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Transport and Application Layer Approaches to Improve End-to-end Performance in the Internet PhD Prospectus Talk Amit Mondal Program Committee: Aleksandar.

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Presentation on theme: "Transport and Application Layer Approaches to Improve End-to-end Performance in the Internet PhD Prospectus Talk Amit Mondal Program Committee: Aleksandar."— Presentation transcript:

1 Transport and Application Layer Approaches to Improve End-to-end Performance in the Internet PhD Prospectus Talk Amit Mondal Program Committee: Aleksandar Kuzmanovic, Asst. Professor, Northwestern Univ Peter Dinda, Assoc. Professor, Northwestern Univ Yan Chen, Assoc. Professor, Northwestern Univ Jin Li, Principal Researcher, Microsoft Research

2 The Internet is a commercial infrastructure used by diverse set of applications and services Internet — A multiservice IP network 2 FTPIPTVVoIP Video ConferencingStreaming Gaming

3 Challenges involved…  Applications have end-to-end network performance requirements –Jitter, latency, packet loss, bandwidth, etc  Original Internet –Best effort service –No service assurance –TCP ensures only in-order packet delivery –Destination-based IP routing  Need for Quality-of-service support in the Internet 3 “low delay” “high throughput”

4 QoS and the Internet  QoS Architectures –Integrated Service (Intserv) –Differentiated Service (Diffserv) –Multi Protocol Label Switching (MPLS) –Traffic Engineering and Constraint based routing  Key Challenges –Scalability issues in core –Complex signaling protocols –Deployment overhead  Current Internet still offers only a best-effort service  Motivates to investigate easily deployable solutions that improve end-to-end network performance 4

5 QoS using transport and application layer techniques without network support  Explicit congestion notification [ Floyd 94]  Packet marking and differential dropping [Guo and Matta’01]  Limited transmit [Allman et al. 01]  Service differentiation [Neoreddine and Tobagi’02]  Differential congestion notification [Le et al.’04]  TCP smart framing [Mellia et al. ‘05]  ECN+ [Kuzmanovic’05]  Early retransmit [Allman et al.’06]  TCP SAReno [Yang and Vecinia’02]  PCP [Anderson et al. ‘06] 5

6 Research thesis  Research thesis is the following: “It is possible to further improve end-to-end network performance using transport and application layer approaches without explicit QoS support from the underlying IP network.”  Focus: –Low-latency interactive TCP applications (thin-stream TCP) Telnet, SSH, network games, short web transfers, etc. –Interactive multimedia services Audio/video conferencing, VoIP, streamed multimedia services, etc. 6

7 Multimedia services Low-latency TCP applications 1) Upgrading Mice to Elephants: Effects and End-Point Solutions A. Mondal and A. Kuzmanovic In IEEE/ACM Transactions on Networking, accepted, March 2009 2) Removing Exponential Backoff from TCP A. Mondal and A. Kuzmanovic In ACM SIGCOMM CCR, Volume 38, Number 5, October 2008. 3) When TCP Friendliness Becomes Harmful A. Mondal and A. Kuzmanovic In IEEE INFOCOM 2007 4) Supporting Application Network Flows with Multiple QoS Constraints A. Mondal, P. Sharma, S. Banerjee, and A. Kuzmanovic In IEEE IWQoS 2009 5) SureCall: Characterizing IP Networks for Real-time Audio/Video Conferencing A. Mondal, C. Huang, M. Jain, J. Li, and A. Kuzmanovic Work in progress. 6) A Poisoning-Resilient TCP Stack A. Mondal and A. Kuzmanovic In IEEE ICNP 2007 Publications 7

8 8 Improving thin-stream TCP flows data packets “ dummy” packets strict priority TCP-fair rate Upgrading mice to elephants Packet switchedCircuit switched

9 Going beyond TCP-fair  Differentiated minRTO –Application-limited flows use reduced minRTO value  Short-term padding with dummy packets –Application data followed by three tiny dummy packets  Diversity approach –Send multiple copies of a packet 9

