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2014/10/28 Zhisheng Niu @ Tsinghua University 1

Collaborative and Opportunistic Scheduling

in Mobile Ad Hoc Networks

for Autonomous Multi-robotic Systems

Zhisheng NiuTsinghua National Laboratory for Information Science and Technology

Tsinghua University, Beijing100084

2014.10.28 @ University of Hamburg


Content

Autonomous Multi-robotic Systems

WLAN, WPAN, and Mobile Ad Hoc Networks

A Collaborative and Opportunistic Scheduling Scheme

for Mobile Ad Hoc Networks

Summary

2

Why Robots Communicate?

Robots make decisions based on their sensing without coordination, two robots could decide conflicting

actions based on their sensing

Robot Coordination using Communication if two robots see the ball, they could both decide to go to the

ball. Instead, by communicating what they sensed, they can coordinate their roles and actions

Other examples: 1) Pushing a large object with multiple robots; 2) Searching a room for an object


1. Both robots see the ball.

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2. Each robot communicates to the other its distance to the ball as seen by its own vision.

3. The robot closest to the ball becomes the Attacker.

4. The other robot becomes the Defender.

4

5. The Attacker approaches the ball.

6. The Defender stays in position.

7. The Attacker gets ready to kick the ball.

8. The Defender heads to a defensive position.

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How to Communicate?

Infrastructure-based (centralized, coordinated) Robots send sensed information to a coordinator or

controller

Coordinator/Controller fuses the information, makes decision, and assign actions to robots

Generally good performance, but not scalable and robust

Infrastructure-less (distributed, autonomous) A robot sends its sensed information and his/her role (and

also action?) that he/she wants to take to all their neighbors

The neighbors received the information, take their own roles and actions, and broadcast to their neighbors (?)

Autonomous and robust, but may not optimal in performance. Also, communication overhead may be large


1. One robot sees the ball.

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2. The robot seeing the ball communicatesactions to the other and assigns roles.

3. The robot that sees the ball is the Attacker.

4. The other robot is the Defender.

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5. The Attacker heads to the ball.

6. The Defender moves aside to clear the shot to the goal.

What’s the Problem with Communication?

What kind of communications are being used? Cellular?

WiFi?

Bluetooth?

ZigBee?

Ultra Wide Band?

What are the problems? Packet loss?

Out of connection?

Delay?

Battery life?

Any new requirements? Security?

Reliability?


8

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Two Types of Wireless Networks

channelWireless channel

BS/AP

A B

Infrastructure-based Network

(WLAN, WiMAX)

C D

Multi-hop Network(Ad hoc networks, mesh

networks, sensor networks)

Infrastructure-based Cellular Networks

2014.02.24 牛志升@清华大学 16

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Infrastructure-based Cellular Networks

2014.02.24 17牛志升@清华大学

2020 5G？(BDMA? Massive MIMO) All-IP, U-shape traffic 100-1000Mb/s

(FDMA)

(TDMA)

(CDMA)

(OFDMA, MIMO)

01011011

InternetAccessPoint

0101 1011

• 802.11b– Standard for 2.4GHz ISM band (80 MHz)– Direct sequence (DS) spread spectrum

• 802.11a– Standard for 5GHz NII band (300 MHz)– OFDM with time division– Similar to HiperLAN in Europe

• 802.11g– Standard in 2.4 GHz band with 54Mbps– OFDM

• 802.11n– Standard in 2.4 GHz or 5GHz band– OFDM + MIMO– Speeds up to 250 Mb/s (110 Mb/s

in practice) and about twice the range

Infrastructure-based WLAN

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Infrastructure-less WPAN

Bluetooth (initiated by Ericsson, Danish King’s nick name, IEEE 802.15.1)

Short range connection (10-100 m) in 2.4GNz ISM band

1 data (721 Kbps) and 3 voice (56 Kbps) channels

Bluetooth 2.0/3.0 for higher data rate, 4.0 for low-power

ZigBee (initiated by Honeywell, Bee’s Waggle Dance, IEEE802.15.4)

