Inter-Infrastructure Simulations across Telecom, Power, and Emergency
Services\*

Gerard O'Reilly^1^, *Member, IEEE*, Huseyin Uzunalioglu^1^, Stephen
Conrad^2^, Walt Beyeler^2^

^1^Bell Laboratories, Lucent Technologies, 101 Crawfords Corner Road,
Holmdel, NJ 07733 USA\
^2^Sandia National Laboratories, Albuquerque, NM\
E-mail: goreilly@lucent.com, <huseyin@lucent.com>, <sconrad@sandia.gov>,
wbeyeler@sandia.gov

*Abstract* -- **Critical national infrastructures for power, emergency
services, finance, and other basic industries rcely heavily on
information and telecommunications networks (voice, data, Internet) to
provide services and conduct business. While these networks tend to be
highly reliable, outages do occur which can have cascading effects to
other infrastructures. This paper describes a dynamic simulation model
of a power outage which cascades to impact telecom for services without
power back-up, which cascades to impact emergency services 911 calling,
which causes increased severity of injuries.**

*Index Terms* -- reliability, dynamic simulation, emergency services.

# Introduction

This paper describes a collaboration across infrastructures and the
System Dynamics simulator models to support that collaboration. The
simulation models are implemented using Vensim \[3\], which can be used
for dynamic simulation of other industry infrastructures \[1\]. Previous
efforts have included the N-SMART Voice \[2\] metro area PSTN discrete
event, call-by-call, simulation model. This more detailed model drives
the aggregated systems dynamics representations presented here in the
higher level models across infrastructures.

![](media/image1.wmf){width="2.033333333333333in" height="2.0625in"}

Figure 1 - Pairwise Inter-Infrastructures

The critical national infrastructures are shown on Figure 1. We have
telecommunications depicted at the center since it is critical to all
the others. Around the circle are critical infrastructures for power,
transportation, water, agriculture, emergency services, and the others.

What's new here is that we are no longer taking a smokestack approach to
industries, that is, each within their own perview. But rather, we are
taking them in pairs to look at the cascading of impacts between
industries.

In the next section we make this general discussion more specific. That
is, we simulate three infrastructures (Power, Telecom, and Emergency
Services) together in relation to a specific problem that might be
encountered in the future. In particular, power blackouts may cause loss
of telephone service for those without power back-up, which then impacts
the ability of people to call 911 in emergency service situations. The
resulting impact is that regular injuries become major injuries, and
major injuries could become fatal.

# Power, Telecom and Emergency Services

shows the potential cascading of events across infrastructures.

![](media/image2.wmf){width="3.4604166666666667in"
height="1.6055555555555556in"}

Figure 2 - Cascading of Impacts across infrastructures

## Inter-Infrastructure Vulnerability: Power and Telecom (Today's situation)

Today, there is very little cascading of impacts due to a power
blackout. Most people still have wireline phones that continue to work
during a blackout. Why? Central offices have back-up batteries and/or
emergency diesel generators to power the telephone lines during a
blackout. Hence, people have access to emergency services (police, fire,
medical) even during a blackout.

## Inter-Infrastructure Vulnerability: Power and Telecom (A future situation)

It is a fact that more and more people are moving to situations where
their phones won't work in the event of a blackout. These situations
include:

1.  People with only cordless phones, which need power to operate.

2.  People with wireless only service. It is estimated that about 4% of
    households in 2004 have wireless only service, i.e., no wireline
    service. This is expected to grow rapidly because of the economic
    incentive to do so. \[4\]

3.  People with voice over cable telephony service. The cable modems
    need power to operate.

4.  People with other VoIP arrangements where back-up power is not
    provided.

Where a telephone service has back-up power, we use the terminology
"power lifeline". When it does not, we say "no power lifeline." It is
possible for each of the above 4 categories to have power lifeline, but
it is typically not provided.

