IBM Predicts Cloud Computing Demand for Sports Tournaments

被引:9
作者
Baughman, Aaron K. [1 ]
Bogdany, Richard [1 ]
Harrison, Benjie [1 ]
O'Connell, Brian [1 ]
Pearthree, Herbie [1 ]
Frankel, Brandon [1 ]
McAvoy, Cameron [1 ]
Sun, Sandy [1 ]
Upton, Clay [1 ]
机构
[1] IBM Corp, Res Triangle Pk, NC 27709 USA
关键词
predictive modeling; forecasting; cloud computing; big data; sports; stream computing; social analytics;
D O I
10.1287/inte.2015.0820
中图分类号
C93 [管理学];
学科分类号
12 ; 1201 ; 1202 ; 120202 ;
摘要
The rapid growth of the Internet and of mobile and other smart technologies has generated increased demand on digital platforms, which are supported by enterprise cloud-computing capabilities. To support IBM's leadership in analytics, mobile, and cloud technologies, a small team within IBM Global Technology Services (GTS) developed a system that uses advanced analytics to address the dynamic and unpredictable Web traffic patterns produced by a digital-enterprise workload, while driving greater operational efficiencies in computing and labor resources. Current cloud platforms are reactive; that is, they require human intervention to scale computing resources to meet demand. To address this shortcoming, the GTS team developed the Predictive Cloud Computing (PCC) system. PCC uses multiple advanced analytical techniques, such as novel numerical analysis techniques, discrete-event simulation, and advanced forecasting to produce models that forecast Internet traffic demands in near real time, allocating computing resources as needed. In 2014, GTS applied the PCC system across tennis and golf sporting tournaments reducing our cloud-computing hours by about 50 percent, while driving a reduction in labor through automation. The PCC system continues to expand IBM's technology base; since its inception, it has resulted in 16 patent filings, strengthening IBM's analytics patent portfolio and overall brand.
引用
收藏
页码:33 / 48
页数:16
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