Telecommunication traffic pricing control system

Delay-tolerant calls access slack capacity in a telecommunications network under variable pricing controlled by the network so as to permit the network to pick up or stimulate background traffic loads as and when desired to gain revenue from background idle capacity.

FIELD OF THE INVENTION 
This invention relates to control and pricing of telecommunication traffic. 
BACKGROUND OF THE INVENTION 
Telephone companies have traditionally sought to stimulate demand through 
tariff reductions in off-peak hours. However, fixed-discounting schedules 
are not adaptive to the actual hourly and daily changes in calling 
patterns in response to unpredictable diurnal, cultural, or seasonal 
events. They also risk having the unanticipated effect of overstimulation 
of demand which can threaten network performance objectives. Fixed 
discount schedules are also not specific to individual routes or trunk 
groups and rely for their revenue effectiveness on a single accurate 
overall assessment of price elasticity. And yet the supply-demand curve 
most likely varies across origin-destination pairs and through time 
considerably. It is also slow and costly to effect and publicize changes 
to a fixed discounting scheme. Conventional fixed discount schemes also 
apply to the basic calling services which must be given a guaranteed grade 
of service. 
The economic principle of spot pricing based on current demand and supply 
conditions has been previously studied by Vickrey for public utilities 
such as electricity, telephone, water supply which usually have a rigid 
price structure. Spot pricing has also been studied for some time in the 
power industry. As Dondo and El-Hawary have explained, however, "In spot 
pricing of electricity, the objective is to maximize the producer and 
consumers' social welfare. To maximize this welfare function, the price 
for consumption of electricity should be based on the actual cost incurred 
in supplying power to the consumer". Other work on dynamic pricing for 
electrical power aims to reduce peak demand by shifting some usage into 
non-peak times. But variable pricing in power applications is different 
from the telecommunications market. In the power system there is really no 
equivalent to the use of slack capacity that exists in telecom networks. 
Excess generating capacity may exist but it is not without significant 
cost to use this excess, i.e., fuel must be burned or reservoirs depleted. 
In contrast, using the `background capacity` of an installed operating 
telecom network is almost totally without additional cost for the use of 
the excess transport itself. New costs will arise only in the 
infrastructure to support new forms of access to this slack capacity. 
Variable pricing in the power industry is primarily a generation not 
transport issue. In the telecommunications industry, transport itself is 
the commodity and the users are the generators. 
For long distance telephone service Vickrey also suggested that the price 
should be set such that it equals the short run marginal cost of the call, 
i.e., the cost to the other users of the system in terms of their 
increased blocking, the aim being to vary price in such a way that the 
blocking would remain at a low and constant level. But this is essentially 
a load-levelling use of adaptive pricing that would be applied to all 
traffic. 
In the power industry, a Power Pool scheme is known that facilitates 
variable pricing to match supply offers from private (non-utility) 
generating companies to large-user price bids. Suppliers and users 
register as members of the Power Pool. Pool bidders are either large 
industrial consumers or aggregations of smaller individual users. 
SUMMARY OF THE INVENTION 
The inventors propose real time-variable pricing of slack capacity on 
selected trunk routes. While traditional volume stimulation schemes are 
focused on the low-blocking foreground traffic, the inventor proposes a 
new class of "background" traffic applications that can accept and exploit 
the time-varying slack capacity not used by the foreground conventional 
services. Such applications receive as available service only. The supply 
for this market is the time-varying capacity on each trunk group that is 
not currently needed to meet the network's obligation to provide the 
target blocking levels for foreground on-demand tariff-priced calling. 
According to one aspect of the invention, there is provided a 
telecommunication traffic pricing and control system for a 
telecommunication network that includes at least one trunk group and a 
local access switch for providing access to each trunk group for plural 
subscribers, the telecommunication traffic pricing and control system 
comprising: 
means to measure slack capacity on the trunk group and provide a signal 
representative of slack capacity on the trunk group; 
a price controller having as input the slack capacity signal for generating 
a price to subscribers for use of the slack capacity by delay tolerant 
calls; and 
a first subscriber agent responsive to the price set by the price 
controller for generating a request for service to the local access switch 
for a delay tolerant call when the price for the delay tolerant call meets 
conditions set by the subscriber. 
