Neal N. Xiong @ GSU Slide 1 June 25, 2011 Cloud Computing Services and Architecture Neal N. Xiong Georgia State University.

Neal N. Xiong @ GSU Slide 1

June 25, 2011

Cloud Computing

Services and Architecture

Neal N. Xiong

Georgia State University


June 25, 2011

Know exact case for the routers group: If, good for packets transmission Otherwise, miss packets, reduce QoS of packets transmission Networks resource are not extensive shared (partly shared)

UserUserUserUser

Traditional network application

Router

Cloud

Computing


June 25, 2011

What is a cloud? Definition [Abadi 2009]

shift computer processing, storage, and software away from the desktop and local servers

across the network and into next generation data centers

hosted by large infrastructure companies, such as Amazon, Google, Yahoo, Microsoft, or Sun


June 25, 2011

Dynamic cloud-based network model

North Carolina State University VCL modelhttp://vcl.ncsu.edu/

User/applicationsVCL Software and

Management nodes

Servers


June 25, 2011

VCL model in George Mason University


June 25, 2011

GMU model GMU uses configured IBM® BladeCenter® technology

and open source VCL software Involve the provision of systems and network security,

high-speed network services, a Web portal, a database server, a software image library and management nodes

Web portal manages the end-user reservation interface Database server holds a SQL database used for

managing reservations, images, and the VCL code configuration.

Management nodes are servers used in the

configuration of the overall VCL system.


June 25, 2011

Examples of Cloud Service

A student taking a statistics class might access the Mathematica to complete a homework assignment from a residence hall.

Another student might access Mathematica from home, before heading to work.

Yet another student taking that same statistics class might access Mathematica through a

wireless hub at a local restaurant. VCL applications included Stata v10, SPSS v17,

Matlab 2008a, Maple 13, and Mathematica 7.0.1.


June 25, 2011

VCL login interface in GMU


June 25, 2011

Examples of Cloud Service

For students, computer requirements to access the VCL are very small (remote student, public library).

Any point of minimal Internet access is sufficient to open the door for service, online, goes wherever students go.

For IT professionals, VCL helps address reduced budgets, increased power costs, aging equipment, software management, and the need to provide (software for teaching and learning).

Cost factors include hardware (e.g. bladecenter, workstations), software (e.g. VCL code), software management and imaging, HVAC, electrical, lighting, data storage, Internet access, network wiring, furniture and staff.


June 25, 2011

Improvements in areas of software licensing and maintenance are made through the VCL model as well.

Software use is tracked and metered allowing license purchases to match actual software demand.

Ensure equity in services to distance learners, a component of accreditation of distance education programs.

VCL connects users of very specific applications, exposing opportunities for sharing license costs.

Operational cost per service hour for VCL hardware is less than 1 cent (NCS, $13,000 were saved by reducing hours in 1 lab/1 week)

green Power costs: $11,594/year as compared with $3,944 in 1 lab/1 week


June 25, 2011

Reduced Costs

North Carolina State University: five students use one seat in a physical computer lab, On average, 25 students use one virtual seat in a virtual computing lab.

George Mason Univ: computer labs are available almost 93 hours a week. The VCL is available 168 hours a week. Accounting for maintenance, there are 7884 potential useable hours per year per virtual seat.

offers sophisticated tracking of professional software. The VCL connects users of very specific applications,

exposing opportunities for sharing license costs.


June 25, 2011

Barriers to virtual computing: outdated software licensing model, License costs

vary, change with little notice … add further complexity licensing and licensing

negotiation open doors for coordinated purchases across

departments and institutions.


June 25, 2011

Georgia State University Student Tech Fee Hardware/Software Cost Cycles: Requested vs.

