1. TCOM 513 Optical Communications Networks Spring, 2006 Thomas B. Fowler, Sc.D. Senior Principal Engineer Mitretek Systems

2. 2ControlNumber Topics for TCOM 513 Week 1: Wave Division Multiplexing Week 2: Opto-electronic networks Week 3: Fiber optic system design Week 4: MPLS and Quality of Service Week 5: Heavy tails, Optical control planes Week 6: The business of optical networking: economics and finance Week 7: Future directions in optical networking

3. 3ControlNumber Where we are So far, we’ve examined –How optical networks operate –How to put them together Important questions remains –What kind of network should I build? Size/capacity –Where should I concentrate? Core Metro area Local access

4. 4ControlNumber Topics for tonight Parameters affecting optical networking Pricing of network-type commodities The networking industry after the Big Crash Convergence Opportunities

5. 5ControlNumber Uses of optical technology Campus-short haul –May need to trench fiber, build network yourself Connecting buildings across town –Trenching fiber not generally practical –May want to lease dark fiber or wavelength Going long distances –Unless you want to become IXC, forget about laying your own fiber –Use fiber/service already in ground Dark fiber –Amplifiers, repeaters, etc. provisioned by service provider –You have to do rest of engineering Wavelength service –You have to modulate/demodulate SONET –You just connect your equipment to a standard interface box

6. 6ControlNumber Parameters affecting optical networking Major players –User/consumer –Internet service provider (ISP) –Telco/CLEC –Interexchange carrier (IXC) –Long haul pipe provider –Supplier –Builder/installer

7. 7ControlNumber Players (continued) Other interested parties –Regulators –Legislators/policy makers –Consumer groups –Environmentalists

8. 8ControlNumber Issues Supply side –How to finance construction –How to estimate return on investment (ROI) –How to make a business case for investment –How to ward off obsolescence Demand side –How to price to stimulate demand –How to handle network externalities Network externality: price people are willing to pay depends on how many other people are using network –How to allocate costs to equipment How to price shared services –What should be free?

9. 9ControlNumber Issues (continued) Regulatory side –What should be subsidized, and by whom? –What rules should be in place? Who should be protected? –How to ensure that time constants for regulatory process are shorter than those for technology being regulated

10. 10ControlNumber Supply and demand: Economics 101 Price Utilization Price Revenue Highest price for full Network utilization Demand per vendor (diluted by competition) Low Medium High 100%

11. 11ControlNumber Bandwidth growth (demand) models Actual Assumed

12. 12ControlNumber Limitations to bandwidth growth Demand slows due to legal issues –Generally centered around IPR Digital distribution means perfect copies –Internet radio “tax” Users can only absorb change at a certain rate –Change usually means upgrades Forklift upgrades a hard sell to individuals and businesses –Many are comfortable with current paradigm Regulatory questions are often vexing –Universal service –Cross-subsidization Business case for massive rewiring of U.S. difficult to make –Uncertainty in demand –Payback period may be extended

13. 13ControlNumber Brief history 1980s: R&D phase of optical networks Early 1990s: Major deployments Late 1990s: Dot-com, venture capital boom –Massive build-out –Business case? Who cares? Money spigot is on full! –Set up a company, develop some product, sell out to Cisco, Lucent, or Nortel, or have an IPO, then retire rich! 2000-2002: The big crash –Build out causes oversupply –Optimistic demand forecasts do not materialize –Prices drop –Huge debt load cannot be serviced –Next stop: Chapter 11 2003-2005: Slow recovery, legal and regulatory battles

14. 14ControlNumber Pricing of network services Overview of network services –Guaranteed, elastic, traffic contracts, network control Guaranteed and effective bandwidths –Definition of effective bandwidths –Relevance for pricing Economic models for networks –Basic –Finite resource sharing models/congestion pricing –Implementation mechanisms Pricing for elastic services Pricing for guaranteed services