Preferably, the price controller implements a pricing strategy that is 
dependent on past changes in telecommunications traffic volume on the 
trunk group and past changes in price of delay tolerant calls, and 
preferably implements a set of fuzzy logic rules. The subscriber agent may 
aggregate data from plural other subscriber agents, and store it in a 
storage system. 
These and other aspects of the invention are described in the detailed 
description of the invention and claimed in the claims that follow.

DETAILED DESCRIPTION OF PREFERRED EMBODIMENTS 
In switched public networks the design busy hour levels of traffic occur on 
only a fraction of the yearly and daily traffic cycles, and traffic growth 
only nominally meets the design provisioning levels at the end of the 
provisioning forecast period. In a trunk group that is operating at design 
limits, there is considerable slack capacity in real trunking networks. 
The background capacity at design limits exists only in the form of idle 
time segments dispersed randomly over the trunks of the group. But, at off 
peak times, whole numbers of trunks may be effectively diverted for other 
uses without affecting the 1% g.o.s. guarantee for foreground traffic. In 
this invention, the idle time of the trunk groups is offered to 
subscribers with delay tolerant calls. Delay tolerant calls include: 
updates of large Internet routing tables, remote site database backups, 
and dissemination of newsgroup updates. The information packet associated 
with a delay tolerant call will be referred to as payload. 
A telecommunication traffic pricing and control system for a 
telecommunication network is shown in FIG. 1. The pricing and control 
system is applied to an existing telecommunications network that includes 
one or more trunk groups 10, 12 and a local access switch 14 for providing 
access to each trunk group 10, 12 for plural subscribers. The trunk groups 
10, 12 connect with other intermediate switches 16, 18 and other trunks 
20, 22 leading to call destinations A, X. 
Each switch 14, 16, 18 is conventional and such switches include means to 
measure slack capacity on the trunk groups connected to the switches. The 
switches 14, 16, 18 are capable of sending a signal representative of 
slack capacity on the trunk groups to which the switches are connected. 
That signal may take the form of a signal derived from the group size and 
current carried load, or from group size and blocking probability. 
The slack capacity signals for destination A are provided as an input along 
lines 24, 26 to a price controller 30. The slack capacity signals for 
destination X are provided as an input along lines 32, 34 to price 
controller 36. Other destinations may be provided with their own price 
controllers, each receiving slack capacity signals from the local access 
switch 14. 
The price controllers 30, 36 generate a price to subscribers for use of the 
slack capacity by delay tolerant calls in a manner to be described. The 
pricing strategy of the price controllers 30, 36 preferably seeks to 
maximize revenue for the network operator. This pricing strategy may be 
implemented in several ways, as for example based on a theoretical or 
empirically based time dependent demand and supply model. However, this 
strategy presupposes knowledge of the demand curve, and this is unlikely 
to be known. A preferable model is to continuously update the price 
according to recent changes in the price and demand and expected demand 
changes for that time of day. 
The price, once set is published, or made available to subscriber agents 
40, 42 at subscriber locations 44, 46 respectively. Each subscriber 
location 44, 46 includes the agent itself. The agent may be a computer 
programmed to carry out the functions described in this patent document. 
The subscriber location 44, 46 also includes conventional data 
communications equipment for communicating with the local access switch 14 
and a storage means 48, 50 for storing a delay tolerant message pending 
connection to the network (this may be a hard drive forming part of the 
computer) through lines 61, 63. The lines 61, 63 and other dashed lines 
represent lines connecting subscriber communication equipment to the trunk 
groups 12 through local access switch 14. Various connections may be made 
according to the type of equipment being used, the configuration of the 
switch and the network configuration. 