Low-Rate WPAN (20, 40, 250 Kbps), but very low power consumption and low cost over ISM bands

Mainly used for large-scale sensor networks

Ultra WideBand (UWB) (initiated by Motorola, Pulse Communication)

Impulse radio (no carrier): sends pulses of tens of picoseconds to nanoseconds (Low probability of detection high reliability/security)

Uses a lot of bandwidth (GHz) to achieve very high data rates (~100 Mbps), low delay, and low power

Low range, 10m or less, due to power restriction

Mainly used for high-speed comm and localization2014.02.24 19牛志升@清华大学

Xbee (ZigBee-based but extended, Licensed by DiGi)

Platform XBee XBee-PROPerformance

Power output1mW (+0 dBm) North American & International version

63 mW (+18 dBm) North American version 10 mW (+10 dBm) International version

Indoor/Urban range Up to 100 ft (30 m) Up to 300 ft (90 m)Outdoor/RF line-of-sight range Up to 300 ft (90 m) Up to 1 mile (1.6 km) RF LOSReceiver sensitivity -92 dBm -100 dBm (all variants)RF data rate 250 Kbps 250 KbpsOperating frequency 2.4 GHz 2.4 GHzInterface data rate Up to 115.2 Kbps Up to 115.2 Kbps

NetworkingSpread spectrum type DSSS (Direct Sequence Spread Spectrum)Supported network topologies Point-to-point, point-to-multipoint, & peer-to-peerError handling Retries & acknowledgementsFiltration options PAN ID, Channel, and 64-bit addressesChannel capacity 16 Channels 12 ChannelsAddressing 65,000 network addresses available for each channel

Power

Supply voltage2.8 - 3.4 VDCXBee Footprint Recommendation: 3.0 - 3.4 VDC

2.8 - 3.4 VDCXBee Footprint Recommendation: 3.0 - 3.4 VDC

Transmit current45 mA (@ 3.3 V) boost mode 35 mA (@ 3.3 V) normal mode

215 mA (@ 3.3 V)

Receive current 50 mA (@ 3.3 V) 55 mA (@ 3.3 V)Power-down sleep current <10 µA at 25° C <10 µA at 25° C

GeneralFrequency band 2.4000 - 2.4835 GHz

Physical PropertiesSize 0.960 in x 1.087 in (2.438 cm x 2.761 cm) 0.960 in x 1.297 in (2.438 cm x 3.294 cm)Weight 0.10 oz (3g)Antenna options U.FL, Reverse Polarity SMA (RPSMA), chip antenna or wired whip antennaOperating temperature -40° C to 85° C (industrial) 20

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Infrastructure-less Mobile Ad-Hoc Network

Peer-to-peer communications. No backbone infrastructure. Routing can be multihop and multipath

Network topology is dynamic (Extended concept of mobility: network mobility or moving routers)

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Mobile Ad Hoc Networks

Self-organized multihop multipath communications

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Wireless Mesh Networks

Multi-layer Wireless Communication for Large-Scale Mobile Ad Hoc Networks


MESH

Wireless Sensor Networks

Nodes powered by non-rechargeable batteries

Data flows to centralized location (sink)

Low per-node rates but up to 100,000 nodes.

Data highly correlated in time and space.

Nodes can cooperate in transmission, reception, compression, and signal processing.

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cluster cluster cluster

sinkHead

Head Head

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2007-06-21 Zhisheng Niu @ Tsinghua University 25

Distributed Coordination Function (Virtual carrier sensing)

Sender sends Ready-To-Send (RTS)

Receiver sends Clear-To-Send (CTS)

RTS and CTS reserves the area around sender and receiver for the duration of dialogue

Nodes that overhear RTS and CTS defer transmissions by setting Network Allocation Vector (NAV)