15. 15ControlNumber Some thoughts on network pricing There is no single view on charging for network services –Disparate models, contradictory proposals There is no need to price (or charge for) network services [!] –No congestion in the future [!] –“To cheap to meter” –Charge only for content There is nothing new in network pricing –Economists have said everything before Never mind that they haven’t agreed Need abstraction, model to work with Model Economic Theory Network Abstraction Source: Costas Courcoubetis/U Crete

16. 16ControlNumber Why charge for network services? Charging is not only for making profits –Improving network performance –Providing stability and robustness –Creating revenue (to pay debt service) Charging should provide –Important information for network control –Information for buildout of network Pricing should have certain characteristics –Simple but not simplistic –Understandable –Implementable –Competitive

17. 17ControlNumber Network services as sold to users Packet or cell transport Contract usually has two aspects –Connection or flow performance to be provided by network –Traffic profile to which user must conform Network Service Interface

18. 18ControlNumber Network service types Guaranteed –Network provides some form of performance guarantees Loss Delay Jitter –User may request some amount of network resources –May be subject to admission control –Typical of ATM, FR networks with Committed Information Rate (CIR) –Commonly needed for isochronous traffic (e.g., video)

19. 19ControlNumber Network service types (continued) Elastic or “best effort” –No specific performance guarantees –Performance deteriorates during overload periods –No specific bandwidth request-users can use all available bandwidth –Intended for applications that can adapt sending rate

20. 20ControlNumber Guaranteed services Performance guarantees –Quality of service (QoS): loss, delay, jitter, BER –May be statistical (e.g., loss < 10 -7 ) or deterministic (delay < 25 ms) Required mechanisms –Connection admission control (CAC) –Policing User-network traffic contract –Provides connection’s QoS and traffic description –Network promises to support specified QoS provided that user’s traffic satisfies his specified profile

21. 21ControlNumber Elastic or “best effort” services No specific performance guarantees –Provide some form of fair treatment to different connections Feedback mechanisms used to inform source of congestion or other problems –Explicit (e.g., data rate) –Implicit (e.g., packet loss) Mechanisms programmed into routers, switches to share bandwidth, enforce fairness Source behavior –Increase (additive) when no congestion –Decrease (multiplicative) when congestion present Example: TCP flow control

22. 22ControlNumber ATM Forum Service Categories Service CategoryService TypeQoSTypical Application Constant Bit Rate (CBR) GuaranteedDelay, delay variation, cell loss Circuit emulation, videoconferencing Real-time Variable Bit Rate (rt-VBR) (bursty traffic) GuaranteedDelay, delay variation, cell loss Compressed video/audio Non-real-time Variable Bit Rate (nrt-VBR) (bursty) GuaranteedCell loss bounds only Critical data Available Bit Rate (ABR) Best effortFlow control only LAN interconnection Unspecified Bit Rate (UBR) Best effortNoneFile, message transfer

23. 23ControlNumber Enhancement of IP Infrastructure to Support Diverse Set of Applications Service providers and network managers operating multiple networks to support range of applications –This is not desirable from economic and maintenance standpoint IP infrastructure devices becoming cheaper due to proliferation of the public Internet and private networks –Routers/switches and transmission Current IP infrastructure needs enhancement to support voice, video, and data at acceptable levels –Flow of real-time bit streams This is the challenge for the decade

24. 24ControlNumber VoIP Versus Conventional Telephony Tandem Switch Conventional Telephony: Dedicated End-to-End Connection Central Office IP PBX LAN IP Wide Area Network (WAN_ (e.g., Internet ISP VoIP: No End-to-End Dedicated Connection; Packets Take Best Available Path Through Network

25. 25ControlNumber Benefits Claimed for VoIP Networks Cost savings Simplified, more rapid provisioning Easier management Less maintenance More rapid deployment of new services Unified messaging

