Telecommunication Technology and Management

Chapter 10 and Chapter 11

Thank you for all information and pictures referred in this lecture.www.att.com and www22.verizon.com

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Agenda

Old Technology

Modern Technologies Digital TV Cell Phone: Calling Features Hi-speed Internet

Network Management Expert System Knowledge Discovery and Data Mining

Other Intelligent Applications

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Old Technologies

http://www.prattonline.com/ResponsePoint.htmhttp://www.supermegatrolled.com/just-nokia-3310-destroys-the-dinosaurs/

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Trend of Communication

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Trend of Communication

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Modern Technologies

Digital TV TV Wireless Receiver

Requirements: Wireless service from the Wireless Access Point to the

Wireless Receiver Power outlet and connection of Wireless Receiver to TV

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Modern Technologies

Home DVR Ability to schedule recordings and pause live TV

Record up to four shows at once on a single DVR and play them back in any room

Pause, fast-forward and rewind live or recorded shows on any TV or pause your recorded show in one room and pick it up in another

Play the same recorded shows on different TVs at one time and control them separately

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Modern Technologies

Interactive Applications (between TV and smart phone) Browse available TV content for current or future viewing,

search for content, and remotely manage recordings of shows and movies on DVR.

With qualifying TV plans, download select popular TV episodes/series from the Mobile Library to select smartphones for viewing on the go.

Once a show is downloaded, you can watch it anytime!

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Modern Technologies

TV Multiview

It allows you to choose your own Multiview channels you want to watch.

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Modern Technologies

Phone Services on TV

We can see who's calling without leaving the comfort of their couch! Caller ID notifications and Message Waiting Indicators

(MWI) will display on their TV

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Modern Technologies

Calling Features Call Screening – Only accept calls from a list of p

hone numbers you select.

Call Transfer – Send a call that’s already in progress to a different phone number.

Locate Me - Provides simultaneous ringing on up to four wireless/landline numbers when someone calls your home phone.

Call History – View a list of your recent calls, by date and time, either online or on your TV screen.

Click to Call – Return a phone call using your U-verse TV screen and remote.

Caller ID on TV – See Caller ID and Voice Mail notifications on your TV screen.

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Modern Technologies

Online Photos and Music Customers can now view the photos they've uploaded at

www.flickr.com on channel 91.

Share music and photos from networked Windows PCs to TV

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Modern Technologies

TV for Xbox 360 Access your DVR recordings from your

existing Xbox 360.

Switch seamlessly from playing games to watching TV—without switching video inputs on your TV.

Access the U-verse TV Menu, Guide, and a robust library of On Demand programming.

Chat: Know instantly when your friends are onXbox LIVE®.

Use Xbox IM and Chat while watching TV.

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Modern Technologies: Customer Support

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Modern Technologies

Mobile Phone

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Modern TechnologiesDigital Voice: Calling Features

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Modern TechnologiesDigital Voice: Calling Features

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Modern TechnologiesHi-Speed Internet

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Network Solution for Business

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Fiber Optic Technology!!

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Network Management

Telecommunication networks are extremely complex systems requiring High reliability High availability

The effective management of networks is a critical, but complex, task. Telecommunications industry has heavil

y invested in intelligent technologies.

Telecommunication industry has relied on intelligent solutions to help manage telecommunication networks.

http://www.qbase.gr/en/node/124

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Network Management

Building intelligent applications involved acquiring valuable telecommunication knowledge Human experts Applying this knowledge: an expert system.

This knowledge acquisition process is so time-consuming that it is referred to as the “knowledge acquisition bottleneck”.

Data mining techniques are now being applied to industrial applications to break this bottleneck, Replacing the manual knowledge acquisition process with aut

omated knowledge discovery.

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Data Mining

http://www.laits.utexas.edu/~anorman/BUS.FOR/course.mat/Alex/

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Expert Systems

Expert systems are programs which represent and apply factual knowledge of specific areas of expertise to solve problems

Require a knowledge engineer to acquire knowledge from the domain experts

Encode knowledge in a rule-based expert system

These rules were very “ad-hoc” and as the number of rules increased

Expert system became more difficult to understand and modify

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Expert Systems

The design of telecommunication expert systems needs to recognize all telecommunication equipm

ent incorporates self-diagnostic capabilities

http://www.nextnine.com

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Knowledge Discovery and DataMining Knowledge discovery is a field which has emerged from

various disciplines, Artificial intelligence, Machine learning, Statistics, Databases.

Its process involves identifying valid, novel, potentially useful and ultimately understandable patterns in data

Data mining, the most researched topic in this process, Finding interesting patterns in the data via data analysis and

discovery algorithms.

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Knowledge Discovery and DataMining The knowledge discovery process

Data preparation: selecting, cleaning and preprocessing the data (e.g., filling in missing values) and transforming it so that it is suitable for data mining

Data mining: finding patterns in the data

Interpretation and evaluation: interpreting and evaluating the patterns produced by data mining

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Knowledge Discovery and DataMining A key motivation for knowledge discovery

Replace or minimize the need for the time-consuming process of manually acquiring knowledge from a domain expert.

