INTelligent Energy awaRe NETworks.An EPSRC UK Funded .ppt

《INTelligent Energy awaRe NETworks.An EPSRC UK Funded .ppt》由会员分享，可在线阅读，更多相关《INTelligent Energy awaRe NETworks.An EPSRC UK Funded .ppt（53页珍藏版）》请在麦多课文档分享上搜索。

1、INTelligent Energy awaRe NETworks. An EPSRC UK Funded Project in Green NetworksProfessor Jon Crowcroft, Cambridge And Professor Jaafar ElmirghaniUniversity of Cambridge, & University of Leeds, UK Jon.crowcorftcl.cam.ac.uk j.m.h.elmirghanileeds.ac.uk,Network energy consumption trends Motivation Acces

2、s network power consumption trends Power usage efficiency (PUE) Photonic versus electronic switching Terminal versus network power consumption Wired and wireless network energy consumption comparison Power management approaches Access, metro, core power consumption Energy efficient routing in optica

3、l networks Energy per bit Energy Efficient Routing (EER) Performance Evaluation of EER Sleep cycles Conclusions References,Outline,Network energy consumption trends Motivation Access network power consumption trends Power usage efficiency (PUE) Photonic versus electronic switching Terminal versus ne

4、twork power consumption Wired and wireless network energy consumption comparison Power management approaches Access, metro, core power consumption Energy efficient routing in optical networks Energy per bit Energy Efficient Routing (EER) Performance Evaluation of EER Sleep cycles Co-Optimising Co-Lo

5、 Data Center&Sustainable Energy Production Location Conclusions References,Outline,Motivation,Ministry of Internal Affairs and Communications Japan report concluded that ICT equipment (routers, servers, PCs and network systems) consumed 4% of the total electricity generated all over Japan in 2006, a

6、 figure of 45,000,000 MWh. Over the past five years the figure has grown by more than 20% 1.The goal is to reduce this figure and its CO2 impact. It also has to be observed that ICT can help reduce the ecological impact by reducing journeys and introducing more efficient business processes.Studies i

7、ndicate that for ICT equipment, 50% of CO2 emission is due to the production stage, 45% due to the usage stage and 5% due to the recycling/disposal stage 2. Therefore it pays to reduce the number of elements in the network and to design architectures and protocols with the per-element usage in mind.

8、,Access network power consumption trends,The figure shows NTT DoCoMos energy consumption for communication equipment and number of 3G base stations 1Energy consumption increase is proportional to the number of installed base stations,Power usage efficiency (PUE),PUE is defined as the ratio of “total

9、 energy consumption” to “IT equipment energy consumption” 1.In addition to IT equipment, lighting and air conditioning are the main contributors to the total energy.A typical value of PUE is 1.7 1.Therefore it is worthwhile reducing the equipment, designing the usage carefully, but also examining hi

10、gh temperature / uncooled components.Advanced hardware design and removing the cooling element reduces CO2 emission by 20% to 40% it is estimated 3.,Photonic versus electronic switching,Photonic switching has much lower energy consumption compared to electronic switching.It has been shown that the p

11、ower needed per bit for switching is 100 to 1000 times higher in an electronic semiconductor switch as compared to a photonic switch 4.,Terminal versus network power consumption,Typical current mobile terminal power consumption is 0.83Wh per day (including battery charger and terminal) 1.The corresp

12、onding network power consumption is 120Wh 1.The ratio is 150:1 and therefore the network power consumption is the main contributor to CO2 and effort has to be directed at the network primarily.Significant research effort has gone into extending the mobile terminal battery life by optimising and redu

13、cing its power utilisation from 32Wh per day in 1990 to 0.83Wh per day in 2008, a factor of 38 1, 5.In comparison the network power consumption has received little attention to date.,Wired and wireless network energy consumption comparison,A university campus network has been reported to use 6% of t

14、he total campus power 6. This amount corresponds approximately to the production of 13 tons of nitrogen oxides (a precursor to ozone), 35 tons of sulphur dioxide and 5100 tons of carbon dioxide as a result of burning fossil fuels. If the associated heating and cooling are added, network energy consu

15、mption will double 6. As a result of monitoring on campus networks 6, it was observed that the power consumption of multi port hubs and switches is almost independent of the number of devices connected to the hub or switch. For example a Cisco switch consumed 40 watts with no devices connected and 4

16、2 watts with 16 devices connected. Therefore it pays to reduce the number of elements in the network. It was found on campus 6 that the wired network consumed between 200,000 and 500,000 kWh per year, while the wireless network consumed only 30,000 kWh. A factor of 10 difference between wired and wi