As an example, category 2 on wireless only service is affected only
after several hours of blackout. Cell towers typically depend on battery
back-up (\~4 hours). Hence, a power disruption (blackout) lasting longer
than 4 hours would eliminate telephone service for all those "wireless
only" access arrangements. Figure 3 shows a plot of a potential future
for wireless only service. By 2010, as many as 20-25% of households may
use services with no power lifeline \[4\]\[5\].
![](media/image3.wmf){width="3.1465277777777776in"
height="1.3347222222222221in"}

Figure 3 - Forecast of Wireless only Households

# Telecom Model - Example Vensim Model of Aggregate Wireline + Wireless Network

This section describes a model and uses it as the basis for our
aggregate wireline and wireless network of a metropolitan area of 5
million people.

Let's first review the example inputs representing the metropolitan area
of size 5 million

Number of people in the area 5,000,000

Average Call Holding Time (Wireline) 300 seconds

Average Call Holding Time (Wireless) 180 seconds

Busy Hour Calls /line (Wireline or Wireless) 2

An example traffic profile for a day is shown in Figure 4. The traffic
profile reflects the time-of-day variation of the traffic over a 24 hour
period. Communication networks are designed to handle peak busy hours,
which corresponds to the part of the profile that is equal to 1. Busy
hours on Figure 4 are 10:00 - 12:00, and 16:00 - 20:00. Outside of the
busy hour, the traffic rate is scaled by the factor given by the
profile. As can be seen from Figure 4, the traffic rate becomes very
small during night hours (only 10% of busy hour).

![](media/image4.wmf){width="2.0125in" height="1.8076388888888888in"}

Figure 4 - 24 Hour Example Traffic Profile

The aggregate Vensim Telecom infrastructure model of a metropolitan area
is shown on Figure 5. The telecom disrupt indicator variable (a 0 or 1
variable), on the lower right, indicates whether there is a telecom
disruption given by the Damage Level variable. The indicator is 0 (no
telecom disruption) for this first analysis. A telecom disruption is
dealt with later as a sensitivity.

![](media/image5.wmf){width="2.890277777777778in"
height="2.372916666666667in"}

Figure 5 - Network Model

# Power Blackout Model

A simple power blackout model is represented in Figure 6. The period
under study is 2 days or 48 hours long. Most blackouts last less than
this amount of time. There are three parameters:

-   start time of blackout (say at hour 4 as in the figure)

-   length of blackout (say 34 hours). In our example, this implies
    recovery starts at hour 38.

-   recovery time, that is, length of time after recovery starts that
    the blackout ends. (4 hours in our example. Hence, the end of the
    blackout occurs at hour 42.)

![](media/image6.wmf){width="2.3333333333333335in"
height="1.3333333333333333in"}

Figure 6 - Timeline model of power blackout

The Vensim model of this blackout model along with the number of
wireline and wireless subscribers impacted by the blackout is shown in
Figure 7. The left side takes a metropolitan area of say 5 million
people, breaks them down in households with wireline and wireless
services and eventually ends up with 5 categories of customers

1.  wireline only with power lifeline

2.  wireline only without power lifeline

3.  wireline + wireless with power lifeline

4.  wireline + wireless without power lifeline

5.  wireless only (assumes without power lifeline)

![](media/image7.wmf){width="3.3895833333333334in"
height="1.8222222222222222in"}

Figure 7 - Vensim Model of Power Blackout

The result of all this is a telecom efficiency function on the right
side of Figure 7, explained next.

## Network Telecom Efficiency under Blackout scenario

Combining the simple blackout model with the forecast of lines
throughout the area that are impacted by a power blackout, we get a
network telecom efficiency function, which is really a service
availability index of customers able to make telephone calls. The blue
dashed line on

![](media/image8.wmf){width="3.0145833333333334in"
height="1.7659722222222223in"}

Figure 8 - Network Telecom Efficiency

Figure 8 is the baseline, that is, telecom efficiency = 100% for the
whole period. Everyone is able to make telephone calls. The red solid
line on Figure 8 is the blackout scenario starting at hour 4 and lasting
until hour 42. The blackout starts at hour 4 with a slight dip in
telecom efficiency for those wireline only customers without power
lifeline. Then it dips significantly at hour 8 after all the cell towers
run out of back-up power. We modeled this as an instantaneous drop. In
reality, it would be spread out over a few hours as different cell
towers blackout because their battery reserves run down. Note that
batteries run down as a function of the amount of calling load. So, if
there is a spike in demand for cell usage, the cell towers may last
significantly less than 4 hours on their battery reserve.

