telecommunication networks and integrated services (tns) laboratory department of digital systems...

Telecommunication Networks and integrated Services (TNS)

Laboratory

Department of Digital SystemsUniversity of Piraeus Research Center (UPRC)

University of Piraeus

Green Footprint

Prof. P, Demestichas, Assist. Prof. A Rouskas,

M. Logothetis

Email: {pdemest, arouskas, mlogothe} @unipi.gr

http://tns.ds.unipi.gr/

TNS – Green Footprint

Outline

Introduction - Research Areas - Motivation

Energy efficient Resource Allocation to femtocells Problem Statement

Proposed Solution

Indicative Results

Conclusion – Future Work

Operator-driven Traffic Engineering in Core Networks Problem Formulation

Proposed Solution

Indicative Results

Conclusion – Future Work

Disseminations

2


Introduction / Research Areas

3

Research Areas Wireless Access

High-speed, wireless-access, infrastructures (2G, 3G, B3G, 4G).

Fixed Access – Core Network Optical Networks (WDM, SONET)

Fixed access networks (xDSL, FTTx,)

Emerging wireless world


Motivation

The estimation for 2020 : mobile communication infrastructures will

represent more than 50% of network CO2 emissions.

Need for reduction of transmission powers and energy consumption in

Wireless and Fixed Access

4

Global telecoms footprint [2002 & 2020]


Problem Statement

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Problematic situation All terminals are served through the BS Congestion issues arise Inadequate QoS (delivery probability, delay, etc.)

to the terminals

Femtocells are the opportunity that is exploited They offer their resources for the relief of the

congested BS

Opportunistic Network Creation Terminals are offloaded to femtocells BS is no longer congested Terminals experience higher QoS

Energy efficiency Femtocells are configured to operate at the minimum

possible power level required to cover the terminals Switch off femtocells that have not acquired traffic

Opportunistic Networks are operator governed

extensions of the infrastructure

TNS – Green Footprint 6

Process:

1. Selection of femtocells which are nearest to the terminals that will participate in the ON

2. Initial configuration of femtocells to the max power level

3. Assignment of traffic to femtocells

4. Selection of femtocells that can decrease their power level

5. Gradually decrease the power level of each femtocell to the minimum level that the constraints (coverage and capacity) are not violated

Solution - Energy efficient Resource Allocation to femtocells

Input:The congested BS and its capabilities: RAT, Capacity, CoverageSet of deployed femtocells and their capabilities : RAT, Capacity, Set of possible transmission powersTerminals information: RAT, Location, Mobility level, Sensitivity

Output:The allocation of transmission powers to the femtocells The assignment of terminals to femtocells


Indicative Results [1/4]

7

The delivery probability Increases after the solution

enforcement

Increases as more terminals are offloaded to the femtocells

Decreases as the terminals’ mobility level increases

The delay Decreases after the solution

enforcement

Decreases as more terminals are offloaded to the femtocells

Increases as the terminals’ mobility level increases



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Power and traffic allocation to the femtocells

- For central user distribution many femtocells remain without traffic and are switched off

- For sparse user distribution more terminals need to remain active to cover the traffic

Output of Algorithm



9

BS energy consumption in relation with the number of femtocells Energy consumption decreases

as more femtocells are deployed

BS energy consumption in relation with the number of serving terminals Energy consumption rises while

more terminals are served through the BS



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Femto-terminals need low transmission power to communicate with the femtocells Increased battery lifetime

(25% in average)

Battery’s residual capacity drops at lower rate


Conclusions – Future Work

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Conclusions The algorithm

Allocates the minimum possible transmission power to femtocells that is needed to cover the terminals that are suitable to be offloaded to femtocells

Switches off the femtocells that remain without traffic

Femtocells are an energy efficient solution

Decreased BS power consumption due to the redirection of a proportion of the terminals

Increased battery lifetime of femto-terminals due to the small distance between terminals and femtocells

Future Work

Frequency allocation by taking into account interferences from neighboring BSs in a general sense

Taking into account QoS requirements


Operator-driven Traffic Engineering in Core Networks

12

Computation of optimum

routing configuratio

n

Monitoring

Setting LSPs

Policy

RAN request

s

Video Servers

Ingress LSRs

Egress LSRs

Base Stations

Operator Problem Statement: find the

most suitable routing configuration to accommodate traffic demands, satisfying operator’s policies

Proposed Solution:

CORE - Multilayer Traffic Engineering: IP/MPLS over DWDM (for optical core networks)


Multi-layer Traffic Engineering (MLTE): IP/MPLS over DWDM Core Optical Networks

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Problem Statement: find the most energy-efficient lightpath to accommodate the new traffic demand, while respecting the capacity of fibers and wavelengths.

Proposed Solution (CORE - Multilayer Traffic Engineering: IP/MPLS over DWDM)

Energy efficiency is achieved through the allocation of traffic to dedicated lightpaths, which are restricted at the optical layer only (optical bypass), when this is possible. Our proposed heuristic algorithm (ETAL) activates and exploits more network elements in order to find the necessary portions for establishing lightpaths without aggregating them.



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Find all paths

Order Paths

Find optimal lightpath Minimum conversions

Dedicated lightpath

Optical bypassing

Enforce decision GMPLS signaling

Update network’s status

Heuristic Algorithm: Energy-aware allocation of traffic to lightpaths (ETAL)



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Evaluation: comparisons with energy-efficient routing schemes

Metrics: number of conversions, consumed power, number of activated fibers, number of activated wavelengths, number of activated paths, average length of activated paths

Future WorkDevelop an updated cost function which will include proactive approach


Disseminations

• D. Karvounas, A. Georgakopoulos, D. Panagiotou, V. Stavroulaki, K. Tsagkaris, P. Demestichas, “Achieving energy efficiency through the opportunistic exploitation of resources of infrastructures comprising cells of various sizes”, Journal of Green Engineering, vol.2, issue 3, River Publishers, 2012

D. Karvounas, A. Georgakopoulos, V. Stavroulaki, N. Koutsouris, K. Tsagkaris, P. Demestichas, “Resource Allocation to Femtocells for Coordinated Capacity Expansion of Wireless Access Infrastructures”, accepted for publication at EURASIP Journal on Wireless Communications and Networking, Special Issue on Femtocells in 4G Systems, 2012

V. Foteinos, K. Tsagkaris, P. Peloso, L. Ciavaglia and P. Demestichas, “Energy Savings with Multilayer Traffic Engineering in Future Core Networks”, Journal of Green Engineering, 2012.

V. Foteinos, K. Tsagkaris, P. Peloso, L. Ciavaglia and P. Demestichas, “Energy-Aware Allocation of Traffic to Optical Lightpaths in Multilayer Core Networks”, submitted for publication to IEEE/OSA Journal of Lightwave Technology, 2012.

V. Foteinos, K. Tsagkaris, P. Peloso, L. Ciavaglia and P. Demestichas,” Energy Savings in Multilayer Core Networks”,submitted for publication to IEEE International Conference on Communications, 2012.

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telecommunication networks and integrated services (tns) laboratory department of digital systems...

Documents

terminals femtocells

femtocells bs

selection of femtocells

femtocells input

deployed femtocells

congested terminals

assignment of terminals

femtocells problem statement