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| Content Provider | ACM Digital Library |
|---|---|
| Author | Shroff, Ness B. |
| Abstract | We are in the midst of a major data revolution. The total data generated by humans from the dawn of civilization until the turn of the new millennium is now being generated every two days. Driven by a wide range of data-intensive devices and applications, this growth is expected to continue its astonishing march, and fuel the development of new and larger data centers. In order to exploit the low-cost services offered by these resource-rich data centers, application developers are pushing computing and storage away from the end-devices and instead deeper into the data-centers. Hence, the end-users' experience is now dependent on the performance of the algorithms used for data retrieval, and job scheduling within the data-centers. In particular, providing low-latency services are critically important to the end-user experience for a wide variety of applications. Our goal has been to develop the analytical foundations and methodologies to enable cloud storage and computing solutions that result in low-latency services. In this talk, I will overview some of the recent research efforts at fast data retrieval in these large-scale data center systems. Specifically, our focus will be on the new tools and techniques required to address these complex issues, the progress made, and the open challenges that remain. |
| Starting Page | 1 |
| Ending Page | 1 |
| Page Count | 1 |
| File Format | PDF EPUB |
| ISBN | 9781450334891 |
| DOI | 10.1145/2746285.2746323 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2015-06-22 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Content Type | Text |
| Resource Type | Article |
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