Integrated Routing & MAC Scheduling for Wireless …Integrated Routing & MAC Scheduling for Wireless Mesh Networks Zhibin Wu Dipankar Raychaudhuri WINLAB, ECE Dept. Rutgers University

Integrated Routing & MAC Scheduling for Wireless Mesh Networks

Zhibin Wu

Dipankar Raychaudhuri

WINLAB, ECE Dept. Rutgers University

Outline

Our Perspective of High-Speed Wireless Mesh Networks

Problem & Approaches

Analytic Throughput Bounds for Integrated Routing/scheduling

Protocol and Algorithms: Practical Designs

Simulation Results with IRMA protocols

Conclusions & Future Work

•2 | IRMA fro Wireless Mesh Networks| December 2007

Emerging Broadband Radios and Throughput-Thirsty Devices

Short-range, high-speed radio technologies emerging:Technology Name Link Speed (in Mbps) BW (MHz) Frequency Band

802.11n 74-248 20 or40 2.4GHz and 5GHz

WiMedia 53-480 500+ 3.1 to 10.6 GHz

mm-wave (WPAN) up to 2000 N/A 60GHz

Device need more throughput over the air Mobiles

• More processing power, storage capacity and less cost

• Contents comes from network and share on the network

Wireless Camcorders

Wireless HDTV…


New Forms of Wireless Networks

“Wireless” not only an access technology, but also a networking technology

Wireless devices form a true “wireless network”

Multi-hop wireless peer-to-peer transport

BTS •RNC •PDSN

InternetInternet

Wi-Fi

•WiMAX

•CDMA2000

•BS •ASN-GW

•Wireless Mesh Network


Requirement: High Throughput Bulk data transfer over wireless mesh architecture.

Goal: Protocol and algorithm design to achieve maximal throughput for concurrent end-to-end multihop flows.

Problems:

What’s the achievable end-to-end capacity given a certain “small” number of nodes in the topology?

Is there a feasible design to approximate the capacity?

What’s the control overhead and how it scales with the traffic demands?

Conventional Approach: IEEE 802.11+ ad hoc routing

High-Speed Wireless Mesh Network


CSMA/CA MAC Problems with multi-hop radio network

A simple contention-based protocol fails to handle interference

Link level: Hidden terminals and exposed terminals.o Spatial reuse vs. Collision avoidance.

o Mesh network simulation shows ~68% of RTS get no response

Flow level: Intra and Inter-flow interference

•Self Interference

•Inter-flow Interference

•Hidden Node

•Exposed Node


Wireless MAC Design Techniques

•RTS/CTS, MACA- P, D-LSMA

•DCMA

•IRMA

“Reserve first, access later” is a must to reach interference-free as well as throughput-optimal

Flow-based scheduling design are still offline optimizations, lack of protocols

End-to-End flow scheduling can be optimized jointly with L3


Joint Routing/Scheduling: Example

a 4x performance

gain can be achieved

by carefully selecting

routing paths and

MAC schedules

JOINITLY.

1

2

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5

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7

8

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10

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15

16

(b)

12

3

1516

12

1314

ACK

ACK

ACK

ACK

t

Data

ACK

ACK

DataData

DataData

Data

DataData

ACK

1

2

3

4

5

6

7

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15

16

(a)

RTS12

3

567

139

RTS

RTSCTS ACK

CTS ACK

RTS RTS

t

Data

RTSRTS

Data

•802.11 MAC with designated Min-hop paths

•Synchronized TDMA MAC with better paths


Flow Based Management over TDM Slot Assignments

Design both L2 & L3 protocols based on flow session , e.g. scheduling result won’t change till the end of a traffic session,

better end-to-end performance and less overhead

Traffic flows over HS-WMN are not conventional Internet traffic

Bulk data transfer & Aggregated traffic from multiple clients

To serve long-lived CBR and VBR, TDMA is better.

Traffic is not bursty, require deterministic bandwidth and delay

By satisfying the interference constraint one can guarantee a certain fixed data rate at a given link.

Global synchronization difficulty can be overcome in a small network

Dedicated bandwidth can be specified for control

•Frame n •Frame n+1 •Frame n+2


Contributions of Our Research

Offline Approach: Analytical framework to obtain optimal resource allocations and throughput bounds for end-to-end traffic over single-channel wireless mesh networks, especially for single path routing case.