This telecom efficiency function over time will be input into the
emergency services model discussed next.

# Emergency Services Model

Emergency Services consist of police, fire, and medical emergency
services. While we could break these down into three buckets and deal
with each separately, here we simply bundle them together since they are
all accessed by calling 911 in an emergency \[6\].

Some telecom 911 Facts are included in Table 1. One observes that the
number of 911 calls varies widely between areas.

Table 1 - 911 Calling by City

  -------------------- --------------------- -------------------------- ----------------------------
  [City]{.underline}   [Calls per            [Population]{.underline}   [calls/person]{.underline}
                       year]{.underline}                                

  Washington           1.8 million           563,000                    3.2

  LosAngeles           5 million             3,694,000                  1.4

  Baltimore            1.7 million           651,000                    2.6
  -------------------- --------------------- -------------------------- ----------------------------

For our generic metropolitan area of 5 million people, we will assume
and average 2.5 calls per person per year. This leads to an average of
approximately 34,000 calls per day assuming that the calls are uniformly
distributed over the 365 days of the year.

Now, two-thirds or 66.6% of 911 calls are non-emergencies. A
non-emergency is one in which there is no dispatch of police, fire, or
medical services. So, in the end, with our blackout, many of these
non-emergency calls won't get through but they have little impact since
there was no emergency in the first place.

## Injury facts

In 2003, over 20 million people (\~55,000/day) suffered disabling
injuries at home, work, in their community, or in transportation \[7\].
In addition, about 2.4 million people (\~6,000 per day) die each year.
Deaths by cause and death rates are shown in Table 2. These statistics
represent our baseline conditions when the telecom efficiency index is
at 100%. All of the following tables are from \[7\].

Table 2 -DEATHS AND DEATH RATES 2001

  ----------------------------- ----------------- -----------------------
  **Cause**                     **Number of       **Death Rate per 100k
                                Deaths**          population**

  **All Causes**                **2,416,425**     **847.6**

  Heart disease                 700,142           245.6

  Cancer (malignant neoplasms)  553,768           194.2

  Stroke (cerebrovascular       163,538           57.4
  disease)                                        

  Chronic lower respiratory     123,013           43.1
  diseases                                        

  **Unintentional injuries(i.e. **101,537**       **35.6**
  accidents)**                                    

  \- Motor-vehicle              43,788            15.4

  \- Falls                      15,019            5.3

  \- Poisoning                  14,078            4.9

  \- Choking c                  4,185             1.5

  \- Drowning                   3,281             1.2

  \- All other injuries         21,186            7.4

  Diabetes mellitus             71,372            25.0

  Influenza/pneumonia           62,034            21.8

  Alzheimer's disease           53,852            18.9

  Nephritis/nephrosis           39,480            13.8

  Septicemia                    32,238            11.3
  ----------------------------- ----------------- -----------------------

Unintentional injury is the preferred term for accidental injury in the
public health community.

A disabling injury is defined as one that results in death, some degree
of permanent impairment, or renders the injured person unable to
effectively perform their regular duties or activities for a full day
beyond the day of the injury.

## Costs of Unintentional Injuries

There are two methods commonly used to measure costs. One is the
economic cost framework and the other is the comprehensive cost
framework.

Economic costs are a measure of the productivity lost and expenses
incurred because of injuries. There are five economic cost components:
(a) wage and productivity losses, which include wages, fringe benefits,
household production, and travel delay; (b) medical expenses, including
emergency service costs; (c) administrative expenses, which include the
administrative cost of private and public insurance plus police and
legal costs; (d) motor-vehicle damage, including the value of damage to
property; and (e) uninsured employer costs for crashes involving
workers.

