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INDEX INTRODUCTION
 AIMS AND OBJECTIVES
 LITERATURE SURVEY
 PROBLEM STATEMENT
 PROJECT REQUIREMENT
 UML DIAGRAMS
 PROPOSED ARCHITECTURE
 PROJECT PLAN:
INTRODUCTION
 Multiple-path source routing protocols allow a data source
node to distribute the total traffic among available paths.
 The problem of jamming-aware source routing in which
the source node performs traffic allocation based on
empirical jamming statistics at individual network nodes.
AIMS AND OBJECTIVES
 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).
LITERATURE SURVEY To distribute the total traffic among available
paths the source node performs traffic allocation
based on empirical jamming statistics at
individual network nodes.
 If any path to be disturbed/jammed a routing
path is requested an existing routing path is not
be updated, the responding nodes along the path
will disconnect the routing path.
PROBLEM STATEMENT Today, the development and widespread use
of information technologies is changing the
way people view FIR processes and,
ultimately, the way they Report at any police
station. At the forefront of these new
technologies is Online FIR (First Information
Report) System and at the back-end, the
server is maintaining the Reports.
Proposed System
 We propose techniques for the network nodes to
estimate and characterize the impact of jamming
and for a source node to incorporate these estimates
into its traffic allocation.
 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.
Jamming Behaviors
• disturb wireless communications
• proactive / reactive
• constant, random, repeat, deceiv
• single bit/packet
• outsider / insider
• static / mobile
nondeterministic and dynamic
Multiple-Path routing Anti-jamming techniques =
diversity
 Multiple frequency bands
 Different MAC channels
 Multiple Routing paths
 Multi-Path Routing
 Each source node chooses multiple paths
 Each path is allocated with different traffic
amount (how to avoid congestion?)
 Each path has different probabilities to be
jammed (how to measure this?)
Goal: Efficiently allocate the traffic to maximize the
overall throughput.
http://w3.antd.nist.gov/adhoc/Project_drouting.shtml
 Hardware Requirements:
 Processor : Intel Processor above than 3.0 Ghz
 Hard Disk : 20 GB.
 Ram : 1 GB.
 Software Requirements:
 Operating system : Windows XP SP2 or Higher
 .NET Framework : 3.5 Or Higher
 Reporting Tool : Crystal Reports XI Or Higher
 Other Application : Adobe Acrobat Reader, M S Excel.
System Requirements
PROJECT PLAN
 Project planning is discipline for stating
how to complete a project within a certain
time frame, usually with the define stages
and with designated resources. One view
of project planning divides the activity
into:
Setting objectives (these should be measurable).
 Identifying the needs.
Planning the schedule.
Making supportive plans.
Number of pages(GUI etc).
Validations etc..
UML DIAGRAMS
UML DIAGRAMS
UML DIAGRAMS
UML DIAGRAMS
UML DIAGRAMS
UML DIAGRAMS
Advantages
 Each time a new routing path is requested or an
existing routing path is updated, the responding
nodes along the path will relay the necessary
parameters to the source node as part of the reply
message for the routing path.
 Efficiently allocate the traffic to maximize the
overall throughput.
REFERENCES F. Akyildiz, X. Wang, and W. Wang, “Wireless mesh
networks: Asurvey,” Comput. Netw., vol. 47, no. 4, pp.
445–487
 E. M. Sozer, M. Stojanovic, and J. G. Proakis,
“Underwater acoustic networks,” IEEE J. Ocean. Eng.,
vol. 25, no. 1, pp. 72–83
 [3] R. Anderson, Security Engineering: A Guide to
Building Dependable Distributed Systems. New York:
Wiley
ANY QUERIES..??
Mathematical Model
Roadmap
 Use PDR to approximate the overall throughput
 What is PDR? How to get PDR?
 Use a quadratic program based on Portfolio
Selection Theory to give the optimal solution
 Objective Function? Constraints?
 Use Lagrangian dual decomposition to get a
distributed solution
 Efficiency: accuracy, convergence, scalability.
Represent the throughput - I
Estimate local packet success rates
(LPSR)
 Each node updates (LPSR), Update period T << Ts update
relay period
 Estimated value by Packet Delivery Rate (PDR)
 Variance by the variance of PDR
Represent the throughput - II
End-to-End Packet Success Rate
 Mean
 Variance/covariance
 Given that there are Ls paths at source node s,
what does these two above mean?
Represent the throughput – III Given that the traffic allocation vector at node s is
 Expected throughput:
 Variance:
Formulate Optimal Solution – I
Portfolio Selection
 Analogy of concepts http://proteger.com.my/articles/investment/modernportfolio.html
Formulate Optimal Solution – I
Portfolio Selection (cont’)
 risk-aversion factor ks
 ks = 0 means the throughput is maximized regardless of
any risks
 Ks>0 (0.005 in the simulation)
Formulate Optimal Solution – II
Congestion Avoidance
 Delivery rate from s to node i is
 The aggregate traffic going through link (i,j) is
Formulate Optimal Solution - III
Iterative and Distributed Solution
 Many allocation quadratic program on large-scale networks
can be solved efficiently through decomposition techniques
 Daniel P. Palomar and Mung Chiang, A Tutorial on
Decomposition Methods for Network Utility Maximization.
 Lagrangian dual decomposition
Lagrangian Duality
Decomposition Topology
Decomposition Flow
lagrangian
• the dual function could be solved using a gradient method
Apply to this formulation
Local update at step 3 requires mutual information exchanges at
all the sources……
Future Enhancement
 An ERP can be developed with this algorithm as
illustration of impact of jamming dynamics and
mobility on network throughput and to demonstrate
the efficacy of our traffic allocation algorithm.
