Network Resource ManagementNetwork Resource ManagementJason GaedtkeChief Scientist

W3C Video on the Web WorkshopDecember 2007

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TopicsTopics

• Abstract Compelling network neutrality arguments notwithstanding, not

all IP traffic exhibits uniform distribution requirements (e.g., bandwidth, latency, jitter and TTL).

Further, automated P2P file-sharing agents exploit TCP congestion control algorithms to gain a disproportionate share of network resources.

Some measures should be explored to address this natural, shared-network heterogeneity.

• Heterogeneous Applications and Network Requirements• Web Video Distribution Trends• A Resource Consumption Example (Briscoe Draft)• Potential Management Strategies• References and Collaborative Activities

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Heterogeneous Apps and Network ReqsHeterogeneous Apps and Network Reqs

• Real-Time Apps: dependent upon low-latency delivery, exhibit highly-variable bandwidth requirements, few simultaneous connections Online gaming VoIP and video chat IM and Presence Streaming video

• Interactive Services: tolerant of modest delivery delays, modest bandwidth, few simultaneous connections E-mail Web browsing Progressive download

• Content Distribution: automated, many simultaneous connections, greedy – will consume available bandwidth P2P file-sharing File/mail/news/Web servers

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Web Video Distribution (Background)Web Video Distribution (Background)

• Web Servers/Farms Simple client/server architecture Commodity servers, scaled horizontally

– Capacity– Redundancy/Availability

• Content Distribution Networks (CDNs) Specialized client/server architecture with aggressive caching Geographical distribution and load-balancing

• P2P Networks Decentralized, distributed and self-organizing “Super-nodes” avoid n2 link scaling and search Participants contribute bandwidth, storage and processing

• Hybrid CDN/P2P Networks Benefits of P2P resource sharing; <10% distro costs Seed and “long-tail” content sourced via CDN caches

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A Resource Consumption Example (Briscoe, draft-briscoe-tsvwg-relax-fairness)A Resource Consumption Example (Briscoe, draft-briscoe-tsvwg-relax-fairness)

• 10Mbps, shared access network, 100 subscribers 80 subscribers primarily interactive Web/e-mail:

– 10% concurrency, 2 TCP connections each– 9.9kbps average during congestion– 7.1MB per day (16-hours active)

20 automated P2P file-sharing clients: – 100% concurrency, 100 TCP connections each– 496kbps average during congestion– 3.6GB per day – 500:1 volume skew

TCP congestion control treats each flow equally; greedy apps spawn many connections

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Resource Consumption (4x Capacity)Resource Consumption (4x Capacity)

• 40Mbps shared, 100 subscribers 80 interactive Web/e-mail:

– 4% active (due to more responsive apps)– 40kbps (vs. ~10kbps) during congestion– 11MB (vs. ~7MB) per day

20 automated P2P file-sharing: – 2Mbps (vs. ~500kbps) during congestion– 14GB (vs. ~3.5GB) per day

As expected, a 4x increase in network capacity yields a 4x increase in average, per-flow rates under congestion; only exacerbates skew (>1250:1)

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Resource Consumption (Capacity + Churn)Resource Consumption (Capacity + Churn)

• 40Mbps shared, 60 subscribers: 50 interactive Web/e-mail (30 churn):

– 2.5% active– 80kbps (vs. 40kbps) during congestion– 14MB (vs. 11MB) per day

10 automated P2P file-sharing (10 churn): – 4Mbps (vs. 2Mbps) during congestion– 29GB (vs. 14GB) per day

Trends: fewer subscribers, greater network capacity/cost, >2000:1 consumption skew; ergo,

rational operators will not add capacity

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Resource Consumption SummaryResource Consumption Summary

• TCP congestion control treats all flows equally• Automated P2P agents are (very) greedy

100+ simultaneous connections 100% concurrency

• These aggressive algorithms will absorb an increasing amount of added capacity, thus degrading cost/benefit for other users

• Light, interactive users subsidize P2P distribution

• New economic/technical management strategies should be explored

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Potential Management StrategiesPotential Management Strategies

• Upstream/downstream rate limiting• Aggregate capacity limiting (tiering)• Application-specific throttling (via DPI)• Differentiated/priority service classes• Reservation-based resource management• Explicit protocol-level feedback/heuristics• Variable/metered pricing strategies• Bandwidth/resource trading schemes and

virtual economies• Others?

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References and Collaborative ActivitiesReferences and Collaborative Activities

• IETF Transport Area RFC 2309: Recommendations on Queue Management and

Congestion Avoidance RFC 2581: TCP Congestion Control RFC 2914: Congestion Control Principles draft-briscoe-tsvwg-relax-fairness

• DCIA P4P Working Group• CableLabs PacketCable Multimedia QoS• DSL Forum TR 58/59• Harvard SEAS and Tribler.org

Bandwidth Virtual Economy