Post on 09-Jul-2020
Configuring Telecommunications Equipment and Networks
André Vellino, Ph.D.vellino@sympatico.ca
October 2001
2/17/2002 Configuring Telecom Equipment 2
Overview
n Historical Overview of CLP(BNR)n Constraint-based Configuration with
CLP(BNR)n Configuration for Designn Cost-Analysis of Nodal Equipmentn Cost-Analysis of Network Configurationsn Lessons learned
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A Brief History of CLP(BNR)
XMS-Prolog interpreter 1985Logical Interval Arithmetic (John Cleary) 1987BNR Prolog interpreter for Macintosh 1988Dassault Electronique develop Interlog 1990BNR-Prolog compiler for SPARCstations 1991CLP(BNR) - Integers & Booleans 1992Ports to different HP/DEC/Sun platforms 1993Commercialization of CLP(BNR) by ALS 1994ALS Integrates Interval Constraints 1996
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What is CLP(BNR)
A logic programming system which takes a set of relations over Booleans Naturals and Reals, a set of initial bounds on all the variables and derives a set of posteriori bounds on all the variables using a local propagation, arc-consistency based, fixed-point iteration.
• can express & propagate non-linear constraints• arithmetic is sound \ o.k. to do symbolic manipulation• not very useful for under-constrained linear systems• allows for disjunctive scheduling with Booleans• finite-domain problems expressible with integer-intervals
Attributes
Description
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Configuring DMS Switches (1993)
n Purpose: to show CLP(BNR) can be used to configure Telephony Switching Equipment;n Different shelves can contain line cards
subject to capacity constraints;n Shelves have requirement and exclusion
constraints;n Problem: how to distribute components to
minimize the number of shelves.
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Abstracted Configuration Problembin_types( [blue,red,green]).commodities( [glass, plastic, steel, wood, copper]).
requires(wood,plastic).excludes(glass, copper).excludes(copper,plastic).
capacity( red, wood, 1 ).capacity( green, wood, 2 ).
capacity(red, steel,0).capacity(red,plastic,0).capacity(blue,wood,0).capacity(blue,plastic,0).capacity(green,glass,0).capacity(green,steel,0).
capacity( red, 3).capacity( blue, 1).capacity( green, 4).
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Translation into CLP(BNR)bin([Blue, Green, Red],[Glass,Plastic,Steel,Wood,Copper],Total) :-% declarations
[Blue,Green,Red] : boolean,[Glass,Plastic,Steel,Wood,Copper] : integer(0,_),BinSize:integer(1,4),
% global constraintsRed + Green + Blue == 1,BinSize == Red*3 + Green*4 + Blue*1, Total is (Glass + Plastic + Steel + Wood + Copper),BinSize >= Total,
% requires/excludes constraintsGlass exclusive Copper, Copper exclusive Plastic, if (Wood >= 1) then (Plastic >= 1), if Green then (Glass + Steel == 0), if Green then (Wood =< 2), if Blue then ((Wood + Plastic) == 0), if Red then ((Steel + Wood) == 0), if Red then (Wood =< 1).
X exclusive Y :- X * Y == 0.if A then B :- A =< B.
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Searching for Solutions
Naïve Algorithm (pseudo code):fit_objects(N1…N5) into [bin(M1…M5)|Bins]:-
N1…N5 ≠ 0,bin(M1…M5), K1…K5 = N1…N5 – M1…M5
fit_objects(K1…K5) into (Bins).
solve :- fit_objects(N1…N5) into Bins,enumerate(booleans(Bins)),enumerat(integers(N1…N5)).
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Optimizations
Less Naïve algorithm 1:Pre-sort Bins by colour (eliminate symmetries)Less Naïve Algorithm 2:n Pre-compute (enumerate) all assignments of
components to a binn Fit N1…N5 into bins by assigning an integer coefficient
I0…I28 to each pre-computed binn Constrain the sums of each column to be equal to the
number of components to be slotted
n Enumerate on I0…I28
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Example
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Remarks
n Hard to predict complexity of propagation / enumeration;
n Compared (very favourably) with CHIP and CLP(R) solutions;
n Critical issue: mapping the problem into numerical constraints;
n BUT - Solution looking for a problem!