MAC Protocol for Contention/Collision Avoidance


802.11 Distributed Coordination Function

A

B

C

D

A B C D

Time

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A

B

C

D

A B C D

RTS

Time

RTS



A

B

C

D

A B C D

RTS

CTS

SIFS

NAV Time

CTS

15



A

B

C

D

A B C D

RTS

CTS

DATA

SIFS

NAV

NAV

Time

DATA

SIFS: Short Inter-Frame Space



A

B

C

D

A B C D

RTS

CTS

DATA

SIFS

ACK

NAV

NAV

Time

ACK

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A

B

C

D

A B C D

RTS

CTS

DATA

SIFS

ACK

NAV

NAV

DIFS

Time

Contention Window

DIFS: DCF Inter-Frame Space


802.11 Power Saving Mechanism

Time is divided into beacon intervals

All nodes wake up at the beginning of a beacon interval for a fixed duration of time (ATIM window)

Exchange ATIM (Ad-hoc Traffic Indication Message) during ATIM window

Nodes negotiate channels using ATIM messages Nodes that received ATIM message stay up during for the whole beacon

interval

Nodes that do not receive ATIM message may go into doze mode after ATIM window

Nodes switch to selected channels after ATIM window for the rest of the beacon interval

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A

B

C

Time

Beacon

ATIM Window

Beacon Interval



A

B

C

Time

Beacon

ATIM

ATIM Window

Beacon Interval

18



A

B

C

Time

Beacon

ATIM

ATIM-ACK

ATIM Window

Beacon Interval



A

B

C

Time

Beacon

ATIM

ATIM-ACK

ATIM-RES

ATIM Window

Beacon Interval

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A

B

C

Time

Beacon

ATIM

ATIM-ACK

DATAATIM-RES

Doze Mode

ATIM Window

Beacon Interval



A

B

C

Time

Beacon

ATIM

ATIM-ACK

DATA

ACK

ATIM-RES

Doze Mode

ATIM Window

Beacon Interval

20


Channel Negotiation (multi-channel case)

A

B

C

DTime

ATIM Window

Beacon Interval

Common Channel Selected Channel

Beacon


Channel Negotiation

A

B

C

D

ATIM

ATIM-ACK(1)

ATIM-RES(1)

Time

ATIM Window

Beacon Interval


Beacon

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Channel Negotiation

A

B

C

D

ATIM

ATIM-ACK(1)

ATIM-RES(1)

ATIM-ACK(2)

ATIM ATIM-RES(2)

Time

ATIM Window

Beacon Interval


Beacon


Channel Negotiation

A

B

C

D

ATIM

ATIM-ACK(1)

ATIM-RES(1)

ATIM-ACK(2)

ATIM ATIM-RES(2)

Time

ATIM Window

Beacon Interval


Beacon

RTS

CTS

RTS

CTS

DATA

ACK

ACK

DATA

Channel 1

Channel 1

Channel 2

Channel 2

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RTS/CTS solves Hidden/Expose Terminal Problems

A B CDATA

C does not hear A’s transmission

Hidden Terminal Problem


Hidden Terminal Problem

A B CDATA

C starts transmitting – collides at B

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Solution: Virtual Carrier Sensing

A B CRTS

A sends RTS

D

D overhears RTS and defers transmission



A B CCTS

B sends CTS

D

C overhears CTS and defers transmission

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A B CDATA

D

A sends DATA to B



A B CRTS

D

D overhears RTS and defers transmission

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Route Discovery and Establishment

• Automatic route discovery and establishmentA neighbor either broadcasts the RREQ to its neighbors or satisfies the RREQ by sending a RREP back to the source

Later copies of the same RREQ request are discarded

Node records the address of the sender of RREQ

Entries are discarded after a time-out period

Eventually, a RREQ arrives at a node that possesses the current route for the destination (Comparison of sequence numbers)

Node unicasts a route reply packet (RREP) back to the neighbor from which it received the RREQ. The RREP travels along the path established in the reverse path set-up

Each node along the RREP journey sets up a forward pointer, updates time-out entries, records the destination sequence number of requested destination

2014/10/29 49牛志升@清华大学

Example: AODV (Ad-hoc On-demand Distance Vector)

