intelligent tools for techno- economic modelling and network design tim glover chris voudouris...
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Intelligent Tools for Techno-Economic
Modellingand
Network Design
Tim GloverChris VoudourisAnthony Conway
Edward TsangAli Rais Shaghaghi
Michael Kampouridis
Network DeploymentGiven a new country/city
Where should phone/Internet cover be provided?
Deployment Plan Example
Year 1
Year 2
Year 3
No deployment
Cost vs RevenueCost
Hard optimization problem
Very technicalProfitability
depend on it!
Revenue Based on
business model Commercial
confidential
0 1 2 3 4 5 6 7 8 9 10
-300,000
-200,000
-100,000
0
100,000
200,000
300,000
400,000
Cash Flow
In-vest-mentRevenue
Net
Year
Cost: Fibre Trenching(Graph Problem)
The network may include fibres between exchanges, roads in a town, or conduit in a building.
The task is to minimise: Trenching; and costs for fibre optic
network deployment.
Confidential MaterialTim Glover(BT)
Ali Rais Shaghaghi(Essex)Michael Kampouridis (Essex)
Edward Tsang (Essex)
Intelligent Tools for Fibre Access Network
Design Tim Glover(BT)
Ali Rais Shaghaghi(Essex)Edward Tsang(Essex)
BT NetDesign is a software platform for assisting with physical network design. It is written as a Rich Client Platform Eclipse application. The main components are an extensible data model describing networks as
nodes and linksa graphical editor for viewing and editing networksa problem solving package for representing and
solving network design problems
Fibre Access Network Design using the BT NetDesign platform
For example, the network may consist of fibres between exchanges, roads in a town, or conduit in a building. The problem is to minimise trenching and costs for fibre optic network deployment.
1.Fibre Trenching(Graph Problem)
1
1 2
3
Guided Local Search is a Metaheuristic search method.
Using solution features to improve the local search algorithm
Considerable improvement in solver algorithm in regards to execution time and optimised solution when compared to the existing BT NetDesign algorithms (Simulated Annealing)
Integration to the current BT NetDesign platform
Guided local Search for Graph Problem
In general, an access fibre network consists of a set of Customers, a set of Distribution Points (DPs) and a set of Pick–Up Points (exchanges, or PUPs). These points are located in a network of roads, and possibly open spaces. The problem is to construct a tree of fibres that connects each customer to a PUP, either directly, or via one or more DPs, that minimises the total cost.
2.Access Fibre Network Design
Different DPs are available of different capacities (eg 44, 88).
Different customer types may require different numbers of connections
Different cables are available that bundle together different numbers of fibres
Different roads may have different costs associated with digging trenches
Digging a trench across a road costs more than digging along a pavement.
There is a maximum reach between customers and DPs, and between DPs and PUPs
Some considerations affecting cost
Tightly constrained problem In some cases finding a single feasible solution
could take months
Conventional search methods were unable to solve the problem
Use of advanced CS methods to have fast and optimised solutions In Cases of extremely tightly constrained problems
the CS solver would ensure that at least one solution is found
Intelligence for solving constraint satisfaction network design problem
Benefit of joint work to date
This work has mainly focused on introducing novel intelligent problem solving algorithms to the BT NetDesign platform.
They have contributed mainly into two areasGraph ProblemAccess Fibre Network Design
Concluding Remarks
Intelligent Tools for Techno-Economic
Modellingand
Network DesignTim Glover (BT)
Michael Kampouridis (Essex)Ali Rais Shaghaghi (Essex)
Edward Tsang (Essex)
Techno-economic modelling for FTTx
Produce a model whichAnalyses the technological requirements of the
deployment of an FTTx investmente.g. number of workers, trenching length, cable
lengthAnalyses the economical requirements of the
above deploymente.g annual cost, annual revenue, cash flow
Purpose of model: to advice on the viability and profitability of the investment
Model inputsArea population
Social category
Competition
Budget
Rental tariffs and number of customers
PAYG tariffs and number of customers
Study period
Model outputsAnnual revenue
Annual cost
Cash flow
Net Present Value
Internal Rate of Return
Need for intelligenceWhile a techno-economic model can evaluate
different deployment plans, the number of such plans can be very largee.g. if we plan to roll-out to 50 cities within the
next 5 years, the number of different deployment plans is 550
Computationally expensive to evaluate all available deployment plans
Question: “What is the deployment plan that offers the highest profit”?
Adding intelligenceUse different heuristics to locate the optimal
deployment planSimple Hill ClimbingSteepest Ascent Hill ClimbingGenetic Algorithms
Heat Map-Deployment Plan for London
Improvement of up to 18% in the NPV-equivalent to millions of pounds savings
Graphs
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
-40000000
-20000000
0
20000000
40000000
60000000
80000000
Cash Flow
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 200
10000000
20000000
30000000
40000000
50000000
60000000
70000000
Annual Revenue
ConclusionUse of intelligent methods for finding optimal
deployment plans for FTTx deployment
Results show that thanks to the methods used, there has been an increase in the profitability of the investment
Presented a techno-economic tool for evaluation of such investment