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Overview
n Historical Overview of CLP(BNR)n Constraint-based Configuration with
CLP(BNR)n Configuration for Designn Cost-Analysis of Nodal Equipmentn Cost-Analysis of Network Configurationsn Lessons learned
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Context
n Nortel (Northern Telecom) Products:n Switching / Routing Equipmentn Transport Equipment
n Need for design tools that allow the system architect to predict the effect of alternative designs atn board-level;n node-level and n network-level
n Dates: 1994-1995n No constraints allowed (politics)!
Networks
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n Goalsn To model software, hardware and network
architecture dependencies and costsn Means
n A “Product Specification Language” interpreted by a home-grown TMS (truth maintenance system)w/ dependency-directed backtracking
n Endsn Input: system design parametersn Output: Equipment, Software and Network
Configurations and their costs
Modeling a Next-Generation
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Configuration Problem
n Givenn A set of system components;n An architecture that specifies how to connect
these components;n User requirements for specific cases;Select eithern A set of components that satisfies all the
requirementsOr n Detect the inconsistencies in the requirements
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Conventional Design Cycle
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SpreadSheet Models
n Disadvantagesn Not re-useable in system analysis or fault
diagnosisn No intelligence for optimizing
configurations
n Advantagesn Widespread use and commercial supportn Support for statistical analysis and financial
forecasting
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Configuration-Based Design
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KBS-Approaches
n Benefitsn Allow system designer to explore design variations
by constructing an explicit, understandable, reusable, maintainable, declarative system model;
n Intelligent configuration engines suitable for optimization;
n Costsn Support for development and visualization tools not
available commercially;n Requires training to use effectively.
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Overview
n Context / Historical Overviewn Constraint-based Configuration with
CLP(BNR)n Configuration for Designn Cost-Analysis of Nodal Equipmentn Cost-Analysis of Network Configurationsn Lessons learned
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Distributed ATM Architecture
ATMSE
PSTN
BTS
555 555
Radio Access Unit
PSTN Access Unit
System ManagerATM
SE
ATMSE
Call Processing Engine
Data Server
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Equipment Unit
Root Module
Access Module
Card Card. . .Access Module
Card Card. . .Service Module
Card Card. . .. . .
OC-3
SI-0 SI-0
Characteristics230 mm wide4 SI-0 pt-pt links @ 200 Mb/s (proprietary OC3-ATM link)“plug-in backplane”
ATMSE
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Module Shelves
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PSL Hardware Model
Radio-Access-Unit
supplies: 14 T1-ports
consumes:2 ATM-access-ports
T1-Interface
consumes: 1 T1-portsupplies: 96 RF-channels
ATM Backbone Network
supplies: 64 155MB-Access-Ports
PSTN-Access-Unit
supplies: 1-8 Module-ports
consumes:2 ATM-access-ports
supplies: 300mm shelf
DSP Module
consumes: 1 Module-portconsumes: 50mm slotsupplies: 200 Echo Cancellers
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Sample PSL Specificationcomponent_class('PSTN-access-unit',
'pstn-access-unit',[],[consumes(atm_access_port,2)],[supplies(pstn_ce_port,2),supplies(pstn_access_module_port,8)],
[cost(0)],[]).
component_class('PSTN Access Root Module','pstn-access-ce',[],[consumes(pstn_ce_port,2)],[supplies(sts_3c_interface_port,2) ],[cost(2357)],[]).
component_class('155MB ATM Spigot Box','pstn-access-sts3',[],[consumes(sts_3c_interface_port,1)],[supplies('atm_channels',8064)],[cost(1500)],[]).
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Sample PSL Inputs
Input0.01 blocking_probability.200 subscribers.0.1 erlangs_of_traffic_per_subscriber.0.25 mips_of_call_processing_per_call.0.9 speech_coders_per_voice_channel.
Intermediate Outputdemand(erlangs,20,user).demand(radio_channels,30,user).demand(atm_channels,30,user).demand(pstn_channels,30,user).demand(call_processing_mips,7.5,user).demand(hlr_processing_mips,7.5,user).demand(vlr_processing_mips,7.5,user).demand(ac_processing_mips,7.5,user).demand(eir_processing_mips,7.5,user).demand('Speech Coders',27,user).demand('Echo Cancellors',30,user).
