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Network Resource Management Jason Gaedtke Chief Scientist W3C Video on the Web Workshop December 2007.

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Presentation on theme: "Network Resource Management Jason Gaedtke Chief Scientist W3C Video on the Web Workshop December 2007."— Presentation transcript:

1 Network Resource Management Jason Gaedtke Chief Scientist W3C Video on the Web Workshop December 2007

2 5/20/2015© Cable Television Laboratories, Inc. 2007. All Rights Reserved. Proprietary/Confidential2 Topics 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

3 5/20/2015© Cable Television Laboratories, Inc. 2007. All Rights Reserved. Proprietary/Confidential3 Heterogeneous 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

4 5/20/2015© Cable Television Laboratories, Inc. 2007. All Rights Reserved. Proprietary/Confidential4 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 n 2 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

5 5/20/2015© Cable Television Laboratories, Inc. 2007. All Rights Reserved. Proprietary/Confidential5 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

6 5/20/2015© Cable Television Laboratories, Inc. 2007. All Rights Reserved. Proprietary/Confidential6 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)

7 5/20/2015© Cable Television Laboratories, Inc. 2007. All Rights Reserved. Proprietary/Confidential7 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

8 5/20/2015© Cable Television Laboratories, Inc. 2007. All Rights Reserved. Proprietary/Confidential8 Resource 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

9 5/20/2015© Cable Television Laboratories, Inc. 2007. All Rights Reserved. Proprietary/Confidential9 Potential 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?

10 5/20/2015© Cable Television Laboratories, Inc. 2007. All Rights Reserved. Proprietary/Confidential10 References 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


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