26. 26ControlNumber Risks Associated with VoIP Regulatory uncertainty Immature protocols and standards Data, telecommunications clash of cultures Unproven reliability and availability Security issues with IP networks Potential need for major network upgrades Enhanced 911 problems Network ubiquity problems Immature billing

27. 27ControlNumber Generic VoIP Architecture (Local and Long Distance) VoIP Gateway Digital phones (non-IP) Conventional PBX with VoIP trunk card Legacy PBX site IP Telephony Router Small Office Site with VoIP IP PBX Medium-Large Site with IP PBX Large Enterprise Site with multiple IP PBXs IP VPN with Call Routing and Media Gateway Functions Tail-end hop off to Telco for offnet calls Translation IP PBX

28. 28ControlNumber Real-Time / Multimedia Requirements Support for a range of diverse applications –Support for a range of bandwidth E.g., 128 Kbps collaborative video conferencing to 45+ Mbps video-on- demand –Support for a range of performance for voice, video, multimedia, critical data Delay, delay variation, packet loss Support a range of communication models –Point-to-point, multipoint, multicast, broadcast Use of QoS for cybersecurity looks promising

29. 29ControlNumber Solution Alternatives Massive overbuild –Brute force approach Feasible in good old POTS days –Due to fractal nature of Internet traffic, difficult to know how much capacity is enough Fractal = self-similar on multiple time scales Quality of Service (QoS) / Class of Service (CoS) –Preferentially routes packets based on type of traffic they carry –Does require software and / or hardware upgrades Complex nature of Internet and other networks makes prediction of performance difficult

30. 30ControlNumber Time scales of network control

31. 31ControlNumber Network control and pricing Set of feasible service offerings depends on network control mechanisms and provisioning capabilities Economic incentives influence both of these Network control –Controls cell or packet flows to guarantee contracts Pricing –Controls demand in order to improve efficiency demand

32. 32ControlNumber Network control and pricing (continued) Prices differentiate quality of service, not content Prices depend on demand –Driven toward cost by competition –But set on margin Prices proportional to –Effective bandwidth for guaranteed services –Throughput for best effort services

33. 33ControlNumber Economic models for networks Context –Communications services are economic commodities –Exist within law of supply and demand Supply –Amount produced or available –Determined by technology of network elements, including management and control, cost Demand –Amount users want –Trade-off between QoS and willingness to pay –Affected by competition, business climate Market interaction between service providers and users comes through price

34. 34ControlNumber Economic models (continued) Terminology –Price: associated with unit of service –Tariff: price structure as function of demand Common general form: a + bx, where x is demand Instrument for pursuing policy objectives –Charge: amount to be paid For more details, see http://www.aueb.gr/users/courcou/presentations/itc99/sld001.htm

35. 35ControlNumber Economics in telecommunications Large amount of work done on design of public utility tariffs for telephony –1970s: peak load pricing, cross-subsidization (local by long distance) –1980s, 90s: cost-based (subsidy-free) pricing, nonlinear pricing, peak load pricing under uncertainty, others Does not directly translate into good models for data –Sharing of equipment/facilities –Burstiness of traffic Complicated by diversity of new user-network contracts, multiplexing capabilities, resource sharing models

36. 36ControlNumber Sharing finite resources Network resource management occurs in various time scales –Short time scales Amount of resources is fixed Control deals with optimal sharing –Long time scales Resources expanded in order to improve average performance Marginal cost pricing combines above time scales, so operates in time frame of output expansion Short time scale problem –Prices used to control way resources shared –Can be used as input for deciding capacity expansion

37. 37ControlNumber Congestion pricing Types of congestion –Demand exceeds capacity (I) –Overall performance depends on usage patterns (II) Technology suggests that (II) is of limited interest –Under heavy multiplexing, solution of (II) -> solution of (I) –(I) is relatively simple (add more capacity or raise prices) –(II) requires performance model of network usage

