Data Center Simulations in OMNET++ ASAD W. MALIK NUST SCHOOL OF - - PowerPoint PPT Presentation

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Data Center Simulations in OMNET++ ASAD W. MALIK NUST SCHOOL OF - - PowerPoint PPT Presentation

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CloudNetSim++: A Toolkit for Data Center Simulations in OMNET++ ASAD W. MALIK NUST SCHOOL OF ELECTRICAL ENGINEERING AND COMPUTER SCIENCE, PAKISTAN Team Members Kashif Bilal: North Dakota State University, Fargo, USA Khurram Aziz:

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CloudNetSim++: A Toolkit for Data Center Simulations in OMNET++

ASAD W. MALIK

NUST SCHOOL OF ELECTRICAL ENGINEERING AND COMPUTER SCIENCE, PAKISTAN

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Team Members

 Kashif Bilal:

North Dakota State University, Fargo, USA

 Khurram Aziz:

Comsats institute of information technology, PAK

 Dzmitry Kliazovich:

University of Luxembourg, Luxembourg

 Nasir Ghani:

University of south florida, Florida, USA

 Samee U. Khan:

North Dakota State University, Fargo, USA

 Rajkumar Buyya:

University of Melbourne, Australia

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Outline

 Introduction  Related Work  Motivation  CloudNetSim++ Features  CloudNetSim++ Architecture  Performance Evaluation  Conclusion

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Introduction

 Cloud computing services have become increasingly popular  “Market Tends” estimates that cloud-based SaaS will increase from US $

13.4 billion in 2011 to $32.2 billion in 2016 *

 Similarly, in IaaS and PaaS markets are estimed growth from $7.6 billion in

2011 to $ 35.5 billion in 2016 *

 Require massive infrastructure to support this enormous growth  Large geographically distributed data centers requires considerable

amount of energy

 High power consumption generates heat and requires an accompanying

cooling system that costs in a range of $2 to $5 million per year

* L. Columbus, “Cloud Computing and Enterprise Software Forecast Update, 2012,” Forbes, 8 Nov. 2012; www.forbes.com/sites/louiscolumbus/2012/11/08/cloud-computing-and- enterprisesoftware-forecast-update-2012

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Introduction

 Failure to keep data center temperature within operational ranges

drastically decreases hardware reliability

 The techniques, Dynamic Voltage and Frequency Scaling (DVFS) and

Dynamic Power Management (DPM) is widely adopted

 Idle server may consume about 2/3 of the peak load*  Workload of data center fluctuates on the hourly basis  Average load account only 30% of data center resources**  This allow putting rest 70% into a sleep mode for most of the time  To achieve this, central coordination and energy-aware scheduling is

required

*Chen G, He W, Liu J, Nath S, Rigas L, Xiao L, Zhao F (2008) Energy-aware server provisioning and load dispatching for connection-intensive internet services. In: The 5th USENIX symposium on networked systems design and implementation, Berkeley, CA, USA **Liu J, Zhao F, Liu X, He W (2009) Challenges Towards Elastic Power Management in Internet Data Centers. In: Proceedings of the 2nd international workshop on cyber-physical systems (WCPS), in conjunction with ICDCS 2009, Montreal, Quebec, Canada, June

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Related Work

Simulator Available Language GUI Comm. Model Energy Model Simulation Time CloudSim Open Source Java No Limited Yes Second NetworkCloudSim Open Source Java No Full No Second iCanCloud Open Source C++ Yes Full No Second DCSim+ Open Source Java No No No Minutes GreenCloud Open Source C++, oTcl Limited Full Yes Minutes

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Motivation

 To build a comprehensive Cloud simulator that facilitate

 Students  Researchers  Industry

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CloudNetSim++: Features

 Support Service Level Agreement (SLA)  Support various scheduling algorithms  Distributed data centers  Configurable number of data centers  Configurable number of racks and servers  Configurable physical link properties  Energy Module  Support multiple users

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CloudNetSim++: High Level Architecture

OMNeT++ Multiple Client Data center-I Data center-II Centralize Scheduler INET

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CloudNetSim++: Node Level Architecture

App Module Energy Module Queue Module Communication Module Compute Node Energy Module Communication Module Router/Switches

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CloudNetSim++

 Energy Computation

 Flexible data center model, compute energy utilization of following components

 Servers  Data center architecture, router and switches

 Power management, Dynamic Voltage Frequency Scaling (DVFS) technique  V2 ∗ F  The average power consumption is stated as below  P = P

C + CPUf ∗ f

 P

C : power consumed not scale to frequency

 CPUf ∗ f : represent frequency depended power consumption

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CloudNetSim++

 Power consumption of switches stated as:  𝑄𝑡𝑥𝑗𝑢𝑑ℎ = 𝑄𝑑ℎ𝑏𝑡𝑡𝑗𝑡 + 𝑜𝑚𝑗𝑜𝑓𝑑𝑏𝑠𝑒 . 𝑄𝑚𝑗𝑜𝑓𝑑𝑏𝑠𝑒 + 𝑗=0