Routing Scheme

B

S

E

C G

F

A

H

D

Y

I

K

P

L

J

TZ

RREQ

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AODV: Example

B

S

E

C G

F

A

H

D

Y

I

K

P

L

J

TZ

Reverse Path

Setup2014/10/29 51牛志升@清华大学

AODV: Example

B

S

E

C G

F

A

H

D

Y

I

K

P

L

J

TZ

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AODV: Example

B

S

E

C G

F

A

H

D

Y

I

K

P

L

J

TZ

2014/10/29 53牛志升@清华大学

AODV: Example

B

S

E

C G

F

A

H

D

Y

I

K

P

L

J

TZ

RREP

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AODV: Example

B

S

E

C G

F

A

H

D

Y

I

K

P

L

J

TZ

Forward Path

Setup

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AODV (Example)

B

S

E

C G

F

A

H

D

Y

I

K

P

L

J

TZ

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AODV (Example)

B

S

E

C G

F

A

H

D

Y

I

K

P

L

J

TZ

2014/10/29 57牛志升@清华大学

AODV (Example)

B

S

E

C G

F

A

H

D

Y

I

K

P

L

J

TZ

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Routing Algorithms in MRMC Networks

In MRMC, the shortest path algorithm does not work well Different radios may have different characters Interference among radios is not considered in shortest path

Need to exploit channel diversity Selecting channel diverse routes

Interface switching cost has to be considered Switching interfaces incurs a delay A node may be on different routes, requiring switching

A

B

C

D

1 1

2 1

Route A-C-D is betterWhen possible, select routes where

different hops are on different channelsRoute A-B-D is better

A

B

C

D2 1

2 1

E3

When possible, select routes that do not require frequent switching

2014/10/28 Zhisheng Niu @ Tsinghua University

Opportunistic Scheduling

Multi-User Diversity In a multiuser system, channels

(timeslots/subcarriers/antennas) that are poor to one user may be the best for others

Multi-Link Diversity Scheduling the link that has the

instantaneously best channel condition would increase the system and link capacity.

Opportunistic Scheduling

f

f

f

f

f

f

2014/10/28 60Zhisheng Niu @ Tsinghua University

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Dynamics in Wireless Channels and Diversities

Wireless channel varies dramatically over time/frequency/space Interferences, Fading, Multipath, Doppler, …

Traditional view treats the channel uncertainty as obstacle and therefore try to avoid it e.g., interleave, AMC (adaptive modulation and coding)

Modern view treats the channel variation as opportunity and therefore try to exploit it Diversity: always choose the best frequency/time/antenna to transmit and leave

out the poor ones e.g., OFDM, MIMO

channel


Key Challenges for Exploiting MU Diversity in MANET

Absence of a central scheduler: Transmitter Cooperation!

Neighboring transmitters should jointly determine the “on-peak” flows

Transmitter should offer more transmission opportunities to the flow which has not achieved its QoS requirement

Neighboring transmitters should be coordinated to reserve the shared wireless bandwidth to reduce the potential collision to that flow

Absence of a dedicated channel for feedback A complement scheme needs to be designed, which has to avoid collisions

and to have an acceptable overhead


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The Existing Opportunistic Algorithms


Exploit Time Diversity only but not Multi-user Diversity

Auto Rate Fallback (ARF)

ARF protocol attempt to use higher transmission rates after consecutive transmission successes, and revert to lower rates after failures.

Receiver Based Auto Rate (RBAR)

RBAR using physical-layer analysis of the RTS message determines the rate by receiver.

Opportunistic Auto Rate (OAR) protocol

OAR [1] opportunistically send multiple back-to-back data packets whenever the channel quality is good.

[1] B. Sadeghi, V. Kanodia, A. Sabharwal, and E. Knightly. “Opportunistic Media Access for Multirate Ad Hoc Networks,” Proc. ACM MOBICOM’ 02,2002.