10 10 Removing Exponential Backoff from TCP  Congestion collapse –1986: throughput from LBL to UC Berkeley dropped from 32Kbps to 40 bps  V. Jacobson, “Congestion Avoidance and Control,” in ACM CCR, 18(4): 314-329, Aug 1988. –Slow start –Dynamic window sizing –RTT variance estimation –Exponential retransmit timer backoff

11 11 Why Exponential Backoff?  Jacobson adopted exponential backoff from the classical shared-medium Ethernet protocol –“IP gateway has essentially the same behavior as Ether in a shared-medium network.”

12 12 Why Exponential Backoff?  Jacobson adopted exponential backoff from the classical shared-medium Ethernet protocol –“IP gateway has essentially the same behavior as Ether in a shared-medium network.” – Not true! C C

13 Removing exponential backoff from TCP and its implications  Other reasons: no admission control, finite flow size, skewed traffic distribution, etc.  When to resend a packet? –Implicit packet conservation principle As soon as the retransmission timeout expires –End-to-end performance can only improve if we remove the exponential backoff from TCP  Implications –Significant improvement of response times for short and interactive TCP flows 13

14 Multiple QoS Constraints  The Internet evolves towards the global multiservice IP network –Diverse applications and different QoS requirements  Many applications have multiple QoS requirements –Video streaming, VoIP, Video conferencing, etc.  Need support for end-to-end QoS guarantee under multiple constraints  Multiple QoS constraints often make the routing problem intractable 14

15 QoS provisioning using overlay networks  Build Overlay Backbone –Deploy overlay nodes at strategic locations in the Internet  Provide support for per-flow forwarding –e.g. Anagran Flow Aware Routers  Flow route management architecture –Discover and setup end-to-end paths for individual flows with diverse flow QoS requirements –Monitor end-to-end flow performance to trigger path adaptation 15

16 Overlay flow QoS management architecture 16 AS3 AS4 AS1 AS2 End user Overlay node Physical link Logical link Sensing local link characteristics Find a path to X with b/w > b, delay < d and loss < l% Configure intermediate overlay nodes for per-flow forwarding Adapt to different path dynamically as current path fails to meet QoS parameters

17 Contribution  Design a scalable QoS routing protocol which finds path under multiple constraints  Propose a distributed algorithm for dynamic path adaptation  Evaluate accuracy, efficiency and scalability of the protocol using large-scale simulation and compare with other existing approaches  Build a functional prototype using Click modular router 17

18 Design challenges  Multiple QoS metrics –Finding a feasible path using Dijkstra’s algorithm is NP- Complete –Randomized and approximation algorithms –Single composite metric derived from multiple metrics Paths might not meet individual QoS constraints  Dynamic overlay-link properties –Increases control message overhead 18

19 Overview of our Multi-constraint QoS routing protocol (MCQoS)  Path vector protocol to disseminate path information –Tag with QoS parameters  How to aggregate path information when multiple QoS metrics are considered? –Distribute the best paths for each metrics  What about QoS requests which could be served by paths which are not in the best path set? –On-demand route discovery 19

20 MCQoS: Disseminating path information 20 B A QoS Path Table XAS1 (2ms, 0.01%, 128Kbps) AS3 (3ms, 0.02%, 378Kbps) AS5 Delay XAS1 (2ms, 0.0%, 128Kbps) AS3 (3ms, 0.005%, 378Kbps) AS5 Loss XAS1 (10ms, 0.01%, 1Mbps) AS3 (5ms, 0.01%, 768Kbps) AS5 B/w Local link info Tag QoS characteristics Advertise best path for each QoS metric

21 MCQoS: Aggregating path information  What about QoS requests in the undecidable region? 21 Delay Bandwidth (b/w) infeasible undecideable best b/w best delay feasible There will feasible requests that can be supported but the source node might not know about those paths, thus cannot admit flows based on local information The source node already knows a path if the QoS request falls in the feasible region There cannot exist a feasible path in the network if the QoS request falls in the infeasible region

