DocumentCode :
2017257
Title :
Online Risk Analytics on the Cloud
Author :
Kim, Hyunjoo ; Chaudhari, Shivangi ; Parashar, Manish ; Marty, Christopher
Author_Institution :
Dept. of Electr. & Comput. Eng., State Univ. of New Jersey, Piscataway, NJ
fYear :
2009
fDate :
18-21 May 2009
Firstpage :
484
Lastpage :
489
Abstract :
In todays turbulent market conditions, the ability to generate accurate and timely risk measures has become critical to operating successfully, and necessary for survival. Value-at-risk (VaR) is a market standard risk measure used by senior management and regulators to quantify the risk level of a firm´s holdings. However, the time-critical nature and dynamic computational workloads of VaR applications, make it essential for computing infrastructures to handle bursts in computing and storage resources needs. This requires on-demand scalability, dynamic provisioning, and the integration of distributed resources. While emerging utility computing services and clouds have the potential for cost-effectively supporting such spikes in resource requirements, integrating clouds with computing platforms and data centers, as well as developing and managing applications to utilize the platform remains a challenge. In this paper, we focus on the dynamic resource requirements of online risk analytics applications and how they can be addressed by cloud environments. Specifically, we demonstrate how the CometCloud autonomic computing engine can support online multi-resolution VaR analytics using and integration of private and Internet cloud resources.
Keywords :
Internet; risk analysis; CometCloud autonomic computing engine; Internet cloud resources; distributed resources; dynamic provisioning; ondemand scalability; online risk analytics applications; senior management; standard risk measure; storage resources needs; value-at-risk; Cloud computing; Measurement standards; Reactive power; Regulators; Resource management; Risk analysis; Risk management; Scalability; Search engines; Time factors;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Cluster Computing and the Grid, 2009. CCGRID '09. 9th IEEE/ACM International Symposium on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-3935-5
Electronic_ISBN :
978-0-7695-3622-4
Type :
conf
DOI :
10.1109/CCGRID.2009.82
Filename :
5071909
Link To Document :
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