38. 38ControlNumber Congestion pricing summary Congestion price p controls sharing of C –Determination of p based on network measurements Users i and j solve local optimization problems –Need only prices posted by network –Adjust x (network utilization)

39. 39ControlNumber Expanding capacity Benefit B of operating network link of capacity C under congestion price p r = cost (fixed or variable) To maximize B, solve dB/dC = 0 If p > r var then buy more capacity until p = r var

40. 40ControlNumber Pricing at different time scales Congestion occurs at different times of day –Implies hierarchy of decisions for users –Higher level: how much to transmit during day, night –Lower level: How fast, priority, when

41. 41ControlNumber Pricing at different time scales (continued) Lower level decision depends on more detailed information Time-of-day pricing typically takes into account average congestion during that period, q=network utilization

42. 42ControlNumber Implementation approaches

43. 43ControlNumber Charging for “best effort” services Elastic demand –Flexible contract with network –No guarantees on delay, throughput –Examples: TCP/IP, ATM ABR, UBR Sources of randomness –Number of users –Amount of data –Amount of available resources

44. 44ControlNumber Charging for “best effort” services (continued) Need for flow control to regulate traffic Notions of “fairness” tend not to be economically efficient Goal: provide optimal economic sharing of resources Two time scales –Fast: flow control maintains orderly flows –Slow: adjustment of prices regulates demand Common approach: congestion pricing –To reduce excess pricing –To account for delay costs Prices can be computed two ways –Dynamically based on demand –Approximated from historical (time-of-day) demand

45. 45ControlNumber Charging for “best effort” services (continued) Issues –Cost of computing prices –Cost of exchanging information with users –Stability of pricing mechanism –User preference

46. 46ControlNumber The telecom world today after the Big Crash Overview of the current situation Evolution vs. revolution The growth paradigm The culture clash The winning strategy Fear vs. Greed Future architecture

47. 47ControlNumber Current landscape Specialized (horizontal) Service providers Vertically Integrated providers Optical equipment manufacturers Optical fiber manufacturers Legacy equipment manufacturers Content providers Access Internet Long-haul Application

48. 48ControlNumber Major players Optical equipment manufacturers –Nortel –Lucent –Alcatel –Ciena –Cisco –Juniper –Sycamore –JDS Uniphase Optical fiber manufacturers –Corning –Pirelli –Alcatel

49. 49ControlNumber Major players (continued) Optical network providers –Major IXCs (AT&T, Worldcom, Sprint) –Level3 –Global Crossing Content providers –AOL –Internet Portals (e.g., Yahoo, Google)

50. 50ControlNumber How to think about the networking problem Source: J. McQuillan/NGN2000

51. 51ControlNumber How to think about the networking problem (continued) Evolution –Future looks like the present, only more of it –Same players, evolving technology, increasing demand Revolution –Next Generation (NG) providers will build NG networks using NG technology from NG vendors using NG funds from (??) –New applications, new ways of doing things, new paradigms will chase out the old Organic growth –Old and new will coexist in more complex, larger whole

52. 52ControlNumber Paradigm shift: crash of the 1990s model Source: J. McQuillan/NGN2000

53. 53ControlNumber Old paradigm Grow through acquisitions –Use increasing value of your stock to finance purchase of startups or competitors –Create positive feedback loop –Commonly used by major players Cisco Lucent Nortel

54. 54ControlNumber Old paradigm (continued) Source: J. McQuillan/NGN99

55. 55ControlNumber Old paradigm (continued) Source: J. McQuillan/NGN2000

56. 56ControlNumber How the world changes… Source: J. McQuillan/NGN2000

57. 57ControlNumber New paradigm Not yet emerged Likely to focus more on value than utility –Wild predictions won’t justify investment Jupiter: By 2005, 75% of retail sales will be online –Too many people burned in dot com flameout

