CCNxCon2012: Session 2: A Content-Centric Approach for Requesting and Disseminating Monitoring Information in Wireless Mesh Networks

A Content-Centric Approach
for Requesting and Disseminating
Monitoring Information !in WMN

Julien Boite – CCNxCon 2012 – 12/09/2012

2 / Outline

Context
!  Wireless Mesh Networks
!  Adaptive Flow-based Gateway Selection Objective

Measurement Approaches
!  End-to-end Measurements Scalability Issue
!  Proposed Hop-by-Hop Measurements Approach

A Use Case For Content-Centric Networking
!  Transposition to the CCN world
DSC/DT/CEA/TAI – 9/28/12

Conclusion and Future Work

3 / Context

Wireless Mesh Networks
!  Nowadays deployed as access networks
"  Rural dead zones, urban zones, campus-wide
"  Commercial deployments use WiFi / WiMax [1][2]

!  Provide users with a wide range of communication services
"  Heterogeneous quality constraints

!  Gateways and backhaul links play a key role
"  Most of traffic goes to the Internet [3]
"  Multiple GWs spread over the network !"& !"% !"#$%$&&

!  Different backhaul technologies
"  ADSL, Ethernet, wireless, HF, satellite
"  Heterogeneous and dynamic performances !"$ !"#$%&'%
!"#

4 / Context

Adaptive Flow-based Gateway Selection Objective
!  How to ensure that QoS-constrained flows always benefit from the best
quality available?
"  Fluctuating performances inside the Wireless Mesh Network
"  Time-varying capabilities of gateways and backhaul networks
"  Diversity of applications and flows’ constraints
!"#$%$&&

!  Limitations of ad hoc routing protocols [4] !"& !"%

"  Specific metrics have been proposed (ETX, ETT, etc.) [5]
#  Allow taking into account links quality, load,
performances inside the WMN
"  But still a unique metric to choose a default
gateway on each mesh router
!"$ !"#$%&'%
!"#

!  Limitations of load balancing schemes [6-9]
$ Right choices
"  Focus on avoiding congestion or resource usage optimization for QoS ??
"  Does not consider the QoS requirements of flows
"  Dos not consider heterogeneous and dynamic performance of backhaul links

5 / Context

Adaptive Flow-based Gateway Selection Objective
!  Objective
"  Dynamically map the requirements of
QoS-constrained flows onto the gateway and
backhaul network that best deals with it
"  Configure forwarding accordingly,
at the flow level of granularity

!  Software entities embedded on mesh routers
"  Form an overlay, communicate one with another
"  Interact with local node (gather info, enforce config)
#  Trigger E2E measurements through each GW Decide
#  Apply forwarding decisions
Execute

Monitor
"  Run algorithms for intelligent reactive decision making
#  Performance comparison with regard to flows’ constrains
Network Element
"  Existing framework for implementation [10]

6 / Measurement Approaches

Decide

Monitor Execute

Network Element

!  How to efficiently monitor end-to-end performances to feed the decision
making process?


End-to-end Measurements Scalability Issue
!  Monitoring performances offered by gateways and their backhaul network
"  Passive probing $ considered, but not sufficient
"  Active probing generates overhead $ scalability of end-to-end measurements?
"  Model for computing the overhead (nb packets) in grid topologies
#  Dng = nb hops from mesh router n to GW g
#  Mp = nb probe packets ; N = nb nodes ; G = nb GWs
25000
Overhead inside the WMN
Overhead outside the WMN
Total overhead
'
20000

( !"#$%$&&
Overhead (nb packets)

15000
!"& !"%

10000

5000

!"$ !"#$%&'%
!"#
0
0 10 20 30 40 50 60 70 80 90 100
Nb nodes


Proposed Hop-by-Hop Measurements Approach
!  To reduce the overhead generated to monitor performances offered
by gateways and their backhaul network
"  Hop-by-hop probing mechanism + Control protocol and memory on nodes

R1

Probe Control message Memory
Wireless link Backhaul link


"  Probing mechanism + Control protocol and memory

R1




R1




R2
R1



!  Results compared to E2E measurements
"  Potential for reducing overhead inside and outside the WMN
Pj,n = probability that node at distance j from requesting
"  Model for computing the overhead +
node n provides the result without generating more probes
Ms = nb signaling packets
9000
E2E strategy inside WMN
E2E strategy outside WMN
8000 E2E strategy total overhead
Hop-by-Hop strategy inside WMN
Hop-by-Hop strategy outside WMN '
7000
Hop-by-Hop strategy total overhead

6000 ( !"#$%$&&

5000 !"& !"%

4000

3000

2000

1000 !"$ !"#$%&'%
!"#

0
0 10 20 30 40 50 60 70 80 90 100
Nb nodes

17 / A Use Case for Content-Centric Networking

Transposition to the CCN world
!  Monitoring results $ content
"  Naming (for hierarchical prefix-based routing):
/domain.net/measurement/GW_ID/requestor/target

!  Gateways $ content repository
"  Content produced if not available

!  Requests / Responses $ Interest packets / Data packets
"  Interest packets sent to the IP
next hops towards gateways

!  Memory $ content store

"  Dealing with measurements validity: FreshnessSeconds1

!  What about measurements and results aggregation ?

