Network Selection in
Heterogeneous Wireless Networks

By
Yashwant
110603
EC-7
CONTENT
•
•
•
•
•
•
•
•

Hetrogeneous Wireless Network
Handover
Network Selection
Multi-criteria Decision Making
TOPSIS
SA...
Heterogeneous Wireless Networks
•
•
•
•
•

Co-existing radio access technologies
WWANs, WPANs, WLANs, WMANs
coverage overl...
Heterogeneous Wireless Networks

4
HANDOVER
• Service continuity
• Select best network with minimum processing
delay
• Vertical Handover
• Horizontal Handove...
Network Selection
• Based on various criteria
– Traffic demand
– Quality of service
– Bandwidth and round-trip-time estima...
Multi-criteria Decision Making
• Selection of the best, from a set of alternatives, each of
which is evaluated against mul...
Important terms…
• Alternatives – These are the options which are to be evaluated
for selection of the best.
• Example: (f...
Important terms…
• Weights – These estimates relative importance of
criteria.



Each attribute is given certain points ...
Important terms…


Decision makers – These are experts who are
assigned with the task of weighting each attribute.
There ...
Important terms…


Decision matrix – A table that is used to objectively make
decision about making selection from a rang...
TOPSIS
Technique for Order Preference by Similarity to Ideal
Solution
In this method two artificial alternatives are hypot...
Steps involved in TOPSIS…
• Step 1 – standardize the decision matrix.
– This step transforms various attribute dimensions ...
Steps involved in TOPSIS…
• Step 1 – standardize the decision matrix.
– This step transforms various attribute dimensions ...
Steps involved in TOPSIS…
• Step 1 – standardize the decision matrix.
– This step transforms various attribute dimensions ...
Standardized decision matrix….

Criteria

Network 1

Bandwidth

Network 2

Network 3

9 / 13.93

Network 2

Network 3

Qos...
Standardized decision matrix….

Criteria

Network 1

Network 2

Bandwidth

9 / 13.93

8 / 13.93

Network 1

Network 2

Net...
Standardized decision matrix….

Criteria

Network 1

Network 2

Network 3

Bandwidth

9 / 13.93

8 / 13.93

7 / 13.93

Net...
Standardized decision matrix….
Similarly….
Criteria

Network 1

Network 2

Network 3

Bandwidth
bandwidth

0.65

0.57

0.5...
Steps involved in TOPSIS…
• Step 2 - Construct weighted standardized decision matrix
by multiplying attributes weight to e...
Steps involved in TOPSIS…
• Step 2 - Construct weighted standardized decision matrix
by multiplying attributes weight to e...
Steps involved in TOPSIS…
• Step 2 - construct weighted standardized decision matrix
by multiplying attributes weight to e...
Steps involved in TOPSIS…
• Step 2 - construct weighted standardized decision matrix
by multiplying attributes weight to e...
Steps involved in TOPSIS…
• Step 2 - construct weighted standardized decision matrix
by multiplying attributes weight to e...
Steps involved in TOPSIS…
• Step 3 – Determine ideal solution and negative ideal solution.
A set of maximum values for eac...
Steps involved in TOPSIS…
• Step 3 – Determine ideal solution and negative ideal solution.
A set of minimum values for eac...
Steps involved in TOPSIS…
• Step 4 – Determine separation from ideal solution. Si*
Criteria

Network1

Network 2

Network ...
Steps involved in TOPSIS…
• Step 5 – Determine separation from negative ideal solution.
Criteria

Network 1

Network 2

Ne...
Steps involved in TOPSIS…
• Step 6 – Determine relative closeness to ideal solution.
Criteria

Network 1

Network 2

Netwo...
OVERALL
ALGORITHM
Simple Additive Weighting
(SAW) Method

• Simple Additive Weighting – Weighted Average –
Weighted Sum
• A global (total) s...
Steps in SAW…..
• Step 1-Normalization of decision matrix
decision….. matrix…..
Criteria

Network 1

Network 2

Network 3
...
Steps involved in SAW…
• Step 2 Evaluation of score for each alternative
n
w j rij

V(ai) = Vi =.

j 1

Criteria
bandwidth...
Steps involved in SAW…
• Evaluation of score for each alternative….
Criteria

Network 1

Bandwidth

Network 2

Network 3

...
COMPARISION
• Criteria
1.
2.
3.
4.
5.