58. 58ControlNumber The culture clash Source: J. McQuillan/NGN2000

59. 59ControlNumber Culture clash (continued) “Bell heads” –Name sometimes given to RBOC workers –Refers to anyone who thinks in terms of enterprise networking High reliability and availability Relatively slow pace of change Priority on customer service –Often thought of as voice oriented “Net heads” –Name given to IT folks who value network connections –Different set of values Innovation outweighs inconveniences of crashes Customer service a low priority –Often thought of as data oriented

60. 60ControlNumber Culture clash (continued) Bell heads: “We know how to build and operate massive mission critical networks, so we will control the Next Generation networks” Net heads: “We are the only ones who ‘get it’, so we will control them”

61. 61ControlNumber Who will be the winner? RBOCs CLECs, GXCs Source: J. McQuillan/NGN2000

62. 62ControlNumber What will be the winning strategy? Vertical integration –Traditional telephone/telecommunications model –Own all facilities and data centers –Offer customers one-stop shopping Horizontal specialization –Offer “best in class” services –Lease facilities/services from others –Do one thing well –Take advantage of standard interfaces

63. 63ControlNumber Clash between fear and greed Fear: profits are most important –People invest money expecting that income will exceed expenditures for any company –“Value” investing Greed: only growth matters –Grab market share and increase volume –Don’t worry about anything else –“Utility” investing: make a useful product, everything else will take care of itself

64. 64ControlNumber Fear vs. Greed Fear Era Greed Era P/E S&P 500 Index / 10 year moving average of profits Source: Robert Schiller/Yale J. McQuillan/NGN2000

65. 65ControlNumber Future architecture Innovation –Multi-service switches will allow support of all traffic Legacy Internet as a service –Services will otherwise remain separate Very efficient at what they do Convergence –Internet (or private IP network) will be bearer of all services Voice Data Video

66. 66ControlNumber Convergence Topics Definition of convergence Types of convergence History of convergence efforts Drivers (benefits) Impediments Rollout

67. 67ControlNumber What is convergence? “Convergence” is a buzz word often used –Brandished as wave of future –Meaning far from clear Questions of interest –To what extent is convergence real and wave of future –To what extent is convergence just hype Basic idea: use of some common infrastructure to support multiple services

68. 68ControlNumber Levels of convergence Content Business Telecom/IT (e.g., ASPs, network computing) Telecom/IT (e.g., ASPs, network computing) Application (e.g. music, video over Internet) Application (e.g. music, video over Internet) Switching (e.g., VoIP) Switching (e.g., VoIP) Transport (e.g., multiplexed channels) Transport (e.g., multiplexed channels) Increasing visibility to user—closer to edge reflects

69. 69ControlNumber Why convergence? Most significant is a vision of the future: a more elegant world where everything is simpler Most telecom services are a result technological limitations existing at the time of their introduction –Bandwidth of early telephone gear (~200-3000 Hz) –DSn bandwidth is multiple of 64K used for voice –NTSC color TV state-of-art in 1940s In theory, convergence promises a “clean slate” approach –Everything (or at least many things) reengineered to provide better, more flexible service to the user In practice, a mixed bag, with some successes, many disappointments, areas still under development

70. 70ControlNumber The present situation Current telecom infrastructure worldwide is circuit oriented –SONET, ATM –Works well –Cost effective –Will not change overnight Content-provider media in similar situation –Radio, TV –Vast installed base of equipment “Service providers are not going to discard what they own and know how to operate” — J. McQuillan –And what is making them money

71. 71ControlNumber The present situation (continued) But: the Internet continues to grow, and needs a new infrastructure –Which may be able to support or deliver content now delivered separately Most of today’s public network revenues and profits do not come from the Internet

72. 72ControlNumber Convergence at transport layer PresentFutureTime Frame Different physical cabling for different services (e.g., one copper wire for switched voice, different copper wire for T1) All types of traffic ride over single pipe (optical, SONET- based for long-haul, high-volume access; cable TV, copper) Already here. Developed using multiplexing and implemented from 1960s onward. Technology is mature, though new implementations may come in next 5- 10 years (e.g., IP over photons)