Funded

0500000

1000000

1500000

2000000

2500000

3000000

35000002001

2002

2003

2004

2005

2006

2007

2008

2009

2010

HW RequestHW FundedSW RequestSW Funded


June 25, 2011

VCL login interface in Georgia State University


June 25, 2011

Graph analysis for this data

Laptop (seconds)

VCL (seconds)

0.75000 0.73440

0.54690 0.23440

0.48440 0.04690

0.07810 0.03130

0.04690 0.01560

Window: the comparison

between Laptop and VCL


June 25, 2011

Graph analysis for this dataMac: the comparison

between Laptop and VCL

Laptop (seconds)

VCL (seconds)

1,449.70000 944.95310

1,924.40000 1,038.10000

1,952.30000 1,208.70000

2,185.70000 1,382.60000

2,520.50000 1,546.10000

2,780.20000 1,709.50000

1,648.00000 1,072.30000


June 25, 2011

Comparison between Laptop and VCL

Laptop (seconds) VCL (seconds) Improvement

0.75000 0.73440 2.08%

0.54690 0.23440 57.14%

0.48440 0.04690 90.32%

0.07810 0.03130 59.92%

0.04690 0.01560 66.74%

Laptop (seconds) VCL (seconds)

1,449.70000 944.95310 34.82%

1,924.40000 1,038.10000 46.06%

1,952.30000 1,208.70000 38.09%

2,185.70000 1,382.60000 36.74%

2,520.50000 1,546.10000 38.66%

2,780.20000 1,709.50000 38.51%

1,648.00000 1,072.30000 34.93%


June 25, 2011

Dynamic cloud-based network model

U.S.

southern

state

education

Cloud,

sponsored

By IBM,

SURA

&

TTP/ELC


June 25, 2011

Q & A

Thank You!


June 25, 2011

[1-RED] S. Floyd and V. Jacobson, ”Random early detection gateways for congestion avoidance,” IEEE/ACM Transactions on Networking, Vol. 1, pp. 397-413, Aug. 1993.

[2-RED] C. V. Hollot, V. Misra, D. Towsley, and W. B. Gong, ”A Control Theoretic Analysis of RED,” Proceedings of IEEE INFOCOM 2001, Anchorage, Alaska, vol. 3, pp. 1510-1519, April 2001.

[3- Adaptive RED] Sally Floyd, Ramakrishna Gummadi and Scott Shenker, ”Adaptive RED: An algorithm for increasing the robustness of RED’s active queue management,” Berkeley, CA, Technical Report, to appear, 2001.

References


June 25, 2011

References

[4-PD-RED] Jinsheng Sun, King-Tim Ko, Guanrong Chen, Sammy Chan, and Moshe Zukerman, ”PD-RED: to improve the performance of RED,” IEEE Communications Letters, vol. 7, no. 8, pp. 406-408, August 2003.

[5-PI-RED] C. V. Hollot, Vishal Maisra, Don Towsley and Wer-Bo Gong, ”On designing improved controllers for AQM routers supporting TCP flows,” Proceedings of IEEE INFOCOM 2001, Anchorage, Alaska, April 2001.

[6- SPI-RED] Naixue Xiong, Xavier Défago, Xiaohua Jia, Yan Yang, Yanxiang He: Design and Analysis of a Self-Tuning Proportional and Integral Controller for Active Queue Management Routers to Support TCP Flows. INFOCOM 2006.


June 25, 2011

References

[7-LRC-RED] Naixue Xiong, Laurence T. Yang, Yan Yang, Xavier Defago, Yanxiang He, “A Novel Numerical Algorithm Based onSelf-Tuning Controller to Support TCP Flows,“ Mathematics and Computers in Simulation, 79(4):1178-1188, 2008. (Elsevier)

[8-RED] H. Zhang, C. V. Hollot, D. Towsley, and V. Misra, “A self-tuning

structure for adaptation in TCP/AQM networks,” ACM SIGMETRICS

Performance Evaluation Review, Vol. 31, No. 1, pp. 302-303, June 2003.

[9-RED] W. Fang, Kang G. Shin, Dilip D. Kandlur, and D. Saha, ”The

BLUE active queue management algorithms,” IEEE/ACM Transactions on

Networking, Vol. 10, No. 4, pp. 513-528, Aug. 2002.


June 25, 2011

References[10-RED] Y. Gao and J. C. Hou, “A state feedback control approach to

Stabilizing queues for ECN-enabled TCP flows,” in Proceedings of IEEE

INFOCOM 2003, Vol. 3, pp. 2301-2311, San Francisco, CA, March 30 –

April 2, 2003.