Subscriber agent 44 is a single subscriber and has a standard telephone 52 
for regular connection to the network through line 53. Subscriber agent 46 
is an aggregrator service bureau connected via a user interface 54 to 
several subscribers, who each may have their own agent. The local 
connections between an aggregator agent 46 and its subscribers may 
themselves be established by dialup connections to the aggregator 46 from 
its clients made through the same local access switch 14. The effect is 
still as shown in FIGS. 1 and 2, however, and this possibility is not 
overlaid on the figure to avoid unnecessary further complexity in the 
drawing. 
The subscriber agents 40, 42 are responsive to the price set by the price 
controller and generate a request for service to the local access switch 
14 through lines 41, 43 for a delay tolerant call when the price for the 
delay tolerant call meets conditions satisfactory to the subscriber. The 
conditions under which the subscriber will request service are specified 
by the subscriber and stored in the agent's computer. Upon deciding to 
request service, the agent 42, 44 sends a request for service signal to 
the service manager 60 via line 62. The service manager 60 logs the call, 
authorizes the local access switch 14 via line 64 to make the desired 
connection and sends a signal to the account manager 64 to later generate 
a billing for the subscriber. 
The subscriber aggregrator 46 logs all delay-tolerant service requests from 
its pool of subtending users. For some applications the aggregator 46 may 
have means to alert the intended user when the desired network slack 
capacity is available or ready, leaving the payload stored with the source 
or to be generated then by the source. In a medium or large business the 
agent/aggregator 44, 46 may be interfaced to subscriber equipment 49, 51 
which may include one or more LANs, file servers, PBXes, FAX machines, 
telephones or other communications devices through which user-designated 
service-delay-tolerant data, video, voice-mail, e-mail, fax, and even low 
priority voice call requests may be collected and summarized by totals 
intended for respective destinations. Users retain the ability to make 
ordinary on-demand use of the switched network as needed as for example 
using telephone 52. 
The conventional data communications equipment at the subscriber agent 44, 
46 may be a conventional ISDN or ATM network access facility, analogous to 
the C.O. trunks on a PBX today. The basic rate ISDN interface provides two 
B channels and one D channel to the user. Each B channel has a bandwidth 
of 64 kbps and can be used by the user to transmit both voice and data. 
The D channel has a bandwidth of 16 kbps and is used to carry signaling 
information for the B channels. The D channel gives an opportunity for 
direct interaction between the user and the telecommunication network 
through the local access switch 14. The agent 44, 46 is logically 
connected via the ISDN D channel (or on a designated ATM VCI) and the 
local access switch 14, to the service manager 60 and regularly receives a 
list of current prices (per unit time) for each destination on which the 
background transport service is offered. When the agent 44, 46 decides 
that a particular price meets the objective of its user strategy, the 
agent 44, 46 signals the service manager 60 of its agreement to pay at the 
current offered rate to the required destination, and forwards the 
connections set up data. The service manager 60 then sets up the 
connection and begins charging the agent 44, 46 for the time used in the 
current pricing intervals at the agreed price. The price from the price 
controller 30 is updated at update intervals, at which the network can 
adjust the price offering. The service manager 60 may override the price 
from the price controller 30 and raise the price back to full tariff at 
any time. The agent 44, 46 may also cancel the connection at any time at 
its discretion. The service manager 60 also reserves the right to 
terminate (and stop charging for) any background connection in progress, 
if essential to protect the foreground g.o.s. The user agent 44, 46 may 
revisit its decision for any connection that is ongoing into the next 
price update period, if the price changes. 
The strategy of the subscriber agent 44, 46 is selected by the subscriber, 
and may be a simple strategy such as: Send payload X only when price is 
less than Y. Various strategies would be available to the subscriber that 
may be implemented in software in the agent's computer. 
The subscriber agent 44, 46 may also be integrated with a PBX with 
signalling between network and customer agents on the ISDN D channel with 
user-to-network type packets or, in an ATM context, a virtual channel can 
be established with agent-network interactions supported by Q.931 
signalling. The aggregrator 46 may serve groups of medium and small 
businesses and perhaps some residential users by logging all their access 
requests and implementing a decision strategy on their collective behalf 
for participation in the slack capacity market pool. 
