IBM Predicts Cloud Computing Demand for Sports Tournaments

Aaron K. Baughman,Richard J. Bogdany, Benjie Harrison, Brian O'Connell, Herbert D. Pearthree, Brandon Frankel,Cameron McAvoy,Sandy Sun,Clay Upton

Periodicals(2016)

引用 9|浏览28
暂无评分
摘要
AbstractThe 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.
更多
查看译文
关键词
predictive modeling, forecasting, cloud computing, big data, sports, stream computing, social analytics
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要