73. 73ControlNumber Convergence at switching layer PresentFutureTime Frame Separately defined services utilize different transport and switching technologies, legacy of implementation and technology history (voice, T1, FR, ATM, etc.) All types of traffic ride over IP packets; need for separately defined and provisioned services (voice, T1, FR, ATM, etc.) diminishes; service definition applied at edge of network 5-10 years. Some applications such as VoIP PBXs are already commercially available

74. 74ControlNumber Convergence at application (content) layer PresentFutureTime Frame Applications (content) delivered to user (voice, TV, videotape, Internet) have separate delivery vehicles, different user hardware, different business arrangements. Applications (content) will come over single pipe, e.g., Internet. Requires convergence at network layer. 10-20 years

75. 75ControlNumber Example of convergence at application layer Sources: Beville, 1988; Time, 20 October 1997

76. 76ControlNumber Convergence at IT/Telecom layer PresentFutureTime Frame Application Service Providers (ASPs) take over processing and content delivery; grid computing being done on a no- charge basis ASP model will continue to expand; more specialized service provider models may emerge. Grid computing unlikely to become commercially viable 5-10 years

77. 77ControlNumber History of convergence efforts 1960s — conversion of telephone system to digital technology; time-division multiplexing 1975 — SBS’ “The One” 1982 — Integrated voice/data PBX 1988 — ISDN 1991 — BISDN 1998 — Sprint’s ION 2003 — VoIP, IP PBX

78. 78ControlNumber History of efforts to implement convergence Transport 1960s — Conversion of telephone system to digital technology; time-division multiplexing 1980s — SONET 2000s — All optical networks (?) Status: Successful Switching 1975 — SBS’ “The One” 1982 — Integrated voice/data PBX 1988 — ISDN 1991 — BISDN 1998 — Sprint’s ION 2003 — VoIP, IP PBX (?) Status: Has not lived up to promises Application 1990s — Delivery of audio, graphics, text via Internet 2000s — Home entertainment/ video (?) Status: Evolving; full impact not yet clear IT/Telecom 1990s — Network (grid) computing, e.g. SETI@Home; ASPs 2000s — Commercial grid computing (?) Status: ASPs successful; other areas not yet clear

79. 79ControlNumber Drivers for convergence

80. 80ControlNumber Drivers behind convergence (benefits) Economies of scale in service delivery Simplified management Variety of end user interface equipment minimized Simplified provisioning (cabling, etc.) at user site Ability to define and deliver new service types much greater and faster

81. 81ControlNumber Impediments to convergence Business/organization changes required may be great Human factors: time required for people to adjust to new ways of doing things –Can be measured in generations Deployment time (time to depreciate and replace existing equipment and infrastructure) Regulatory and legal issues

82. 82ControlNumber Impediments to convergence

83. 83ControlNumber Forces acting on convergence Regulatory issues Inertia of infrastructure Need to make business case Human factors Protocol and compatibility issues Clash of cultures Interoperability with existing infrastructure Unproven reliability and availability Convergence Lower cost Simplified provisioning Easier management Fewer user interfaces More rapid provisioning Improved services New services Simplification of user’s life Less maintenance  Drivers Impediments 

84. 84ControlNumber Major changes likely to result from convergence Improved, faster access Specific defined services such as T1, Switched Voice, FR, likely to fade as service definition moves to edge of network New services quickly designed and rolled out Business models in many industries will have to be changed –Current content delivery paradigms –Infrastructure to support content delivery More outsourcing as network increasingly viewed as resource

