TCOM 540 Session 3

Agenda Quiz Review Session 1 homework Address real-world data issues

The Real World – Getting Data A network design is only as good as the data that supports it –Traffic data –Cost data

The Real World – Getting Data (2) Different types of information are needed and available for –Voice networks –Data networks

Voice Traffic Data Realistically, most large users acquire voice by a Virtual Private Network (VPN) approach –This may change - e.g., VoIP That is, user buys a service, not a network Traffic rides on common user infrastructure of IXC –Takes advantage of economies of scale

Voice VPN IXC “cloud” IXC POP CO User Site A IXC = InterExchange Carrier POP = Point of Presence CO = Central Office (Local Exchange Carrier) User Site B User Site D User Site C User Site E Access lines Offnet

Voice Traffic Data Needs What data is needed to acquire a VPN? –Your sites (i.e., on-net locations) –Traffic matrix (i.e., point-to-point traffic file) for on-net traffic – Site-to-offnet traffic –Optionally, time-of-day profiles –Features required and usage

Voice Traffic Data Sources Current carrier should provide Call Detail Records (CDR) –Originating #, terminating #, time of day, duration, features used, charges CDR may require considerable manipulation to provide useful data –Format changes –Site identification –Large number of records (millions per month for a large organization)

Call Detail Records – Additional Information oduct/voice/vpdd/cdd/3_1/cdr.htmhttp:// oduct/voice/vpdd/cdd/3_1/cdr.htm ut.htmlhttp:// ut.html

Voice Traffic Data Sources (2) If CDR not available, may have to estimate traffic based on site size (people) and assumed calling patterns

Voice VPN Costs Basic price structure is usually fairly simple –Postalized CONUS on-on, on-off, and off-off rates –Off-net access (i.e., switched access) usually included –On-net access (usually dedicated not switched) is not included May be available from carrier as pass-through from LEC tariff

Voice VPN Costs (2) Reliable comparative price information not easily available –AT&T no longer dominant carrier –Best prices are in private contracts between carrier and customer Carriers supposed to post tariff-equivalent information, but usually partial, obscure or missing –Private services such as Valucom, CCMI provide some tariff/contract information

Voice VPN Costs (3) Prices very dependent upon commitment –Volume ($ or minutes) –Duration of contract Variety of bargaining techniques are available to buyers –Subject of later session

Data Traffic Data Data is much more complicated than voice Different types of traffic – –File transfer –Database access –Web browsing –VoIP –Streaming video –Etc., etc.

Data Traffic Data (2) Different requirements –Speed –Latency –Delay –Loss –Reliability/availability

Data Traffic Data (3) Information often less complete and more difficult to acquire than for voice –Exact traffic for applications riding on the network may only be known to the “owner” of the application –Telecom supplier will probably only provide information needed for billing –Equipment such as routers and concentrators (e.g., Cisco MC3810) can be configured to collect traffic data, but usually aren’t …

An Example – FTS2000 FTS2000 was a VPN that replaced the General Services Administration’s FTS network about 1990 –FTS was an on-net to on-net private line network providing long-distance voice service for non-defense agencies –FTS2000 included off-net voice, dedicated circuits, circuit switched data, and packet switched data

FTS2000 (2) Only on-net to on-net voice data available –Very limited response to surveys of customer agencies Projected data, off-net voice and inbound WATS requirements (i.e., 800 service) requirements as proportional to voice traffic Constant of proportionality for 800 service was chosen as 2.5% –Wanted to have some representation, but not enough to unduly influence the selection

FTS2000 (3) Actual 800 service traffic was much higher –Approximately equal to on-net voice –Main sources were IRS and SSA Overall voice traffic was about three times the estimate –Because the prices declined with increasing volume, network was significantly more cost- effective than projected

Traffic Generators The preceding example showed the use of a traffic generation algorithm –Which turned out to be not very accurate as a predictor of actual traffic … –Cahn also gives a couple of examples of real cases where traffic generators had to be used May need to generate both traffic and costs

A Small Complete Design 5 nodes at specific locations (V&H) Types of links available for use (capacities) –Formula to convert bps on links to packets per second at nodes Traffic Link costs Switch capabilities Other miscellaneous data

Node Locations

Close Up N1 N2 N3 N4 N5

Lines and Traffic Line T1, speed = Traffic – each node sends to each other node –How many entries in traffic table?

Line T1, speed = Traffic – each node sends to each other node –20 entries in traffic table Lines and Traffic

Cost Tariff information provided N1N2N3N4N5 N N N N N51000

Comparison of Cost and Distance N1N2N3N4N5 N N N N N51000 Cost Distance

Cost as a Function of Distance We can easily discern that Cost = *distance Next week we’ll look at some other tariff models

Equipment Costing site equipment is one of the more complex parts of the process in real life –Many suppliers, models, capabilities –Switches, routers, multiplexers, etc., all have different characteristics The equipment table makes fairly gross simplifications to render the problem tractable

Equipment (2) Example uses –Three size categories (small, medium, large) –Four speed categories (slow,medium, fast and vfast) –Plus vlargevfast, no_equip and infeasg Equipment characteristics defined in terms of –Cost –Reliability –Max links (low speed, T1) –“ADAPT_CST” –“DEFAULT”

Scaling If we have a 100-node problem rather than a 5 node problem –Line types, equipment, and other parameters tables may not change at all –Sites table grows to 100 rows –Traffic table could grow to 10,000 rows –Cost table could grow to 4,950 rows

Scaling (2) Tables of this size or larger require automation to develop accurately

Homework Session 3 Read Cahn, Chapter 5 Do exercises 4.3, 4.4 Download DELITE and try using it