The Existing Opportunistic Algorithms


[3] J. Wang, H. Zhai, Y. Fang, J. M. Shea and D. Wu, "OSAR: Utilizing Multiuser Diversity in Wireless Ad Hoc Networks," IEEE Trans. on Mobile Computing, vol. 5, no. 12, pp. 1764-1779, Dec. 2006.

MAD: Media Access Diversity[2]

OSAR: Opportunistic packet-scheduling and auto-rate[3]

A sender broadcasts a probing multicast/group RTS packet, then its receivers measure the SINR and send back the result by CTS packets. The sender then selects the receiver with the best channel condition.

[2] Z. Ji, Y. Yang, J. Zhou, M. Takai, R. Bagrodia, “Exploiting medium access diversity in rate adaptive wireless LANs,”, in Proc. ACM MobiCom’04, pp. 345–359, Sept. 2004.

Exploiting multi-user diversity but not multi-link diversityNo cooperation among neighboring transmitters (local optimization only without QoS guarantee)

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If without cooperation,

If A chooses B, and then F chooses G by local scheduling, link A-B is corrupted by hidden terminal F in link F-G.

If a bandwidth requirement is assigned to the flow A-B, this link suffers a high collision probability induced by hidden terminal F.

Why Cooperative Scheduling?


Cooperative & Opportunistic Scheduling with QoS Constraints

Exploit time-diversity and multiuser diversity simultaneously, while providing QoS guarantee

Through cooperation, some transmissions are deferred to favor some other links which have not achieved their QoS requirements

2014/10/28

Our Solution: QoS-Aware COS

Zhisheng Niu @ Tsinghua University 6666

TIFS: Traffic-control Inter-Frame Space[1] Q. Zhang, Q. Chen, F. Yang, X. Shen, Z. Niu, "Cooperative and Opportunistic Transmission for IEEE 802.11-based Ad Hoc Networks,"IEEE Networks, vol.21, No.1, pp.14-20, 2007.[2] Q. Chen, Q. Zhang, Z. Niu, "QoS-aware Cooperative and Opportunistic Scheduling Exploiting Multi-user Diversity for Rate AdaptiveAd Hoc Networks," IEEE Trans. Vech. Tech., vol.57, no.2, pp.1113-1125, April 2008.[3] Q. Chen, Q. Zhang, Z. Niu, “A Graph Theory based Opportunistic Link Scheduling for Wireless Ad Hoc Networks”, IEEE Trans.Wireless Comm., Oct. 2009.

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Problem Formulation

Cooprative & Opportunistic Scheduling (COS) with QoS requirements

Selection policy Q(t)Data rate of ith link

Indicator Function IXContention Function c(i, j, t)

Bandwidth Requirement Gi

…(1)


Optimal Solution

Proposition 1: The optimal solution of opportunistic scheduling (1), if one exists, is of the following form.

in which Sm is an MIS, and λi’s are the KKT values.

Maximal Independent Set (MIS):= { S1, S2, S3, S4 } = { (F2), (F3), (F1,F4), (F1,F5) }

Conflict Graph


(i.e., the link set selected by the optimal scheduling should be a MIS)

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Here we focus on the minimum bandwidth constraints and the network throughput maximization,

in which

Therefore, the optimal criteria is: Credits

The KKT values can be calculated by stochastic approximation algorithm

Optimal Scheduling


An Example

Considering the four MIS Ω={{F1,F5},{F2},{F3},{F4}}

Suppose that the credits of the four MIS are 7, 6, 5 and 4

Then, the credits of flows F1 to F5 are {7, 6, 5, 4, 7} and the credits of the transmitter A and D are both 7. flow's credit is set to the largest credit of the MIS's those include this

flow

transmitter's credit is set to the largest credit of the flows originated by this transmitter.

Then a set of flows, in one MIS with the largest credit, in this example flow 1 and 5, are scheduled to transmit simultaneously.