22 MCQoS: On-demand route discovery  Admit or deny flow based on local QoS table if in feasible or infeasible region  Otherwise, On-demand route discovery for requests in undecideable region  Exploit advertisement received from neighbors to reduce search space while route discovery 22 Delay B/W feasible infeasible undecideable AB C D E

23 23 C B D A E 10ms12Mbps 100ms 50Mbps 2ms5Mbps 8ms20Mbps 4ms5Mbps 105ms 50Mbps 5ms5Mbps 106ms 50Mbps 120ms, 15Mbps OK 10ms12Mbps 100ms 50Mbps 2ms5Mbps 8ms20Mbps 10ms, 3Mbps OK 10ms, 100Mbps X 15ms, 15Mbps ??? 10ms, 3Mbps OK ABD…E 120ms, 15Mbps OK ABC…E 10ms, 100Mbps X ---- (2ms, 20Mbps) (5ms, 100Mbps) (1ms, 100Mbps) 15ms, 15Mbps OK ABD…E Requests: best b/w best delay MCQoS: Illustration through example

24 Overhead analysis of path dissemination 24 4 6 5 2 3 1 10 8 4 7 5 9 6 In MCQoS protocol, a node advertises only the best path to a destination. Thus many alternative paths are pruned, which increases scalability.

25 Overhead analysis of on-demand route discovery  Parameters –Average out-degree of the nodes –Overlay distance between source to destination  Worst case –Message overhead is proportional to sum of all possible path lengths from source to destination  Amortized cost –Fraction of request in undecidable region –Limit no of hops of route discovery 25 More than 99% of the undecidable region is discovered within 5 hops from the source node, thus amortized cost will be significantly less than worst case scenario.

26 Convergence time of path dissemination 26 Being path vector based protocol MCQoS takes longer time to converge, but does not involve any NP-hard computation, thus scale with network size  Convergence time: how long does it take to stabilize for a given network snapshot?  Re-stabilization time: how long does it take to stabilize once a link metric changes?  QRON: Link state based multi-QoS routing protocol using composite metric approach

27 Message overhead of path dissemination 27 Message overhead of MCQoS is comparable to Link- State based (QRON) protocol

28 Elaborating the undecidable region 28 Depletion area  Global feasible region: feasible region at the source node if the source node knew all alternative paths like link-state protocol  Depletion area: part of global feasible QoS region not known at the source node because many alternate paths are suppressed  K-hop path: paths in the undecidabe region discovered within k-hops of on-demand route discovery process

29 Overhead of on-demand path discovery 29 More than 90% of the depletion area is discovered within 3 hops  How many hops does it take to discover the entire depletion area?  We measure the fraction of depletion area discovered within k hops from the source node

30 Improvement in accuracy by MCQoS 30  A feasible path with a composite metric might not satisfy individual QoS metrics.  The line-segment based approach often suffers from loss/distortion.  Our hybrid approach has no false positive and false negative percentage can be reduced to less than one 1% by 3-hop on-demand route discovery.

31 QoS violation ratio in dynamic environment with MCQoS 31 Arrival rate (conn/sec) 60120240300600 Violation ratio (%) 0.320.330.780.41.12  100 node topology  Generate QoS requests with certain arrival rate with b/w [5Mbps, 55Mbps] and delay [100ms,400ms]  Each flow lasts between 5 to 10 minutes  We simulate the network behavior for 10 minutes  New flows arrive before network stabilizes –Expect to observe QoS violation The QoS violation ratio is negligible even with arrival rate of 600 conn/sec.