The Packet Jitter (J)
The Packet delay (D)
Utilization (U)
The Packet Loss (L)
The ...
COMPARISON
• Comparision of ranking order
COMPARISION
• Difference between ranking values..
COMPARISION……
Ranking abnormality..
Simulation results
• Ranking abnormalities
• Precision
• Ranking identifications
CONCLUSION
Although TOPSIS surfers from the ranking
abnormality problem, it provides a more
precision in alternative ranki...
Network selection techniques:SAW and TOPSIS
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Network selection techniques:SAW and TOPSIS

  1. 1. Network Selection in Heterogeneous Wireless Networks By Yashwant 110603 EC-7
  2. 2. CONTENT • • • • • • • • Hetrogeneous Wireless Network Handover Network Selection Multi-criteria Decision Making TOPSIS SAW Comparison conclusion
  3. 3. Heterogeneous Wireless Networks • • • • • Co-existing radio access technologies WWANs, WPANs, WLANs, WMANs coverage overlapping one another always best connected(ABC) Different network architectures and protocols for transport, routing and mobility management. • Reliability, spectrum efficiency, increased coverage. • Multi-homing & multimode interfaces
  4. 4. Heterogeneous Wireless Networks 4
  5. 5. HANDOVER • Service continuity • Select best network with minimum processing delay • Vertical Handover • Horizontal Handover
  6. 6. Network Selection • Based on various criteria – Traffic demand – Quality of service – Bandwidth and round-trip-time estimations – Application requirements – Registration cost – Security of data 6
  7. 7. Multi-criteria Decision Making • Selection of the best, from a set of alternatives, each of which is evaluated against multiple criteria. • Some problem solving techniques are : • SAW (Simple Additive Weighting) • TOPSIS (Technique for Order Preference by Similarity to the Ideal Solution) • ELECTRE (Elimination et Choice Translating Reality) • AHP (The Analytical Hierarchy Process) • SMART (The Simple Multi Attribute Rating Technique ) • ANP (Analytic network process)
  8. 8. Important terms… • Alternatives – These are the options which are to be evaluated for selection of the best. • Example: (for Network problem)net1,net2,net3,net4 etc. • Criteria or Attributes – These will impact the selection of alternatives Example: (for Network problem) Bandwidth, QoS, Cost, security level etc.  Completeness: It is important to ensure that all of the important criteria are included.  Redundancy: In principle, criteria that have been judged relatively unimportant or to be duplicates should be removed at a very early stage.  Operationality: It is important that each alternative can be judged against each criterion.
  9. 9. Important terms… • Weights – These estimates relative importance of criteria.   Each attribute is given certain points on 0-10 or 0-100 rating scale by a team of experts or decision makers. Example: criteria     Bandwidth QoS Security Cost weight - 4 2 6 8 rating scale 10 very good -1 none 10 very good -1 none 1 low-10 very high 1 low-10 very high
  10. 10. Important terms…  Decision makers – These are experts who are assigned with the task of weighting each attribute. There can be ‘n’ number of decision makers.  Example:  criteria rating scale Bandwidth QoS Security cost - Criteria 10 very good -1 none 10 very good -1 none 10 low-1 very high 10 low-1 very high Decision makers Harry Ron Attributes weights Hermoine bandwidth 4 2 6 =4 Qos 2 3 1 =2 Security 6 4 8 =6 Cost 8 9 7 =8
  11. 11. Important terms…  Decision matrix – A table that is used to objectively make decision about making selection from a range of options. Criteria Network 1 Network 2 Network 3 Bandwidth 9 8 7 Qos 7 7 8 Security 6 9 6 COST 7 6 6
  12. 12. TOPSIS Technique for Order Preference by Similarity to Ideal Solution In this method two artificial alternatives are hypothesized:  Ideal alternative: One which has the best attributes values (i.e. max. benefit attributes and min. cost attributes) • Negative ideal alternative: One which has the worst attribute values. (i.e. min. benefit attributes and max. cost attributes) TOPSIS selects the alternative that is the closest to the ideal solution and farthest from negative ideal solution.