85. 85ControlNumber Broadband penetration in home market

86. 86ControlNumber Expected rollout sequence for convergence

87. 87ControlNumber Non-technological factors expected to slow deployment of converged solutions Regulatory and legal issues: the existing telephone system is part of a web of subsidies and social programs which cannot be turned off overnight Human factors: people have to change their habits and way of thinking—something which can require generations Economics of replacing existing infrastructure: nothing will be replaced just for the sake of technological elegance; there has to be a business case Proof of long-term reliability and robustness: hard-headed CIOs and CEOs will demand to see the backup data, case studies, and histories Demonstrated cost effectiveness: When all the costs are added up, will it still be cheaper to go with a single infrastructure

88. 88ControlNumber Non-technological factors expected to slow deployment of converged solutions (continued) Development of new billing and support systems: Anyone in the business knows that this is an extremely formidable problem. Existing systems work well, but developing new ones that work as well will be very expensive and time- consuming Need to interoperate with existing (legacy) infrastructure: New technology has to be able to integrate and interoperate with existing infrastructure, both within and without a company’s boundaries.

89. 89ControlNumber Recommended steps Create a strategic vision for the future of the networks and services that will help organizations achieve their business objectives. Develop a business case to rationalize the investment and returns –Include “soft” benefits –Do not overlook hidden costs and risks Identify the correct stage in the technology life cycle when the benefits of implementing convergence are maximized and the risks are minimized –Not likely to be in early stages Develop a gradual migration strategy to integrate existing legacy and converged infrastructures –Back-up strategy should be in place to mitigate risks that go with an evolving technology

90. 90ControlNumber Recommended steps (continued) Carefully examine the experiences of other similar organizations which have implemented the technology –Determine how successful the technology is –Whether it has met performance and business expectations. Determine external factors which may impact project success –Human factors –Cultural clashes –Regulatory issues –Legal matters –Evolving standards –Stability of companies manufacturing products –Availability of second sources

91. 91ControlNumber Lessons learned from past Festina lente (Augustus) –Technology tends to be hyped –Non-technological factors govern if and when acceptance will happen –Drop-in replacements easier and faster than those requiring societal reorganization

92. 92ControlNumber Where the opportunities are for optical networking Access (last mile) –Necessary if really broad broadband ever to reach homes (10 Mbps or greater) Metro –High speed network connectivity to businesses –Debate between SONET and Gigabit/10 Gigabit Ethernet Long-haul –Buy fibers, equipment, and networks for pennies on the dollar Global Crossing Enterprise

93. 93ControlNumber Optical access alternatives Source: R. Lin/Terawave Networks/NGN2000

94. 94ControlNumber Passive Optical Networking Source: R. Lin/Terawave Networks/NGN2000

95. 95ControlNumber Verizon FIOS

96. 96ControlNumber Verizon FIOS (continued) Pricing for FiOS: * 5 Mbps/2 Mbps for $34.95 a month as part of a calling package, or $39.95 a month stand-alone * 15 Mbps/2 Mbps for $44.95 a month as part of a calling package, or $49.95 a month stand-alone * 30 Mbps/5 Mbps at $199.95 All FiOS Internet Service packages include: * Free installation by Verizon professionals * Ultra high-speed Internet access * Free networking router * MSN™ Premium Internet Software – a $99 annual value * 24/7 live technical support * Up to nine verizon.net e-mail accounts * Access to newsgroups * Personal Web space of 10 MB TV also available

97. 97ControlNumber Home access speed trends

98. 98ControlNumber Long haul Country (and world) already well covered with long-haul networks Much dark fiber Laying more fiber now difficult to justify Better to buy up assets of failed companies

99. 99ControlNumber Cost competition is brutal in long-haul

100. 100ControlNumber Metro Undoubtedly some opportunities exist Many companies already in the field Ethernet solution typically used

101. 101ControlNumber Enterprise Networks are strategic business factors Run mission-critical applications –Data must be shared with many locations –Network downtime unacceptable Disaster recovery of prime importance –Can require transfer of terabytes of data Often look to outsource