Online Approach: IRMA System Design

Separation of control and data: Global Control Plane

Centralized and distributed heuristic algorithms.


Obtaining throughput Bounds from LP Optimizations

Maximize end-to-end throughput : multi-commodity network flow problem (linear programming)

Analytical throughput bounds with protocol interference model for following scenarios:

Min-hop routing + link Scheduling

oThe path for each <s, d> is known as the min-hop path.

Joint routing/scheduling (route is uncertain)

o Multipath Routing: traffic from s to d is split in multiple routes– More optimal than single-path routing

– Linear programming , but NP-hard to get all constraints

o Single path routing.– Mixed integer programming problem

– Using maximal utilization rounding to avoid integer variables


Numerical Results

Gaps between the throughput bounds obtained by LP optimizations and a 802.11 system simulation shows huge potential for integrated protocol design

[Gupta’00] :Given n nodes randomly located in a unit disk, transport capacity with interference-free protocols is

Network capacity decreases with increasing number of flows


IRMA System Model

Global control plane and data planeAll control signaling on a separate plane

Parameters of IRMA component in data plane is determined by control algorithms

Control Algorithms

Global Control Plane (GCP)

Data Packet

Control Message

•Protocol stacks in IRMA system

•Application

•CSMA MAC

•Control Plane •Data Plane

PHY

TDMA MAC

•Controlled Routing

PHY

• Routing

IRMA Control Agent

•IRMA Algorithms

IRMA Component


IRMA System Control Cycle

Control Cycle:

Detection and report of new or changed traffic demands.

IRMA optimization determine the paths and conflict-free TDMA schedules for each node.

IRMA components (Routing and MAC) transform and work with the new working parameters to ensure QoS.

•Traffic Variation

Detection

IRMA

• Optimization

Path/Schedule Adjust

Working

Bootstrap

Topology

DiscoveryLoad default

• IRMA parameters


Heuristic Algorithms for IRMA

Centralized Algorithms

Existing a central entity collect global information (topology, BW, interference relationship) and run optimization algorithms

CIRMA-MH: solves min-hop routing, then optimizes link scheduling based on routing results and real-time flow demands.

CIRMA-BR: attempts to optimize routing and scheduling decisions simultaneously, using available MAC bandwidth information to route around congested areas.

Distributed Algorithms (DIRMA-MH and DIRMA-BR)

each node needs to figure out the “best” schedule and route for its traffic in a distributed manner, with local information exchange only (in the control plane).

Optimization for the whole flow is conducted hop by hop (source to sink)


CIRMA-MH

MH (Min-hop) routing + TDMA link scheduling based on the path selection

Inputs of the algorithm: Topology (G(V,E))

Traffic Profile (source-destination, bandwidth requirement) and

Interference-index k

TDMA frame length T (Number of slots in a frame)

Output: route selection and MAC TDMA slot assignments

CIRMA-MH Algorithm:

1. Find the shortest route with hop metric

2. For each link e in each flow Fi , assign earliest available slot x for this link as long as it does not conflict with the links already scheduled in this slot x

3. Repeat step 2 until all bandwidth requirements are fulfilled or no more slots are available.


CIRMA-BR

Min-hop routes are not optimal, cause local congestions

Better paths can be found and yield higher throughput than MH paths

Joint TDMA Link Scheduling and Bandwidth Aware Routing (BR)

CIRMA-BR Algorithm:

1. Sorting the flow in ascending order by bandwidth requirements

2. For each flow Fi , i= 1,2 …, M

a) Generate link Metric based on available “free” TDMA Slots

b) finding shortest path for flow Fi with the “bandwidth” metric. and assign conflict-free TDMA slots for this flow

(a) (b) A C

D B

A C

B D

•Different routes used by (a) CIRMA-MH and (b) CIRMA-BR in a 6x6 grid for two

vertical flows


DIRMA-MH

Distributed TDMA link schedule setup:

Lock and reserve (too ideal)

Schedule first, correct later

SUPD messages

Coordinate neighbors/interferers to mark the slot in Free/TxOK/RxOK/Prohibited States.