17、reless which indicates that the focus has to be on the wired network for energy saving. In the US, ICT accounts for 3% of the total country energy consumption 7, 8.,Power management approaches,Internet power usage has continued to increase over the past decade due to (i) more absolute number of devi

18、ces (ii) higher active power of devices and (iii) more active hours of usage per day 9.Can shut off CPU and instruction level (nano to micro seconds), inter-packet or intra-flow CPU halt or shut-off (micro to millisecond) and inter-flow, the entire computer/communication can be turned off (seconds t

19、o hours) 9.,Access, metro, core power consumption (1),Energy consumption is rapidly developing into an environmental and political concern 11, 12. It has been studied in transport, buildings etc, but less in telecom.There is also concern about constructing and maintaining large data centres and swit

20、ching centres 13.Therefore the question has been raised whether the Internet growth will be constrained by power rather than bandwidth 11.In 11 the conclusion reached is that photonic switching alone will not solve the Internet energy consumption problem (ie need to look at the overall picture inclu

21、ding switching, routing protocols etc).In some studies the extra power needed for cooling is assumed to be equal to the power used by the equipment 11, 14.In the access (based on PON) typical power consumption estimates are 10W for optical network units (ONU) and 100W for optical line terminal which

22、 resides in an edge node and connects to several ONUS 11.A typical edge router in the metro, for example Cisco 12816, consumes 4.21 kW 11, 15.A typical core router, such as Cisco CRS-1 multishelf system with 92 Tb/s full duplex switching capacity consumes 1020 kW 11, 15.,Access, metro, core power co

23、nsumption (2),WDM systems connecting the edge nodes to the core node consume 1.5 kW for every 64 wavelengths 11, 16.Typically one multiwavelength amplifier is required per fibre, consuming around 6W 11, 16. The WDM terminal systems connecting core nodes consume 811 W for every 176 channels, while ea

24、ch intermediate line amplifier consumes 622 W for every 176 channels 11, 17.,Some more on motivation & techniques,Current estimates indicate that power consumption accounts for about half the cost of ownership of communication networks 18, 19. Energy saving in networks is possible due to two main re

25、asons 18: Networks are provisioned at present for the worst case scenario and many times over provisioned (3 to 5 times). Therefore varying the number of active elements and sections of a network according to demand can save power.The power consumption of the network at present remains substantial e

26、ven when the network elements are idle. Therefore provisioning just the right amount and introducing sleep operations during idle times can help.,Summary,Consider energy used in manufacturing as well as operation, therefore reduce the number of network components.Consider PUE, therefore uncooled com

27、ponents and systems are attractive.Photonic switching instead of electronic routing whenever possible.Network power consumption higher than that of the terminal.Wired part still consumes more power than the wireless part.Reduce the “over provisioning” whenever possible.Introduce sleep modes and slee

28、p cycles.Power consumption can account for up to half of the operating costs in networks.,Network energy consumption trends Motivation Access network power consumption trends Power usage efficiency (PUE) Photonic versus electronic switching Terminal versus network power consumption Wired and wireles

29、s network energy consumption comparison Power management approaches Access, metro, core power consumption Energy efficient routing in optical networks Energy per bit Energy Efficient Routing (EER) Performance Evaluation of EER Sleep cycles Conclusions References,Outline,The energy costs of the netwo

30、rk will grow as the amount of data on the network increases.As the network expands in its capacity, energy consumption in the core network is an important concern for the networking industry.Some of the possible approaches that can reduce the energy consumption include, put to sleep some of the wave

31、length routed nodes and, at a network level consider changing routes during low traffic periods.These two approaches decrease the QoS and connectivity. Energy consumption can be reduced so long as the QoS performance remains within SLA,Energy efficient routing in optical networks,Using intelligent o

32、ptical control planes, lightpaths (or wavelength channels) can have dynamic route selection polices.By using an efficient optical control management mechanism, network nodes (WRN) can be set to ON or OFF states.During the OFF cycle the nodes, adopt a sleep mode, cutting down the traffic routed throu

33、gh them. Traffic originating at the node or destined to the node is handledThe energy reduction achieved due to a sleep cycle is at the cost of decrease in QoS.,Energy efficient routing in optical networks,Wavelength routed node (WRN) used in the network architecture,Energy per bit and WRN architect

34、ure used in the study,The two different types of energy associated with the optical networks, Energy associated with the transmission of one optical bit over fiber, Energy consumed by a router (WRN) for switching an optical signal.,Fig: Wavelength routed node (WRN) used in the network architecture,T

