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Bandwidth Aggregation in Heterogeneous Networks Kameswari Chebrolu, Ramesh Rao Department of ECE University of California, San Diego.

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Presentation on theme: "Bandwidth Aggregation in Heterogeneous Networks Kameswari Chebrolu, Ramesh Rao Department of ECE University of California, San Diego."— Presentation transcript:

1 Bandwidth Aggregation in Heterogeneous Networks Kameswari Chebrolu, Ramesh Rao Department of ECE University of California, San Diego

2 Introduction Recent mobile Internet growth spurred deployment of different wireless technologies –e.g. GPRS, CDMA2000, HDR, 802.11, Bluetooth, Iridium etc End-Users have flexibility regarding Interface choice –Can choose any number of interfaces to best fit application needs Simultaneous use of multiple interfaces opens interesting possibilities –Bandwidth Aggregation, Mobility Support, Security, Reliability Problem Statement: –How to effectively aggregate bandwidth across multiple network interfaces?

3 Motivation Applications will drive next-generation network deployments Video Applications Video-on-demand Interactive video Video conferencing Multiplayer games –Bandwidth requirements: 250 Kbps to 2-3 Mbps –Problem: Wireless interfaces have bandwidth limitations 50 Kbps – 384 Kbps (GPRS, CDMA2000) TCP applications can also benefit from bandwidth aggregation

4 Challenges in Bandwidth Aggregation Use of multiple interfaces  Reordering Video applications have stringent QoS requirements –Interactive applications One way latency of 150ms, Max limit 400ms Frame loss rate < 1% –Video on Demand (with VCR functions): One way latency of 1-2 sec Frame loss rate < 1% –Cannot tolerate excess delay due to reordering TCP applications –More than 3 duplicate acks invokes congestion control –Bandwidth probing issues Inter arrival between acks does not reflect available bandwidth

5 Related Work Link-Layer Solutions –Bonding – aggregates circuit switched lines –IMA – ATM technology for aggregating multiple point-to- point links –Multilink PPP Stripe Protocol –Generic load-sharing protocol based on Surplus Round Robin (SRR) –Minimizes packet processing overhead –SRR similar to WRR Accounts for variable sized packets Surplus (unused bandwidth) is carried on to next round

6 Related Work (Contd.) Transport-Layer Solutions –RMTP Reliable rate-based transport protocol Flow and congestion control based on bandwidth estimation –Parallel TCP (pTCP) Opens multiple TCP connections on each interface Handles congestion and blackout through data reallocation and redundant striping Network-Layer Solutions –Based on tunneling –Weighted round-robin based scheduling

7 Research Contibution Solution Approach: –Bandwidth aggregation at IP-level –Meet application requirements using multiple interfaces Contributions: –Architecture for using multiple interfaces based on Mobile-IP –Scheduling algorithm based on estimated delivery time

8 Outline Architecture Scheduling algorithm Evaluation –Analysis –Trace-based simulation Ongoing work

9 Outline Architecture Scheduling algorithm Evaluation –Analysis –Trace-based simulation Ongoing work

10 Architecture for Bandwidth Aggregation Link-Layer Solutions infeasible –End point is an IP address Application/Transport Layer Solutions –Need to modify/rewrite code –Ensure compatibility with existing infrastructure Network Layer solution –IP – a single standard –Application transparency and interoperability –Cleanest Solution

11 Our Architecture

12 Architecture Details Mobile IP based –Packets pass through Home Agent (HA) –Simultaneous Binding - multiple Care-of-Address registration –Intelligent scheduling of packets to multiple addresses Radio Access Network Selection Unit (RSU) –Located on Mobile Host (MH) –Selects right interfaces based on app. reqmts. and cost –Update bindings with HA Traffic Management Unit (TMU) –Located on HA and MH –Processes and schedules the incoming traffic onto multiple paths –Conveys application type and end goal requirements to HA Scheduling Algorithm in TMU is crucial –Focus on Interactive Real-Time Applications

13 Scheduling Algorithm – Design Considerations Bandwidth –Interested in WWAN system (CDMA2000, GPRS etc) Provide only a few hundred kbps –Not interested in WLAN/WPAN systems –Wireless hop is the bottleneck link Delay/Jitter –Wireline Delay – between HA and Base-Station (BS) Delay values and variation small If large, variation may likely be masked at BS as wireless hop is bottleneck –Wireless Delay – between Base-Station and MH Queuing delay and transmission delay

14 Scheduling Algorithm – Design Considerations Qos Support –Interested in systems that provide QoS (CDMA2000, UMTS etc not HDR) –Negotiated bandwidth and loss rate guaranteed for duration of session

15 Design Possibility – Weighted Round Robin Schedules packets based on bandwidths of interfaces Not suitable for real-time applications Example: Three interfaces with bandwidth ratios 5:2:1 Packets 1-5 sent on IF1, 6-7 sent on IF2, 8 on IF3 Packet 6 arrives ahead of packets 3,4,5 Packet 3 suffers excess delay due to reordering Ideal ordering: IF1 – 1,2,4,5,6; IF2 – 3,7; IF3 – 8 Variants of WRR – Surplus Round Robin (SRR), Shortest Queue First face similar problems

