Energy EfficientSleepMode

Transcription

1 Energy EfficientSleepMode Management forcellularnetworks Simone Morosi, Pierpaolo Piunti, Enrico Del Re University of Florence - CNIT ETSI Workshop on Energy Efficiency June 2012, Genoa, Italy

2 Outline Introduction and Motivation An insight in the Energy Saving Strategies Scenario Results Conslusion ETSI Workshop on Energy Efficiency 2

3 Introduction and Motivation In order to satisfy the capacity demand growth, the operators will have to increase the number of deployed cells: on the other hand the energy costs and the global footprint of mobile communication systems keep on growing at an unbearable rate. Therefore, the scientific community is investigating new techniques that allow reduction of energy consumption of ICT introducing the concept of Green ICT. ETSI Workshop on Energy Efficiency 3

4 Introduction and Motivation EARTH Project FP7 - Deliverable D2.1: Economic and Ecological Impact of ICT Fonte: A.P. Sokolov et al., Probabilistic Forecast for 21 Century Climate Based on Uncertainties in Emissions (without Policy) and Climate Parameters, Report 169, Jan 2009 ETSI Workshop on Energy Efficiency 4

5 Introduction and Motivation Global carbon footprint of mobile communications projected until 2020 (CI with a continuation of current trends and a high data scenario) Expected evolution of energy prices EARTH Project FP7 - Deliverable D2.1: Economic and Ecological Impact of ICT ETSI Workshop on Energy Efficiency 5

6 Introduction and Motivation Power consumption in mobile network Power consumption in a BTS The adoption of the green strategies must afford the same capabilities of the communication systems that do not resort to them. Therefore, the overprovisioningof the today systems is to be taken into account and tackled. ETSI Workshop on Energy Efficiency 6

7 Introduction and Motivation Daily traffic and energy consumption Traffic behavior vs power consumption for a real cellular site [normalized values] ETSI Workshop on Energy Efficiency 7

8 An insight in the Energy Saving Strategies We focus on deactivation of power amplifiers (sleep mode of the resources), with the goal of determining when a carrier or a set of carrier or the whole cell can be switched off without decreasing network performance. The optimal solutions is based on the perfect knowledge of requested channelateachmomentoftheday. Two sub-optimum traffic prediction and management strategies are proposed: while the former approach is based on real-time measurements of resources which are exploited by the communications, the latter is based on traffic forecasting. ETSI Workshop on Energy Efficiency 8

9 Holt-Winter Traffic Forecast Holt-Winter exponential smoothing is used in historical series analysis. Traffic in a cell has a periodic behavior and it can be analyzed as an historical series. S I b t t t Y α Y t = β + S 1 β t ( α )( S b ) t = + 1 t 1 t 1 I t L ( ) I t L ( S t S t 1 ) + ( 1 γ ) b 1 = γ t ( S t mb t ) I t L m F t + m = + + S t I t b t L Y t F t+m Smoothedseries Seasonal component Trend component Numberof periods in a season Measured series Forecasted series of m values α, β and γ can be tuned in order to minimize the error between forecasted series and measured series D. Tikunov and T. Nishimura, Traffic prediction for mobile network using Holt-Winter s exponential smoothing, in Software, Telecommunications and Computer Networks, 2007, 15 th International Conference onsoftcom 2007, sept ETSI Workshop on Energy Efficiency 9

10 Forecasting Based Sleep Mode Algorithm (FBSMA) ETSI Workshop on Energy Efficiency 10

11 Real-Time Measurements Sleep Mode Algorithm (RTMSA) ETSI Workshop on Energy Efficiency 11

12 Scenario 3-sector GSM cellwheregsm1800 coverageisoverlappedtogsm900 coverage(foreachsector2 GSM900 carriers and 4 GSM1800 carriers). four HSDPA Micro-cell overlapped to a Macro-cell (1 carrier/cell). ETSI Workshop on Energy Efficiency 12

13 Power Consumption Model Macro P TX P Macro = + PSP C 1+ µ PA P stat micro P = µ micro TX PA C stat TX ( 1+ C )( C ) + P stat SP P μ PA P SP C C C P P SP,stat /P SP,NL C PS PA efficiency SignalProcessing consumption Fractionofconsumptionsduetocooling Fractionofconsumptionsduetopowersupply and battery backup SignalProcessing consumptions:static/per link PowerSupplyloss P dyn micro P µ PA stat ( 1 CTX ) CTX, NL + PSP NL N L micro TX =, P = P + micro stat micro P dyn micro Oliver Arnold, Fred Richter, Gerhard Fettweis, Oliver Blume; Power Consumption Modeling of DifferentBase Station Types in Heterogeneous Cellular Networks ; Future Network and MobileSummit 2010 Conference Proceedings. ETSI Workshop on Energy Efficiency 13

14 Results In GSM scenario some resources can be switchedoff during night-time and during other periods of the day. FBSMA updates the network configuration each hour (thanks to traffic forecast), RTMSA updates network configuration more frequently following quasi-istantaneous traffic measurements. FBSMA RTMSA ETSI Workshop on Energy Efficiency 14

15 Results In HSDPA scenario, due to low traffic values, during nigthtime some resources are not needed and can be switched-off. During the rest of the day, in the considered scenario (1 carrier/cell) the amount of traffic does not allow other switch-off procedures. ETSI Workshop on Energy Efficiency 15

16 Results ETSI Workshop on Energy Efficiency 16

17 Conclusions As for the energy saving purpose, the FBSMA behaves better than the RTMSA in a voice scenario: moreover, It is also characterized by a lower number of network configuration updates. In a HSDPA data traffic scenario the performance of considered strategies is quite similar. Nonetheless, a highly reliable data traffic forecast allows the FBSMA to switch off or on the resources before and later than RTMSA, respectively. ETSI Workshop on Energy Efficiency 17

18 Energy EfficientSleepMode Management forcellularnetworks Simone Morosi, Pierpaolo Piunti, Enrico Del Re University of Florence - CNIT ETSI Workshop on Energy Efficiency June 2012, Genoa, Italy