Periodically broadcasted or triggered

SREQ/SAPP/SREJ

Reserve the slot to schedule a link transmission

SCAN (Schedule Cancel)

Release slot if no longer needed for this link

Correct schedule errors if collision is detected

A B FD ECSREQ

SAPPSUPDSUPD

SREQ

SAPPSREQ

SREJ

•Slot State Transitions

•Solve Hidden Node and Exposed Problems

Free RX-OKTX-OK

Prohibited

Update Update Update

Updat e

Send SREQ, Receive SAPP

SREQ+SR EJ

SCAN

Update

SREQ+SR EJ SREQ+SR

EJ

Reserved

Receive SREQ, Send SAPP


DIRMA-BR

Dynamic hop-by-hop routing/scheduling

1. Put “forwarders” in a candidate pool

2. Candidates are sorted based on the combination of two metrics:

o M1:Distance to d

o M2: Available BW for this hop and next hop

3. Select the candidate with smallest metric as forwarder and reserve schedules

4. Choose the next candidate if fails

5. Fall back to MH path and reserve if all fails

Min-hop direction

Interference-aware direction

Interfered Area

C

BA

D


Performance Evaluation

Implement the GCP and IRMA algorithms in ns-2.28

A separate control radio and channel in GCP

Compare the performance

IRMA algorithms

Baseline approacheso DSDV+802.11o AODV+802.11

•Ns-2 Simulation Parameters


Simulation Results

40-node mesh topology

Varying number of source-destination pairs

Comparing IRMA algorithms with conventional layered approaches

Results show that our IRMA schemes can provide up to ~200% gains.

DIRMA-MH algorithm achieves results amount to 90% of CIRMA-MH

Both BR algorithms behave better than MH algorithms in most of the cases.

• CIRMA-BR vs. CIRMA-MH 22.4% more , DIRMA-BR vs. DIRMA-MH 2.37% more

The DIRMA-BR algorithm is not very good because per-hop selection is based upon volatile local information


Evaluation of the Control Overhead

IRMA approach reduce signaling overhead because per-flow control is much more efficient than per-packet control

Overhead Statistics

Baseline: RTS/CTS + routing overhead

IRMA: All control signaling in GCP

Simulation Topology

4x4 grid

10 traffic sessions with random start/end

Traffic duration: exponential distributed.

Results normalized by end-to-end throughput


Centralized Protocols vs. Distributed Protocols

CIRMA

Route and scheduling need to be disseminated when each traffic session begins/ends

Don't scale with increasing number of flows and size of network

DIRMA

Most overhead comes from system bootstrap, discovery and interference characterization

Negligible overhead for scheduling and path selection


Conclusion and Future Work

•Fundamental need for cross-layer integration and joint optimization for superior network performance in WMN.

• Joint Routing and Scheduling show up to 300% performance gain in numerical results

•We proposed IRMA for wireless mesh networks and discussed:

Flow-based Interference-free scheduling

Realistic system model

heuristic, promising online algorithms

Simulation results show that IRMA design improve end-to-end throughput significantly with modest signaling overhead.

•How much gains when channel assignment is also incorporated

•Guarantee Fairness & QoS.


Please visit http://www.winlab.rutgers.edu/~zhibinwu


http://www.winlab.rutgers.edu/~zhibinwu

Related Publications

1. Z. Wu, S. Ganu and D. Raychaudhuri, ''IRMA: Integrated routing and MAC scheduling in multihop wireless mesh networks'', in Proceedings of the Second IEEE Workshop on Wireless Mesh Networks, Reston VA, Sept 2006.

2. Z. Wu, S. Ganu, I. Seskar and D. Raychaudhuri, ''Experimental investigation of PHY layer rate control and frequency selection in 802.11-based ad-hoc networks'', in Proceedings of ACM SIGCOMM Workshops, August, 2005.

3. S. Zhao, Z. Wu, A. Acharya and D. Raychaudhuri, ''PARMA: A PHY/MAC aware routing metric for ad-hoc wireless networks with multi-rate radios'', in Proceedings of IEEE WoWMoM'05, June 2005.