The system as shown in FIG. 1, and FIG. 2 allows the following activities 
to occur simultaneously. A subscriber 66 (for example a small company) may 
make a conventional on-demand connection to destination X through line 67 
while the same subscribers' agent 44 simultaneously receives background 
service price updates to destinations via the permanent logical connection 
to the service manager 60 at the local access switch 14 and at the same 
time a variably priced connection to destination A is in progress for a 
local user through agent 44. 
Aggregator agent 46 serves a variably priced connection to destination x 
through to one of its client subscribers, while at the same time it 
receives and stores at storage 50 (for example) a number of fax 
transmissions from another aggregator client to be lodged with the 
aggregator agent for later dispatch according to the aggregator's 
price-acceptance and dispatch management strategy. 
There are two basic types of service that the subscriber agent 44 or an 
aggregator agent 46 may provide for its users or clients: 
(1) a connection to the specified destination number. Such a connection 
passes through the user/agent interface 40, 42 when available and directly 
connects the user to his destination. The time of establishing the 
connection is not generally on demand, rather, it is determined by the 
time at which the networks' price offer to the destination locale is 
accepted by the aggregator/agents strategy or policy which may include 
maximum price limits set by the user when the connection request was 
logged with the aggregator 46 or agent 44. An example of this might be 
when someone wishes to have a personal video conference, or dialup onto a 
remote host, but the exact times of which may be flexible for the user, 
within certain desired price and time window constraints the user may 
register with the agent. Another example is an Internet Service Provider 
(ISP) who might log a connection request which would be used to enhance 
throughput for its users, if the augmentation circuit request is 
obtainable below a certain price. Thus, the uncertainty of getting the 
extra connection or not may be tolerable if the average effect is an 
improvement perceived by the ISPs clients. Conversely the ISP may increase 
what it is willing to pay for the extra connection if it senses its own 
"busy hour". 
(2) a bulk data dispatch task. The user lodges the transport request with 
the agent (eg, price limits, time limits, destination number, information 
type), and uploads the data quantities to be transmitted temporarily to 
the storage system 50. The quantity of data is then on-line for the agent 
44 to dispatch later via the agent-network price cooperation, under the 
agents' autonomous decision-making. Exemplary usages include: volumes of 
fax or remote-site backup of large data files; image and/or video clip 
archiving service which responds to requests from its customers in either 
an immediate sending mode, or, at its clients options, in a cost-saving, 
delayed delivery mode; distributing newsgroup file updates or downloading 
large binaries for virtual reality games. 
On the network side, the service manager 60 and price controller 30 are 
implemented in computers running at Class 4 or Class 5 switching centres. 
The price controllers 30, 36 receive blocking or carried traffic 
measurements for all trunk groups at their respective sites. Price 
controllers 30, 36 may preferably collect both carried load and blocking 
measurements from the trunk groups 10, 12 en-route for each destination. 
Blocking is the most sensitive measure of available capacity when loads 
are relatively high, but is a very weak measure of load (hence slack 
capacity available) when the traffic intensity is lower. Blocking can take 
a long time to measure accurately at low load therefore carried traffic 
measurements are better used when the actual blocking events over a short 
measurement interval are zero. If ATM networking is used, loss, delay or 
call admission blocking measures are provided to the price controller 30, 
36. The description that follows applies to a conventional 
circuit-switched trunking network, but may be simply modified to apply to 
an ATM network. A single logical trunk group is assumed to exist between 
each origin-destination pair. In the more general case of tandem switched 
connections, the end to end blocking and carried traffic replaces the 
single-group measures used in the description below. 
Based on the time of day, on its price-optimizing strategy, on the current 
intensity of on-demand foreground tariffed traffic and on the currently 
admitted background traffic, the price controller 30, 36 regularly updates 
its list of destination prices to all subscriber agents 44, 46. The price 
controller's objective is to find the price for each destination that will 
continually maximize the product of background traffic volume elicited and 
the price offered by the network to bring this traffic out, without 
jeopardizing the g.o.s. (blocking) for the foreground traffic. 
