Can ISPs be Profitable Without Violating Network Neutrality? Amogh Dhamdhere Constantine Dovrolis Georgia Tech

Amogh Dhamdhere NetEcon 2008 Disclaimer This is not a game theory talk

Amogh Dhamdhere NetEcon 2008 The Network Neutrality Debate Recent Trend: Large amounts of video and peer-to- peer traffic on the Internet Access Providers (AP) deliver content to users Recent trend: Not profitable Flat rates, commoditization of Internet access Content providers (CP) generate the content Profitable (think Google) Tension between AP and CPs: “Network neutrality” debate Traffic shaping/prioritization by ISPs

Amogh Dhamdhere NetEcon 2008 A Technical View Previous work Mostly non-technical Emotional debates in the press, painting APs as villians But what about the underlying problem: Non- profitability of Access Providers? Our approach: A quantitative look at AP profitability Investigate reasons for non-profitability Evaluate strategies for the AP to increase profit

Amogh Dhamdhere NetEcon 2008 Modeling AP Profitability Three AS types: AP, CP and transit provider (TP) Focus on the AP AS links customer-provider (customer pays provider) peering (no payments) AP and CPs can transfer traffic either through customer-provider or peering links TP AP CP

Amogh Dhamdhere NetEcon 2008 Baseline model AP and CP connect to the TP as customers N users of AP, charged a flat rate R ($/month) Flat rate prices decrease due to competition Transit pricing: 95 th percentile of traffic volume 95th / mean = 2:1 for normal traffic, 4:1 for video 1 More video means higher transit payment by AP AP users: Heavy tailed distribution of content downloaded per month High variability in AP costs 1 Norton’06: Internet Video: The Next Wave of Massive Disruption to the U.S. Peering Ecosystem

Amogh Dhamdhere NetEcon 2008 AP Strategies – Charging Charging strategies AP charges “heavy hitters” according to volume downloaded AP caps heavy hitters AP charges CP (non-network neutral) Charging strategies are disruptive AP users may depart, depending on existing competition Parameter d determines shape of departure probability curve AP cannot control customer departure probability

Amogh Dhamdhere NetEcon 2008 AP Strategy – Charging Heavy Hitters Threshold T to identify heavy downloaders Charge “by volume” for heavy hitters c(D) = D*R/T, where download amount D, threshold T, flat rate R Customer departure probability depends on T and d AP’s profit is sensitive to customer departure probability For some values of d, no threshold gives larger profit than baseline !!

Amogh Dhamdhere NetEcon 2008 AP Strategies - Connection Connection Strategies AP caches content from CPs AP peers selectively with CPs Goal: Save transit costs paid to the transit provider Does not increase the AP’s revenue Non-disruptive AP does not risk losing customers

Amogh Dhamdhere NetEcon 2008 AP Strategy – Cache CP Content AP caches content from some CPs locally Saves transit costs, as content is served locally Increases local costs incurred by the AP Critical parameters: Fraction of content that can be cached (h) and cost incurred for caching (s) Live content cannot be cached! Profit is sensitive to h, s

Amogh Dhamdhere NetEcon 2008 AP Strategies – Peering with CPs Peering selectively with Content Providers can save transit costs, without risk of losing its users But, peering is not free Fixed, traffic dependent costs Peering cost classes for CPs “Low”: CPs at the same geographical location/IXP “Medium”: CPs at nearby location/IXP “Hard”: CPs in different continents Cost benefit analysis: r = Estimated benefit/Estimated Cost Peer if r > R

Amogh Dhamdhere NetEcon 2008 AP Strategies – Peering with CPs Optimal point exists for the cost-benefit threshold R AP controls the factor R Significant reduction in AP costs with selective peering Greater benefit with fewer CPs (more traffic from the largest CPs) AP can leverage expansion by large CPs

Amogh Dhamdhere NetEcon 2008 Conclusions Network Neutrality research should also focus on the underlying problem: Non-profitability of ISPs How can ISPs be profitable in spite of increasing traffic, heavy-hitter users and video traffic ? Charging schemes that target heavy hitters may not work in the presence of competition in the AP market Profit highly sensitive to customer departure probability Out of the AP’s control Connection strategies such as peering selectively with Content Providers seem promising Completely under the AP’s control

Amogh Dhamdhere NetEcon 2008 Thank You !

Amogh Dhamdhere NetEcon 2008 AP Strategy – Capping Heavy Hitters AP caps download rate for users Limits the total amount of traffic handled Saves transit costs and local costs, but does not increase revenue AP profit depends on customer departure probability For some values of d, no threshold gives larger profit than baseline !! No significant improvement over baseline

Amogh Dhamdhere NetEcon 2008 AP Strategy – Charging CPs AP directly charges the top sources of content (CPs) Increases revenue, but violates “network neutrality” Subject to customer departure due to discriminatory practices AP profit depends on customer departure probability