The total cost of unintentional injuries in 2003 in the USA was \$607.7
billion.

The information below shows the average economic costs in 2003 per death
and per injury.

Table 3 -ECONOMIC COSTS per Death or Non-fatal injury, 2003

  --------------------------------------------------- -------------------
  Death                                               \$1,120,000

  Nonfatal Disabling Injury                           \$45,500

  \- Incapacitating injury \[8\] .                    \$55,500

  \- Non-incapacitating evident injury                \$18,200

  \- Possible injury .                                \$10,300
  --------------------------------------------------- -------------------

Economic costs, however, should not be used for cost-benefit analysis
because they do not reflect what society is willing to pay to prevent a
fatality or injury.

Comprehensive costs include not only the economic cost components, but
also a measure of the value of lost quality of life associated with the
deaths and injuries, that is, what society is willing to pay to prevent
them. The values of lost quality of life were obtained through empirical
studies of what people actually pay to reduce their safety and health
risks, such as through the purchase of air bags or smoke detectors.
Comprehensive costs should be used for cost-benefit analysis. Besides
the estimated \$607.7 billion in economic losses from unintentional
injuries in 2003, lost quality of life from those injuries is valued at
an additional \$1,366.6 billion, making the comprehensive cost \$1,974.3
billion in 2003.

## Assumed Costs for injuries and non-injury related illnesses

The information in Table 4 are the assumed Economic costs we use in our
study developed from information in the previous tables. The injury
related cost come from Table 3 with the cost per regular injury the
average of non-incapacitating evident injury and possible injury. The
right side of Table 4 represents the assumed costs for all those causes
of illness (e.g., heart attacks) that are not injury related (see Table
2). Since there was no data on these costs, we assumed they were 25% of
the injury related costs.

Table 4 - Economic Cost per injury

  --------------------- ------------- ---------------------- -------------
  **Injury**                          **Non-injury related   
                                      illness**              

  Cost per no injury:   0             Cost per non-injury    0
                                      illness                

  Cost per regular      \$14,250      Cost per regular       \$3,562
  injury:                             non-injury             

  Cost per major        \$55,500      Cost per major         \$13,875
  injury:                             non-injury:            

  Cost per fatal        \$1,120,000   Cost per fatal         \$280,000
  injury: (Death)                     non-injury (Death)     
  --------------------- ------------- ---------------------- -------------

# Vensim Model of Emergency Services - 911 calls

Figure 9 represents the emergency services Vensim model starting on the
left with the telecom efficiency function developed previously in Figure
7 and Figure 8. It starts on the left with the level of 911 calls (i.e.,
0.4 calls per second or 120 calls every 5 minutes). This is
approximately consistent with the 34,000 calls per day to 911 assumed to
be evenly distributed over the 24 hours in a day.

We then divide the calls up into those that get through and those that
don't as a function of the telecom efficiency. We next separate out the
non-emergencies (66.67%), and then divide the calls into 7 buckets as
follows:

-   no injuries

-   regular injury and regular non-injury illnesses

-   major injury and major non-injury illnesses

-   fatal injury and fatal non-injury illnesses (death)

The split between injuries and non-injury illnesses (heart attacks,
asthma attacks, etc.) is represented by the factor "injury related %".
This factor is estimated at 35.5% \[7\] because

-   In 2002 in the USA, there were 38.9 emergency room visits per 100
    persons

-   Of those 13.8 or 35.5% of those visits were injury related.

