Configuring Telecommunications Equipment and...

Configuring Telecommunications Equipment and Networks

André Vellino, [email protected]

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


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


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


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.


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).


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.


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)).


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


Example


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!


Overview

n Historical Overview of CLP(BNR)n Constraint-based Configuration with



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


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


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


Conventional Design Cycle


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


Configuration-Based Design


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.


Overview

n Context / Historical Overviewn Constraint-based Configuration with



Distributed ATM Architecture

ATMSE

PSTN

BTS

555 555

Radio Access Unit

PSTN Access Unit

System ManagerATM

SE

ATMSE

Call Processing Engine

Data Server


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


Module Shelves


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


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)],[]).


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).


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


Overview

n Context / Historical Overviewn Constraint-based Configuration with



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


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)


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


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


Switching Center Configurations


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.


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


Equipment Costs Only


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.

Configuring Telecommunications Equipment and...

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