The price controller 30, 36 and service manager 60 are totally in control 
of pricing and of admitting background offered load. In the case of a 
large step increase in offered demand in response to a sharp price drop, 
the service manager 60 need not admit all this load at once. The service 
manager 60 admits the price-stimulated volumes subject to a constraint on 
the estimated blocking on the trunk groups 10, 12 under the total 
(foreground and background) carried load. If the size of the price 
adjustments respond inversely to the apparent responsiveness of the 
environment in which the price controller 30, 36 finds itself, the network 
is not overwhelmed by a transient background load. 
The price controller 30, 36 sets the price for the slack capacity in time 
steps, which may be measured in terms of minutes or hours. The price 
setting for the i.sup.th time-step is approached as a change in price with 
respect to the previous time-step. This tracking incremental change 
orientation has been found much more effective than attempts at rule sets 
that generate an absolute price value for background traffic in each 
interval. The rule sets which were tested to determine a new price 
absolutely for each epoch produced volatile price variations and a poorer 
approximation of the optimal price trajectory. 
The rule set proposed has a small inherent instability which, if all other 
parameters were fixed, (and the system is not operating up against the 
tariff price ceiling) causes a bounded (-5%) alternating variation in 
price. Consequently there is always some "small-signal" exploration on the 
price axis of the (hidden) demand curve. Based on these exploratory price 
changes, an internal variable, "sensitivity" (S), is defined as follows 
(equation 1): 
##EQU1## 
where V.sup.i.sub.cs is the carried background traffic volume observed in 
time-step i and P.sub.i is price in time-step i.. Traffic volume, V, (in 
circuit-seconds) is used because it is a directly measurable quantity. It 
is related to traffic intensity (in Erlangs) by A=V/.DELTA.t where 
.DELTA.t is the time interval over which volume V is observed. Eq. 1 is 
therefore of the same general form as the equation generally known in 
economics for the price elasticity of a commodity: 
##EQU2## 
where V=Q and the minus sign is effected by reversal of P.sub.i subscript 
orders in numerator and denominator. Hence S.sub.i is of the form to be a 
discrete approximation to elasticity. It is, however, an exact 
approximator of the true elasticity present only if the partial derivative 
of V with respect to P is what .DELTA.V/.DELTA.P reflects in a given time 
step. In practice, the offered traffic also changes in response to time, 
not just price (i.e., .delta.V/.delta.t is non-zero) and the observed 
.DELTA.V/.DELTA.P is not solely a measure of .delta.V/.delta.t as desired. 
The price controller 30, 36 may set prices according to S, -thus assuming 
it is an uncorrupted measure of elasticity: If S.sub.i+1 is positive it 
means that the recent history of the system is of volume and price moving 
in opposite directions. This suggests the presence of hidden demand to be 
exploited (e.g., price was decreased and an increase in volume was 
observed). A stronger indication that price should be lowered further is 
if S.sub.i+1 &gt;1 which indicates that the volume increase was more than the 
price decrease, which is the mark of price elasticity and yields a net 
increase in revenue. 
However, traffic also varies significantly with time of day, regardless of 
price effects. There is an inevitable increase for example at, say, 9 AM, 
relative to 6 AM every day. By itself, S can therefore be corrupted and 
misleading when underlying time of day traffic variations are significant. 
A negative sensitivity value in the last epoch means that price and volume 
recently moved in the same direction. In this case, S is likely dominated 
by underlying traffic change effects, not price elasticity, because demand 
does not in practise ever increase in response to a price increase. So in 
these circumstances price should not be lowered even though S alone would 
suggest doing so. S can therefore contribute to rules for lowering price 
but is given less weight in times where high diurnal change is expected 
and if S is returning negative values. On the other hand, at times of day 
(or especially night) when nominal traffic is relatively stable, if the S 
estimate is positive and greater than 1.0, S is a fairly trustworthy 
indication of price elasticity and an opportunity for increased revenue in 
the background service subsystem by a further price reduction. 
From the above considerations, it is apparent that the controller must 
derate the sensitivity estimate under some circumstances because S 
responds to time-of-day effects as well as underlying shifts in the 
potential for price-stimulation. On the other hand if it were known that 
the nominal offered traffic was stable, then S would be a reliable 
indicator of price elasticity. Accordingly, the control rules incorporate 
a coarse set of daily "time zones" as fuzzy sets on the variable t. 
