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Connectivity management for eneRgy
Optimised Wireless Dense networks
Outline
 Facts
 Motivation
 Main objectives and measures of success
 Implementation
 Main contributions of partners
 Concrete project results
2
Facts
 Title: Connectivity management for enerRgy
Optimised Wireless Dense networks (CROWD)
 Call identifier: FP7-ICT-2011-8
 Grant number: 318115
 Start: 1/1/13
 End: 30/6/15 (duration 30 months)
 Total cost: 4,460 k€
 Total funding: 2,978 k€
 Total effort: 443 PM
3
Motivation
 Number of wireless users increasing rapidly
 Load doubles every year
 Current demand is barely supported by existing infrastructure
 The solution necessarily entails the deployment of more
points of access
 Higher density of points of access
 Different wireless technologies (heterogeneous deployment)
 Current available solutions to handle density are not
sufficient
 Most existing solutions take local PHY restricted view
 Higher layer mechanisms are required for optimal operation
 Wireless dense networking can potentially lead to
wireless chaos and huge energy waste
4
Motivation
 To avoid the implosion of wireless capacity due to
increased density we need:
 New mechanisms for wireless devices coordination and
cooperation
 Higher layer algorithms to control and configure network
behavior
5
Main objectives
 Density-proportional capacity
 Throughput scales (almost) linearly with cell density
 Traffic-proportional energy consumption
 Power consumption reduced by up to ~70%
 Mobile user’s QoE
 Significantly lower handover blocking probability and end-to-end delay
variation experienced by mobile users (compared to a scenario without
inter-cell and inter-technology mechanisms)
 Significant reduction of the backhaul load (compared to a scenario with
static backhaul configuration)
 Validation and demonstration
 Deployment and successful operation of a test-bed composed of several
LTE and WLAN stations together within a dense deployment of base
stations and access points
 Dissemination and exploitation
 High-quality publications in peer-reviewed journal and conferences
 Contribution to standardisation
6
WPs: Structure
WP6–ProjectManagement
T6.1ProjectManagement
WP1 – Architecture
T1.1 Architecture
T1.2 Economical Analysis
T1.3 Dissemination and Standardisation
WP2 – Enhanced Wireless Mechanisms
T2.1 Coordinated technologies enhancements
T2.2 Distributed technologies enhancements
T2.3 Opportunistic cooperation of coordinated and distributed technologies
WP3 – Dynamic radio and backhaul configuration
T3.1 Topology discovery and monitoring
T3.2 Global control for dynamic mechanisms
T3.3 Case studies of different configuration algorithms
T3.4 Dynamic backhaul reconfiguration
WP4 – Connectivity Management
T4.1 Access selection
T4.2 Enhanced traffic management in dense wireless networks
T4.3 Session continuity and distributed anchoring
WP5–Integrationanddemonstration
T5.1Integrationandtest-bedsetup
T5.2Experimentalevaluation
T5.3Demonstration
7
WPs: Scope and time scale
Timescale
Short Medium Long
Data flow
Control &
configuration
Enhanced
Wireless
Mechanisms
(WP2)
Mobility
Mechanisms
(WP4)
GlobalOptimisation(WP3)
Control interface
8
Partner roles
Type Partner Main contribution
IND
Intecs (it) - Coordinator MAC layer improvement LTE
Alcatel-Lucent (fr) System analysis and architecture
Orange (fr) Connectivity management (heterogeneous
access selection)
SME Signalion (de) Test bed setup, and operation
RES
Institute IMDEA Networks (es) MAC layer improvement IEEE 802.11
UC3M (es) Connectivity management (session
continuity)
University of Paderborn (de) Dynamic backhaul configuration
mechanisms
10
Concrete project results
1. New solutions for connectivity management
benefiting (rather than suffering) high density in
deployments.
2. Novel heuristic approximation algorithms exploiting
regional-level information for energy efficient
operation.
3. Enhancements at MAC layer for IEEE 802.11 and
LTE that use density “as a resource” and exploit it
through intra- and inter-technology coordination.
4. Dynamic backhaul reconfiguration strategies that
achieve such a consumption that is near
proportional to traffic demands.