𝑆

𝑜𝑞𝑝𝑠𝑢,𝑠 . 𝑄

𝑠  𝑄

𝑑ℎ𝑏𝑡𝑡𝑗𝑡 : Power consumed by switch hardware

 𝑄𝑚𝑗𝑜𝑓𝑑𝑏𝑠𝑒 : Power consumed by a line card  𝑄

𝑠 : Power consumed by a port operating at rate r

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CloudNetSim++: Graphical User Interface

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CloudNetSim++

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CloudNetSim++: Performance Evaluation

 Used two different traffic scenarios

 Many-to-one model  Many-to-many model

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S.No Simulation Parameters Parameters Value 1 Inter-Data Center (DC) topology Star/Mesh 2 Intra-DC topology three-tier 3 Inter-DC link 100-Gbps 4 Data center to data center link (Bit Error Rate) 10−12 5 Core to aggregate link 10 Gbps 6 Aggregate to access link 1 Gbps 7 Access to servers link 1 Gbps 8 Core to aggregate link (BER) 10−12 9 Aggregate to access link (BER) 10−12 10 Access link to computing servers (BER) 10−5 11 Packet size 1500 bytes 12 Core nodes 8 13 Aggregate nodes 16 14 Access nodes 256 15 Computing server 2200 - 9000

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CloudNetSim++: Performance Evaluation

98 45 200 156

DC-East(kWh) DC-West(kWh) DC-South(kWh) DC-North(kWh)

4.086 9.21 16.218 70.633

Core Switch(kWh) Aggregate Switch(kWh) Access Switch(kWh) Server(kWh)

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CloudNetSim++: Performance Evaluation

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CloudNetSim++: Performance Evaluation

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CloudNetSim++: Performance Evaluation

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CloudNetSim++: Available download

 Available for download at  http://cloudnetsim.seecs.edu.pk/

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Conclusion

 Designed to facilitate students, researchers and industry requirement  Provide rich Graphical User Interface – GUI  Modular approach, new modules can easily be incorporated  Configurable architecture  Open source, available to download

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CloudNetSim++ cloudnetsim.seecs.edu.pk

Thank You!

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References

  • A. Vahdat, M. Fares, N, Farrington, R. N. Mysore, G. Porter, and S. Radhakrishnan, “Scale-Out

Networking in the Data Center,” IEEE Micro. Vol. 30, no. 4, p. 29-41, 2010.

  • P. Mahadevan, P. Sharma, S. Banerjee, and P. Ranganathan, “Energy Aware Network

Operations,” in INFOCOM Workshops, pp. 25-30, 2009.

  • J. Shuja, S. A. Madani, K. Bilal, K. Hayat, S. U. Khan, and S. Sarwar, “Energy-efficient data

centers,” Computing, vol. 94 no. 12 pp. 973-994, 2012.

  • R. Beik, “Green Cloud Computing: An Energy-Aware Layer in Software Architecture,” in Spring

Congress on Engineering and Technology (S-CET), pp. 1-4, 2012.

  • J. Moore, J.Chase, P. Ranganathan, and R.Sharma, “Making scheduling cool: temperature-

aware workload placement in data centers,” in USENIX Annual Technical Conference pp. 61-75, 2005.

  • N. Rasmussen, “Calculating Total Cooling Requirements for Data Centers,” produced by

Schneider Electrics Data Center Science Center, 2011, http://www.apcmedia.com/salestools/NRAN5TE6HE/NRAN-5TE6HE R3 EN.pdf. Accessed 31 August 2014.

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References

  • K. Bilal, S. U. R. Malik, S. U. Khan, and A. Y. Zomaya, "Trends and Challenges in Cloud Data Centers," IEEE

Cloud Computing Magazine, vol. 1, no. 1, pp. 10-20, 2014.

  • K. Bilal, S. U. Khan, and A. Y. Zomaya, "Green Data Center Networks: Challenges and Opportunities,"

in 11th IEEE International Conference on Frontiers of Information Technology (FIT), pp. 229-234. 2013.

  • R. Buyya, R. Ranjan, and R.N. Calheiros, “Modeling and simulation of scalable Cloud computing

environments and the CloudSim toolkit: Challenges and opportunities,” in International Conference of High Performance Computing & Simulation, pp. 1-11, 2009.

  • X. Li, X. Jiang, K. Ye, and P. Huang, “DartCSim+: Enhanced CloudSim with the Power and Network

Models Integrated,” in IEEE Sixth International Conference on Cloud Computing, pp.644- 651,2013.

  • S. K. Garg, and R. Buyya, “NetworkCloudSim: modelling parallel applications in cloud simulations.” in

Fourth IEEE International Conference on Utility and Cloud Computing (UCC), pp. 105-113, 2011.

  • D. Kliazovich, P. Bouvry, Y. Audzevich, and S. U. Khan, “GreenCloud: A Packet-Level Simulator of Energy-

Aware Cloud Computing Data Centers,” in IEEE Global Telecommunications Conference (GLOBECOM), pp. 1-5, 2010.

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