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The Challenges of the Optimal Scheduling

The challenges of implementing the optimal scheduling in 802.11 based MANET

Exchanging parameters all over the network is impractical

Use 2-hop information exchanging & average data rates

Difficult to track the time-varying contention graph which is needed in the optimal scheduling

Use average Local Contention Graph (LCG)

To schedule a set of links in an ad hoc network in a deterministic pattern is not trivial

Insert an extra interval (TIFS) into consecutive data transmissions


An Heuristic Adaptive TIFS Setting

Adaptive TIFS Setting Algorithm The optimal TIFS depends on

1) move pattern of the nodes2) number of the neighboring transmitters,3) contention graph,4) QoS requirements of each links.

An adaptive scheme:


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Maximal Weighted Independent Set (MWIS) problem

: an undirected graph: the weight of the vertex v: the sum of the weights of the vertices in X: the set of vertices adjacent to vertex v

MWIS: NP Hard!

vertex vedge

Vertex Links

Edges Contention Relationship

Weight or

A Distributive Approach to the Optimal Solution


12

3

4

Weight

: 5

3+21 = 5

: 2.33

: 1.25

: 4

: Degree

Heuristic Algorithm:(1) select a minimal weighted degree vertex as a vertex in the weighted

independent set Sm(2) delete the vertex and all of its neighbors from the graph(3) repeat this process for the remaining subgraph until the graph becomes

empty.

Weighted Degree (WD):

Exchange weight and WD among neighboring links

A Distributed Heuristic Scheduling


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1. Probing the channel during RTS-CTS exchange2. Update the degree table by

1) probing process2) overhearing the CTS and DATA packets

3. Set the TIFS accordingly

Heuristic Scheduling

(Priority based Transmission)


Group RTS

Heuristic Scheduling: An Example

Cooperative & Opportunistic Scheduling (COS)


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CTS replied &Parameter Exchanging(channel conditions & KKT multipliers)

D replies CTS.

E replies CTS.

C replies CTS.

Packet Scheduling

DATA transmission

ACK repliedNode A reset its TIFS.

Finally, we get two links those can transmit simultaneously!

Heuristic Scheduling: An Example

Cooprative & Opportunistic Scheduling (COS)


Key point 1: How is the overhead?

LN (4bits): No. of Links (Entities) LN<=10LI (8bits): Link IdentifierDR (4bits): Data rate supported, 16 levelsDE (12bits): Weighted Degree of a link

Degree table



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Key point 2: how to set the TIFS?The optimal length of TIFS =

The expect time that the a sender will be scheduled from now.

Single Link Markov Chain:

Multi-Link Markov Chain:

N-Dimension Markov Process，N = the number of links.



Key point 2: how to set the TIFS?The optimal length of TIFS =

The expect time that the a sender will be scheduled from now.

Optimal TIFS:


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Key point 2: how to set the TIFS?An example of the optimal length of TIFS of the first link

T0=10ms, v = 1m/s



Key point 3: what’s the performance bound?

While the average performance of the rate adaptive 802.11 MAC is


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No QoS req. G2=G3=1.5Mbps G2=G3=2.0Mbps

COS: Cooperative & Opportunistic Scheduling

OSAR: opportunistic w/o cooperation

OAR: standard multi-rate 802.11b

Simulation Results

2014/10/28

Grid Topology with hard QoS

Simulation Results

Zhisheng Niu @ Tsinghua University




84

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Random Scenarios

Simulation Results




Conclusions

Proposed an interference-dependent multiuser diversity

model for MANET while considering the QoS requirements

of each flow

Provided an optimal criterion to find the global optimal set

of simultaneously transmitting flows, together with

a heuristic scheduling algorithm

Designed an IEEE 802.11-based QoS-aware distributed

cooperative and opportunistic scheduling (COS) scheme,

which obtains higher network throughput and better QoS

support than the existing schemes with limited local

information.


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Prof. Zhisheng Niu

Room 3-327, FIT Building

School of Information Science and Technology

Tsinghua University, Beijing 10084, China

Email: [email protected]

Tel: 86-10-62781423; Fax: 86-10-62773634

Thank You and Future Contact