16 Our approach: Earliest Delivery First For each path (between HA and MH), estimate arrival time of a packet at MH Estimation based on –Bandwidth of the interface –One-way wireline delay (estimated) on the Internet path Schedule the packet on the path that delivers the packet the earliest Quick remarks –No need for synchronized clocks (relative one-way delay counts) –EDF is not work conserving –EDF cannot totally eliminate reordering –Multiple applications can be handled by combining EDF with Weighted Fair Queuing (WFQ)

17 EDF Details Each path l is associated with three quantities –A variable, which is the time the channel becomes available next. –, the one-way wireline delay (estimate) of the path –, the bandwidth negotiated - the arrival time, - the size of packet i, Packet i scheduled on path l would be delivered at the MH at EDF schedules the packet on the path p for which is updated to

18 Performance of EDF How well can EDF perform? –Can the application QoS requirements be met? –Is performance as good as having a Single-Link (SL) with the same aggregated bandwidth? Approach –Analysis Prove fairness of EDF in distributing bits across different links Compare EDF with SL in terms of work, delay, jitter and buffering –Simulation Consider application performance level metrics Measure sensitivity of the algorithm to bandwidth asymmetry, number of interfaces, delay variation, channel losses

19 Properties of EDF Notation: – - max packet Size, – number of interfaces, - bandwidth of link l, - weight of link l (normalized bandwidth) Assumptions: –, and When packets are of constant size, they arrive in order at the client For variable sized packets – Given P packets to transmit, the maximum difference in normalized bits allocated to any two pair of links is –For WRR, this amount is a function of P and can be unbounded –For SRR it is

20 Properties of EDF (Contd.) For any time t, the difference between the total number of bits W serviced by SL and EDF is The difference in delay experienced by a packet i in SL and EDF is bounded by The jitter experienced by a packet i without buffering is upper bounded by The jitter experienced by a packet I with buffering is upper bounded by The buffer size needed to deliver the packets in order is

21 Experimental Methodology Trace driven simulation Server –Video frame traces – office cam (Mpeg4 and H.263) For MPEG-4, avg – 400kbps, peak - 2Mbps, frame period - 40ms For H.263, avg – 260kbps, peak – 1.5Mbps, frame period - variable Maximum packet size assumed is 1400 byte Home Agent –Employs scheduling algorithm Base-Station –No cross traffic –Serve packets first-come-first-serve basis

22 Experimental Methodology (Contd.) Client –Begin video display after a fixed delay – startup latency L –Afterwards, display frames consecutively every t seconds (frame period) –Arrival after playback deadline results in frame loss –Startup latency bounds one-way delay of packets Internet Path –Packet delay traces collected over different Internet paths –Hosts on UCSD, UCB, Duke, CMU –Wireline delay range used 15ms – 22 ms (one-way) Algorithms under comparison –Single Link – SL –Surplus Round Robin - SRR

23 Application Performance Metrics Backlog in the system Delay experienced by packets Frame Loss probability - Fraction of packets that miss playback deadline Glitch Duration: Number of consecutive frames that cannot be displayed Glitch Rate: Number of glitches/sec

24 Bandwidth Allocation % Bandwidth Needed over SL to achieve 0% frame loss, MPEG-4, BS = 3

25 Backlog SLEDFSRR Backlog in the system between HA and Client application, MPEG-4 Bandwidth fixed at 600kbps

26 Delay Distribution Cumulative Percentage of Delay, Mpeg-4, BS=3

27 Frame Loss probability

28 Sensitivity to Bandwidth Asymmetry

29 Sensitivity to Number of Interfaces

30 Extensions to EDF

31 Other Results Delay Variation : EDF –Truncated Gaussian with mean 22ms, std. devn. 0-10ms –For a split 5:3:1 at 225ms, No variation introduces 0.26% frame loss 5ms variation, 0.27% frame loss 10ms variation, 0.28% frame loss Channel Losses –Limited retransmissions help Other Applications –Non-Interactive Applications Large tolerance for delay  no big difference in relative perf. –Video-On-Demand Applications High peak-to-mean rates imply over-provisioning of bandwidth –Choice of scheduling algorithm does not matter

32 Summary Network-layer architecture to enable multiple communication paths EDF scheduling algorithm: reduces delay experienced by packets in presence of multi-path. An analysis of the algorithm shows that it doesn’t differ much from idealized SL Trace-driven simulations –EDF mimics SL closely –Outperforms by a large margin WRR based approaches

33 Ongoing Work Bandwidth Aggregation in Best-Effort Systems –Bandwidth Estimation at MH –Work ahead scheduling TCP –Support TCP applications –Network layer solutions Ad-hoc Networks Security


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