EECS228a Lecture 2 Research Topics Jean Walrand - PowerPoint PPT Presentation

EECS228a – Lecture 2 Research Topics Jean Walrand www.eecs.berkeley.edu/~wlr

Outline Economics of Networks Routing Congestion Control Traffic Models Walrand EECS 228a 52

Economics of Networks Outline Hangover Pricing of Services Competition of Users Competition of Providers Suggested Readings: n http://www.bgsu.edu/departments/tcom/annota.htm n http://info.isoc.org/internet-history/ n http://www.spp.umich.edu/ipps/papers/info- nets/Economic_FAQs/FAQs/FAQs.html Walrand EECS 228a 53

Economics of Networks Hangover Bubble: Wired Walrand EECS 228a 54

Economics of Networks Hangover Bubble: Wireless Walrand EECS 228a 55

Economics of Networks Hangover Over-Investment n Based on unrealistic growth forecast n Overcapacity: Fiber 5x100 in three years n Too many companies competing for same market Debt n Wireless: Expensive spectrum licenses n Fibers n IT in companies: PCs, Servers, Networks Walrand EECS 228a 56

Economics Key Ideas Value of services to users: externality, QoS, CoS Market segmentation Flat rate pricing; congestion pricing; Paris metro pricing; time-of-day pricing Incentive compatibility Inter-ISP settlements; Peering agreements Internet as a public good Walrand EECS 228a 57

Economics Value of Services Externality: Kazaa Value per bit: email vs. fax vs. picture Value of bit rate: video stream vs. radio Value of low latency: video stream vs. video conference Value of low response time: browsing with DSL vs. browsing with 56k QoS affects value and usage Value of QoS depends on application and user Walrand EECS 228a 58

Economics Market Segmentation Businesses vs. Residential Customers Network Application Providers vs. public Web Sites Principle: Charge more users with higher utility Walrand EECS 228a 59

Economics Differentiated Pricing Examples: n First Class & Economy in plane: More space but much more expensive n Paris Metro: More expensive Fewer Users Better Service (e.g., Stanford vs. Berkeley?) Suggests Class of Service: n Better service by mechanism: e.g., priority n Better service by fewer users: e.g., expensive network; congestion pricing (e.g., packet marking); time-of-day Alternative: QoS: You know what you pay for n Service Level Agreement (implementation?) n QoS of accepted calls: end-to-end test Walrand EECS 228a 60

Economics Incentive Compatibility How to discover the user’s willingness to pay? Examples: n California Electricity: Providers offer bids and CA buys cheaper first prices escalade n Highest bidder auction: Spectrum auctions n Highest gets but two highest pay n Second highest price: Incentive compatible Walrand EECS 228a 61

Economics Competition Basic supply and demand: n More capacity than traffic prices drop and providers go bankrupt Internet traffic doubles every year instead of every 100 days …. Quality service is still rare and valuable: n Businesses use video conference over ISDN n Expensive commutes and business travel n Users pay a lot for CATV and pay-per-view n T1 service expensive: demand exists Walrand EECS 228a 62

Economics Game Theory Framework to analyze result of interaction of self-interested agents Suggests strategies for n Pricing services n Peering agreements n Routing n QoS definitions n Evolution of industry (e.g., consolidation vs. specialization) Two parts: Games & Mechanism Design Walrand EECS 228a 63

Routing Outline Motivation Granularity Types Issues Walrand EECS 228a 64

Routing Motivation Reduce delays: Avoid OAK NY SF Improve reliability: Protection Sensor networks: Many open questions Ad Hoc networks: More robust, provide QoS IP/Optical: Improve coordination Walrand EECS 228a 65

Routing Granularity Light Path: WDM Cross-Connect: SONET Circuit: Telephone Label Switched Path: MPLS; ATM Connection Packet Walrand EECS 228a 66

Routing Granularity (cont) Benefit of LSP vs SONET is not obvious: n Consider traffic from SF to NY; If that traffic is essentially constant, then SONET is good enough. If not, LSP/SONET is preferable. n If traffic is self-similar, then fluctuations persist at high rate Walrand EECS 228a 67

Routing Types On-line vs. Off-line Centralized vs. Distributed Link State; Distance Vector; Path Vector Source-based vs. Destination-based QoS routing Ad Hoc; Location-Based Ant-routing (reinforcement) Unicast vs. multicast Protection routing Peer-to-peer vs. overlay Walrand EECS 228a 68

Routing Issues Benefits Implementability: n Scalability: communications required; complexity; convergence time n Robustness: sensitivity to errors Walrand EECS 228a 69

Congestion Control Outline Motivation Examples Issues Walrand EECS 228a 70

Congestion Control Motivation At user level: Issues with QoS At network level: Losses, inefficiency, unfairness At switch level: Scalability problems Walrand EECS 228a 71

Congestion Control Examples TCP Congestion in routers Call Admission Control Walrand EECS 228a 72

Congestion Control Issues Fairness vs. Optimality Simplicity Robustness Walrand EECS 228a 73

Traffic Models Outline Why bother? Transactions Packet flows Walrand EECS 228a 74

Traffic Models Why Bother? Network should be robust; not based on detailed traffic assumptions Traffic characteristics impact n Effectiveness of multiplexing n Buffer sizes required n Time scale of bandwidth allocations Walrand EECS 228a 75

Traffic Models Transactions File transfers: n File sizes: Heavy tailed n Timing of requests: Poisson n Geography: w Kazaa – poor locality w Akamai – improved locality Other applications: n video conferences n VoIP Walrand EECS 228a 76

Traffic Models Packet Flows Self-Similarity: n Heavy Tail + TCP Self Similar Flows n Heavy Tail Files + Structure of Web Sites Self Similarity Relevance: n Not obvious – a matter of time scale Walrand EECS 228a 77