Survey on Signaling Techniques for
Cognitive Networks
Dzmitry Kliazovich
University of Luxembourg, Luxembourg
Fabrizio Granelli
University of Trento, Italy
Nelson da Fonseca
University of Campinas, Brazil
Cognitive Networks
Cognitive networks can plan, decide, and act based
on network conditions, learn to adapt future
decision, all for achieving end-to-end goals
• From technological perspective
– Evolution towards unified QoS-aware environment
• From business perspective
– Profit on self-management and common heterogeneous
platforms
June 10, 2011
Dzmitry Kliazovich ([email protected])
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Cognitive Networks
• Cognitive networks
• Modular design
Application
Transport
Network
Datalink
Physical
There is a clear need for new signaling
techniques and design approaches.
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Signaling Techniques
• Node-level signaling
– Information sharing between different layers of
the protocol stack to achieve node-centric goals
• Network-level signaling
– Information sharing between network nodes to
achieve end-to-end goals
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Dzmitry Kliazovich ([email protected])
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Signaling Techniques: Intra-Node
• Interlayer signaling pipe
• Direction: Layer-to-layer along the packet flow
• Association: Signaling is associated with packets
• Carriers: Packet headers or kernel packet structures
Q. Wang and M. A. Abu-Rgheff, “Cross-layer signaling for nextgeneration wireless systems,” IEEE Wireless
Communications and Networking (WCNC), pp. 1084 – 1089, 2003.
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Signaling Techniques: Intra-Node
• Direct interlayer communication
• Direction: Bidirectional between any layers
• Association: signaling is not associated with data flow
• Carriers: ICMP packets or kernel call-back functions
Q. Wang and M. A. Abu-Rgheff, “Cross-layer signaling for nextgeneration wireless systems,” IEEE Wireless
Communications and Networking (WCNC), pp. 1084 – 1089, 2003.
June 10, 2011
Dzmitry Kliazovich ([email protected])
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Signaling Techniques: Intra-Node
• Central cognitive plane
Transport
Network
Datalink
Signaling plane
Application
Physical
• Direction: Any-to-any
• Association: maintained only if explicitly mentioned
• Carriers: kernel functions
V. T. Raisinghani and S. Iyer, “Cross Layer Feedback Architecture for Mobile Device Protocol Stacks,” IEEE
Communications Magazine, vol. 44, no. 1, pp. 85 – 92, 2006
June 10, 2011
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Signaling Techniques: Network Level
• Packet headers
• Direction: Along with a packet flow
• Association: signaling information is associated with data
• Carriers: packet headers
V. T. Raisinghani and S. Iyer, “Cross Layer Feedback Architecture for Mobile Device Protocol Stacks,” IEEE
Communications Magazine, vol. 44, no. 1, pp. 85 – 92, 2006
June 10, 2011
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Signaling Techniques: Network Level
• ICMP messages
• Direction: Anywhere in the network
• Association: not maintained
• Carriers: ICMP packets
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Signaling Techniques: Network Level
• Explicit notification schemes
– Congestion (ECN), loss (ELN), bad state (EBSN)
• Direction: Signaling loop through the receiver
• Association: signaling information associated with data flow
• Carriers: packet headers or ICMP messages
June 10, 2011
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Signaling Techniques: Network Level
• Wireless channel information
• Direction: Base station broadcasts to entire cell
• Association: Not maintained
• Carriers: Broadcast out-of-band channel
B.-J. Kim, “A network service providing wireless channel information for adaptive mobile applications: I:
Proposal,” IEEE International Conference on Communications (ICC), pp. 1345 – 1351, 2001.
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Common Cognitive Node Architecture
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Signaling Techniques: Comparison
Metrics
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Signaling method
Scope
Type of signaling
Signaling latency
Communication overhead
In-band/Out-of-band
Direction of signaling
Packet association
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Signaling Techniques: Comparison
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Conclusions
• Signaling is a key enabler for cognitive network
implementations using existing protocol stacks
• Proper signaling architectures are yet to be
designed
• Upcoming solutions are envisioned to adapt a
combination of intra-node and network-level
signaling
June 10, 2011
Dzmitry Kliazovich ([email protected])
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Thank you!
Contact information of the authors:
Dzmitry Kliazovich
University of Luxembourg
[email protected]
Fabrizio Granelli
Nelson L. S. da Fonseca
University of Trento, Italy
[email protected]
State University of Campinas, Brazil
[email protected]