1http://www.ccnx.org/releases/latest/doc/technical/Staleness.html

18 / A Use Case for Content-Centric Networking

Transposition to the CCN world

!  Face mapped to an application
"  Forward unserved Interest packets to this face
$ Entry in the PIT for content name CN1 with incoming Face
"  Trigger a measurement up to the IP next hop towards a gateway
"  Send a new Interest packet to the next hop towards the gateway (specific Face)
$ New entry in the PIT with the application’s Face, content name must different than CN1
"  This PIT entry is consumed when receiving the Data packet, forwarded to the application
"  Aggregate measurement results
"  Generate a new Data packet with the originally requested content name CN1
$ The first entry added in the PIT is consumed and the Data packets is forwarded back towards the
requestor

!  Manipulating FIB entries is necessary to achieve this routing behaviour

19 / Conclusion and Future Work

Conclusion
!  Hop-by-Hop Measurement Approach
"  Great potential for reducing overhead both inside and outside a WMN
"  The more mesh routers request for identical measurements and the more frequent these
requests, the lowest the overhead
"  Probing mechanisms + control protocol for requesting and dissimenating measurment results
!  Could be implemented using CCN mechanisms
"  Interception of messages by an application to perform measurements and aggregate results

Future Work
!  CCN implementation
!  Study the overhead in more realistic scenarios

"  Average distance to obtain a result ?
"  Impact of timers duration ?

20 / Questions ?

Thank you!
Contact: julien.boite@thalesgroup.com

Paper
Q2SWinet 2012 – “Scaling End-to-end Measurements in Heterogeneous
Wireless Mesh Networks”

Acknowledgments
Vania Conan Thales Communications & Security

Gérard Nguengang Thales Communications & Security
Mathieu Bouet Thales Communications & Security
Alain Ploix Université de Technologie de Troyes
Dominique Gaïti Université de Technologie de Troyes

21 / References

[1] Meraki Inc. (2011). [Online]. Available: http://meraki.com
[2] Ozone. (2010). [Online]. Available: http://www.ozone.net
[3] J. Jun and M.L. Sichitiu, “The nominal capacity of Wireless Mesh Networks”, Wireless Communications, IEEE, vol.
10, no. 5, pp. 8-14, 2003
[4] M. Abolhasan, T. Wysocki and E. Dutkiewicz, “A review of routing protocols for mobile ad hoc networks”, Ad Hoc
Networks, vol. 2, no. 1, pp.1-22, 2004
[5] M. Campista, P. Esposito, I. Moraes, L. Costa, O. Duarte, D. Passos, C. de Albuquerque, D. Saade and M. Rubinstein,
“Routing metrics and protocols for wireless mesh networks”, Network, IEEE, vol. 22, no. 1, pp. 6–12, 2008
[6] D. Nandiraju, L. Santhanam, N. Nandiraju and D.P. Agrawal, “Achieving load balancing in wireless mesh networks
through multiple gateways”, in Proc. of 2006 IEEE MASS, 2006, pp. 807-812
[7] Y. Bejerano, S.-J. Han and A. Kumar, “Efficient load-balancing routing for wireless mesh networks”, Computer
Networks, vol. 51, no. 10, pp. 2450–2466, 2007
[8] J. Baliosian, J. Visca, E. Grampín, L. Vidal and M. Giachino, “A rule-based distributed system for self-optimization
of constrained devices”, in Proc. of 2009 IFIP/IEEE Int. Symposium on Integrated Network Management (IM), 2009, pp.
41–48
[9] E. Ancillotti, R. Bruno and M. Conti, “Load-balanced routing and gateway selection in wireless mesh networks:
Design, implementation and experimentation”, in Proc. of 2010 IEEE Int. Symposium on WoWMoM, 2010, pp. 1–7
[10] J. Boite, G. Nguengang, M. Israël, V. Conan, “CONEMAF: A modular multi agent framework for autonomic network
management”, in Proc. of the Int. Conference on Agents and Artificial Intelligence (ICAART), 2010, vol. 2, pp. 224–231

[11] Networking Named Content, 2009, V. Jacobson, D.K. Smetters, J.D. Thornton, M.F. Plass, N.H. Briggs and R.L.
Braynard, in Proceedings of the 5th international conference on Emerging networking experiments and technologies,
pp. 1-12
[12] Project CCNx™. http://www.ccnx.org, Sep. 2009


!  Monitoring performances offered by gateways and their backhaul network
"  Hop-by-hop strategy properties
#  The more mesh routers request for identical measurements, the lowest overhead
#  If all nodes request for the same measurement (metric/dest) before timers expire, induced
overhead is the same for all topologies
#  If not all nodes request for the same measurement, induced overhead is topology-dependent

N 3 2 1
160 n=20
... GW GW
n=18
140
Linear topology
1
120
Star topology

100 N 3 2 1
... GW GW
80
2 3

Linear topology
60
1

40 Star topology

20 ...
Linear topology for each n in [1;20]
n=1 Dense topology for each n in [1;20]
0
2 3 N
0 2 4 6 8 10 12 14 16 18 20
Nb nodes performing a measurement (k)

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CCNxCon2012: Session 2: A Content-Centric Approach for Requesting and Disseminating Monitoring Information in Wireless Mesh Networks