4. Z. Wu, D. Raychaudhuri, ''D-LSMA: Distributed link scheduling multiple access protocol for QoS in ad-hoc networks'', in Proceedings of IEEE GLOBECOM '04, November 2004, pp 1670-1675

•26 | IRMA fro Wireless Mesh Networks| November 2007

Single-Path Routing vs. Multi-path Routing

Single Path Routing Multi-path Routing

Capacity/Throughput Less throughput bounds compare to multi-path routing

Load balancing over more routes, utilizing more capacity

Traffic Split No Yes. Arbitrary splitting, difficult for wireless implementation

Robust Resilient to link failures

Overhead More Route-discovery overhead, More soft states

Algorithm Dijkstra, Bellman-ford, OSPF (BGP)

Route-discovery by flooding

Packet Ordering Out-of-sequence problem

Compatibility Good. Bad•We prefer single path routing from system design perspective..

About interference models

A node cannot derive the distance of a “hidden node” in “interference neighborhood” because it cannot decode the packet and correlate this signal with the node identifier.

•Successful transmission

•1) dij ≤

Ri

•2) R’k ≤

dkj

•k

•dk

j

•dij

•R ’k

•R’i•R

i •i •j

•k

•Unsuccessful transmission

•1) dij ≤

Ri

•2) R’k ≥

dkj

•k•R ’k

•Ri•i •j•d

ij

•dk

j

•R’i

Conflict Graph

Coloring Conflict Graph

Connectivity Graph G Conflict Graph G’

1 2

3 4

1

3

2

4

1

2

4

3

Each edge in G is a vertex in G’

Two adjacent vertexes in G’ cannot have same color

IRMA-MH Example

Link bandwidth 1Mbps,

10 slots in each TDMA frame

3 flows: 15 14, 5 10,11 1

Each flow has offer load 0.2Mbps, demanding 2 slots per frame

Slot No AfterSchedulingflow 15-14for 1st slotdemand

Afterschedulingflow 5-10for 1st slotdemand

After Schedulingflow 11-1for 1st slotdemand

After Schedulingflow 15-4 for 2nd slot

(fail!)

1 15-3, 7-14 15-3, 7-14 15-3, 7-14 15-3, 7-14

2 3-4 3-4 3-4 3-4

3 4-5 4-5 4-5 4-5

4 5-7 5-7 5-7 5-7

5 5-6 5-6 5-6

6 6-9 6-9 6-9

7 9-10 9-10, 4-1 9-10, 4-1

8 11-9 11-9, 15-3

9 9-6 9-6

10 6-4 6-4

•8

•2

•3

•5•1

•6

•7

•9

•4

•10

•11

•12

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•14

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•G (V,E)

Scheduling results:

Each flow only obtains a 1-slot/per frame bandwidth (0.1M throughput)

Impossible to accommodate those flows with 0.2Mbps throughput.

Increase to 20slots/frame does not help, because each flow will require 4 slots/frame.

No slot to assign

edge 3-4

•30

LP Formulation of Integrated Routing and MAC Scheduling (2)

Find the analytical throughput bounds Min-hop routing + link SchedulingoThe path for each <s, d> is known as the min-hop path.Joint routing/schedulingoSingle path routing, but path is uncertain.oMixed integer programming problem

Observations and conclusions from previous and our LP analysisIt’s NP-hard to find all link conflict constraints in LP formulation.Possible optimal routing paths can be found to yield better throughput than min-hop pathsOptimal solution needs global knowledge

Our contribution: Offline Optimization + Online algorithms

Overview of Wireless Networking Technologies

Low-rate cellular networks vs. High-speed LAN/PAN.

Centralized Cellular Networks support global mobility, but with low link speed and complex architecture

Wi-Fi based technologies provide high-speed link access, but limited mobility support.

Inter-technology convergence:

oUMA and Femto Cell•Range

GSM(2G)

WiMAX

Wi-Fi

UMTS/CDMA2000

LTE/UMB

Global MobilityLocal Mobility

Femto Cell

MANET

100+ Mbps, low-power,

short range, minimal mobility

UMA

Bluetooth


High-Speed Wireless Mesh Network (1)

Scope of the HS-WMN cannot be large:

[Gupta’00] :Given n nodes randomly located in a unit disk, the uniform per node throughput capacity with interference-free protocols is

A small or mid-size network with less than 100 nodes.


High Speed Wireless Mesh Network (2)

Mobility cause significant throughput reduction

Even slight random movement cause route failure and packet loss.

Uncertainty of routing discovery disrupts traffic and reduce throughput

We focus on a multi-hop network with small number of nodes and minimal mobility. Each node is equipped with one or more short range, high-speed radios.

