roee diamant, prof. lutz lampe robust spatial reuse scheduling in underwater acoustic communication...
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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
11
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?