Bandwidth Aggregation in Heterogeneous Networks

Kameswari Chebrolu, Ramesh RaoDepartment of ECE

University of California, San Diego

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?

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

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

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

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

Outline

• Architecture• Scheduling algorithm• Evaluation

– Analysis– Trace-based simulation

• Ongoing work

Outline

• Architecture• Scheduling algorithm• Evaluation

– Analysis– Trace-based simulation

• Ongoing work

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

Our Architecture

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

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

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

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

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)

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

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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

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

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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

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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

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

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

Bandwidth Allocation

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

Backlog

SL EDF SRR

Backlog in the system between HA and Client application, MPEG-4

• Bandwidth fixed at 600kbps

Delay Distribution

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

Frame Loss probability

Sensitivity to Bandwidth Asymmetry

Sensitivity to Number of Interfaces

Extensions to EDF

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

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

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