Knowledge discovery is especially attractive to the telecommunications industry since: Telecommunication networks are typically too complex to build

complete simulation models

Huge quantities of data are routinely available

Domain experts often are not aware of subtle patterns in data and hence automated knowledge discovery can acquire new, previously unknown, knowledge

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Network Management Applications Max & Opti-Max: Locating Problems in the Local

Loop The Max (Maintenance administrator expert) system

diagnoses customer reported telephone problems in the local loop, the final segment of the telephone network that connects the customer to a central office

Max is a rule-based expert system Diagnoses problems based on results of an electrical test on the

customer’s phone line, Specific knowledge of the customer’s phone line and general

equipment knowledge.

Max determines where the trouble lies and selects the type of technician to solve the problem.

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Network Management Applications Max & Opti-Max: Locating Problems in the Local Loop

Problem of Max its performance is affected by the local characteristics of each site

and thus numerous rule parameters must be tuned to optimize its performance.

This tuning process is time consuming and for this reason a system called Opti-Max was created to automatically tune these parameters to appropriate values.

Opti-Max takes as input a set of training examples, Problem description and a diagnosis assigned by an expert,

Uses a hill-climbing search to find a set of parameter values which perform well on these examples. Opti-Max performs a type of automated knowledge discovery.

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Network Management Applications Trouble Locator: Locating Cable Network Troubles

It determines the location of troubles in a local telephone cable network Data generated by a nightly automated test to help narrow down potential ca

bles or network equipment which may be faulty; Test results are not sufficient to determine the exact cause.

The Trouble Locator uses a Bayesian network and Bayesian inference to solve this problem. The system begins by generating a local plant topology graph and then from

this generates a Bayesian network, where each node in the network contains state information (belief of failure) of a plant component.

This system is used by preventative maintenance analysts as a decision support system.

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Network Management Applications TASA: Finding Frequently Occurring Alarm Episode

s The Telecommunication Network Alarm Sequence Analyze

r (TASA) System for extracting knowledge about the behavior of the net

work from a database of telecommunication network alarms.

The goal of this system To locate regularities in the alarm sequences in order to filter r

edundant alarms Locate problems in the network Predict future faults

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Network Management Applications TASA operates in two phases

First phase: specialized algorithms are used to find rules that describe frequently occurring alarm episodes from the sequential alarm data

An example rule describing an alarm episode is: if alarms of types A and B occur within 5 seconds,

then an alarm of type C occurs within 60 seconds with probability 0.7.

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Network Management Applications Second phase: collections of episodes are

interactively manipulated by the user Interesting episodes from the original set can be

found

TASA supports this process by providing operations to prune uninteresting episodes Order the set of episodes Group similar episodes

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Network Management Applications Scout: Identifying Network Faults via Data Mining

It operates by mining historical telecommunication data Machine learning Correlation techniques.

Scout identifies patterns of chronic problems directly from the data by examining the network behavior over periods of days and weeks.

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Other Intelligent Applications APRI: Predicting Uncollectible Debt

The Advanced Pattern Recognition and Identification (APRI) system To predict the probability of uncollectible debt based on

historical data, including data of past uncollectibles

The output of APRI is fed into a decision support system which can take a variety of actions Blocking a call from being completed.

APRI automatically constructs Bayesian network models for classification problems using extremely large databases.

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ANSWER: A Hybrid Approach to Ne twork Management

Automatic Network Surveillance with Expert Rules (ANSWER) ANSWER utilizes both rule-based and object-orie

nted technologies

Employing a rule-based extension to the C++ object-oriented programming language.

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Forecasting Telecommunication Equipment Failures from Time Series Data Errors may occur during the transmission of data over the networ

k, These errors can be detected and the data rerouted through alter

nate paths.

The effect of the failure of a single component is limited due to the redundancy in modern large-scale telecommunications networks.

Modern telecommunication equipment contains self-diagnostic testing capabilities. When any of these tests fail, an alarm message is sent to a centr

alized site, where it may be handled by a human or by an expert system

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Challenging Works

Existing Researches: http://www.research.att.com/evergreen/

what_we_do/research.html?fbid=A_Kn38ajPF9#Computing and Communications Foundations

Existing Software's: http://www.research.att.com/export/sites/att_labs/

software_tools/index.html?fbid=A_Kn38ajPF9

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Telecommunication Union

ITU (International Telecommunication Union) is the United Nations specialized agency for information and communication technologies – ICTs. สหภาพโทรคมนาคมระหว่�างประเทศ http://www.itu.int/en/Pages/default.aspx

National Broadcasting and Telecommunications Commission (NBTC) คณะกรรมการก�จการกระจายเส�ยง ก�จการโทรท�ศน�และก�จการโทรคมนาคม

แห�งชาติ� http://www.nbtc.go.th/wps/portal/NTC/eng

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References

http://www.att.com/ Gary Weiss, John Eddy, Sholom Weiss, “INTELLIGENT

TELECOMMUNICATION TECHNOLOGIES”, AT&T Labs, AT&T Corporation, United States

http://www22.verizon.com/home/aboutfios/

http://www.research.att.com/evergreen/what_we_do/research.html?fbid=A_Kn38ajPF9#Computing and Communications Foundations

http://www.research.att.com/export/sites/att_labs/software_tools/index.html?fbid=A_Kn38ajPF9