Energy Usage in Cloud - Network

Salih Safa BACANLI

• Energy usage for network in private and public cloud

• Software as a Service, Storage as a Service, Processing as a Service Energy Usage Comparison

• Conclusion

Energy Usage in Cloud

The report of CDP states that usage of cloud not only can improve business process efficiency and flexbility but also can decrease the CO2 emissions. The report continues by saying “by 2020, large U.S. companies that use cloud computing can achieve annual energy savings of $12.3 billion and annual carbon reductions equivalent to 200 million barrels of oil – enough to power 5.7 million cars for one year.” Shimkus(2011) states in his article that cloud computing can reduce 38 percent of world data center energy use by 2020.

• Although the usage of cloud computing decreases the energy usage, in another point of view it is increasing it’s percentage of energy usage. Kuruppasamy et al.(2013) states that cloud network emit over 150 metric tons of CO2 per year. Cloud computing is becoming an item in the list that contains the key elements that use a serious percentage of energy.

• Green Energy

• Cost

Cloud Structure

Transportation Cost in Cloud

Baliga et al.(2010) have made an analysis of energy consumption of cloud computing. They have stated that transport and switching can have a significant effect on energy consumption (Baliga et al., 2010). They have made an concrete statement that cloud computing can be energy efficient if the computation tasks are infrequent or have low intensity. They continue by saying that there are also some cases where computing on local pc will be more energy efficient. They have offered virtualization, consolidation of servers and advanced cooling system to decrease energy consumption significantly.

Private Cloud Energy Usage

Pes, Ples, and Pg are the powers consumed by the Ethernet switches, small Ethernet switches, and data center gateway routers, respectively. Ces, Cles and Cg are the capacities of the corresponding equipment in bits per second.

• 3Pes is because of the switches in the data center.

• 3 for outer paranthesis is for cooling

• private cloud would significantly increase network traffic. authors assumed an average utilization of 33%. The second factor of three in (1) is to account for this underutilization of corporate networks

0.46 J/b

Public Cloud Energy Usage

•

• Pes,Pbg, Pg ,Ppe,Pc,andPw the powers consumed by the Ethernet switches, broadband gateway routers, data center gateway routers, provider edge routers, core routers, and WDM transport equipment, respectively.

• Ces, Cbg, Cg , Cpe, Cc,and Cware the capacities of the corre-sponding equipment in bits per second.

• 6 for cooling • 3 for metro network switches • 2 for edge router in the edge network and the gateway router in the data

center • 2 for core routers allows for the fact that core routers are usually

provisioned for future growth of double the current demand • In the model customer traffic must traverse three hops to reach the

network core, two hops from the network core to the server, and a further average of eight core hops, which leads to an average of 13 hops in total. The factor of nine for routers and factor of eight for WDM transport equipment account for the eight core hops.

• Divide by 2: for core WDM transport equipment because many of the core hops are between co-located switches or routers and so WDM transport is not used.

• 2.7 J/b

Storage as a Service, Baliga et al(2010)

After 100 downloads/sec servers and transport becomes an important percentage. That’s why storage gets 0%.

• Cloud is nice if you don’t use very often?

Average document size 1.25 MB

Software as a Service Baliga et al(2010)

Low end laptop: 18W Mid range PC 70 W

Processing as a service

Encoding: Convert & compress video file

Baliga et al.’s Conclusion

• Baliga et al. (2010) concluded that private cloud computing is more energy efficient than public cloud computing due to the energy savings in transport. However, it is not clear whether in general the energy consumption saving in transport with a private cloud offsets the higher energy consumption due to lower utilization of servers and storage. The reason why public cloud is not energy efficient is that users need to connect internet to access public cloud. Optical bypass can be used to reduce the number of router hops through the network and thus the energy consumption in transport.

Conclusion

• If cloud is used for not very frequent jobs, it is energy efficient.

• Private clouds are more energy efficient.

• Transportation becomes a key factor in public clouds and making public cloud less energy efficient.

• For developing energy efficient clouds, we need to work on low power using devices and efficient network topologies.

• Questions?

References

• Dickinson, P(n.a.). Cloud Computing – The IT Solution for the 21st Century, CDP [ONLINE] Retrieved from https://www.cdproject.net/en-US/WhatWeDo/Pages/Cloud-Computing.aspx [10 September 2013]

• Shimkus, J. (2011, 21 July). Cloud Computing Saves Energy and CO2 Emissions, Energy Digital [ONLINE],Retrieved from http://www.energydigital.com/green_technology/cloud-computing-saves-energy-and-co2-emissions [10 September 2013]

• Karuppasamy M., Suprakash S.& Balakannan S. P. (2013).Energy Efficient Cloud Networks Towards A Sustainable Green Environment, International Journal of Research in Engineering & Advanced Technology, 1(1), Retrieved from http://www.ijreat.org/Papers%202013/Volume1/IJREATV1I1133.pdf [10 September 2013]

• M. Mazzucco, D. Dyachuk, and R. Deters, "Maximizing Cloud Providers Revenues via Energy Aware Allocation Policies," in Proc. 3rd IEEE International Conference on Cloud Computing (IEEE Cloud), July 2010.

• Yuan, X. (2011), On Nonblocking Folded-Clos Networks in Computer Communication Environments., in'IPDPS' , IEEE, , pp. 188-196 .

• J. Baliga , R. W. A. Ayre , K. Hinton and R. S. Tucker "Green cloud computing: Balancing energy in processing, storage, and transport", Proc. IEEE, vol. 99, no. 1, pp.149 -167 2011

• Rajendran Parthiban, Rodney S. Tucker, and Chris Leckie, "Waveband Grooming and IP Aggregation in Optical Networks," J. Lightwave Technol. 21, 2476- (2003) http://www.opticsinfobase.org/jlt/abstract.cfm?URI=jlt-21-11-2476

• Natalie EnrightJerger, Retrieved from: http://ece757.ece.wisc.edu/lect09b-interconnects-topology-routing.pdf [26 .09.2013]

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