  13. 13. Steps involved in TOPSIS… • Step 1 – standardize the decision matrix. – This step transforms various attribute dimensions into non-dimensional attributes, which allows comparisons across criteria. – For standardizing, each column of decision matrix, is divided by root of sum of square of respective columns. Criteria Network 1 Network 2 Network 3 Root of sum of square Bandwidth 9 8 7= = 13.93 QoS 7 7 8= =12.73 Security 6 9 6= =12.37 Cost 7 6 6= = 11.00 DECISION MATRIX
  14. 14. Steps involved in TOPSIS… • Step 1 – standardize the decision matrix. – This step transforms various attribute dimensions into non-dimensional attributes, which allows comparisons across criteria. – For standardizing, each column of decision matrix, is divided by root of sum of square of respective columns. Criteria Network 1 Network 2 Network 3 RSS Bandwidth 9 8 7= = 13.93 Qos 7 7 8= =12.73 Security 6 9 6= =12.37 COST 7 6 6= = 11.00
  15. 15. Steps involved in TOPSIS… • Step 1 – standardize the decision matrix. – This step transforms various attribute dimensions into non-dimensional attributes, which allows comparisons across criteria. – For standardizing, each column of decision matrix, is divided by root of sum of square of respective columns. Criteria Network 1 Network 2 Network 3 RSS Bandwidth 9 8 7= = 13.93 Qos 7 7 8= =12.73 Security 6 9 6= =12.37 COST 7 6 6= = 11.00
  16. 16. Standardized decision matrix…. Criteria Network 1 Bandwidth Network 2 Network 3 9 / 13.93 Network 2 Network 3 Qos Security COST Criteria Bandwidth Qos Security COST Network 1 0.65
  17. 17. Standardized decision matrix…. Criteria Network 1 Network 2 Bandwidth 9 / 13.93 8 / 13.93 Network 1 Network 2 Network 3 Qos Security COST Criteria Bandwidth Qos Security COST 0.65 0.57 Network 3
  18. 18. Standardized decision matrix…. Criteria Network 1 Network 2 Network 3 Bandwidth 9 / 13.93 8 / 13.93 7 / 13.93 Network 1 Network 2 Network 3 Qos Security COST Criteria Bandwidth Qos Security COST 0.65 0.57 0.50
  19. 19. Standardized decision matrix…. Similarly…. Criteria Network 1 Network 2 Network 3 Bandwidth bandwidth 0.65 0.57 0.50 Qos QoS 0.55 0.55 0.63 Security SECURITY 0.49 0.73 0.49 COST 0.64 0.55 0.55
  20. 20. Steps involved in TOPSIS… • Step 2 - Construct weighted standardized decision matrix by multiplying attributes weight to each rating. Criteria Network 1 Network 2 Network 3 bandwidth X 0.65 0.57 0.50 Qos 0.55 0.55 0.63 Security 0.49 0.73 0.49 COST 0.64 0.55 0.55 Attributes weights Criteria Bandwidth Qos Security COST Network 1 2.6 Network 2 Standardized decision matrix Network 3 Weighted Standardized decision matrix
  21. 21. Steps involved in TOPSIS… • Step 2 - Construct weighted standardized decision matrix by multiplying attributes weight to each rating. Criteria bandwidth Network 1 Network 2 Network 3 0.65 0.57 0.50 QoS 0.55 0.55 0.63 Security 0.49 0.73 0.49 Cost 0.64 0.55 0.55 Attributes weights Criteria Bandwidth Qos Security Cost Network 1 2.6 X Standardized decision matrix Network 2 2.28 Network 3 Weighted Standardized decision matrix
  22. 22. Steps involved in TOPSIS… • Step 2 - construct weighted standardized decision matrix by multiplying attributes weight to each rating. Criteria bandwidth Network 1 Network 2 Network 3 0.65 0.57 0.50 X 0.55 0.55 0.63 Security 0.49 0.73 0.49 Cost 0.64 0.55 0.55 QoS Attributes weights Criteria Network 1 bandwidth 2.6 Qos 1.1 Securit Cost Standardized decision matrix Network 2 2.28 Network 3 Weighted Standardized decision matrix
  23. 23. Steps involved in TOPSIS… • Step 2 - construct weighted standardized decision matrix by multiplying attributes weight to each rating. Similarly…. Criteria Network 1 Network 2 Network 3 Bandwidth bandwidth 2.6 2.28 2 Qos QoS 1.1 1.1 1.26 Security SECURITY 2.94 4.38 2.94 Cost COST 5.12 4.4 4.4 Weighted Standardized decision matrix
  24. 24. Steps involved in TOPSIS… • Step 2 - construct weighted standardized decision matrix by multiplying attributes weight to each rating. Similarly…. Criteria Network 1 Network 2 Network 3 Bandwidth bandwidth 2.6 2.28 2 Qos QoS 1.1 1.1 1.26 Security SECURITY 2.94 4.38 2.94 Cost COST 5.12 4.4 4.4 Weighted Standardized decision matrix