35、he energy associated with the transmission of 1 bit can be expressed as,Energy per Bit,The power consumed in an optical network path is given by,If an optical bit traverses H hops, with each hop consisting of k optical inline amplifiers, then the total energy consumed due to WRN and EDFAs is,The ene

36、rgy per bit across a fiber of length Ln between the nodes n,n+1 is given by,The energy required to transmit an optical bit across H hops is given by,Energy per Bit,Energy per bit,Calculation of energy needed,Calculation of energy needed,Parameters used,We propose an Anycasting routing technique to m

37、inimize the energy consumption in the optical network.Anycasting is defined as the communication paradigm, in which the user has the ability to choose a probable destination from a group of possible destinations unlike deciding it a-priori as in unicast.An Anycast request is denoted as a two-tuple (

38、s,Ds), where s is the source node initiating a session and Ds is set of probable destinations.A sleep cycle is defined as the time duration in which a WRN cuts off the traffic routed through it and adopts an OFF state.,Energy Efficient Routing (EER) Algorithm,Definition: We denote the network elemen

39、t vector for a link i as,The overall NEV for a route R, consisting of links i, i + 1, . . ., j 1, j is given by,Definition: We define the threshold parameters for a service () as,Energy Efficient Routing (EER) Algorithm,Fig: Burst header packet fields used in the EER algorithm,Energy Efficient Routi

40、ng (EER) Algorithm,The National Science Foundation (NSF) network topology and the Italian network are considered in our study. Random sleep modes were considered. We have considered the service threshold vector as ,NSF network,Italian Mesh Network (IMnet),Performance Evaluation,Comparison of energy

41、dissipation in the NSF network for Shortest Path Routing (SPR) and Energy Efficient Routing (EER), under varying traffic.,EER and SPR algorithms in NSFNet,Average power consumption for each lightpath in various anycast scenarios in NSFNet,Average energy saving obtained due to anycasting in NSFNet,En

42、ergy consumed and energy saved for different anycasting orders (k), NSFNet,Average blocking probability in various anycast scenarios in NSFNet,Average power consumption for each lightpath in various anycast scenarios in IMNet,Blocking probability NSFNet, Energy consumption at different anycasting or

43、ders (k), IMNet,Average energy saving obtained due to anycasting in IMNet,Average blocking probability in various anycast scenarios in IMNet,Energy saved and blocking probability IMNet,Power saving obtained with sleep modes in 4/1 NSFnet and 6/1 IMnet,Power saving obtained with sleep modes in 4/1 NS

44、Fnet and 6/1 IMnet,We have computed the energy required to transmit a bit in an optical channel. We have evaluated the energy consumption based on per hop parameters and node architecture.Using anycasting communication and efficient BHP signaling, we have minimized the energy consumption in optical

45、burst switched networks.The energy saving is obtained without significantly scarifying the QoS.,Summary,Summary,Network energy consumption trends Motivation Access network power consumption trends Power usage efficiency (PUE) Photonic versus electronic switching Terminal versus network power consump

46、tion Wired and wireless network energy consumption comparison Power management approaches Access, metro, core power consumption Energy efficient routing in optical networks Energy per bit Energy Efficient Routing (EER) Performance Evaluation of EER Sleep cycles Conclusions References,Outline,Related

47、 Work,Different solutions have been proposed to save energy in optical networks In previous work 1 a static sleep cycles algorithm was proposed to reduce the amount of energy consumed in optical networks. The network is divided into clusters of nodes. Clusters are set to switch between the ON and OF

48、F modes statically. Putting some nodes in sleep state means that some traffic flows will have to take longer routes, i.e. energy is saved at the expense of QoS.,_ 1 B.G.Bathula, J. M. H. Elmirghani, “Green Networks: Energy Efficient Design for Optical Networks,“ Proceedings of Sixth IEEE/IFIP Intern

49、ational Conference on Wireless and Optical Communications Networks (WOCN 2009), Apr. 2009, pp. 1-5.,In this work we propose an intelligent sleep cycles algorithm where nodes switch between the ON and OFF modes dynamically according to the traffic flows in the network.The major consideration for any

50、energy saving solution is the trade off between the amount of energy saved and the level of performance degradation.Dynamic sleep cycles are expected to save more energy while keeping the network performance within acceptable levels.When nodes go to sleep, they can still transmit and receive traffic

51、 but they cannot route traffic.Nodes monitor the traffic flows passing through. A monitoring window period is defined. If within the monitoring window the overall blocking probability is less than a certain threshold, some nodes are selected to go to sleep according to the traffic flow and their location in the network topology.,