5. An integrated testbed suitable to validate all the
other project results under realistic conditions.11
End of Presentation
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Presentation short 2012

  • 1. Connectivity management for eneRgy Optimised Wireless Dense networks
  • 2. Outline  Facts  Motivation  Main objectives and measures of success  Implementation  Main contributions of partners  Concrete project results 2
  • 3. Facts  Title: Connectivity management for enerRgy Optimised Wireless Dense networks (CROWD)  Call identifier: FP7-ICT-2011-8  Grant number: 318115  Start: 1/1/13  End: 30/6/15 (duration 30 months)  Total cost: 4,460 k€  Total funding: 2,978 k€  Total effort: 443 PM 3
  • 4. Motivation  Number of wireless users increasing rapidly  Load doubles every year  Current demand is barely supported by existing infrastructure  The solution necessarily entails the deployment of more points of access  Higher density of points of access  Different wireless technologies (heterogeneous deployment)  Current available solutions to handle density are not sufficient  Most existing solutions take local PHY restricted view  Higher layer mechanisms are required for optimal operation  Wireless dense networking can potentially lead to wireless chaos and huge energy waste 4
  • 5. Motivation  To avoid the implosion of wireless capacity due to increased density we need:  New mechanisms for wireless devices coordination and cooperation  Higher layer algorithms to control and configure network behavior 5
  • 6. Main objectives  Density-proportional capacity  Throughput scales (almost) linearly with cell density  Traffic-proportional energy consumption  Power consumption reduced by up to ~70%  Mobile user’s QoE  Significantly lower handover blocking probability and end-to-end delay variation experienced by mobile users (compared to a scenario without inter-cell and inter-technology mechanisms)  Significant reduction of the backhaul load (compared to a scenario with static backhaul configuration)  Validation and demonstration  Deployment and successful operation of a test-bed composed of several LTE and WLAN stations together within a dense deployment of base stations and access points  Dissemination and exploitation  High-quality publications in peer-reviewed journal and conferences  Contribution to standardisation 6
  • 7. WPs: Structure WP6–ProjectManagement T6.1ProjectManagement WP1 – Architecture T1.1 Architecture T1.2 Economical Analysis T1.3 Dissemination and Standardisation WP2 – Enhanced Wireless Mechanisms T2.1 Coordinated technologies enhancements T2.2 Distributed technologies enhancements T2.3 Opportunistic cooperation of coordinated and distributed technologies WP3 – Dynamic radio and backhaul configuration T3.1 Topology discovery and monitoring T3.2 Global control for dynamic mechanisms T3.3 Case studies of different configuration algorithms T3.4 Dynamic backhaul reconfiguration WP4 – Connectivity Management T4.1 Access selection T4.2 Enhanced traffic management in dense wireless networks T4.3 Session continuity and distributed anchoring WP5–Integrationanddemonstration T5.1Integrationandtest-bedsetup T5.2Experimentalevaluation T5.3Demonstration 7
  • 8. WPs: Scope and time scale Timescale Short Medium Long Data flow Control & configuration Enhanced Wireless Mechanisms (WP2) Mobility Mechanisms (WP4) GlobalOptimisation(WP3) Control interface 8
  • 9. Partner roles Type Partner Main contribution IND Intecs (it) - Coordinator MAC layer improvement LTE Alcatel-Lucent (fr) System analysis and architecture Orange (fr) Connectivity management (heterogeneous access selection) SME Signalion (de) Test bed setup, and operation RES Institute IMDEA Networks (es) MAC layer improvement IEEE 802.11 UC3M (es) Connectivity management (session continuity) University of Paderborn (de) Dynamic backhaul configuration mechanisms 10
  • 10. Concrete project results 1. New solutions for connectivity management benefiting (rather than suffering) high density in deployments. 2. Novel heuristic approximation algorithms exploiting regional-level information for energy efficient operation. 3. Enhancements at MAC layer for IEEE 802.11 and LTE that use density “as a resource” and exploit it through intra- and inter-technology coordination. 4. Dynamic backhaul reconfiguration strategies that achieve such a consumption that is near proportional to traffic demands. 5. An integrated testbed suitable to validate all the other project results under realistic conditions.11