
total traffic among available paths. In this article, we consider the problem of jamming-
aware source routing in which the source node performs traffic allocation based on empirical
jamming statistics at individual network nodes. We formulate this traffic allocation as a lossy
network flow optimization problem using portfolio selection theory from financial statistics.
We show that in multi-source networks, this centralized optimization problem can be solved
using a distributed algorithm based on decomposition in network utility maximization
(NUM). We demonstrate the network’s ability to estimate the impact of jamming and
incorporate these estimates into the traffic allocation problem. Finally, we simulate the
achievable throughput using our proposed traffic allocation method in several scenarios.

       .
INDEX

1. INTRODUCTION                          1

  1.1   INTRODUCTION TO PROJECT          1
  1.2   EXISTING SYSTEM                  2
  1.3   PROPOSED SYSTEM                  2

2. SYSTEM ANALYSIS                       5

  2.1   FEASIBILITY STUDY                5

        2.1.1   ECONOMICAL FEASIBILITY   5
        2.1.2   TECHNICAL FEASIBILITY    5
        2.1.3   SOCIAL FEASIBILITY       6

  2.2   SYSTEM REQUIREMENT               6
        2.2.1   SOFTWARE REQUIREMENT     6
        2.2.2   HARDWARE REQUIREMENT     6

3. LANGAUGE SPECIFICATION                7
  3.1   FEATURES OF .NET                 7
  3.2   THE .NET FRAMEWORK               7
  3.3   CONSTRUCTORS AND DESTRUCTORS     11
  3.4   GARBAGE COLLECTION               11
  3.5   OVERLOADING                      12
  3.6   MULTITHREADING                   12

4. SYSTEM DESIGN                         13

  4.1   ACTIVITY DIAGRAM                 13
  4.2   CLASS DIAGRAM                    14
  4.3   FLOW CHART                       15
  4.4   SEQUENCE DIAGRAM                 16
  4.5   USE CASE DIAGRAM                 17
5. SYSTEM TESTING AND MAINTENANCE   18

  5.1. UNIT TESTING                 19
  5.2. INTEGRATION TESTING          19
6. SYSTEM IMPLEMENTATION            20

7. CONCLUSION                       21

8. LITERATURE REVIEW                22

9. REFERENCES                       52

10.SCREEN SHOTS                     53

Chani index

  • 1.
    ABSTRACT Multiple-path source routing protocols allow a data source node to distribute the total traffic among available paths. In this article, we consider the problem of jamming- aware source routing in which the source node performs traffic allocation based on empirical jamming statistics at individual network nodes. We formulate this traffic allocation as a lossy network flow optimization problem using portfolio selection theory from financial statistics. We show that in multi-source networks, this centralized optimization problem can be solved using a distributed algorithm based on decomposition in network utility maximization (NUM). We demonstrate the network’s ability to estimate the impact of jamming and incorporate these estimates into the traffic allocation problem. Finally, we simulate the achievable throughput using our proposed traffic allocation method in several scenarios. .
  • 2.
    INDEX 1. INTRODUCTION 1 1.1 INTRODUCTION TO PROJECT 1 1.2 EXISTING SYSTEM 2 1.3 PROPOSED SYSTEM 2 2. SYSTEM ANALYSIS 5 2.1 FEASIBILITY STUDY 5 2.1.1 ECONOMICAL FEASIBILITY 5 2.1.2 TECHNICAL FEASIBILITY 5 2.1.3 SOCIAL FEASIBILITY 6 2.2 SYSTEM REQUIREMENT 6 2.2.1 SOFTWARE REQUIREMENT 6 2.2.2 HARDWARE REQUIREMENT 6 3. LANGAUGE SPECIFICATION 7 3.1 FEATURES OF .NET 7 3.2 THE .NET FRAMEWORK 7 3.3 CONSTRUCTORS AND DESTRUCTORS 11 3.4 GARBAGE COLLECTION 11 3.5 OVERLOADING 12 3.6 MULTITHREADING 12 4. SYSTEM DESIGN 13 4.1 ACTIVITY DIAGRAM 13 4.2 CLASS DIAGRAM 14 4.3 FLOW CHART 15 4.4 SEQUENCE DIAGRAM 16 4.5 USE CASE DIAGRAM 17
  • 3.
    5. SYSTEM TESTINGAND MAINTENANCE 18 5.1. UNIT TESTING 19 5.2. INTEGRATION TESTING 19 6. SYSTEM IMPLEMENTATION 20 7. CONCLUSION 21 8. LITERATURE REVIEW 22 9. REFERENCES 52 10.SCREEN SHOTS 53