Generic time-of-day considerations then modify the weight of the other 
rules that are based on the sensitivity estimate. This tends to decouple 
underlying diurnal cyclic effects from true elasticity effects. 
Another group of rules that contribute to the price output are based on the 
estimated blocking of the foreground traffic on the trunk group. These 
rules contribute to an increase in price when the foreground blocking 
estimate increases while still below the target grade of service, 
B.sub.max in two successive intervals. The blocking-based rules gain 
strength rapidly to force the price towards full tariff, however, as the 
blocking level rises "close to B.sub.max ". An explicit "crisp" rule 
clamps the background price at a small value (for example 5%) actually 
above tariff as an absolute maximum price for background demand if the 
blocking estimate ever exceeds Bmax. The service price, in practice, may 
be allowed to go slightly above tariff if driven by the blocking-related 
rules on the principle that the background should be completely squelched 
(equivalently, charged the same as foreground traffic) if the blocking 
estimate even suggests-threatening foreground g.o.s. Note that when the 
background price reaches tariff, then background traffic (if any is still 
offered by the agents at P=1.0) is conceptually equivalent to ordinary 
traffic that has just arrived through a different access system. 
A collection of 22 fuzzy logic rules have been developed for use in the 
price controller 30, 36. The variables employed and the fuzzy membership 
functions defined on them are summarized in Table 1. Except where noted 
below, membership functions which do not straddle zero were all 
trapezoidal in shape. Those that straddle zero are the "negligible change" 
sets, and they have triangular membership functions. Fuzzy set boundaries 
are adjusted in practice, and may be tuned to a representative training 
case. All rules are of the general form: 
if (variable-name) is (name of a fuzzy set defined on this variable) . . . 
AND/OR . . . {similar terms . . . } then (name of a fuzzy set defined on 
.DELTA.P) as for example the following rule set: 
Rule 1: If sensitivity is INCREASING and price is DECREASING then RAISE 
PRICE SIGNIFICANTLY. 
Rule 2: If sensitivity is INCREASING and price is INCREASING then LOWER 
PRICE SIGNIFICANTLY. 
Rule 3: If sensitivity is CONSTANT and price is INCREASING then LOWER PRICE 
SLIGHTLY. 
Rule 4: If sensitivity is CONSTANT and price is DECREASING then RAISE PRICE 
SLIGHTLY. 
Rule 5: If sensitivity is INCREASING and price is CONSTANT then LOWER PRICE 
SLIGHTLY. 
Rule 6: If sensitivity is DECREASING and price is CONSTANT then RAISE PRICE 
SIGNIFICANTLY. 
Rule 7: If sensitivity is DECREASING MEDIUM and price is INCREASING MEDIUM 
then HOLD PRICE. 
Rule 8: If sensitivity is DECREASING SMALL and price is INCREASING SMALL 
the HOLD PRICE. 
Rule 9: If sensitivity is DECREASING BIG and price is INCREASING BIG then 
HOLD PRICE. 
Rule 10: If sensitivity is INCREASING MEDIUM and price is DECREASING MEDIUM 
then HOLD PRICE. 
Rule 11: If sensitivity is INCREASING SMALL and price is DECREASING SMALL 
then HOLD PRICE. 
Rule 12: If sensitivity is INCREASING BIG and price is DECREASING BIG then 
HOLD PRICE. 
Rule 13: If sensitivity is INCREASING BIG and price is DECREASING MEDIUM 
then LOWER PRICE SLIGHTLY. 
Rule 14: If sensitivity is INCREASING MEDIUM and price is DECREASING SMALL 
then LOWER PRICE SLIGHTLY. 
Rule 15: If sensitivity is INCREASING BIG and price is DECREASING SMALL 
then LOWER PRICE SIGNIFICANTLY. 
Rule 16: If sensitivity is DECREASING MEDIUM and price is INCREASING SMALL 
then RAISE PRICE SLIGHTLY. 
