2016/09/12 by Shantenu Jha, Daniel S. Katz, Jha, Shantenu +9
Computer Science · Decision Sciences · #Advanced Data Storage Technologies #Distributed #Distributed and Parallel Computing Systems #FOS: Computer and information sciences #Parallel #Scientific Computing and Data Management #and Cluster Computing (cs.DC)
paper · pdf · doi:10.48550/arxiv.1609.03647
openalex publication_date 2016/09/12 · openalex created_date 2022/10/02 · openalex updated_date 2026/07/28
A common feature across many science and engineering applications is the\namount and diversity of data and computation that must be integrated to yield\ninsights. Data sets are growing larger and becoming distributed; and their\nlocation, availability and properties are often time-dependent. Collectively,\nthese characteristics give rise to dynamic distributed data-intensive\napplications. While "static" data applications have received significant\nattention, the characteristics, requirements, and software systems for the\nanalysis of large volumes of dynamic, distributed data, and data-intensive\napplications have received relatively less attention. This paper surveys\nseveral representative dynamic distributed data-intensive application\nscenarios, provides a common conceptual framework to understand them, and\nexamines the infrastructure used in support of applications.\n