![](media/image9.wmf){width="3.36875in" height="2.2583333333333333in"}

Figure 9 - Emergency Services model

## Response time for 911 (measured in minutes)

The response time to 911 calls in the USA is amazingly fast for those
emergency calls that require dispatch. Note that the non-emergency calls
don't require dispatch. The response time is tracked for every call, and
a measure of effectiveness is the average response time. A typical
example is given by Pinellas County, Florida where it is approximately 5
minutes which is the time from receipt of call to dispatch plus the time
to arrive at the scene of the emergency \[9\]. This is the baseline
scenario where all 911 calls are completed through the telecom network.
Now all these calls result in either no injury or non-injury illness,
regular injury or regular non-injury illness, major injury or major
non-injury illness or fatal injury or fatal non-injury illness. The no
injury or non-injury illness category is assumed to include all the
non-emergency calls (66.6% of all calls). Regular injuries or regular
non-injury illness occurs in 70% of the calls, major injuries or major
non-injury illness occurs in 29.8% of the calls, and fatal injuries or
fatal non-injury illnesses occur in 0.2% of the calls. The major
injuries and major non-injury illness (29.8%) and the fatal injury and
fatal non-injury illness (0.2%) are approximately consistent with the
injury and death facts presently previously.

The blackout scenario forces us to ask the question: What if the
potential 911 caller can't get through because their phone is dead?
Hence, there can be no emergency service response. We postulate what
would happen in Figure 10. We would have changes in the level of injury.

-   No injuries category would remain the same

-   Most regular injuries remain regular injuries, but some regular
    injuries would become major injuries

-   Most major injuries remain major injuries but some major injuries
    become worse and even fatal (death)

![](media/image10.wmf){width="2.8916666666666666in"
height="0.7083333333333334in"}

Figure 10 - Changes in injury levels if 911 wasn't available

## Key Assumptions for our study: 

The level of changes to these categories is subject to speculation. In
what follows, we have assumed that the fraction of overall regular
injuries would go down (to say 44% from 70% in the baseline), since many
of those injuries would become major injuries. Major injuries would
increase (to 55.6% from 29.8% in the baseline) of the total, and fatal
injuries would increase as well (to 0.4% from 0.2% in the baseline)
since some of those major injuries would result in fatality. These
transition levels require further investigation and drive the results
presented next.

We further assume that the same process would work for non-injury
related illnesses. They would become more serious or fatal if there was
no 911 response.

# Summary Results -- Injuries and Cost

Combining all of the previous models, the results below show a
comparison between the baseline model where telecom and 911 calling is
working fine, and the blackout scenario where a significant fraction of
the population can't call 911. Figure 11 and Figure 12 show the changes
in injury levels and non-injury levels.

![](media/image11.wmf){width="2.9131944444444446in" height="1.45625in"}

Figure 11 - Number of
injuries![](media/image12.wmf){width="3.015277777777778in"
height="1.4229166666666666in"}

Figure 12 -Number of non-injuries

Figure 13 shows the overall cost results by multiplying the injuries and
non-injuries by the cost per injury and cost per non-injury. While the
regular injury and non-injury cost goes down somewhat because there are
less regular injuries and non-injuries, the major injury and non-injury
costs goes up since there is many more of them. In addition, the fatal
injury and non-injury (death) category also shows an increase.
![](media/image13.wmf){width="3.3895833333333334in"
height="1.1944444444444444in"}

Figure 13 - Cost by level of injury and non-injury

The summary costs for each of the scenarios are shown in

Table 5 - Summary Costs

  ---------------------------------------- ------------------------------
  **Baseline Total =**                     **\$342 M**

  **Blackout Total =**                     **[\$378 M]{.underline}**

  Incremental Cost =                       \$ 36 M
  ---------------------------------------- ------------------------------

The bottom line is that there is a substantial increase in injuries and
non-injuries and death with those resulting economic costs. For a
blackout lasting approximately 30 hours, for metropolitan area of 5
million people, the incremental economic cost is estimated at \$36M.
Note that the comprehensive costs to society will be greater, probably
by a factor of 3

# Sensitivity Study - Blackout + Telecom Disruption

So far, we have investigated two scenarios:

1.  Baseline scenario: no blackout

2.  Blackout scenario.

In both of these we assumed there was no simultaneous infrastructure
disruption to the telecom network, except for that caused by lack of
power. In this sensitivity study, we add a telecom disruption to the
whole network lasting from 8 AM to 10 PM of day 1 of our two day period,
knocking out 75% of the network capacity.