Collaboration Diagram

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Jamming aware traffic allocation for multiple-path routing using portfolio selection.

  • 1. INDEX INTRODUCTION  AIMS AND OBJECTIVES  LITERATURE SURVEY  PROBLEM STATEMENT  PROJECT REQUIREMENT  UML DIAGRAMS  PROPOSED ARCHITECTURE  PROJECT PLAN:
  • 2. INTRODUCTION  Multiple-path source routing protocols allow a data source node to distribute the total traffic among available paths.  The problem of jamming-aware source routing in which the source node performs traffic allocation based on empirical jamming statistics at individual network nodes.
  • 3. AIMS AND OBJECTIVES  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).
  • 4. LITERATURE SURVEY To distribute the total traffic among available paths the source node performs traffic allocation based on empirical jamming statistics at individual network nodes.  If any path to be disturbed/jammed a routing path is requested an existing routing path is not be updated, the responding nodes along the path will disconnect the routing path.
  • 5. PROBLEM STATEMENT Today, the development and widespread use of information technologies is changing the way people view FIR processes and, ultimately, the way they Report at any police station. At the forefront of these new technologies is Online FIR (First Information Report) System and at the back-end, the server is maintaining the Reports.
  • 6. Proposed System  We propose techniques for the network nodes to estimate and characterize the impact of jamming and for a source node to incorporate these estimates into its traffic allocation.  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.
  • 7. Jamming Behaviors • disturb wireless communications • proactive / reactive • constant, random, repeat, deceiv • single bit/packet • outsider / insider • static / mobile nondeterministic and dynamic
  • 8. Multiple-Path routing Anti-jamming techniques = diversity  Multiple frequency bands  Different MAC channels  Multiple Routing paths  Multi-Path Routing  Each source node chooses multiple paths  Each path is allocated with different traffic amount (how to avoid congestion?)  Each path has different probabilities to be jammed (how to measure this?) Goal: Efficiently allocate the traffic to maximize the overall throughput. http://w3.antd.nist.gov/adhoc/Project_drouting.shtml
  • 9.  Hardware Requirements:  Processor : Intel Processor above than 3.0 Ghz  Hard Disk : 20 GB.  Ram : 1 GB.  Software Requirements:  Operating system : Windows XP SP2 or Higher  .NET Framework : 3.5 Or Higher  Reporting Tool : Crystal Reports XI Or Higher  Other Application : Adobe Acrobat Reader, M S Excel. System Requirements
  • 10. PROJECT PLAN  Project planning is discipline for stating how to complete a project within a certain time frame, usually with the define stages and with designated resources. One view of project planning divides the activity into:
  • 11. Setting objectives (these should be measurable).  Identifying the needs. Planning the schedule. Making supportive plans. Number of pages(GUI etc). Validations etc..
  • 18. Advantages  Each time a new routing path is requested or an existing routing path is updated, the responding nodes along the path will relay the necessary parameters to the source node as part of the reply message for the routing path.  Efficiently allocate the traffic to maximize the overall throughput.
  • 19. REFERENCES F. Akyildiz, X. Wang, and W. Wang, “Wireless mesh networks: Asurvey,” Comput. Netw., vol. 47, no. 4, pp. 445–487  E. M. Sozer, M. Stojanovic, and J. G. Proakis, “Underwater acoustic networks,” IEEE J. Ocean. Eng., vol. 25, no. 1, pp. 72–83  [3] R. Anderson, Security Engineering: A Guide to Building Dependable Distributed Systems. New York: Wiley
  • 21.
  • 23. Roadmap  Use PDR to approximate the overall throughput  What is PDR? How to get PDR?  Use a quadratic program based on Portfolio Selection Theory to give the optimal solution  Objective Function? Constraints?  Use Lagrangian dual decomposition to get a distributed solution  Efficiency: accuracy, convergence, scalability.
  • 24. Represent the throughput - I Estimate local packet success rates (LPSR)  Each node updates (LPSR), Update period T << Ts update relay period  Estimated value by Packet Delivery Rate (PDR)  Variance by the variance of PDR
  • 25. Represent the throughput - II End-to-End Packet Success Rate  Mean  Variance/covariance  Given that there are Ls paths at source node s, what does these two above mean?
  • 26. Represent the throughput – III Given that the traffic allocation vector at node s is  Expected throughput:  Variance:
  • 27. Formulate Optimal Solution – I Portfolio Selection  Analogy of concepts http://proteger.com.my/articles/investment/modernportfolio.html
  • 28. Formulate Optimal Solution – I Portfolio Selection (cont’)  risk-aversion factor ks  ks = 0 means the throughput is maximized regardless of any risks  Ks>0 (0.005 in the simulation)
  • 29. Formulate Optimal Solution – II Congestion Avoidance  Delivery rate from s to node i is  The aggregate traffic going through link (i,j) is
  • 31. Iterative and Distributed Solution  Many allocation quadratic program on large-scale networks can be solved efficiently through decomposition techniques  Daniel P. Palomar and Mung Chiang, A Tutorial on Decomposition Methods for Network Utility Maximization.  Lagrangian dual decomposition
  • 34. Decomposition Flow lagrangian • the dual function could be solved using a gradient method
  • 35. Apply to this formulation Local update at step 3 requires mutual information exchanges at all the sources……
  • 36. Future Enhancement  An ERP can be developed with this algorithm as illustration of impact of jamming dynamics and mobility on network throughput and to demonstrate the efficacy of our traffic allocation algorithm.