The document discusses network selection techniques for heterogeneous wireless networks. It describes TOPSIS and SAW, two multi-criteria decision making methods for network selection based on criteria such as bandwidth, quality of service, cost and security. TOPSIS selects the network closest to an ideal solution and farthest from a negative ideal solution based on a weighted standardized decision matrix. SAW calculates a global score for each network by taking a weighted average of normalized criteria values. The document provides steps and examples to apply these methods for objective network selection.
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. 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. 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. 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. 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. 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. 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. 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. 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. 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
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