[11-RED] Chonggang Wang, Bin Li, Y. Thomas Hou, Kazem Sohraby, Yu

Lin, ”LRED: A Robust Active Queue Management Scheme Based on

Packet Loss Ratio,” Proceedings of IEEE INFOCOM 2004, Hong Kong,

March 2004.

[12-RED] C. V. Hollot, V. Misra, D. Towsley and W. B. Gong, “Analysis

and design of controllers for AQM routers supporting TCP flows,” IEEE

Transactions on Automatic Control, Vol. 47, pp. 945-959, June 2002.


June 25, 2011

References[13] Z. Zhao, S. Darbha, and A. L. N. Reddy, “A Method for Estimating

the Proportion of Nonresponsive Traffic At a Router,” IEEE/ACM

Trans. on Networking, vol. 12, no. 4, pp. 708–718, Aug. 2004.

[1 book] Craig Partridge, “Gigabit Networking,” Addison-Wesley, ISDN 0-201-56333-9.

[2 book] James F. F. Kurose and Keith W. Ross,

"Computer Networking: A Top-Down Approach", 4th edition, Addison Wesley, (ISBN: 10: 0321497708)


June 25, 2011

25

XEx ' XEx ' XEx '

Protecting datacenters must first secure cloud resources

and uphold user privacy and data integrity.

Trust overlay networks could be applied to build

reputation systems for establishing the trust among

interactive datacenters.

A FD technique is suggested to protect shared data

objects and massively distributed software modules.

The new approach could be more cost-effective than using

the traditional encryption and firewalls to secure the

clouds.

Security and Trust Crisis in Cloud Computing


June 25, 2011

Computing clouds are changing the whole IT , service industry, and global economy. Clearly, cloud computing demands ubiquity, efficiency, security, and trustworthiness.

Cloud computing has become a common practice in business, government, education, and entertainment leveraging 50 millions of servers globally installed at thousands of datacenters today.

Private clouds will become widespread in addition to using a few public clouds, that are under heavy competition among Google, MS, Amazon, Intel, EMC, IBM, SGI, VMWare, Saleforce.com, etc.

Effective reliable management, guaranteed security, user privacy, data integrity, mobility support, and copyright protection are crucial to the universal acceptance of cloud as a ubiquitous service.

Security and Trust Crisis in Cloud Computing


June 25, 2011

Content: Reliable, Performance Distributed file system Bandwidth to Data • Scan 100TB Datasets on 1000 node cluster • Remote storage @ 10MB/s = 165 mins • Local storage @ 50-200MB/s = 33-8

mins • Moving computation is more efficient than moving data • Need visibility into data placement


June 25, 2011

Scaling Reliably • Failure is not an option, it’s a rule ! • 1000 nodes, MTBF < 1 day • 4000 disks, 8000 cores, 25 switches,

1000 NICs, 2000 DIMMS (16TB RAM) • Need fault tolerant store with reasonable availability guarantees • Handle hardware faults transparently


June 25, 2011

Hadoop Distributed File System (HDFS)

• Data is organized into files and directories • Files are divided into uniform sized blocks (default 64MB) and distributed across

cluster nodes • HDFS exposes block placement so that computation can be migrated to data


June 25, 2011

Problems of CPU-GPU Hybrid Clusters Scheduling Map tasks onto CPUs and

GPUs efficiently is difficult Dependence on computational resource

# of CPU cores, GPUs, amount of memory, memory bandwidth, I/O bandwidth to storage

Dependence on applications GPU computation characteristic

Pros. Peak performance, memory bandwidth Cons. Complex instructions

Hybrid Scheduling with CPUs and GPUs to make use of each excellence → Exploit computing resources

Neal N. Xiong @ GSU Slide 1 June 25, 2011 Cloud Computing Services and Architecture Neal N. Xiong Georgia State University.

Documents

gsu slide

gmu slide

userapplications vcl

software management

management nodes servers

vcl applications

open source vcl software

george mason university