32 MCQoS enabled overlay node prototype 32 MCQoSS3S3 Click Router DataInDataOut Flow setup Local link characteristics Peers (path ads) Control Plane Data Plane QoS path setup (Y:p -> X:q, Dms, L%, BKbps) Rt. discovery req, Rt. discovery reply QoS Path table Flow setup req Flow idNext hop Y:p ->X:qC

33 Summary  Designed a scalable multiple constraints QoS flow route management protocol –hybrid approach of path vector routing and on-demand route discovery –Keep balance between flow setup time and control message overhead –No complex NP-hard computation  Performed large-scale simulations to demonstrate the efficiency and scalability of the approach  Built a prototype using Click modular router 33

34 Audio/video conferencing in the Internet  Identify real problems  Quantify impacts of various network components  Investigate solutions 34

35 SureCall platform  Distributed measurement platform to collect packet level trace of synthetically generated A/V conferencing traffic –Light-weight master controller –Clients running on volunteers’ machines –SureCall clients can be automatically upgraded without user intervention  Available from Call.htm Call.htm 35

36 SureCall measurement  Master controller schedules AV sessions between clients –VoIP or audio-video conferencing  Clients send emulated audio/video traffic in both directions using UDP –Audio bitrate : 24 kbps –Video bitrate: 192 kbps –STUN NAT traversal protocol for home users  Network connectivity close to the clients –ICMP packet pair with TTL=2  Traceroute to other endpoint at the beginning and end of AV session  Environmental details on client machines –CPU load, network interface type 36

37 SureCall deployment  Microsoft global enterprise network  Residential network  Current deployment status –80 unique machines Enterprise - 32 Home – 20 Both – 28  Enterprise trace and Home trace –Two separate masters (within enterprise network and in public Internet) 37

38 SureCall dataset  4,800 hours of packet traces –4,100 from enterprise –700 from home  1968 unique IP addresses –Enterprise - 1212 –Home -756 38

39 Objectives  Quantify impact of various network components on Audio/Video conferencing performance –Enterprise vs. residential networks –Effect of WiFi and VPN connection  Study network characteristics that can be leveraged to design improved audio/video conferencing algorithms –Correlation between jitter and packet loss –ICMP to detect last mile congestion  Investigate application and transport layer techniques to improve performance 39

40 PhD dissertation timeline  Oct, 2009 – Jan, 2010 1)Analyze SureCall traces to characterize IP networks for Audio/video conferencing 2)Investigate techniques to improve quality of audio/video conferencing 3)Extend SureCall for mobile devices running Windows Mobile  Feb, 2010 – June, 2010 : 1)Job interview preparation and appear in job interviews 2)Write PhD dissertation 3)Defend PhD thesis in June, 2010 40

41 Backup slides 41

42 Route maintenance in MCQoS  Route maintenance through path patching  Each intermediate node knows the QoS requirements from the node to the destination  Upstream node periodically pushes QoS requirements to downstream nodes  As a node detects QoS violation, it triggers alternate path search at local node –Notify upstream node if no alternative path 42 AG B E H FD C

43 Experimental evaluation of MCQoS  Built an event-driven simulator  Generated random flat topology of nodes using GT- ITM –Outdegree min(10, size/2)  Assigned link metrics from actual planetlab link measurement data 43

44 ‘Composite Metric’ approach to multi-QoS routing (1/2) 44  Composite Metric = K1*delay + k2/bw where k1=1, k2 = 10^7, delay in sec, b/w in bps  False positive: flow is admitted but the path does not meet the QoS  False negative: there exists a feasible path but the flow is not admitted

45 ‘Composite Metric’ approach to multi-QoS routing (2/2) 45

46 ‘Line Segment’ approach to multi-QoS routing (1/2) 46  Lui et al. proposed line segment based approach to for topology aggregation in delay-bw plane. Tam et al. designed a distance vector based QoS protocol using the line-segment approach  False positive: Fraction of undecidable region that is actually infeasible, but the approach labels as feasible.  False negative: Fraction of undecidable region that is feasible, but the approach labels as infeasible.

47 ‘Line Segment’ approach to multi-QoS routing (2/2) 47

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