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Sample PSL OutputsCode Description Qty Cost==== =========== === ====ac-ppc AC-Power PC 1 2000ac-unit Authentication Centre Unit 1 0atm_backbone ATM Backbone Network 1 200000bts36 Base Transceiver Station-36 1 60000cp-ppc CP-Power PC 1 2000cp-unit Call Processing Unit 4 0eir-ppc Equipment Identity Register-Power PC 1 2000eir-unit Equipment Identity Register-Unit 1 0hlr-ppc HLR-Power PC 1 2000hlr-unit Home Location Register Unit 1 0pc-atm-card PC-ATM-Card 5 5000pc-disk Mass Storage 14 14000pstn-access-ce PSTN Access Common-Equipment Level-0 1 2357pstn-access-dsp SC/EC-module Density-2 3 7050pstn-access-ec Echo Cancellor Software 3 0pstn-access-oc3 OC-3 Chanelized Voice 1 1435pstn-access-sc Speech Coding Software 6 0pstn-access-sts3 155MB ATM Spigot Box 1 1500pstn-access-unit PSTN-access-unit 1 0radio-access-ce Radio Access Common-Equipment Level-0 1 2357radio-access-t1 T-1 2 2648radio-access-unit Radio-access-unit 1 0vlr-ppc VLR-Power PC 1 2000vlr-unit Visitor Location Register Unit 1 0
Total cost is 306347
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Overview
n Context / Historical Overviewn Constraint-based Configuration with
CLP(BNR)n Configuration for Designn Cost-Analysis of Nodal Equipmentn Cost-Analysis of Network Configurationsn Lessons learned
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Cost-comparison of Wireless ATM vs. GSM Network Architectures
Given n Traffic capacity requirementsn Base-Station cell-distributionsn Sparing designs for fault-tolerancen Distribution of processing in the network
Computen Nodal and transport costs
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A wireless network in North Carolina
Raleigh
Charlotte
Columbia
PSTN
PSTNPSTN
3 BSCs (Winston)
BSC (Myrtle)BSC (Fay)
130 mi287 mi
183 mi
BSC (Gold)
(5 BSCs + 1 MSC)
(3 BSCs(2 BSCs
BSC (Hick)
2 BSCs (Chare)
2 BSCs (Spart)
BSC (Florence)
52 mi114 mi
45mi
45mi83mi
97mi
106mi
125mi
74mi
5mi
5mi5mi
+ 1 MSC)+1 MSC)
BSC (Wilm)
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MSC and Cell DistributionColumbia
2 BSC, 38 cells co-located with MSCChare: 2 BSC, 39 cells,6400 subsSpart: 2 BSC, 55 cells,11850 subsMyrtl: 1BSC, 10 cells, 1640 subsFlorence: 1 BSC, 18 cells, 2900 subs
Charlotte5 BSC, 99 cells, co-located with MSC
Hick, 3 BSCs, 67 cells, 6400 subsWinston, 1 BSC, 22 cells, 14530 subs
Raleigh3 BSC, 77 cells, co-located with MSC
Fay, 1 BSC, 26 cells, 5750Wilm, 1 BSC, 21 cells, 3800Gold, 1 BSC, 22 cells, 7040
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Traffic Summary
Total number of subscribers . . . . . . . . . 100,855Erlangs per subscriber . . . . . . . . . . . . . 0.0275Total Erlangs in system . . . . . . . . . . . . . . 2,774Total cells in system . . . . . . . . . . . . . . . . 488Average configured trafic channels/cell . . . . 56Average Erlangs per cell . . . . . . . . . . . . . . 5.7Average required TCH/cell @ P=0.1 . . . . . . 12
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Switching Center Configurations
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4 Scenarios
(1) Process calls as early as possible at the BSC (i.e. minimize bandwidth consumption)
(2) Concentrate call processing at the MSC (i.e. minimized processing equipment)
(3) Provide redundancy/ fault tolerance in the Network rather than in the nodes
(4) Distribute all processing in the network.
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Results
$0.00
$100.00
$200.00
$300.00
$400.00
$500.00
$600.00
Scenario 1 Scenario 2 Scenario 3 Scenario 4 GSM
Equipment Cost
• Includes BTS Backhaul• Assumes 71% Margin on Equipment
Back Haul Cost
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Equipment Costs Only
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Lessons Learned
n System designers want tools explore design spaces and observe the impact of nodal and board-level design decisions on network architecture (and vice-versa);
n System designers don’t care what algorithms are being used for optimization, but they want to have control over what is being optimized.
n Optimization algorithms should be integrated in a familiar environment, e.g. spreadsheet or a user-specifiable, special-purpose configuration language;
n Users need to visualize the results.