Rule 17: If sensitivity is DECREASING BIG and price is INCREASING SMALL 
then RAISE PRICE SIGNIFICANTLY. 
Rule 18: If sensitivity is DECREASING BIG and price is INCREASING MEDIUM 
then RAISE PRICE SLIGHTLY. 
Rule 19: If sensivity is CONSTANT and price is CONSTANT then HOLD PRICE. 
Rule 20: If price is ABOVE TARIFF then LOWER PRICE SIGNIFICANTLY. 
When blocking increases, this pricing strategy, as implemented by the price 
controller, tends to increase price over that suggested by the latency 
change. Additional rules to provide price changes in response to blocking 
changes may then be used: 
Rule 21: If blocking is INCREASING then RAISE PRICE SIGNIFICANTLY. 
Rule 22: If blocking is DECREASING then LOWER PRICE SIGNIFICANTLY. 
To avoid blocking increasing too much, the price may be raised whenever 
blocking increases beyond a set amount for example 1%. 
When the weight of all rules are evaluated, the degree of membership in 
each fuzzy set defined on the output variable P is established. To make 
the output price change suitably responsive and capable of a wide range of 
output price step changes, a monotonic increasing-only output membership 
functions may be used, except for HOLD PRICE, which is triangular about 
zero price change. 
In a model of the plan, results shown in Table II were obtained. Table II 
shows that the FL price controller consistently outperformed the 
tariff-only pricing strategy by 13 to 14%, based on a model with 
.alpha.=-0.3 and 2&lt;L&lt;7, where .alpha. is a measure of the shape of the 
hidden curve relating total demand to price, such that demand, D, equals 
1-.alpha.P-.alpha.P.sup.2 . . . 0&lt;P&lt;1 and L is the latency factor, which 
represents the upper limit to demand stimulation, relative to the 
foreground only traffic, if price were brought to the zero limit. 
Separately, Table III shows a 43% increase in the theoretical maximum 
(total) earnings as .alpha. goes from -1 to +1 and shows that the fuzzy 
logic price controller 30, 36 yielded revenue gains over tariff-only 
operations of 4.2% at .alpha.=-1 up to 20.7% in the most optimistic case 
of .alpha.=1. Note, however, that while the fuzzy logic price controller 
30, 36 improves performance relative to fixed pricing as .alpha. 
increases, the performance relative to the optimum for attainable revenue 
seems to deteriorate: While the absolute earnings go on increasing with 
.alpha., the percentage of theoretical revenue achieved drops by about 9% 
(from 89.93 to 80.61%) as the economic conditions for stimulation grow 
more favourable. Detailed inspection of the simulation cases for Table III 
showed that this is largely due to some blocking implications which the FL 
controller takes into account which the analytical model for P.sub.opt 
does not reflect. The price controller 30, 36 has the objective of 
maximizing revenue while keeping the estimated foreground blocking levels 
under B.sub.max (0.02 in these simulations). However, while the optimum 
price benchmark calculation has P&lt;1 built in to it, it has no inherent 
constraint regarding P(B) and can recommend pricing that corresponds to 
stimulation of stimulated traffic which would indeed exceed B.sub.max. 
This is largely why the fuzzy logic price controller 30, 36 performance 
appears to degrade in the cases of high .alpha., because P.sub.opt can 
range low enough to overstimulate from a blocking viewpoint, while still 
being optimal solely from a revenue viewpoint. But these high theoretical 
levels of stimulation are areas where the price controller 30, 36 will not 
follow, as it is backing off, watching for the foreground blocking 
implications. In fact this departure of the price controller simulation 
and the purely economic optimum pricing, demonstrates that the controller 
will forfeit some theoretically achievable background revenue to operate 
without degrading foreground g.o.s. In fact, in the case of .alpha.=1, 
inspection showed that the purely revenue-optimal price strategy can 
generate peak offered traffic demand points that would cause as much as 
22% blocking, if it was allowed. This confirms the need in practise to 
explicitly constrain the working domain of the controller in both P&lt;1 and 
P(B)&lt;B.sub.max senses, as in the exemplary price controller 30, 36 
described. 