The additional scenario with both blackout and telecom disruption
reduces the overall telecom efficiency to very low levels during the
periods of blackout and telecom disruption. Hence very few 911 calls get
through during this period. This results in more major injuries and
major non-injury and more fatal injury and non-injuries. Table 6 shows
the summary costs. The costs are increased to \$63M over baseline,
almost double that of the blackout only scenario.

Table 6 - Summary Costs

  --------------------------------------------------- -------------------
  **Baseline Total =**                                **\$342 M**

  **Blackout and Telecom Disruption Total =**         **[\$405
                                                      M]{.underline}**

  Incremental Cost =                                  \$ 63 M
  --------------------------------------------------- -------------------

# Possible Future Work

There are a number of important areas to continue this research:

-   Investigate additional reference sources for both economic costs and
    comprehensive costs of injuries and non-injuries.

-   Investigate the rate of change in injuries as a function of 911
    response time due to all sources of emergency: police/fire/emergency
    medical services.

-   Investigate new power blackout scenarios, and additional
    simultaneous disruption scenarios, coupling power blackouts with
    major telecom disruptions.

-   Investigate the total cost as a function of the length of the power
    blackout.

-   Investigate the general business costs of a power blackout resulting
    in loss of telecommunications services. In some industries, for
    example, airline reservations, this has been estimated at \$1M per
    hour. The general business costs should be much larger in our
    example than for the emergency services infrastructure. For example,
    the August 14, 2003 blackout affected 50 million people. It lasted
    up to 4 days in various parts of USA and Canada. Its estimated costs
    were between \$4B and \$10B \[10\]. Using our 38 hour blackout,
    effecting 5 million people, this would translate to an impact of
    between \$160M and \$400M.

-   Investigate possible access to 911 during a blackout. It depends on
    several factors. Wireline phones (with power lifeline) will still
    work. A wireless only person (whose phone is out) may have access to
    someone else's wireline phone if available. What's the probability
    of availability of a wireline phone in an emergency? There will be
    some delay in getting access to that working wireline phone (i.e.
    run to a neighbors house, or use a business line nearby).

-   What mitigation is possible to guarantee access to 911? Battery
    backup for 24 hours at cell sites at high load, or diesel generators
    installed at all cell sites. (But cell phones will still lose their
    charge after some time and usage.) Very inexpensive wireline
    lifeline service (i.e., stays up during a blackout), so people would
    opt to keep it. What is the cost of mitigation?

# References {#references .unnumbered}

1.  Walt Beyeler, Stephen Conrad, Thomas Corbet, Gerard P. O'Reilly,
    David D. Picklesimer, "Inter- Infrastructure Modeling - Ports and
    Telecommunications," Bell Labs Technical Journal, Volume 9, Number
    2, 2004, 91-105.

2.  David J. Houck, Eunyoung Kim, Gerard P. O'Reilly, David D.
    Picklesimer, Huseyin Uzunalioglu, "A Network Survivability Model For
    Critical National Infrastructure," Bell Labs Technical Journal,
    Volume 8, Number 4, 2003.

3.  Vensim, [www.vensim.com](http://www.vensim.com/).

4.  New York Times, "Dangling Broadband from the Phone Stick", Business
    section, March 19, 2005.

5.  Goldman Sachs, Global Investment Research Report, Telecom Services,
    Wireline and Broadband, April 16, 2004.

6.  http://www.911dispatch.com/index.html

7.  National Safety Council, Injury facts 2004 edition.

8.  Manual on Classification of Motor Vehicle Traffic Accidents, ANSI
    D16.1-1996 (6th ed.). National Safety Council.

9.  www.ci.tarpon-springs.fl.us/911.htm.

10. U.S.- Canada Power System Outage Task Force, "Final Report on the
    August 14, 2003 Blackout in the United States and Canada: Causes and
    Recommendations, April, 2004.