The efficiency of large-scale applications is strongly dependent
\non good data management techniques. In this paper,
\nwe claim that the ability to specify data requirements in
\na time-varying manner facilitates data management and improves
\napplication efficiency. This is because requirements
\nsuch as availability, bandwidth and latency can vary significantly
\nwith time. Consequently, the storage system can
\ndynamically change the allocation of resources to data objects.
\nWe describe how an application may specify these
\ndynamic requirements using utility functions, and outline
\na strategy towards achieving an optimal allocation of resources
\nto data objects.<\/p>\n","protected":false},"excerpt":{"rendered":"
The efficiency of large-scale applications is strongly dependent on good data management techniques. In this paper, we claim that the ability to specify data requirements in a time-varying manner facilitates data management and improves application efficiency. This is because requirements such as availability, bandwidth and latency can vary significantly with time. Consequently, the storage system […]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","msr-author-ordering":null,"msr_publishername":"IEEE Communications Society","msr_publisher_other":"","msr_booktitle":"Proceedings of the 1st International Workshop on Hot Topics in Dependability (HotDep)","msr_chapter":"","msr_edition":"Proceedings of the 1st International Workshop on Hot Topics in Dependability (HotDep)","msr_editors":"","msr_how_published":"","msr_isbn":"","msr_issue":"","msr_journal":"","msr_number":"","msr_organization":"","msr_pages_string":"","msr_page_range_start":"","msr_page_range_end":"","msr_series":"","msr_volume":"","msr_copyright":"Copyright \u00a9 2007 IEEE. Reprinted from IEEE Communications Society. This material is posted here with permission of the IEEE. 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