  25. 25. Steps involved in TOPSIS… • Step 3 – Determine ideal solution and negative ideal solution. A set of maximum values for each criteria is Ideal solution. Criteria Network 1 Network 2 Network 3 Max.2.6 2.28 Qos 1.1 1.1 Max. 1.26 Security 2.94 Max.4.38 4.4 2.94 Bandwidth Cost Max.5.12 2 Ideal solution = {2.6, 1.26, 4.38, 5.12} 4.4 2.6 1.26 4.38 5.12
  26. 26. Steps involved in TOPSIS… • Step 3 – Determine ideal solution and negative ideal solution. A set of minimum values for each criteria is Negative Ideal solution. Criteria Network 1 Network 2 Bandwidth 2.6 Qos 1.1 2.28 Min. 1.1 Min. 2.94 4.38 2.94 5.12 Min. 4.4 4.4 SECURITY COST Network 3 Min. 2 1.26 Negative Ideal solution = {2.6, 1.26, 2.94, 4.4} 2.0 1.1 2.94 4.4
  27. 27. Steps involved in TOPSIS… • Step 4 – Determine separation from ideal solution. Si* Criteria Network1 Network 2 Network 3 (2.6-2.6)2 (2.28-2.6) 2 (2.0-2.6) 2 Qos (1.1-1.26) 2 (1.1-1.26) 2 (1.26-1.26) 2 SECURITY (2.94-2.94) 2 (4.38-2.94) 2 (2.94-2.94) 2 COST (5.12-4.4) 2 (4.4-4.4) 2 (4.4-4.4) 2 Bandwidth Criteria Network 1 Network 2 Network 3 Bandwidth 0.0 0.10 0.36 Qos 0.02 0.02 0.0 SECURITY 0.0 2.07 0.0 COST 0.51 0.0 0.0 = = = (0.+0.02+0+0.51)1/2 (.1+.02+2.07+0)1/2 (0.36+.0+0+0)1/2 S* = 0.74 1.48 0.6
  28. 28. Steps involved in TOPSIS… • Step 5 – Determine separation from negative ideal solution. Criteria Network 1 Network 2 Network 3 Bandwidth (2.6-2.0)2 (2.28-2.0) 2 (2.0-2.0) 2 Qos (1.1-1.1) 2 (1.1-1.1) 2 (1.26-1.1) 2 SECURITY (2.94-4.38) 2 (4.38-4.38) 2 (2.94-4.38) 2 COST (5.12-5.12) 2 (4.4-5.12) 2 (4.4-5.12) 2 Criteria Network 1 Network 2 Network 3 Bandwidth 0.36 0.07 0.0 Qos 0.0 0.0 0.02 SECURITY 2.07 0.0 2.07 COST 0.0 0.51 0.51 = = = (0.36+0+2+0)1/2 (.07+0+0+.51)1/2 (0+.02+2+.51)1/2 Si’ = 1.56 0.773 1.618
  29. 29. Steps involved in TOPSIS… • Step 6 – Determine relative closeness to ideal solution. Criteria Network 1 Network 2 Network 3 Si * 0.74 1.48 0.6 Si ’ 1.56 0.773 1.618 Si*+Si’ 2.3 2.253 2.218 1.56/2.3 0.77/2.25 1.62/2.21 0.68 0.343 Si’ /(Si*+Si’ ) Max. 0.729 BEST
  30. 30. OVERALL ALGORITHM
  31. 31. Simple Additive Weighting (SAW) Method • Simple Additive Weighting – Weighted Average – Weighted Sum • A global (total) score in the SAW is obtained by adding contributions from each attribute. • A common numerical scaling system such as normalization (instead of single dimensional value functions) is required to permit addition among attribute values. • Value (global score) of an alternative can be expressed as: n w j rij V(ai) = Vi = j 1
  32. 32. Steps in SAW….. • Step 1-Normalization of decision matrix decision….. matrix….. Criteria Network 1 Network 2 Network 3 Bandwidth 9 8 7 Qos 7 7 8 Security 6 9 6 COST 7 6 6 Criteria Bandwidth Network 1 Network 2 Network 3 1 .88 .77 Qos .875 .875 1 Security .66 1 .66 1 .857 .857 COST
  33. 33. Steps involved in SAW… • Step 2 Evaluation of score for each alternative n w j rij V(ai) = Vi =. j 1 Criteria bandwidth Network 1 Network 2 Network 3 1 0.88 0.77 QoS 0.875 0.875 1 Security 0.66 1 0.66 1 0.857 0.857 Cost Attributes weights Criteria Bandwidth Qos Security Cost Network 1 4 Standardized decision matrix Network 2 3.52 Network 3 Weighted normalized decision matrix
  34. 34. Steps involved in SAW… • Evaluation of score for each alternative…. Criteria Network 1 Bandwidth Network 2 Network 3 4 3.52 3.08 Qos 1.75 1.75 2 Security 3.96 6 3.96 8 7 7 Cost sscore 17.71 18.27 BEST 16.04
  35. 35. COMPARISION • Criteria 1. 2. 3. 4. 5. The Packet Jitter (J) The Packet delay (D) Utilization (U) The Packet Loss (L) The Cost (CB)
  36. 36. COMPARISON • Comparision of ranking order
  37. 37. COMPARISION • Difference between ranking values..
  38. 38. COMPARISION…… Ranking abnormality..
  39. 39. Simulation results • Ranking abnormalities • Precision • Ranking identifications
  40. 40. CONCLUSION Although TOPSIS surfers from the ranking abnormality problem, it provides a more precision in alternative rankings compared to SAW.
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