•34 | IRMA fro Wireless Mesh Networks December 2007

Application Scenarios for HS-WMN

Wireless links can be used to replace Ethernet cables, phone lines, USB/Firewire

Wireless connectivity among consumer electronics devices, PCs.

Multimedia-content sharing in home among HDTV, DVD Player, iPod, XBOX

Integrated voice, video and data services

•35 | IRMA fro Wireless Mesh Networks December 2007

Problem Definition & Current Approaches

Requirement: High Throughput Bulk data transfer over wireless mesh architecture.

Goal: Protocol and algorithm design to achieve maximal throughput for concurrent end to end multihop flows.

Problems:

What’s the achievable end-to-end capacity given a certain “small” number of nodes in the topology?

Is there a feasible design to approximate the capacity?

What’s the control overhead and how it scales with the traffic demands?

Conventional Approach: IEEE 802.11+ ad hoc routing

CSMA/CA is “bad” in multi-hop wireless networks.

Poor interaction between two independent distributed L3 and L2 protocols


Cross-Layer Routing/MAC

Optimizing the performance of individual layers is not like to work beyond a certain point [Barrett et al.’02].

A routing protocol needs to interact with the MAC layer in order to improve its performance. Adopting multiple performance metrics from layer-2 into routing protocols is an example.

However, interaction between MAC and routing layers is so close that merely exchanging parameters between them is not adequate.

Merging certain functions of MAC and routing protocols is a promising approach.

It is particularly meaningful for multi-radio or multi-channel routing, because the channel/radio selection in the MAC layer can help the path selection in the routing layer.


Interference-free TDMA Scheduling

Scheduling requires perfect interference awareness

to know exactly whose interference affect which node

Implication of R’>R: A node cannot discover a “hidden node”

Solutions come with overhead:

Obtain location information from GPS and exchange

Use a dedicate control radio to communicate in interference range

Deliver scheduling information to k-hop neighborhood (k>1).

Collision-free link scheduling not good as a per-packet mechanism.

•Unsuccessful transmission

kR’k

Rii •jdij

dkj

R’i

Protocol Model of Interference

ittingnot transm is such that k, nodeany )2

)1'kkj

iij

R d

Rd

≤

≤

•Transmission range: R

•Interference range: R’

•Conditions for a successful transmission:

•1) dij ≤

Ri

•2) R’k ≥

dkj


System Approach

Joint FDMA/TDMA/Routing Time/Frequency assignment

Traffic Map

Joint FDMA/TDMA/Routing Time/Frequency assignment

Traffic Map


Theoretical background for Joint Scheduling/Routing

Maximize end-to-end throughput : multi-commodity network flow problem (linear programming)

Interference-free scheduling: coloring problem (graph theory)

Finding maximal independent set in the conflict graph

Connectivity Graph G Conflict Graph G’

1 2

3 4

1

3

2

4

1

2

4

3

Each edge in G is a vertex in G’

Two adjacent vertexes in G’ cannot have same color


A Typical Simulation Topology


Challenges for Online Approach

Real-time characterization:

Information gathering beyond neighborhood.

Interference detection

o K-hop approximation

o A 2nd radio monitors as far as up to interference range

Run-time Optimization

LP optimization algorithms are NP-hard

Control overhead and robustness

Concise, timely and accurate signaling.

Solution: A dedicated control plane

Same radio with a dedicated BW slice in time/frequency

Another radio use a dedicated control channel


LP Formulation of Integrated Routing and MAC Scheduling

∑=

M

1i ifMaximize

10 ≤≤≤≤ qrfqr iii

LeeBWfefi

i ∈≤=∑ each for ),()(

•8

•2

•3

•5•1

•6

•7

•9

•4

•10

•11

•12

•13

•14

•15

•16

•17

•G (V,E)

•M concurrent flows from s to d

•L: link set selected as paths

•r: offer-load/demands for each flow

•Subject to:

•+

1) Flow conservation>< iii dsf ,for path thealong same keeps

Constraints for link conflict based on “conflict graph” in interference model

•3) Fairness tradeoff

•2) Link capacity

•s1

•d1

•s2 •d2

•s3

•d3


Integrated Routing & MAC Scheduling for Wireless …Integrated Routing & MAC Scheduling for Wireless Mesh Networks Zhibin Wu Dipankar Raychaudhuri WINLAB, ECE Dept. Rutgers University

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