In calculating revenue optimization, lost revenue from traffic displacement 
should be accounted for wherein some degree of displacement would occur 
from the foreground tariff-calling service to the background 
delay-tolerant service mode. This might occur particularly if the network 
guaranteed the price for a predefined multi interval period. This would, 
however, be more complicated for the price controller 30, 36, in terms of 
not jeopardizing foreground g.o.s. and optimizing the price setting. 
When latent demand and demand curve conditions cannot support a revenue 
gain the price controller 30, 36 offers no price reductions and the whole 
system effectively merges with the foreground tariff-priced operations. 
Only when the controller senses exploitable volumes of latent 
delay-tolerant demand, in conjunction with its own slack capacity to carry 
that demand does it discount the pricing to bring forward volumes of 
paying traffic on otherwise lightly loaded facilities. The aim of the 
controller will be to continually approximate the revenue-maximization 
point on the hidden demand curve for background capacity. 
Unlike schemes for variable pricing and fixed telephoned tariff discounts, 
the price control of the present invention does not vary price for all 
subscribers as a means to limit demand to maintain a target blocking 
level. The subscribers may pay a subscription fee to join in the "market" 
for the surplus transport capacity and then use pricing to stimulate, not 
limit, traffic, creating a "surplus capacity market". The new mode of 
access also serves only delay-tolerant and suspendible applications. Note 
that by delay tolerant here, is meant delay in receiving service. This is 
not the same as tolerance to delay variance which the same words usually 
refers to in ATM. 
Finally, the service manager 60 may be controlled with a computer, such as 
a personal computer 63, to offer special price promotions, and feedback 
from the service manager 60 may provide service volumes and pricing back 
to the computer 62 for monitoring of the service. 
A person skilled in the art could make immaterial modifications to the 
invention described in this patent document without departing from the 
essence of the invention that is intended to be covered by the scope of 
the claims that follow. 
TABLE I 
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Variables and Fuzzy Sets Employed 
Variable 
Description Fuzzy Sets on Variable Domain 
______________________________________ 
S.sub.i 
sensitivity (Eq.(15) 
"negative big, medium", small", 
negligible change", and positive 
mirror-image sets 
P(B).sub.i 
measured foreground- 
"very low","OK","close to 
blocking B.sub.max " 
.DELTA.P(B) 
P(B).sub.i - P(B).sub.i-I 
"decreasing","increasing" 
.DELTA.P.sub.i-I 
last two price changes, 
"increased/decreased {signif- 
.DELTA.P.sub.i 
respectively cantly, medium, . . . slightly}" 
and "negligible change" 
t.sub.i 
time of day "night,""early AM","morning", 
"mid-day", "PM","late PM", 
"evening" 
P.sub.i 
Background price (per unit 
"very low","moderate","near 
time to specific destina- 
tarrif,""virtually at tariff" 
tion) 
______________________________________ 
TABLE II 
______________________________________ 
Total revenue as a percent of theoretical maximum for randomized 
3-day simulations (.alpha. = -0.3,2 &lt; L &lt; 7, A.sub.ot (t) = training 
case 
+/- 30% randomization) 
Price fixed at Tariff 
F.L. Controller 
______________________________________ 
Case 1 73.81% 87.85% 
Case 2 74.28% 89.61% 
Case 3 74.06% 86.96% 
Case 4 73.94% 86.51% 
Case 5 73.98% 89.50% 
______________________________________ 
TABLE III 
______________________________________ 
Total revenues as a percent of theoretical maximums 
for the 3-day simulation case with varying .alpha. 
Total revenue 
.alpha., shape of at Optimum Price 
D(P) Price fixed at tariff 
F.L. Controller 
(relative to .alpha. = -1) 
______________________________________ 
.alpha. = -1 
85.76% 89.83% 1.0 
.alpha. = -0.5 
76.98% 88.78% 1.114 
.alpha. = 0 
69.82% 87.58% 1.228 
.alpha. = 0.5 
64.28% 83.74% 1.334 
.alpha. = 1 
59.87% 80.61% 1.432 
______________________________________