Roee Diamant, Prof. Lutz Lampe

Robust Spatial Reuse Scheduling in Underwater Acoustic Communication Networks

Outline

Very quick introduction on underwater communication

Graph coloring and the broadcast scheduling problem

Robust spatial reuse scheduling

Some simulation results

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Motivations Applications [1]: Ocean exploration Remote data retrieval (warning systems, pollution control) Military underwater surveillance Offshore underwater oil exploration

High traffic broadcast communications networks are required

Applications

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Motivations Applications [1]: Ocean exploration Remote data retrieval (warning systems, pollution control) Military underwater surveillance Offshore underwater oil exploration

Cables are heavy, deployment is expensive.

Wireless communication [2]: Radio (30Hz-300Hz) Optical (short distances, pointing precision)

UWAC: Underwater Acoustic Communications

High traffic broadcast communications networks are required

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I wish…

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Challenges of UWAC [2]

Sea trial

Fast time-varying frequency-selective channel

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Challenges of UWAC [2]

Half-duplex communications (transducers limitations)

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Challenges of UWAC [3,4]

Character RF UWAC Effect

Propagation delay T 2·105.T

ThroughputTransmission

rate ~109 bps ~102 bps

Error probabilities ~10-7 ~10-4 Reliability

Frequency ~GHz ~KHz SNR

Outline

Very quick into. on underwater communication

Graph coloring and the broadcast scheduling problem

Robust spatial reuse scheduling

Some simulation results

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System Model High traffic broadcast communication (e.g. navigation)

primary conflicts:

The network’s connectivity matrix is shared.

Changes in the network are slow

Find time-slot assignment which is robust to topology uncertainties

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Coloring the network Topology-based broadcast scheduling problem (T-BSP) [6]: For minimal time-frame duration, maximize channel utilization

T-BSP transforms into graph-coloring [5] Graph representation:

Node = Vertex; Link = Edge; Time-slot = Color

Minimize number of colors (adjacent vertices gets different colors)

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Spatial reuse Topology based assignment. Examples:

Each node gets a unique color

Graph colored with only two colors

Less colors = better availability.

Spatial reuse: performance increase the more sparse the network is

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Topology Uncertainties Different time frame yields different schedule:

Our approach: combining topology-information with a-priori “skeleton” topology-transparent schedule, shared by all nodes.

Time slot

Tx nodes

1 1

2 2,3,43

2 41

Time slot

Tx nodes

1 1

2 2,4

3 3,4

3

2 41

total networkfailure!

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Flow in topology-transparent schedules Vertex with higher degree (often bottleneck) gets fewer colors:

Additional problem – fairness in resource assignment

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2 41

Time slot Tx nodes

1 1

2 2,3,4

3 3,2,4

4 4,2,3

)TDMA skeleton(

Flow constraints are needed

Outline

Very quick into. on underwater communication

Graph coloring and the broadcast scheduling problem

Robust spatial reuse scheduling

Some simulation results

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Offline: Rearrange the skeleton matrix . For each column and a designated “slot-node” , . Online (Given the network topology): Remove conflicts Set for each node that is a one-hop neighbor of

Online: Maximize channel utilization (for each column ) Find all independent sets that include and a maximum

number of pre-assigned nodes in the th column of .

j 1, jrj

S

m

j S

0, mjS jr

j

:S

:skelI :A

Robust Broadcast Scheduling Problem (R-BSP)

jr

jr

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Problem Formulation Channel utilization maximization problem (CUMP)- RBSP:

Solution: For each column of the skeleton schedule, choose the independent set with the maximal cardinality.

a

cAa

aIT

:s.t

1max skel

a

j

skel

1skel

skelskel1

skel1

skelskel

aa

IIIIM

skelaUsed to impose minimumFlow in the network

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Last remarks

While the BPS involves solving two integer linear programming,

the RBSP does not require usage of optimization techniques.

We formulated the RBSP also for differential fairness, in which the variance of the node time-slot assignments is minimized.

The choice of the skeleton matrix affects the performance. In the paper we give guidelines for choosing the skeleton matrix. Next, we show results for TDMA skeleton schedule and topology-transparent schedule from [7].

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Outline

Very quick into. on underwater communication

Spatial reuse using graph coloring

Robust spatial reuse scheduling

Some simulation results

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Throughput

Fixed topology Time-varying topology

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Transmission Delay

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SummaryTopology-based BSP is not robust to topology-uncertainties,

and topology-transparent schedules do not fully utilize the channelProblem:

Our Solution: Combine T-BSP with topology-transparent skeleton schedule

Performance: Robustness to topology-uncertainties and higher throughput Is achieved at the cost of scheduling delay

Roee Diamant, Lutz Lampe. “Robust Spatial Reuse Scheduling in UnderwaterAcoustic Communication Networks,” submitted for publication in the IEEETransactions on Wireless Communications journal, Feb. 2011.

Roee Diamant, Lutz Lampe “Underwater Localization with Time-Synchronization and Propagation Speed Uncertainties,” IEEE vehiculartechnology conference (VTC), Sep. 2011, San Francisco, USA.

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Further work In this work we utilized the (possible) sparsity of the network

topology to schedule broadcast transmissions.

centralized solution that fits only small networks

Further work includes a distributed handshake scheduling protocol for unicast communications, that applies spatial and time reuse.

Additional research: Underwater acoustic localization and tracking, LOS and NLOS

classification

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Reference

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[1] J. Partan, J. Kurose, and B. Levine, “A Survey of Practical Issues in Underwater Networks,” in International Conference on Mobile Computing and Networking (MobiCom), Los Angeles, CA, USA, Sep. 2006

[2] W. Burdic, Underwater Acoustic System Analysis. Los Altos, CA, USA: Peninsula Publishing, 2002

[3] N. Chirdchoo, W. Soh, and K. C. Chua, “Aloha-based MAC Protocols with Collision Avoidance for Underwater Acoust Networks,” in The IEEE Conference on Computer Communications (Infocom), Anchorage, Alaska, USA, May 2007

[4] M. Molins and M. Stojanovic, “Slotted Fama: a MAC Protocol for Underwater Acoustic Networks,” in IEEE Oceans2006, Singapore, May 2006

[5] M. Molloy and B. Reed, Graph Coloring and the Probabilistic Method. Springer-Verlag Berlin Heidelberg, 2002.

[6] S. Menon, “A Sequential Approach for Optimal Broadcast Scheduling in Packet Radio Networks,” vol. 57, no. 3, pp. 764–770, Mar. 2009

[7] Z. Cai, M. Lu, and C. Georghiades, “Topology-Transparent Time Division Multiple Access Broadcast Scheduling in Multihop Packet Radio Networks,” vol. 52, no. 4, pp. 970–984, Jul. 2003

Thank you

Questions?